传感器技术外文文献及中文翻译
传感器SRM驱动器中英文对照外文翻译文献

中英文对照翻译(文档含英文原文和中文翻译)A Simple Excitation Position Detection Method for Sensorless SRM DriveAcknowledgementsThe research for this paper was performed in Dr. G. Schröder’s laboratory during Mr. Kim’s 2006summer intern program of Siegen University, Germany. The authors thank KRF(Korea ResearchFoundation) for supporting the program.Keywords« Switched Reluctance Drive », « Sensorless Control »AbstractThis paper describes a simplified novel sensorless control of an SRM by detecting a current levelduring the non-excitation period. Since the inductance of the motor is a function of the rotor position,a simple detecting current pulse caused by a regulated pulse voltage gives information on the rotorposition. In this paper, a small detecting pulse current is compared to the preset current levels whichare proportional to turn-on and turn-off positions. And the comparison results are used for theexcitation of the next phase. The suggested method is verified by some simulations and experimentaltests.IntroductionA switched reluctance motor (hereinafter referred to as an “SRM”) is a power drive device whichcan be easily and inexpensively manufactured, and it has relatively high reliability since it is proofagainst certain drive faults. Hence, an SRM drive system has some characteristics comparable with anexisting induction motor in view of high torque, a high output density, a high-efficient variable speeddrive, and an economic power inverter in application fields such as industrial machinery, airplanes,automobiles, consumer devices, and others[1-2].In the control of an SRM, on accurate information of rotor position is essential for correctphasewinding excitation. Since the output torque is dependent on the excitation period and excited phasecurrent, the accuracy of the rotor position is very important. In a general speed control system, anoptical encoder is widely used for detecting of the rotor position. Recently, sensorless control andposition detecting techniques are interesting in practical applications due to problems of opticalencoder in harsh environment and cost.In order to get a sensorless rotor position, mathematical based observers and flux detecting methodsare used[3-6]. Since the accuracy of the estimated rotor position of an observer is dependent on themathematical model and electrical parameters, the estimation error is large in the low speed range.And it is very difficult to get the rotor position in standstill. Although the flux detecting method caneasily estimate the rotor position without any complex mathematical model, a look-up table of fluxand rotor position is required. And the relationship of flux and rotor position has non-linearcharacteristic due to the saturation effect. Recently, fuzzy logic and ANN(Artificial Neural Networks)have been used in speed estimation[7-8]This paper presents a simplified novel approach of sensorless control without a complex calculationof the rotor position from the estimated inductance. Since the output torque is dependent on excitationposition and excited current, the proposed sensorless scheme determines the excitation pattern onlyfrom the detecting current in a non-excited phase winding during the detecting period. The turn-on andturn-off positions are determined by the detecting phase current levels that are inverse-proportional torotor position in the detecting period of the previously excited phase. In order to get a linearrelationship between rotor position and detected phase current, a short test voltage is applied duringthe detecting period. Since the proposed sensorless scheme does not use a complex inductancecalculation, the excitation pattern can be easily determined by a simple comparator. The suggestedmethod is verified by some simulations and experimental tests.The General Principles of SRMFig. 1 shows an SR drive system and its torque characteristics. In the Fig. 1, the output torque isproduced in the inductance variation region shown in Fig. 1(b).(a) SR drivesystem(b) Torque characteristicswith constant currentFig. 1: SR drive system and torque characteristicsThe output torque can be explained by the relationship of current and inductance as follows.In order to estimate the phase inductance, the phase current excited by a switching test pulse voltageis used at every sampling period shown as Fig. 2.Fig. 2: Waveform of test pulse voltage and phase current for inductance estimationThe voltage equation for estimating the phase inductance can be derived disregarding the voltagedrop of the phase resistance and the back-emf. From (2), the phase inductance that is a function of therotor position is calculated, and the rotor position is estimated from the calculated inductance according to (3). In spite of a complex calculation, the estimated rotor position from the calculatedinductance has some error due to the saturation effect including the non-linear characteristics of theinductance and the voltage drop of the phase resistance.The Proposed Sensorless Control Scheme of SRMSwitching Pattern DeterminationFig. 3: The proposed detecting scheme of sensorless excitationFig. 3 shows the proposed detecting algorithm of the sensorless excitation of the 3-phase SRM.Differently from a general excitation method, the proposed scheme has excitation, detecting and nonexcitationperiods in each phase.In the excitation period which is determined by the others non-excited phases, excited phase currentproduces output torque. And the applied voltage of each phase winding in the excitation period iscontrolled by the speed controller and excitation current controller. The amplified detected current inthe detecting period, is compared to preset turn-on and turn-off currents, I on and I off which aredetermined by position-current characteristic of the proto-type SRM. The comparison result offers the other phase’s turn-on and turn-off position θon and θoff , respectively. In the non-excitation period,the phase current does not flow through the phase winding. In the detecting period, the amplifieddetected current has nearly linear slope due to the decreasing phase inductance. Since the width of thetest pulse voltage is very narrow and the detected current is very small, saturation effect of phaseinductance can be ignored. So the slope of the detecting current is linear according to rotor position ineach phase windings. But the detecting period of an un-excited phase is located inthe negative torqueregion shown as Fig. 2. Since the detecting phase current produces negative torque and DC-linkvoltage can be changed, test pulse voltage should be limited and controlled for the stable operation. Inorder to limit the negative torque produced from detecting current, the duration of test pulse voltage iscontrolled according to DC-link voltage in this paper. The maximum detecting phase current isproduced in the minimum inductance range and the detecting period of voltage pulse can be derived asfollows with negative torque limit T NLMT. In this paper, the negative torque limit T NLMT is determined as2% of rated torqueof SRM, and the maximum period of test pulse is limited to 20[us].where, θmax and θmin are the rotor position of maximum inductance, L max and minimum inductance,L min , respectively.Fig. 4 shows the detailed block diagram of the sensorless switching position detecting method. Theproposed turn-on and turn-off position estimator consists of the position level generator and thecurrent level comparator. The position level generator produces turn-on and turn-off current levelsfrom pre-calculated look-up table.Fig. 4: The block diagram of the proposed sensorless switching position detectionThe content of the look-up table is simply measured with a fixed test voltage pulse according torotor position. Because the test voltage pulse is short due to the limitation of negative torqueproduction, the output current levels are approximately inverse proportional to the inductance. If thesensorless control system uses a fixed turn-on and turn-off position, thelook-up table can be omitted.Since the detecting pulse current is very small due to the limitation of negative torque, it is amplifiedand limited a by zener diode. The referenceturn-on and turn-off position, θ*on , θ*off change with I on and I off from the position-current look-up table. The look-up table is simple pre-measured with testpulses. And the presetturn-on and turn-off position current are compared to the amplified detectingcurrent. The trigger pulses are generated when the detecting current is larger then each preset value.The trigger pulses are input as interrupts of the DSP, and estimated turn-on, turn-off position are determined. The