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/℃.     

基于漂移补偿的数字水印方法

在压缩的视频码流中嵌入数字水印时,如果选择在I帧图像的DCT系数中嵌入数字水印,那么后面的P帧和B帧图像的质量会受到很大的影响。提出了利用新的漂移补偿方法来减小I帧图像中的数字水印对后面的P帧图像和B帧图像的影响。实验结果证明该方法明显地提高了P帧和B帧图像质量,同时所需计算量较小。     

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.     

无线传感器网络多路径缠绕模型及其容错路由机制

针对无线传感器网络(WSN)不相交多路径路由中的路径过长问题和缠绕多路径路由中的容错削弱问题,提出一种多路径缠绕模型及其容错路由机制。首先,提出将多路径缠绕量化的思想,通过建立多路径缠绕模型将多路径的缠绕性量化,并通过容错概率模型建立多路径缠绕性与路由容错性的理论关联;其次,基于多路径缠绕模型,通过局部调整多路径的相交度建立容错路由机制。实验结果表明,在典型多路径路由算法——顺序分配路由(SAR)和能量有效容错多路径路由(EEFTMR)上应用该容错路由机制,能有效提高算法的数据包传输成功率,并一定程度上优化算法的能量有效性和端到端传输延迟。     

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。     

A fault-tolerant control strategy for non-linear discrete-time systems: application to the twin-rotor system

In this paper, an active fault-tolerant control scheme is proposed in the case of actuator faults. In particular, the general idea of integrating fault identification and control schemes, which takes into account the fault estimation error is first presented in a linear context. As a result, the so-called separation principle for the controller and the fault identification scheme is developed. Subsequently, the proposed approach is extended to a class of non-linear systems. Similarly to the linear case, it is proven that using a suitable control strategy and a faulty identification scheme it is possible to obtain an integrated fault-tolerant control framework, which takes into account the fault identification error. As a result, a non-linear counterpart of the above-mentioned separation principle is developed. Finally, the last part of the paper shows the application results obtained using a twin-rotor system that confirm the high performance of the proposed approach.     

面向分布式流体系结构的多副本积极容错技术

随着互联网环境下计算系统规模的不断扩大,分布式流体系结构的可靠性问题面临着严峻的挑战。以多模冗余容错技术为基础,针对软错误提出了一种面向分布式流体系结构的多副本积极容错技术TREFT,利用三个程序副本进行高效的检错与纠错。在分布式流体系结构原型系统上的实验结果表明,该技术能有效提高系统的可靠性,具有较低的容错成本,平均增加10.77%的容错开销。     

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.     

一种湿度传感器温度补偿的融合算法

针对自动气象站上湿度传感器在实际应用过程中易受温度影响的问题,提出采用RBF神经网络与最小二乘相结合的融合算法实现湿度传感器的温度补偿。该方法将湿度传感器在温度影响下的特性曲线分为两个非线性段和一个线性段,并且自适应的确定线性段和非线性段,在线性段利用最小二乘方法拟合出直线方程,在非线性段利用RBF神经网络补偿温度产生的影响。仿真结果表明,这种方法简单易行,与一般的BP神经网络和最小二乘多项式方法相比,具有拟合训练速度快,补偿精度高的特点,可以有效用于湿度传感器的温度补偿,提高传感器的测量精度和可靠性。     

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。     

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。