微型航姿系统中磁传感器温度漂移补偿研究

研究了微型航姿系统中地磁传感器的温度特性,根据地磁传感器噪声的频谱特性,设计了带阻数字滤波器;基于地磁传感器测量原理分析传感器输出电压随温度变化的规律,利用多项式相消的方法建立磁传感器温度漂移误差的实时补偿模型,并应用于微型航姿系统的磁航向解算。多次试验结果表明:地磁传感器零偏模型具有良好的重复性,实时温度漂移误差补偿模型可以有效地补偿地磁传感器引起的温度漂移误差;缩短了系统的预热时间,提高了系统输出的磁航向精度。     

Increasing pattern recognition accuracy for chemical sensing by evolutionary based drift compensation

Artificial olfaction systems, which mimic human olfaction by using arrays of gas chemical sensors combined with pattern recognition methods, represent a potentially low-cost tool in many areas of industry such as perfumery, food and drink production, clinical diagnosis, health and safety, environmental monitoring and process control. However, successful applications of these systems are still largely limited to specialized laboratories. Sensor drift, i.e., the lack of a sensor’s stability over time, still limits real industrial setups. This paper presents and discusses an evolutionary based adaptive drift-correction method designed to work with state-of-the-art classification systems. The proposed approach exploits a cutting-edge evolutionary strategy to iteratively tweak the coefficients of a linear transformation which can transparently correct raw sensors’ measures thus mitigating the negative effects of the drift. The method learns the optimal correction strategy without the use of models or other hypotheses on the behavior of the physical chemical sensors.     

A method of sensor fault detection and identification

A method of Bayesian belief network (BBN)-based sensor fault detection and identification is presented. It is applicable to processes operating in transient or at steady-state. A single-sensor BBN model with adaptable nodes is used to handle cases in which process is in transient. The single-sensor BBN model is used as a building block to develop a multi-stage BBN model for all sensors in the process under consideration. In the context of BBN, conditional probability data represents correlation between process measurable variables. For a multi-stage BBN model, the conditional probability data should be available at each time instant during transient periods. This requires generating and processing a massive data bank that reduces computational efficiency. This paper presents a method that reduces the size of the required conditional probability data to one set. The method improves the computational efficiency without sacrificing detection and identification effectiveness. It is applicable to model- and data-driven techniques of generating conditional probability data. Therefore, there is no limitation on the source of process information. Through real-time operation and simulation of two processes, the application and performance of the proposed BBN method are shown. Detection and identification of different sensor fault types (bias, drift and noise) are presented. For one process, a first-principles model is used to generate the conditional probability data, while for the other, real-time process data (measurements) are used.     

电涡流间隙传感器的温度补偿

电涡流间隙传感器具有无接触测量、动态响应快和适应性好等特点,应用领域十分广泛,缺点是温度漂移较大。介绍了电涡流传感器工作原理,并分析了温度漂移的主要因素。建立了检测线圈的数学模型,通过温控试验证明了数学模型的正确性;利用差分方式抵消了检波电路参数的温度漂移,提高间隙信号输出的稳定性。通过试验对检测线圈和检波环节补偿电路进行验证,得出温度-检测线圈输出电压曲线,将补偿前和补偿后试验结果进行对比,满足JJG 644-90标准要求,温度漂移小于12.1%,证明了补偿方法的有效性。     

Compensation of the temperature-dependent offset drift of a Hall sensor

We present a method to cancel the offset of a Hall sensor and compensate its temperature-dependent drift. We adapt and improve a compensation technique based on a correction using the input voltage. A more accurate compensation for the temperature drift is obtained by an offset calibration at two different temperatures. To decrease the calibration time, we propose a procedure for fast heating of the sensor. It consists of forcing a current pulse through a p-n junction of the sensor. Since the resistance of a forward-biased diode is small, this principle is compatible with low-voltage applications. After correction, the resulting offset is less than two percent of the initial offset over the temperature range −10 to +60°C. The corresponding residual equivalent offset is lower than 250 μT.     

单晶硅压力传感器温度漂移的补偿方法

介绍了单晶硅压力传感器温度漂移的机理,阐述了采取串并联电阻网络和有源电路分段等综合补偿方法的补偿原理.实验结果表明:在-45～85℃温区内,补偿后,热零点漂移和热灵敏度漂移从±0.5%FS/℃提高到±0.014%FS/℃.     