rotor speed is simply estimated by the estimated turn-on and turn-off position of eachphase.The Excitation Phase and Position at StandstillIn the standstill, the first switching pattern is determined from detecting current explained in the Fig.4. It shows the relationship between detecting current and each possible position at standstill. In theideal case, point a0, b0 and c0 which the maximum period of each detectingcurrent are the criticalboundary for the first excitation phase.Fig. 5: The detecting currents of each phase according to the standstill positionThe Experimental ResultsIn order to verify the proposed sensorless scheme, a 12/8 SRM and a DSP controller with asymmetric converter are used. Table 1 shows the specifications of the 12/8 SRM under test. The maincontroller is implemented by a TMS320F2812 from Texas Instruments and a600V/25A asymmetricconverter module SK25GAD063T from SEMIKRON.Fig. 6: The experiment set-upThe proposed sensorless PI controller is implemented in a TMS320F2812. An encoder is used forposition monitoring. The asymmetric converter is located under the DSP controller and supplies pulsepower to the motor.Fig. 7 shows the detecting currents according to the rotor position. The peak envelope is reverseproportionalto the phase inductance. Consequently, the estimated rotor position can be derived fromthe peak envelope detection of unexcited windings.Fig. 7: The detecting currents of phase-a according to the rotor positionFig. 8: Phase voltage, switching signal and current of phase-a for switching of phase-b and phase-cFig .8 shows the phase voltage, switching signal and phase-a current. The switching on of phase-cand switching off of phase-b are carried out during the switching signal's interval. Fig. 9 shows the excitation current and amplified detecting current of the phases. The phase currenthas excitation and detecting current periods. The excitation current produces the operating torque. Andthe detecting current pulse is used for excitation position estimation and excitation sequence of otherphases. The amplified peak of the phase excitation current is limited by a zener diode, and the peak ofthe detecting current is amplified for the excitation sequence detection.Fig. 9: The excitation current and detecting currents of each phaseConclusionThis paper presents a simple sensorless control of the SRM using current peak detection at nonexcitedphase winding. Due to a simple current comparator for the excitation sequence determination,a complex calculation for excitation position estimation from estimated inductance that is calculatedby detecting current is not required. Without complex look-up table of flux and rotor position, theexcitation sequence of each phase can be changed by the comparison of peak detecting current in thedetection period of other phases. For the speed estimation, the peak value of the detecting current isused and the filtered estimated speed is used in the speed controller. Since the peak value of detectingcurrent is limited to 200[mA], the saturation effect can be ignored. Accordingly the peak detectedcurrent is limited by the detection sampling period and the period is controlled by the link voltageinformation. The experimental results show that the validation of the proposed method is simple.References[1] J.W. Ahn, “Switched Reluctance Motor”, Osung Media, pp. 364~418, 2004[2] P. J. Lawrenson. "A Brief Status Review of Switched Reluctance Drives", EPE Vol. 2, No. 3, pp. 133-144,1992.[3] M. Ehsani, I. Husain, A. B. Kulkarni, "Elimination of discrete position sensor and currrent sensor in switchedreluctance Mototr Drives", IEEE Trans on IA, Vol.28, pp.128-135, 1992[4] J.W. Ahn, S. J. Park, T. H. Kim, “Inductance Reasoning Method for Sensorles s Control of an SRM”, Journalof KIPE, Vol. 8, No. 5, pp.427~434, Oct. 2003.[5] Ji Lili, Chen hao, "Nonlinear modeling and simulation of switch reluctance motor drive system based onMatlab" Journal of Southeast University, Nov. 2004 pp.149-154 Vol.34 Sep.[6] J. P. Lyns, S. R. MacMinn, and M. A. Preston, “Flux/current Methods for SRM Rotor Position Estimation”,in Conf. Rec. 1991/IEEE-IAS Annu. Meeting, Vol. 1, pp. 484-487 , 1991.[7] E. Mese and D. A. Torrey, “Sensorless Position Estimation for Variable-Relucatnce Machine Using ArtificialNeural Networks”, in Conf. Rec. 1997 IEEE-IAS Annu. Meeting, pp. 540-547.[8] L. Xu and J. Bu, “Position Transducerless Control of a Switched Relucance Motor Using Minimum Magnetizing Input”, , in Conf. Rec. 1997 IEEE-IAS Annu. Meeting, pp. 533-549.传感器SRM驱动器的一种简易励磁位置检测方法鸣谢这篇论文的研究工作是2006年暑假金先生在德国锡根大学做实习项目时在G. 施罗德博士的实验室进行的。
温室大棚智能传感器中英文外文翻译文献

温室大棚智能传感器中英文外文翻译文献(含:英文原文及中文译文)英文原文Smart Infrared Temperature SensorsP RayKeeping up with continuously evolving process technologies is a major challenge for process engineers. Add to that the demands of staying current with rapidly evolving methods of monitoring and controlling those processes, and the assignment can become quite intimidating. However, infrared (IR) temperature sensor manufacturers are giving users the tools they need to meet these challenges: the latest computer-related hardware, software, and communications equipment, as well as leading-edge digital circuitry. Chief among these tools, though, is the next generation of IR thermometers— the smart sensor.Today’s new smart IR sensors represent a union of two rapidly evolving sciences that combine IR temperature measurement with high-speed digital technologies usually associated with the computer. These instruments are called smart sensors because they incorporate microprocessors programmed to act as transceivers for bidirectional, serial communications between sensors on the manufacturing floor and computers in the control room (see Photo 1). And because the circuitry is smaller, the sensors are smaller, simplifying installation in tight orawkward areas. Integrating smart sensors into new or existing process control systems offers an immediate advantage to process control engineers in terms of providing a new level of sophistication in temperature monitoring and control.Integrating Smart Sensors into Process LinesWhile the widespread implementation of smart IR sensors is new, IR temperature measurement has been successfully used in process monitoring and control for decades (see the sidebar, “How Infrared Temperature Sensors Work,” below). In the past, if process engineers needed to ch ange a sensor’s settings, they would have to either shut down the line to remove the sensor or try to manually reset it in place. Either course could cause delays in the line, and, in some cases, be very dangerous. Upgrading a sensor usually required buying a new unit, calibrating it to the process, and installing it while the process line lay inactive. For example, some of the sensors in a wire galvanizing plant used to be mounted over vats of molten lead, zinc, and/or muriatic acid and accessible only by reaching out over the vats from a catwalk. In the interests of safety, the process line would have to be shut down for at least 24 hours to cool before changing and upgrading a sensor.Today, process engineers can remotely configure, monitor, address, upgrade, and maintain their IR temperature sensors. Smart models with bidirectional RS-485 or RS-232 communications capabilities simplifyintegration into process control systems. Once a sensor is installed on a process line, engineers can tailor all its parameters to fit changing conditions—all from a PC in the control room. If, for example, the ambient temperature fluctuates, or the process itself undergoes changes in type, thickness, or temperature, all a process engineer needs to do is customize or restore saved settings at a computer terminal. If a smart sensor fails due to high ambient temperature conditions, a cut cable, or failed components, its fail-safe conditions engage automatically. The sensor activates an alarm to trigger a shutdown, preventing damage to product and machinery. If ovens or coolers fail, HI and LO alarms can also signal that there is a problem and/or shut down the line.Extending a Sensor’s Useful LifeFor smart sensors to be compatible with thousands of different types of processes, they must be fully customizable. Because smart sensors contain EPROMs (erasable programmable read only memory), users can reprogram them to meet their specific process requirements using field calibration, diagnostics, and/or utility software from the sensor manufacturer.Another benefit of owning a smart sensor is that its firmware, the software embedded in its chips, can be upgraded via the communications link to revisions as they become available — without removing the sensor from the process line. Firmware upgrades extend the working life of asensor and can actually make a smart sensor smarter.The Raytek Marathon Series is a full line of 1- and 2-color ratio IR thermometers that can be networked with up to 32 smart sensors. Available models include both integrated units and fiber-optic sensors with electronic enclosures that can be mounted away from high ambient temperatures.