传感技术中的仿生与智能

传感器是信息获取的源头,是信息技术中的关键部件。本文首先阐明了传感器在信息技术中的地位及其重要性;结合仿生技术与人工智能的相关理论,分别对视觉传感器、听觉传感器、嗅觉传感器、味觉传感器、触觉传感器和智能传感器的概念、原理、应用领域进行了介绍;结合当今科技发展趋势,针对传感器技术的发展对策提出了一些建议。     

Effect of Sensor Errors on Automatic Gunfire Control

A formal approach is introduced toward mathematically relating errors in processed sensor data to their impact on error in gunfire of ground based, antiaircraft defense systems. An initial budget for sensor errors is formulated in terms of the accuracy requirements imposed upon the gunfire. The analysis is applicable to gun sites that are remotely located from the sensor as well as to colocated gun sites. Here, the radial components of sensor errors (along the sensor track line) are found to affect the target-miss distance of a remote gun by at least an order of magnitude more than their effect on the miss distance of a colocated gun. However, the effects of the traverse components of sensor errors (across the sensor track line) are found comparable in magnitude between remote and colocated guns.     

基于超磁致伸缩材料的FBG电流传感器温度特性研究

针对基于超磁致伸缩材料的FBG电流传感器,分析了温度对传感头各个部分和整个传感头的影响,通过试验研究了FBG、Fe—Ga超磁致伸缩棒以及传感头三个部分的温度特性。结果表明,FBG的温度特性为线性,Fe—Ga超磁致伸缩棒以及传感头的温度特性整体为非线性,Fe—Ga超磁致伸缩棒的温度响应大于FBG的温度响应,传感头的温度特性主要取决于Fe—Ga超磁致伸缩棒的温度特性。在26℃到60℃范围内,根据传感头的温度特性,可采取分段补偿的方法消除温度影响,将温度特性分为线性区和非线性区两个范围,分别得到了传感头温度特性拟合方程。     

无线传感器网络的异构性研究

随着无线通信技术和微电子技术的快速发展,低成本、高度集成和自组织的无线传感器网络将会逐渐普及.首先总结归纳了无线传感器网络异构性的几种表现形式,如计算能力异构性、节点能量异构性、链路异构性及网络协议异构性,然后介绍了异构无线传感器网络层次网络体系结构和两种适用于无线传感器网络的标准.最后对无线传感器网络的安全问题进行简单探讨.     

热激励谐振式硅微结构压力传感器温度场研究

针对一种以方形硅膜片为一次敏感元件、硅梁谐振子为二次敏感元件 ;采用电阻热激励、压敏电阻拾振的压力微传感器 ,分析了其工作机理 ;依幅值、相位条件讨论了该谐振式微传感器的闭环自激系统 ;建立了微传感器的温度场模型和热应力模型 ,并进行了仿真计算与分析     

复合材料在空间遥感器中的应用进展及关键问题

复合材料凭借其优异的性能已成为空间遥感器的重要材料,包含树脂基复合材料、金属基复合材料、陶瓷基复合材料以及碳/碳复合材料在内不同类型的复合材料皆有大量成功应用的实例。材料和工艺的更新发展,对于空间遥感器系统性能提升或者功能拓展都有着积极的意义。然而从工程化应用水平来看,目前尚处于替代传统材料满足型号产品需求的较低阶段。对空间遥感器所用材料的性能进行了对比与评价,介绍了复合材料在空间遥感器各主要部件中的应用情况,总结了适用于空间遥感器的复合材料及其成型工艺,并对复合材料在工程化应用中的关键技术问题作了进一步探讨,最后对空间遥感器发展对复合材料的需求作了展望。     

基于几何模式识别的发动机传感器故障诊断

提出一种基于几何模式识别技术的发动机传感器故障诊断方法,以解决传感器缓慢漂移故障和由于安装制造差异和性能蜕化等造成的模型不匹配难以区分的问题。传感器测量值输入到自适应模型中,产生一组部件性能修正因子,作为故障模式来对传感器故障进行诊断,每种故障或性能蜕化都对应惟一的模式,采用几何模式识别技术隔离出传感器故障。以某型涡扇发动机为对象进行的仿真结果表明,该方法能诊断出传感器小漂移故障,并能对部件状态进行监控。     

Sensor Optimization Selection Model Based on Testability Constraint

Sensor selection and optimization is one of the important parts in design for testability. To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics and health management especially fault prognostics for testability into account and does not consider the impacts of sensor actual attributes on fault detectability, a novel sensor optimization selection model is proposed. Firstly, a universal architecture for sensor selection and optimization is provided. Secondly, a new testability index named fault predictable rate is defined to describe fault prognostics requirements for testability. Thirdly, a sensor selection and optimization model for prognostics and health management is constructed, which takes sensor cost as objective function and the defined testability indexes as constraint conditions. Due to NP-hard property of the model, a generic algorithm is designed to obtain the optimal solution. At last, a case study is presented to demonstrate the sensor selection approach for a stable tracking servo platform. The application results and comparison analysis show the proposed model and algorithm are effective and feasible. This approach can be used to select sensors for prognostics and health management of any system.     