Experimental evaluation of fault diagnosis in a skew-configured UAV sensor system

This paper presents an experimental evaluation of a hybrid fault detection and isolation scheme against three successive faults in skew-configured inertial sensors of an unmanned aerial vehicle (UAV). An additional small and low-cost inertial measurement unit is installed with a skewed angle to a primary inertial measurement unit. A parity space method and an in-lane monitoring method are combined to increase system tolerance to the occurrence of multiple successive faults during flight. The first and second faults are detected and isolated by the parity space method. The third fault is detected by the parity space method and isolated by the in-lane monitoring method based on the discrete wavelet transform. Hardware in-the-loop tests and flight experiments with a fixed-wing UAV are performed to verify the performance of the proposed fault diagnosis scheme.     

基于六加速度计的陀螺仪漂移补偿算法的研究

为满足机动无人机姿态测量的需求,尝试了一种新的陀螺仪漂移补偿方案：对6只加速度计按回转轴对称布局,从而解算出角速度;并利用Kalman滤波对该解算角速度与陀螺仪的输出进行融合,通过反馈校正来实现对陀螺仪漂移的补偿。仿真结果证明：该方案能有效补偿陀螺仪漂移,具有一定工程应用价值。     

传感器信号的非线性补偿

针对传感器信号中存在的非线性误差 ,介绍了硬件补偿和软件补偿两种方法。硬件补偿是基于电压源可变来实现传感器特性的线性化 ,从而消除了非线性误差 ;软件补偿是通过函数拟合的办法来有效减小信号中的非线性误差 ,进而提高传感器的准确度。     

热催化瓦斯传感器的特性及其补偿方法

针对热催化瓦斯传感器特性漂移严重的问题,在对热催化瓦斯传感器灵敏度、零点时漂以及环境温度、湿度对其影响实测数据的基础上,通过最小二乘法建立了传感器特性漂移的数学模型,并提出了对其特性进行补偿的方法。实验结果表明:补偿后的瓦斯检测精度大大提高。对热催化瓦斯传感器特性漂移的机理进行了分析。     

A knowledge-based system for sensor selection

This paper presents a Knowledge-based system (KBS) developed to allow users, who may not be knowledgeable about sensors, to select sensors suitable for their specific needs. The KBS runs on a micro-computer. The selection criteria are user specified and are based on the desired measurement parameters. The system output includes all of the operational and dimensional parameters of the recommended sensor, price, and vendor information.     

Feedback based adaptive compensation of control system sensor uncertainties

In this paper, the problem of adaptively compensating sensor uncertainties is addressed in a feedback based framework. In this study, sensor characteristics are modeled as parametrizable uncertain functions and a compensator is constructed to adaptively cancel the effects of sensor uncertainties, to generate an adaptive estimate of the plant output. Such an estimated output is used for the feedback control law. Adaptive control schemes using a model reference approach with sensor uncertainty compensation are developed for LTI plants with either known or unknown plant dynamics. A new feedback controller structure is developed for the case when the plant dynamics is unknown, to handle the plant and sensor uncertainties. Simulation results are presented to show that the proposed adaptive sensor uncertainty compensation designs significantly improve system tracking performance.     

热流量传感器温度补偿方法研究

在热流量传感器测量电路中,利用惠斯登电桥平衡电路和热敏电阻器补偿不能解决流体本身温度变化带来的测量误差。介绍一种用于补偿流体温度变化引起测量误差的方法。试验结果表明:采用该方法进行温度补偿后,可以基本消除流体温度变化引起的测量误差,提高系统的测量精度。     

Real-time scheduling for energy harvesting sensor nodes

Energy harvesting has recently emerged as a feasible option to increase the operating time of sensor networks. If each node of the network, however, is powered by a fluctuating energy source, common power management solutions have to be reconceived. This holds in particular if real-time responsiveness of a given application has to be guaranteed. Task scheduling at the single nodes should account for the properties of the energy source, capacity of the energy storage as well as deadlines of the single tasks. We show that conventional scheduling algorithms (like e.g. EDF) are not suitable for this scenario. Based on this motivation, we have constructed optimal scheduling algorithms that jointly handle constraints from both energy and time domain. Further we present an admittance test that decides for arbitrary task sets, whether they can be scheduled without deadline violations. To this end, we introduce the concept of energy variability characterization curves (EVCC) which nicely captures the dynamics of various energy sources. Simulation results show that our algorithms allow significant reductions of the battery size compared to Earliest Deadline First scheduling.