(see Photo 1). Clicking on a sensor window displays the configuration settings for that particular sensor. The Windows graphical interface is intuitive and easy to use. In the configuration screen, process engineers can monitor current sensor settings, adjust them to meet their needs, or reset the sensor back to the factory defaults. All the displayed information comes from the sensor by way of the RS-485 or RS-232 serial connection.The first two columns are for user input. The third monitors the sensor’s parameters in real time. Some parameters can be changed through other screens, custom programming, and direct PC-to-sensor commands. Parameters that can be changed by user input include the following:∙Relay contact can be set to NO (normally open) or NC (normally closed).∙Relay function can be set to alarm or setpoint.∙Temperature units can be changed from degrees Celsius to degreesFahrenheit, or vice versa.∙Display and analog output mode can be changed for smart sensors that have combinedone- and two-color capabilities.∙Laser (if the sensor is equipped with laser aiming) can be turned on or off.∙Milliamp output settings and range can be used as automatic process triggers or alarms. ∙Emissivity (for one-color) or slope (for two-color) ratio thermometers values can be set. Emissivity and slope values for common metal and nonmetal materials, and instructions on how to determine emissivity and slope, are usually included with sensors.∙Signal processing defines the temperature parameters returned. Average returns an object’s average temperature over a period of time; peak -hold returns an object’s peak temperature either over a period of time or by an external trigger.∙HI alarm/LO alarm can be set to warn of improper changes in temperature. On some process lines, this could be triggered by a break in a product or by malfunctioning heater or cooler elements.∙Attenuation indicates alarm and shut down settings for two-color ratio smart sensors. In this example, if the lens is 95% obscured, an alarm warns that the temperature results might be losing accuracy (known as a “dirty window” alarm). More than 95% obscurity can trigger anautomatic shutdown of the process.Using Smart SensorsSmart IR sensors can be used in any manufacturing process in which temperatures are crucial to high-quality product.Six IR temperature sensors can be seen monitoring product temperatures before and after the various thermal processes and before and after drying. The smart sensors are configured on a high-speed multidrop network (defined below) and are individually addressable from the remote supervisory computer. Measured temperatures at all sensor locations can be polled individually or sequentially; the data can be graphed for easy monitoring or archived to document process temperature data. Using remote addressing features, set points, alarms, emissivity, and signal processing, information can be downloaded to each sensor. The result is tighter process control. Remote Online Addressability In a continuous process similar to that in Figure 2, smart sensors can be connected to one another or to other displays, chart recorders, and controllers on a single network. The sensors may be arranged in multidrop or point-to-point configurations, or simply stand alone.In a multidrop configuration, multiple sensors (up to 32 in some cases) can be combined on a network-type cable. Each can have its own “address,” allowing it to be configured separately with different operating parameters. Because smart sensors use RS-485 or FSK (frequency shiftkeyed) communications, they can be located at considerable distances from the control room computer — up to 1200 m (4000 ft.) for RS-485, or 3000 m (10,000 ft.) for FSK. Some processes use RS-232 communications, but cable length is limited to <100 ft.In a point-to-point installation, smart sensors can be connected to chart recorders, process controllers, and displays, as well as to the controlling computer. In this type of installation, digital communications can be combined with milliamp current loops for a complete all-around process communications package.Sometimes, however, specialized processes require specialized software. A wallpaper manufacturer might need a series of sensors programmed to check for breaks and tears along the entire press and coating run, but each area has different ambient and surface temperatures, and each sensor must trigger an alarm if it notices irregularities in the surface. For customized processes such as this, engineers can write their own programs using published protocol data. These custom programs can remotely reconfigure sensors on the fly—without shutting down the process line.Field Calibration and Sensor UpgradesWhether using multidrop, point-to-point, or single sensor networks, process engineers need the proper software tools on their personal computers to calibrate, configure, monitor, and upgrade those sensors.Simple, easy-to-use data acquisition, configuration, and utility programs are usually part of the smart sensor package when purchased, or custom software can be used.With field calibration software, smart sensors can be calibrated, new parameters downloaded directly to the sensor’s circuitry, and the sensor’s current parameters saved and stored as computer data files to ensure that a complete record of calibration and/or parameter changes is kept. One set of calibration techniques can include one-point offset and two- and three-point with variable temperatures:• One-point offset. If a single temperature is used in a particular process, and the sensor reading needs to be offset to make it match a known temperature, one-point offset calibration should be used. This offset will be applied to all temperatures throughout the entire temperature range. For example, if the known temperature along a float glass line is exactly 1800°F, the smart sensor, or series of sensors, can be calibrated to that temperature.• Two-point. If sensor readings must match at two specific temperatures, the two-point calibration shown in Figure 3 should be selected. This technique uses the calibration temperatures to calculate a gain and an offset that are applied to all temperatures throughout the entire range. • Three-point with variable temperature. If the process has a wide range of temperatures, and sensor readings need to match at threespecific temperatures, the best choice is three-point variable temperature calibration (see Figure 4). This technique uses the calibration temperatures to• Three points If the process has a wi de temperature range, the sensor reading must meet three specific temperatures. The best choice is a three-point temperature calibration. This technique uses the calibration temperature to calculate two gains and two offsets. The first gain and offset apply to all temperatures below the midpoint temperature and at all midpoints above the second plate. Three-point calibration is less common than multiple single-dot, but occasionally manufacturers need to implement this technology to meet specific standards.On-site calibration software also allows the use of routine diagnostic methods, including power supply voltage and relay tests that are run on smart sensors. The result is that the process engineer knows that the sensor works best and it makes it easier to do some necessary troubleshooting.3. ConcludesThe new generation of intelligent infrared temperature sensors requires process engineers to keep up with changes brought about by new production technologies and increased production. They can now configure as many sensors as possible to meet the needs of their particular control process and extend the lifespan of these sensors, far beyond theprevious “not smart” designs. Due to the increased production speed, equipment downtime must be reduced. By monitoring equipment as much as possible and fine-tuning temperature variables without the need for shutdown processes, engineers can maintain efficient processes and deliver high-quality products. The digital processing components and communication capabilities of smart infrared sensors provide a degree of flexibility, security, and ease of use that have not been achieved to date.Infrared (IR) radiation is an electromagnetic spectrum that includes radio