A fiber-optic current sensor for aerospace applications

A robust, accurate, broadband, AC sensor using fiber optics that is being developed for space applications at power frequencies as high as 20 kHz is described. It can also be used in low- and high-voltage 60-Hz terrestrial power systems and in 400-Hz aircraft systems. It is intrinsically immune to electromagnetic interference (EMI) and has the added benefit of excellent isolation. The sensor uses the Faraday effect in optical fiber and standard polarimetric measurements to sense electrical current. The primary component of the sensor is a specially treated coil of single-mode optical fiber, through which the current-carrying conductor passes. Improved precision is accomplished by temperature compensation by means of signals from a novel fiber-optic temperature sensor embedded in the sensing head. The technology used in the sensor is discussed, and the results of precision tests conducted at various temperatures within the wide operating range as well as the results of early EMI tests are reported     

耦合服役环境下高耐久性薄膜传感器裂纹监测

现有裂纹监测技术多存在耐久性差、虚警率高的问题。以物理气相沉积（PVD）薄膜传感器为研究对象,提出了提高其耐久性的方案,并检验了其在耦合服役环境下的监测性能。首先,选定了Cu作为使传感器耐久性最佳的导电传感层沉积材料,并采用离子镀氮化铝（AlN）薄膜和涂覆705硅胶对PVD薄膜传感器进行了封装保护;然后,综合考虑服役环境因素,编制加速环境谱,将经过封装的制备有薄膜传感器的试验件进行环境耦合加速试验;最后,对环境试验后的薄膜传感器开展疲劳裂纹监测试验,并将薄膜传感器监测结果与显微镜观察测量结果进行对比。试验结果表明：薄膜传感器能承受1 000 h严酷环境的考验,具有较高的耐久性和稳定性;环境试验后的薄膜传感器对裂纹变化敏感,PVD薄膜传感器的监测结果与基体裂纹扩展的实测信息相一致,PVD薄膜传感器的电位监测信号可以作为裂纹扩展状态和结构损伤程度的监测判据,PVD薄膜传感器可以实现对金属结构裂纹的定量监测,监测精度可达到1 mm。     

Joint sensor registration and track-to-track fusion for distributed trackers

Sensor registration deals with the correction of registration errors and is an inherent problem in all multisensor tracking systems. Traditionally, it is viewed as a least squares or a maximum likelihood problem independent of the fusion problem. We formulate it as a Bayesian estimation problem where sensor registration and track-to-track fusion are treated as joint problems and provide solutions in cases 1) when sensor outputs (i.e., raw data) are available, and 2) when tracker outputs (i.e., tracks) are available. The solution to the latter problem is of particular significance in practical systems as band limited communication links render the transmission of raw data impractical and most of the practical fusion systems have to depend on tracker outputs rather than sensor outputs for fusion. We then show that, under linear Gaussian assumptions, the Bayesian approach leads to a registration solution based on equivalent measurements generated by geographically separated radar trackers. In addition, we show that equivalent measurements are a very effective way of handling sensor registration problem in clutter. Simulation results show that the proposed algorithm adequately estimates the biases, and the resulting central-level trucks are free of registration errors.     

Evaluating sensor technology for UAS collision avoidance

The problem of "sense-and-avoid" for Unmanned Aircraft Systems (UAS) is genuinely multi-dimensional: there is a wide range of UAS sizes, speeds, and maneuverability, as well as missions for which these UAS will be used. There are also a variety of sensors that might be used for sense-and-avoid, which have widely varying capabilities to measure distance or angle to an obstacle, as well as closing rate, and time to collision. Most sensors are not able to provide all required information about the geometry of an encounter; therefore, using a combination of sensors offers one possible solution. We are investigating the concept that there may be a variety of possible sensor solutions for each distinct UAS capability or mission. By studying the breadth of UAS types and missions, and selectively testing certain sensors in the field, we are evaluating the limits to the capabilities of sensors and sensor combinations. This report is on the progress of this multi-dimensional evaluation. We have scoped the dimensions for evaluating UAS capabilities and the capabilities of sensors. We are experimentally evaluating sensor parameters on a variety of aircraft to validate the specified capabilities. This reports on our methodology for field evaluation of sensor technology and the lessons learned on evaluation platforms and capabilities.     