A novel on-line OCID method and its application to input-constrained active fault-tolerant tracker design for unknown nonlinear systems

ABSTRACT

The existing off-line observer/controller identification (OCID) method for linear systems is newly extended in this paper for off-line/on-line identification of known/unknown highly nonlinear systems, and a new input-constrained active fault-tolerant tracker is developed, based on the identified linear models. The advantages of the proposed extended on-line OCID method for linear/nonlinear systems are briefly described as follows: (i) Implement novel servo-control-oriented off-line OCID methods in observer and controller canonical forms for highly nonlinear systems; (ii) Is able to overcome the discontinuity induced by the singular value decomposition (SVD) that should be carried out at each sampling instant; (iii) It directly realises the identified parameters in the observer/controller canonical forms; this simplifies the identification process; (iv) Can be practically implemented for the on-line control of an unknown nonlinear system which was constituted by an unknown open-loop plant, an existing but unknown controller and/or an unknown observer; and (v) Can be utilised to develop a new active fault-tolerant controller to compensate the immovable existing controller of the practical operating system. Finally, the servo-control-oriented off-line OCID method for the highly nonlinear PUMA 560 manipulator is shown in the illustrative examples to demonstrate the superiority of the proposed method.     

基于LS-SVM辨识的温度传感器非线性校正研究

针对人工神经网络等传统方法的不足,提出了一种利用最小二乘支持向量机(LS-SVM)的热电偶非线性校正方法。在该方法中,根据正反馈原理构造形式为幂级数展开模型的非线性补偿器,并利用LS-SVM线性回归算法辨识该补偿器幂级数序列模型的系数。通过该补偿器之后,热电偶可得到理想的线性特性。最后,对铂铑30—铂铑6热电偶(B型)进行非线性校正实验,实验结果表明:在0~1 820℃范围内,校正后系统的线性度小于0.035 3。因此,所提方法有效,且能应用于其他相似系统的非线性校正。     

基于温度传感器的DAC非线性补偿系统设计

针对数/模转换器(DAC)在大温度范围、满量程工作时表现出较大非线性误差的问题,提出了基于温度传感器的DAC非线性补偿方法。该方法首先在不同温度环境下对DAC进行测试和非线性误差计算,通过I2C总线采集多个温度传感器的温度值,并在工作温度和输出值2个维度上使用双线性插值算法解算出任意工作点的补偿值。实验结果表明:在同等条件下,补偿后的DAC非线性误差比补偿前降低了1个数量级。     

实时嵌入式容错系统的关键技术研究

简要回顾了容错技术的发展过程并分析了不同故障模型下系统的客错方式.对于瞬时故障、间歇性故障的容错可采用软件冗余方法,在实时嵌入式系统中采用软件容错时必须考虑任务的可调度性;而永久性故障则采用硬件冗余方法来解决.在此基础上,描述了一种实时双机嵌入式容错系统的模型,研究了构建容错系统需要解决的双机同步、故障检测及仲裁切换等关键问题和相应的解决方法.     

振弦式传感器非线性补偿设计

振弦式传感器被测力与输出频率之间是一种非线性关系 ,它严重影响了传感器的测量性能。这里针对此问题提出了一种非线性补偿结构的设计方法。通过非线性补偿结构 ,可以使被测力与输出频率之间近似为线性关系。通过实际计算 ,给出了一种非线性补偿的结构参数 ,得到的结果验证了方法的可行性     

数字测量系统中传感器温度补偿的一种新方法

提出一种对传感器温度系数的校正新方法——采用二次方程校正法和温度补偿算法相结合的温度校正方法。该算法简单可靠、易实现。将A/D转换器的数字输出量和环境温度T都作为微控制器(MCU)的输入,经MCU处理运算后,获得准确的传感器测量值。