waves, microwaves, visible light, and ultraviolet light, as well as gamma rays and X-rays. The IR is between the visible part of the spectrum and radio waves. Infrared wavelengths are usually expressed in micrometers and the spectral range is from 0.7 to 1000 microns. Only the 0.7-14 micron band is used for infrared temperature measurement.Using advanced optical systems and detectors, non-contact infrared thermometers can focus on almost any part or part of the 0.7-14 μm band. Because each object (except blackbody) emits the best infrared energy at a specific point along the infrared wavelength of the line, each process may require a unique sensor model with specific optics and detector types. For example, a sensor, a narrow concentration of polyethylene and related materials concentrated in the 3.43 μm spectral ran ge suitable for measuring surface temperature. A sensor is set at 5 microns to measure the glass surface. Light sensors are used for metal and metal foils. Thebroader spectral range is used to measure lower temperature surfaces such as paper, cardboard, poly, and aluminum foil composites.An object reflects the increase or decrease of emission infrared energy through its temperature. It is emitted energy, measured at the target emissivity, which indicates the temperature of an object.Emissivity is a term used to quantify the energy and light emitting properties of different materials and surfaces. Infrared sensors have an adjustable emissivity setting, usually from 0.1 to 1.0, allowing accurate measurement of several surface types of temperature. The emitted energy comes from an object and reaches the infrared sensor through its optical system, which focuses on one or more light-sensitive detectors on the energy source. The detector's infrared energy is then converted into electrical signals, which in turn are converted into temperature values based on the sensor's calibration equation and the target's emissivity. This temperature value can be displayed on the sensor or converted to a digital output in a smart sensor and displayed on the computer terminal.中文译文智能红外温度传感器P Ray跟上不断发展的工艺技术对工艺工程师来说是一向重大挑战。
光学传感器毕业论文中英文文献及翻译

英文文献及中文翻译一种精确测量倾斜角度的光学传感器摘要本文主要介绍了一种新型光学传感器,它可以同时准确地测量倾斜角或两轴倾斜角度。
这种传感器是基于激光干涉原理,因此具有很高的精度。
设计制作了一个传感器的模型来论证这个新的方法,这是一个光电传感器,传感器中没有移动的部分。
由正交于铅垂面的流动水平面提供参考面。
传感器和绝对水平面之间的角度随着被测量的物体倾斜而改变,这些变化反映在条纹图案的中心位置的转移方式。
不同的干涉条纹的中心位置随倾斜角的变化而改变。
干涉条纹图案进行记录和处理,转化为两轴、水平和垂直倾斜角度。
当使用1024*1024像素的传感器时,测量范围为700弧秒,其精度可高达+/ - 1弧秒。
关键词:倾斜角度传感器,倾斜仪,激光干涉I 介绍市场上目前有几种类型的商业倾斜角度测量传感器。
有些是角度传感器,有些是倾斜仪,它们的工作原理不同。
电解液体、电容和钟摆是现在大多数倾斜角度传感器和倾斜仪的三个主要工作原理。
在这里,我们提出了一种新的光学方法,建立了一个用激光、光学元件和图像传感器的光电传感器,它可以同时做精确的倾斜角度测量,不需要进行机械的移动,其工作原理是基于光学干涉,相干激光作为光源。
光线通过一个装满液态油的玻璃油盒。
由正交于铅垂面的流动水平面提供参考面。
当激光束穿过油箱有两束光线反射回来,一束是液体的表面产生的,另一束是容器玻璃产生的,干涉条纹就是由这两条光线形成的,条纹图案将随着倾斜角度的变化产生相应的变化,条纹图案采集和处理后将反映倾斜角度信息,光学工作原理使它不受磁场的影响。
该传感器可以同时测量两轴倾角。
流动的水平面确保了参考面是一个绝对的水平面。
高灵敏度光学干涉测量原理,保证了较高的精度。
II 原理图1说明了工作原理示意图,O点是光线扩大镜头的焦点,O点可以看作是点光源,它发出球面波。
由于地球重力的影响,液体油面始终保持水平,因此用油面作为参考平面。
该容器是玻璃材料的。
当传感器被放在目标表面时,其底部表面将连同目标对象一起倾斜。
传感器技术论文中英文对照资料外文翻译文献

传感器技术论文中英文对照资料外文翻译文献Development of New Sensor TechnologiesSensors are devices that can convert physical。
chemical。
logical quantities。
etc。
into electrical signals。
The output signals can take different forms。
such as voltage。
current。
frequency。
pulse。
etc。
and can meet the requirements of n n。
processing。
recording。
display。
and control。
They are indispensable components in automatic n systems and automatic control systems。
If computers are compared to brains。
then sensors are like the five senses。
Sensors can correctly sense the measured quantity and convert it into a corresponding output。
playing a decisive role in the quality of the system。
The higher the degree of n。
the higher the requirements for sensors。
In today's n age。
the n industry includes three parts: sensing technology。
n technology。
and computer technology。
传感器技术外文文献及中文翻译

Sensor technologyA sensor is a device which produces a signal in response to its detecting or measuring a property ,such as position , force , torque , pressure , temperature , humidity , speed , acceleration , or vibration .Traditionally ,sensors (such as actuators and switches )have been used to set limits on the performance of machines .Common examples are (a) stops on machine tools to restrict work table movements ,(b) pressure and temperature gages with automatics shut-off features , and (c) governors on engines to prevent excessive speed of operation . Sensor technology has become an important aspect of manufacturing processes and systems .It is essential for proper data acquisition and for the monitoring , communication , and computer control of machines and systems .Because they convert one quantity to another , sensors often are referred to as transducers .Analog sensors produce a signal , such as voltage ,which is proportional to the measured quantity .Digital sensors have numeric or digital outputs that can be transferred to computers directly .Analog-to-coverter(ADC) is available for interfacing analog sensors with computers .Classifications of SensorsSensors that are of interest in manufacturing may be classified generally as follows:Machanical sensors measure such as quantities aspositions ,shape ,velocity ,force ,torque , pressure , vibration , strain , and mass .Electrical sensors measure voltage , current , charge , and conductivity .Magnetic sensors measure magnetic field ,flux , and permeablity .Thermal sensors measure temperature , flux ,conductivity , and special heat .Other types are acoustic , ultrasonic , chemical , optical , radiation , laser ,and fiber-optic .Depending on its application , a sensor may consist of metallic , nonmetallic , organic , or inorganic materials , as well as fluids ,gases ,plasmas , or semiconductors .Using the special characteristics of these materials , sensors covert the quantity or property measured to analog or digital output. The operation of an ordinary mercury thermometer , for example , is based on the difference between the thermal expansion of mercury and that of glass.Similarly , a machine part , a physical obstruction , or barrier in a space can be detected by breaking the beam of light when sensed by a photoelectric cell . A proximity sensor ( which senses and measures the distance between it and an object or a moving member of a machine ) can be based on acoustics , magnetism , capacitance , or optics . Other actuators contact the object and take appropriate action ( usually by electromechanical means ) . Sensors are essential to the conduct of intelligent robots , and are being developed with capabilities that resemble those of humans ( smart sensors , see the following ).This is America, the development of such a surgery Lin Bai an example, through the screen, through a remote control operator to control another manipulator, through the realization of the right abdominal surgery A few years ago our country theexhibition, the United States has been successful in achieving the right to the heart valve surgery and bypass surgery. This robot has in the area, caused a great sensation, but also, AESOP's surgical robot, In fact, it through some equipment to some of the lesions inspections, through a manipulator can be achieved on some parts of the operation Also including remotely operated manipulator, and many doctors are able to participate in the robot under surgery Robot doctor to include doctors with pliers, tweezers or a knife to replace the nurses, while lighting automatically to the doctor's movements linked, the doctor hands off, lighting went off, This is very good, a doctor's assistant.Tactile sensing is the continuous of variable contact forces , commonly by an array of sensors . Such a system is capable of performing within an arbitrarythree-dimensional space .has gradually shifted from manufacturing tonon-manufacturing and service industries, we are talking about the car manufacturer belonging to the manufacturing industry, However, the services sector including cleaning, refueling, rescue, rescue, relief, etc. These belong to the non-manufacturing industries and service industries, so here is compared with the industrial robot, it is a very important difference. It is primarily a mobile platform, it can move to sports, there are some arms operate, also installed some as a force sensor and visual sensors, ultrasonic ranging sensors, etc. It’s surrounding environment for the conduct of identification, to determine its campaign to complete some work, this is service robot’s one of the basic characteristicsIn visual sensing (machine vision , computer vision ) , cameral optically sense the presence and shape of the object . A microprocessor then processes the