基于模糊奇偶方程的非线性系统传感器故障诊断

 给出了一种非线性系统传感器的故障诊断方法。该方法将T-S 模糊模型、全解耦奇偶方程和参数估计相结合,同时对非线性系统的多个传感器的故障进行检测、隔离与识别。设计出用于产生残差的线性系统全解耦奇偶方程,并给出了全解耦奇偶向量的存在条件,全解耦奇偶方程产生的残差仅对一个传感器故障敏感,而对系统状态、扰动输入和其它传感器输出解耦。引入T-S 模型将全解耦奇偶方程推广到非线性系统中得到了模糊奇偶方程。传感器的故障模型表示为刻度因子和偏差的形式,根据残差信息应用卡尔曼估计方法可识别出故障模型的参数。最后给出了某型号飞机控制系统传感器的故障诊断仿真实例。     

高温耐辐照声发射传感器

研制了一种新的耐高温抗辐照声发射传感器,并讨论了传感器制作工艺上的特点和优点。在经受400℃和2.4×10~6GYγ辐照的考验后,传感器仍保持性能稳定。     

Sensor/actuator placement for flexible space structures

A new approach for the placement of sensors and actuators in the active control of flexible space structures is developed. The approach converts the discrete nature of sensor and actuator positioning problems to a nonlinear programming optimization through approximation of the control forces and output measurements by spatially continuous functions. The locations of the sensors and actuators are optimized in order to move the transmission zeros of the system further to the left of the imaginary axis. This criterion for sensor/actuator placement can be useful for optimal regulation and tracking problems, as well as for low authority controller designs. Two performance metrics are considered for the optimization and are applied to the sensor/actuator positioning of a large-order flexible space structure     

采用一组卡尔曼滤波器检测发动机传感器故障

在发动机全功能数字电子控制系统中,提高传感器工作的可靠性是十分重要的,除了不断对传感器本身的性能加以改进提高外,现在广泛地采用了余度技术。近二十年来对解析余度(Analyt ical Redundancy)进行了广泛的研究,解析余度(AR)方法是基于各状态变量之间存在的解析关系,在系统可观条件下,利用无故障的输出测量值去估计(构造)已故障传感器正常工作状态时的输出信息,从而实现对故障的检测、隔离与重构,保证控制系统具有预定的控制性能。      

Tracking with distributed sets of proximity sensors using geometric invariants

We propose a new approach to forming an estimate of a target track in a distributed sensor system using very limited sensor information. This approach uses a central fusion system that collects only the peak energy information from each sensor and assumes that the energy attenuates as a power law in range from the source. A geometrical invariance property of the proximity of the distributed sensors relative to a target track is used to generate potential target track paths. Numerical simulation examples are presented to illustrate the practicality of the technique.     

Design of on-board calibration methods for a digital sun sensor based on Levenberg–Marquardt algorithm and Kalman filters

Digital sun sensor is one of the most important sensors used in the Attitude Determination System (ADS) of the satellite. Due to the harsh environmental conditions that exist in the space, various distortions may occur in the sun sensor optical system that lead to the reduced accuracy of this equipment. So, it is necessary to recalibrate the optical parameters of the aforementioned sensors. For this purpose, first a novel attitude independent error model is proposed for the SS-411 sun sensor that includes the central point of the CCD array, installation error, filter thickness and sensor misalignment. So, the mutual interfaces between the sensor parameters are considered in the developed model. In order to extract the sensor parameters, a nonlinear optimization technique called the Levenberg–Marquardt is applied to the developed model as a batch algorithm. In addition, the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) have been utilized as sequential strategies. It will be shown that by considering a worst case of variation amount for sensor parameters, an accuracy improvement of about 17° is achieved by the developed calibration algorithms. Comparison between the developed algorithms represents that UKF has higher accuracy, shorter time convergence but higher computational load.     

In-Flight Parity Vector Compensation for FDI

The performance of a failure detection and isolation (FDI) algorithm applied to a redundant strapdown inertial measurement unit (IMU) is limited by sensor errors such as input axis misalignment, scale factor errors, and biases. A techique is presented for improving the performance of FDI algorithms applied to redundant strapdown IMUs. A Kalman filter provides estimates of those linear combinations of sensor errors that affect the parity vector. These estimates are used to form a compensated parity vector which does not include the effects of sensor errors. The compensated parity vector is then used in place of the uncompensated parity vector to make FDI decisions. Simulation results are presented in which the algorithm is tested in a realistic flight environment that includes vehicle maneuvers, the effects of turbulence, and sensor failures. The results show that the algorithm can significantly improve FDI performance, especially during vehicle maneuvers.     

雷达和红外成像双传感器信息融合目标识别研究

提出了一种利用目标的雷达和红外成像２种独立的传感器信息的互补性来构造特征向量的信息融合方法——联合向量空间法,并用对应的自适应信息融合系统进行目标识别。仿真证实比用单传感器的效果明显优越,从而说明了本文方法的有效性。