image ( usually in less than one second ) , the image is measured , and the measurements are digitized ( image recognition ) .Machine vision is suitable particularly for inaccessible parts , in hostile manufacturing environments , for measuring a large number of small features , and in situations where physics contact with the part may cause damage .Small sensors have the capability to perform a logic function , to conducttwo-way communication , and to make a decisions and take appropriate actions . The necessary input and the knowledge required to make a decision can be built into a smart sensor . For example , a computer chip with sensors can be programmed to turn a machine tool off when a cutting tool fails . Likewise , a smart sensor can stop a mobile robot or a robot arm from accidentally coming in contact with an object or people by using quantities such as distance , heat , and noise .Sensor fusion . Sensor fusion basically involves the integration of multiple sensors in such a manner where the individual data from each of the sensors ( such as force , vibration , temperature , and dimensions ) are combined to provide a higher level of information and reliability . A common application of sensor fusion occurs when someone drinks a cup of hot coffee . Although we take such a quotidian event for granted ,it readily can be seen that this process involves data input from the person's eyes , lips , tongue , and hands .Through our basic senses of sight , hearing , smell , taste , and touch , there is real-time monitoring of relative movements , positions , and temperatures . Thus if the coffee is too hot , the hand movement of the cup toward the lip is controlled and adjusted accordingly .The earliest applications of sensor fusion were in robot movement control , missile flight tracking , and similar military applications . Primarily because these activities involve movements that mimic human behavior . Another example of sensor fusion is a machine operation in which a set of different but integrated sensors monitors (a) the dimensions and surface finish of workpiece , (b) tool forces , vibrations ,and wear ,(c) the temperature in various regions of the tool-workpiece system , and (d) the spindle power .An important aspect in sensor fusion is sensor validation : the failure of one particular sensor is detected so that the control system maintains high reliability . For this application ,the receiving of redundant data from different sensors is essential . It can be seen that the receiving , integrating of all data from various sensors can be a complex problem .With advances in sensor size , quality , and technology and continued developments in computer-control systems , artificial neural networks , sensor fusion has become practical and available at low cost .Movement is relatively independent of the number of components, the equivalent of our body, waist is a rotary degree of freedom We have to be able to hold his arm, Arm can be bent, then this three degrees of freedom, Meanwhile there is a wrist posture adjustment to the use of the three autonomy, the general robot has six degrees of freedom. We will be able to space the three locations, three postures, the robot fully achieved, and of course we have less than six degrees of freedomFiber-optic sensors are being developed for gas-turbine engines . These sensors will be installed in critical locations and will monitor the conditions inside the engine , such as temperature , pressure , and flow of gas . Continuous monitoring of the signals from thes sensors will help detect possible engine problems and also provide the necessary data for improving the efficiency of the engines .传感器技术传感器一种通过检测某一参数而产生信号的装置。
湿度传感器系统中英文对照外文翻译文献

中英文资料外文翻译文献英文:The right design for a relative humidity sensor systemOptimizing the response characteristics and accuracy of a humidity sensor system1 OverviewTo make the right choice when selecting a relative humidity sensor for an application, it is important to know and to be able to judge the deciding factors. In addition to long-term stability, which is a measure on how much a sensor changes its properties over time, these factors also include the measurement accuracy and the response characteristics of the sensor. Capacitive humidity sensors are based on the principle that a humidity-sensitive polymer absorbs or releases moisture as a function of the relative ambient humidity. Because this method is only a spot measurement at the sensor location, and usually the humidity of the surroundings is the desired quantity, the sensor must be brought into moisture equilibrium with the surroundings to obtain a precise measurement value. This process is realized by various transport phenomena (cf. the section titled "The housing effect on the response time"), which exhibit a time constant. Accuracy and response time are thus closely dependent on each other, and the design of a humidity measurement system becomes a challenge.2Measurement accuracyThe term measurement accuracy of a humidity sensor is understood primarily to refer to the deviation of the value measured by the sensor from the actual humidity. To determine the measurement accuracy, references, such as chilled mirror hygrometers, whose own tolerance must be taken into account, are used. In addition to this trivial component, humidity sensors require a given time for reaching stable humidity and temperature equilibrium (the humidity is a function of temperature and decreases with increasing temperature; a difference between sensor and ambient temperature leads to measurement errors). This response time thus has a significant effect on the value measured by the sensor and thus on the determinedaccuracy.This time-dependent characteristic is explained in more detail in the following.3Response characteristics and response timeThe response characteristics are defined by various parameters. These are:●The actual response characteristics of the humidity sensor at constant temperature.(1) How quickly the sensitive polymer absorbs or releases moisture until equilibrium is reached (intrinsic response time)(2) How fast the entire system reaches humidity equilibrium (housing effect)●The thermal response characteristics of the humidity sensor at a non-constant temperature(3) The thermal mass of the sensor(4) The system's thermal mass, which is thermally coupled to the sensor (e.g. printed circuit board)(5) Heat sources in the direct surroundings of the sensor (electronic components)(1) and (3) are determined entirely by the sensor itself, (1) primarily by the characteristics of the sensitive polymer.(2) and (4) are primarily determined by the construction of the entire system (shape and size of housing andreadout circuitry).(5) is determined by heat-emitting electronic components.These points will be discussed in more detail in the following.The intrinsic response time (1)Qualitatively, the response characteristics of capacitive humidity sensors look like the following (Fig. 1).Fig. 1: Typical and idealized response characteristics of capacitive humidity sensors (schematic)Because these response characteristics are especially pronounced at high humidity values, an isothermal humidity jump from 40% to 100% was selected here for illustration. The desired ideal behavior of the sensor is indicated in blue. In practice, however, the sensor behaves according to the red line, approximately according to:RH-t=(E-S)*(1-e)+S(t)Here, the time span 1 is usually very short (typ. 1 – 30 min.), in contrast, the time span 2 is very long (typ. Many hours to days). Here the connection of measurement accuracy and response characteristics becomes clear (t until RH=100% is reached). The value at t4 (Fig. 1) is considered to be an exact measured value. However, this assumes that both the humidity and also the temperature remain stable during this entire time, and that the testing waits until this very long measurement time is completed. These conditions are both very hard to achieve and unusual in practice. For the calibration, there are the following two approaches, which both find use in practice (cf. Fig. 2):1.The measured value at t2 (Fig. 1) is used as a calibration reference.Advantage:●The required measurement time for reaching the end value (in the example 100%) isclearly shortened,corresponds to practice, and achieves an apparent short responsetime of the sensor (cf. Fig. 2).Disadvantage:●If the conditions are similar for a long time (e.g., wet periods in outdoor operation),the sensors exceed the correct end value (in the example 100%) undesirably by upto 10% (cf. Fig. 2).2. The measured value at t4 (Fig. 1) is used as a calibration reference.Advantage:●Even for similar conditions over a long time (e.g., wet periods in outdoor operation),an exact measurement result is obtained (cf. Fig. 2).Disadvantage:●For a humidity jump like in Fig. 1, the sensors very quickly deliver the measuredvalue at t2, but reaching a stable end value (about 3-6% higher) takes a long time(apparent longer response time)(cf. Fig. 2).In order to take into account both approaches optimally, the measured values at t3 (cf. Fig. 1) are used as the calibration reference by Sensirion AG.Fig. 2: Response characteristics of different humidity measurement systemsThe housing effect on the response time (2)Here, two types of transport phenomena play a deciding role:●Convection: For this very fast process, the air, whose humidity is to be determined,is transported to the sensor by means of ventilation.●Diffusion: This very slow process is determined by the thermal, molecularself-motion of the water molecules. It occurs even in "stationary" air (e.g., within ahousing), but leads to a long response time.In order to achieve favorable response characteristics in the humidity measurement system, the very fast convection process must be supported by large housing openings and the slow diffusion process must be supported by a small housing around the sensor (small "deadvolume") with "stationary" air reduced to a minimum. The following applies:Thermal effects (3), (4), and (5)Because the total thermal mass of the humidity measurement system (sensor + housing)has a significant effect on its response time, the total thermal mass must be kept as low aspossible. The greater the total thermal mass, the more inert the measurement system becomesthermally and its response time, which is temperature-dependent, increases. In order toprevent measurement errors, the sensor should not be mounted in the vicinity of heatgenerating components.4Summary –what should be taken into account when designing a humidity measurement systemIn order to achieve error-free operation of a humidity-measurement system with response times as short as possible, the following points should be taken into account especially for the selection of the sensor and for the design of the system.●The selection of the humidity sensor element. It should●be as small as possible,●have a thermal mass that is as low as possible,●work with a polymer, which exhibits minimal fluctuations in measured values duringthe time span 2(cf. Fig. 1); testing gives simple information on this condition,●provide calibration, which corresponds to the requirements (see above), e. g.,SHT11/SHT15 from Sensirion.●The housing design (cf. Formula 1). It should●have air openings that are as large as possible in the vicinity of the sensor or thesensor should be operated outside of the housing à good convection!●enclose a "dead volume" that is as small as possible around the sensor àlittlediffusion!●The sensor should be decoupled thermally as much as possible from other components,so that the response characteristics of the sensor are not negatively affected by the thermal inertia of the entire system.(e.g., its own printed circuit board for the humidity sensor, structurally partitioning the housing to create a small volume for the humidity sensor, see Fig. 3)Fig. 3: Mounting example for Sensirion sensors SHT11 and SHT15 with slits for thermal decoupling●The sensor should not be mounted in the vicinity of heat sources. If it was, measuredtemperature would increase and measured humidity decrease.5Design proposalThe challenge is to realize a system that operates cleanly by optimally taking into account all of the points in section 4. The already calibrated SMD humidity sensors SHT11 and SHT15 from Sensirion are the ideal solution. For optimum integration of the sensors in a measurement system, Sensirion AG has also developed a filter cap as an adapter aid, which takes into account as much as possible the points in section 4 and also protects the sensor against contaminants with a filter membrane. Fig. 4 shows schematically how the sensors can be ideally integrated into a housing wall by means of the filter cap SF1.Fig. 4: Filter cap for SHT11 and SHT15In addition to the advantages mentioned above, there is also the option of building an IP67-compatible humidity measurement device (with O-ring, cf. Fig. 4) with optimal performance. Detailed information is available on the Sensirion Web site.译文:相对湿度传感器系统的正确设计湿度传感器系统精度及响应特性的优化1.综述为了在相对湿度的应用方面对传感器做出正确的选择,了解和评估那些起决定作用的因素是非常重要的。
红外传感器中英文对照外文翻译文献

中英文对照翻译外文资料Moving Object Counting with an Infrared Sensor NetworkAbstractWireless Sensor Network (WSN) has become a hot research topic recently. Great benefit can be gained through the deployment of the WSN over a wide range ofapplications, covering the domains of commercial, military as well as residential. In this project, we design a counting system which tracks people who pass through a detecting zone as well as the corresponding moving directions. Such a system can be deployed in traffic control, resource management, and human flow control. Our design is based on our self-made cost-effective Infrared Sensing Module board which co-operates with a WSN. The design of our system includes Infrared Sensing Module design, sensor clustering, node communication, system architecture and deployment. We conduct a series of experiments to evaluate the system performance which demonstrates the efficiency of our Moving Object Counting system.Keywords:Infrared radiation,Wireless Sensor Node1.1 Introduction to InfraredInfrared radiation is a part of the electromagnetic radiation with a wavelength lying between visible light and radio waves. Infrared have be widely used nowadaysincluding data communications, night vision, object tracking and so on. People commonly use infrared in data communication, since it is easily generated and only suffers little from electromagnetic interference. Take the TV remote control as an example, which can be found in everyone's home. The infrared remote control systems use infrared light-emitting diodes (LEDs) to send out an IR (infrared) signal when the button is pushed. A different pattern of pulses indicates the corresponding button being pushed. To allow the control of multiple appliances such as a TV, VCR, and cable box, without interference, systems generally have a preamble and an address to synchronize the receiver and identify the source and location of the infrared signal. To encode the data, systems generally vary the width of the pulses (pulse-width modulation) or the width of the spaces between the pulses (pulse space modulation). Another popular system, bi-phase encoding, uses signal transitions to convey information. Each pulse is actually a burst of IR at the carrier frequency.A 'high' means a burst of IR energy at the carrier frequency and a 'low' represents an absence of IR energy. There is no encoding standard.However, while a great many home entertainment devices use their own proprietary encoding schemes, some quasi-standards do exist. These include RC-5, RC-6, and REC-80. In addition, many manufacturers, such as NEC, have also established their own standards.Wireless Sensor Network (WSN) has become a hot research topic recently. Great benefit can be gained through the deployment of the WSN over a wide range ofapplications, covering the domains of commercial, military as well as residential. In this project, we design a counting system which tracks people who pass through a detecting zone as well as the corresponding moving directions. Such a system can be deployed in traffic control, resource management, and human flow control. Our design is based on our self-made cost-effective Infrared Sensing Module board which co-operates with a WSN. The design of our system includes Infrared Sensing Module design, sensor clustering, node communication, system architecture and deployment. We conduct a series of experiments to evaluate the system performance which demonstrates the efficiency of our Moving Object Counting system.1.2 Wireless sensor networkWireless sensor network (WSN) is a wireless network which consists of a vast number of autonomous sensor nodes using sensors to monitor physical or environmental conditions, such as temperature,acoustics, vibration, pressure, motion or pollutants, at different locations. Each node in a sensor network is typically equipped with a wireless communications device, a small microcontroller, one or more sensors, and an energy source, usually a battery. The size of a single sensor node can be as large as a shoebox and can be as small as the size of a grain of dust, depending on different applications. The cost of sensor nodes is similarly variable, ranging from hundreds of dollars to a few cents, depending on the size of the sensor network and the complexity requirement of the individual sensor nodes. The size and cost are constrained by sensor nodes, therefore, have result in corresponding limitations on available inputs such as energy, memory, computational speed and bandwidth. The development of wireless sensor networks (WSN) was originally motivated by military applications such as battlefield surveillance. Due to the advancement in micro-electronic mechanical system technology (MEMS), embedded microprocessors, and wireless networking, the WSN can be benefited in many civilian application areas, including habitat monitoring, healthcare applications, and home automation.1.3 Types of Wireless Sensor NetworksWireless sensor network nodes are typically less complex than general-purpose operating systems both because of the special requirements of sensor network applications and the resource constraintsin sensor network hardware platforms. The operating system does not need to include support for user interfaces. Furthermore, the resource constraints in terms of memory and memory mapping hardware support make mechanisms such as virtual memory either unnecessary or impossible to implement. TinyOS [TinyOS] is possibly the first operating system specifically designed for wireless sensor networks. Unlike most other operating systems, TinyOS is based on an event-driven programming model instead of multithreading. TinyOS programs are composed into event handlers and tasks with run to completion-semantics. When an external event occurs, such as an incoming data packet or a sensor reading, TinyOS calls the appropriate event handler to handle the event. The TinyOS system and programs are both written in a special programming language called nesC [nesC] which is an extension to the C programming language. NesC is designed to detect race conditions between tasks and event handlers. There are also operating systems that allow programming in C. Examples of such operating systems include Contiki [Contiki], and MANTIS. Contiki is designed to support loading modules over the network and supports run-time loading of standard ELF files. The Contiki kernel is event-driven, like TinyOS, but the system supports multithreading on a per-application basis. Unlike the event-driven Contiki kernel, the MANTIS kernel is based on preemptive multithreading. With preemptive multithreading, applications do not needto explicitly yield the microprocessor to other processes.1.4 Introduction to Wireless Sensor NodeA sensor node, also known as a mote, is a node in a wireless sensor network that is capable of performing processing, gathering sensory information and communicating with other connected nodes in the network. Sensor node should be in small size, consuming extremely low energy, autonomous and operate unattended, and adaptive to the environment. As wireless sensor nodes are micro-electronic sensor device, they can only be equipped with a limited power source. The main components of a sensor node include sensors, microcontroller, transceiver, and power source. Sensors are hardware devices that can produce measurable response to a change in a physical condition such as light density and sound density. The continuous analog signal collected by the sensors is digitized by Analog-to-Digital converter. The digitized signal is then passed to controllers for further processing. Most of the theoretical work on WSNs considers Passive and Omni directional sensors. Passive and Omni directional sensors sense the data without actually manipulating the environment with active probing, while no notion of “direction” involved in these measurements. Commonly people deploy sensor for detecting heat (e.g. thermal sensor), light (e.g. infrared sensor), ultra sound (e.g. ultrasonic sensor), or electromagnetism (e.g. magnetic sensor). In practice, a sensor node can equip with more than one sensor.Microcontroller performs tasks, processes data and controls the operations of other components in the sensor node. The sensor node is responsible for the signal processing upon the detection of the physical events as needed or on demand. It handles the interruption from the transceiver. In addition, it deals with the internal behavior, such as application-specific computation.The function of both transmitter and receiver are combined into a single device know as transceivers that are used in sensor nodes. Transceivers allow a sensor node to exchange information between the neighboring sensors and the sink node (a central receiver). The operational states of a transceiver are Transmit, Receive, Idle and Sleep. Power is stored either in the batteries or the capacitors. Batteries are the main source of power supply for the sensor nodes. Two types of batteries used are chargeable and non-rechargeable. They are also classified according to electrochemical material used for electrode such as NiCd(nickel-cadmium), NiZn(nickel-zinc), Nimh(nickel metal hydride), and Lithium-Ion. Current sensors are developed which are able to renew their energy from solar to vibration energy. Two major power saving policies used areDynamic Power Management (DPM) and Dynamic V oltage Scaling (DVS). DPM takes care of shutting down parts of sensor node which are not currently used or active. DVS scheme varies the power levelsdepending on the non-deterministic workload. By varying the voltage along with the frequency, it is possible to obtain quadratic reduction in power consumption.1.5 ChallengesThe major challenges in the design and implementation of the wireless sensor network are mainly the energy limitation, hardware limitation and the area of coverage. Energy is the scarcest resource of WSN nodes, and it determines the lifetime of WSNs. WSNs are meant to be deployed in large numbers in various environments, including remote and hostile regions, with ad-hoc communications as key. For this reason, algorithms and protocols need to be lifetime maximization, robustness and fault tolerance and self-configuration. The challenge in hardware is to produce low cost and tiny sensor nodes. With respect to these objectives, current sensor nodes usually have limited computational capability and memory space. Consequently, the application software and algorithms in WSN should be well-optimized and condensed. In order to maximize the coverage area with a high stability and robustness of each signal node, multi-hop communication with low power consumption is preferred. Furthermore, to deal with the large network size, the designed protocol for a large scale WSN must be distributed.1.6 Research IssuesResearchers are interested in various areas of wireless sensornetwork, which include the design, implementation, and operation. These include hardware, software and middleware, which means primitives between the software and the hardware. As the WSNs are generally deployed in the resources-constrained environments with battery operated node, the researchers are mainly focus on the issues of energy optimization, coverage areas improvement, errors reduction, sensor network application, data security, sensor node mobility, and data packet routing algorithm among the sensors. In literature, a large group of researchers devoted a great amount of effort in the WSN. They focused in various areas, including physical property, sensor training, security through intelligent node cooperation, medium access, sensor coverage with random and deterministic placement, object locating and tracking, sensor location determination, addressing, energy efficient broadcasting and active scheduling, energy conserved routing, connectivity, data dissemination and gathering, sensor centric quality of routing, topology control and maintenance, etc.中文译文移动目标点数与红外传感器网络摘要无线传感器网络(WSN)已成为最近的一个研究热点。
传感器外文翻译

毕业设计(论文)外文文献翻译院系:光电与通信工程年级专业:12电子信息工程姓名:刘燊学号:1106012133附件:Advances in Sensor Technology Development指导老师评语:指导教师签名:年月日——摘自夏伟强,樊尚春传感器技术的的新发展仪器仪表学报传感器技术的新进展传感器技术是新技术革命和信息社会的重要技术基础,是一门多学科交叉的科学技术,被公认为现代信息技术的源头。
近些年,传感器技术发展很快,取得了许多新进展,尤其在气体传感器、生物传感器、视觉传感器等方面取得了很多进展。
美国麻省理工学院华人科学家张曙光领导的研究小组借助一种特殊溶液,成功地找到了大规模制造嗅觉感受器的办法;同样是麻省理工学院的研究人员利用气相色谱-质谱技术感受识别气体分子,研制出一种能对微量有毒气体做出强烈反应的微型传感器;俄罗斯科学家以从一种普通蘑菇中提取的混合物为原料,与压电石英晶振构成谐振式传感器,能够探测空气中含量极低的酚成分;日本科学家研制出能快速识别流感病毒纳米传感器,有望以纳米技术为快速识别流感病毒、乙型肝炎病毒、疯牛病病原体和残留农药等物质提供新手段;西班牙巴塞罗那自治大学研制出新型缩微DNA分析传感器,这种传感器能将分析 DNA链的时间缩短到几分钟或几小时,智能仪器与传感器技术、空间生物智能传感技术。
可以在亲子鉴定到检测遗传修饰食物的一系列化验中应用,此外还能确定新药的遗传毒性;美国国家标准与技术研究院研发出一种超灵敏微型核磁共振(NMR)传感器,该微型传感器与微流体通道并列置于一个硅芯片之上,这项技术将核磁共振的探测灵敏度提升到一个新的台阶,将在化学分析中具有广泛的应用前景。
我国传感器技术虽然与国外相比还有很大差距,但近两年也取得了一些进展和突破,诞生了一些新产品,有些在国家重大型号工程中获得应用。
如资源环境技术领域中的环境监测及环境风险评价技术、大气复合污染关键气态污染物的快速在线监测技术和大气细粒子和超细粒子的快速在线监测技术,海洋技术领域中的海洋水质污染综合参数在线监测技术和海洋金属污染物现场和在线监测技术等。
- 1、下载文档前请自行甄别文档内容的完整性,平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益,请联系客服反馈,我们会尽快为您处理(人工客服工作时间:9:00-18:30)。
Sensor technologyA sensor is a device which produces a signal in response to its detecting or measuring a property ,such as position , force , torque , pressure , temperature , humidity , speed , acceleration , or vibration .Traditionally ,sensors (such as actuators and switches )have been used to set limits on the performance of machines .Common examples are (a) stops on machine tools to restrict work table movements ,(b) pressure and temperature gages with automatics shut-off features , and (c) governors on engines to prevent excessive speed of operation . Sensor technology has become an important aspect of manufacturing processes and systems .It is essential for proper data acquisition and for the monitoring , communication , and computer control of machines and systems .Because they convert one quantity to another , sensors often are referred to as transducers .Analog sensors produce a signal , such as voltage ,which is proportional to the measured quantity .Digital sensors have numeric or digital outputs that can be transferred to computers directly .Analog-to-coverter(ADC) is available for interfacing analog sensors with computers .Classifications of SensorsSensors that are of interest in manufacturing may be classified generally as follows:Machanical sensors measure such as quantities aspositions ,shape ,velocity ,force ,torque , pressure , vibration , strain , and mass .Electrical sensors measure voltage , current , charge , and conductivity .Magnetic sensors measure magnetic field ,flux , and permeablity .Thermal sensors measure temperature , flux ,conductivity , and special heat .Other types are acoustic , ultrasonic , chemical , optical , radiation , laser ,and fiber-optic .Depending on its application , a sensor may consist of metallic , nonmetallic , organic , or inorganic materials , as well as fluids ,gases ,plasmas , or semiconductors .Using the special characteristics of these materials , sensors covert the quantity or property measured to analog or digital output. The operation of an ordinary mercury thermometer , for example , is based on the difference between the thermal expansion of mercury and that of glass.Similarly , a machine part , a physical obstruction , or barrier in a space can be detected by breaking the beam of light when sensed by a photoelectric cell . A proximity sensor ( which senses and measures the distance between it and an object or a moving member of a machine ) can be based on acoustics , magnetism , capacitance , or optics . Other actuators contact the object and take appropriate action ( usually by electromechanical means ) . Sensors are essential to the conduct of intelligent robots , and are being developed with capabilities that resemble those of humans ( smart sensors , see the following ).This is America, the development of such a surgery Lin Bai an example, through the screen, through a remote control operator to control another manipulator, through the realization of the right abdominal surgery A few years ago our country theexhibition, the United States has been successful in achieving the right to the heart valve surgery and bypass surgery. This robot has in the area, caused a great sensation, but also, AESOP's surgical robot, In fact, it through some equipment to some of the lesions inspections, through a manipulator can be achieved on some parts of the operation Also including remotely operated manipulator, and many doctors are able to participate in the robot under surgery Robot doctor to include doctors with pliers, tweezers or a knife to replace the nurses, while lighting automatically to the doctor's movements linked, the doctor hands off, lighting went off, This is very good, a doctor's assistant.Tactile sensing is the continuous of variable contact forces , commonly by an array of sensors . Such a system is capable of performing within an arbitrarythree-dimensional space .has gradually shifted from manufacturing tonon-manufacturing and service industries, we are talking about the car manufacturer belonging to the manufacturing industry, However, the services sector including cleaning, refueling, rescue, rescue, relief, etc. These belong to the non-manufacturing industries and service industries, so here is compared with the industrial robot, it is a very important difference. It is primarily a mobile platform, it can move to sports, there are some arms operate, also installed some as a force sensor and visual sensors, ultrasonic ranging sensors, etc. It’s surrounding environment for the conduct of identification, to determine its campaign to complete some work, this is service robot’s one of the basic characteristicsIn visual sensing (machine vision , computer vision ) , cameral optically sense the presence and shape of the object . A microprocessor then processes the image ( usually in less than one second ) , the image is measured , and the measurements are digitized ( image recognition ) .Machine vision is suitable particularly for inaccessible parts , in hostile manufacturing environments , for measuring a large number of small features , and in situations where physics contact with the part may cause damage .Small sensors have the capability to perform a logic function , to conducttwo-way communication , and to make a decisions and take appropriate actions . The necessary input and the knowledge required to make a decision can be built into a smart sensor . For example , a computer chip with sensors can be programmed to turn a machine tool off when a cutting tool fails . Likewise , a smart sensor can stop a mobile robot or a robot arm from accidentally coming in contact with an object or people by using quantities such as distance , heat , and noise .Sensor fusion . Sensor fusion basically involves the integration of multiple sensors in such a manner where the individual data from each of the sensors ( such as force , vibration , temperature , and dimensions ) are combined to provide a higher level of information and reliability . A common application of sensor fusion occurs when someone drinks a cup of hot coffee . Although we take such a quotidian event for granted ,it readily can be seen that this process involves data input from the person's eyes , lips , tongue , and hands .Through our basic senses of sight , hearing , smell , taste , and touch , there is real-time monitoring of relative movements , positions , and temperatures . Thus if the coffee is too hot , the hand movement of the cup toward the lip is controlled and adjusted accordingly .The earliest applications of sensor fusion were in robot movement control , missile flight tracking , and similar military applications . Primarily because these activities involve movements that mimic human behavior . Another example of sensor fusion is a machine operation in which a set of different but integrated sensors monitors (a) the dimensions and surface finish of workpiece , (b) tool forces , vibrations ,and wear ,(c) the temperature in various regions of the tool-workpiece system , and (d) the spindle power .An important aspect in sensor fusion is sensor validation : the failure of one particular sensor is detected so that the control system maintains high reliability . For this application ,the receiving of redundant data from different sensors is essential . It can be seen that the receiving , integrating of all data from various sensors can be a complex problem .With advances in sensor size , quality , and technology and continued developments in computer-control systems , artificial neural networks , sensor fusion has become practical and available at low cost .Movement is relatively independent of the number of components, the equivalent of our body, waist is a rotary degree of freedom We have to be able to hold his arm, Arm can be bent, then this three degrees of freedom, Meanwhile there is a wrist posture adjustment to the use of the three autonomy, the general robot has six degrees of freedom. We will be able to space the three locations, three postures, the robot fully achieved, and of course we have less than six degrees of freedomFiber-optic sensors are being developed for gas-turbine engines . These sensors will be installed in critical locations and will monitor the conditions inside the engine , such as temperature , pressure , and flow of gas . Continuous monitoring of the signals from thes sensors will help detect possible engine problems and also provide the necessary data for improving the efficiency of the engines .传感器技术传感器一种通过检测某一参数而产生信号的装置。