THE ML BEARING ESTIMATION BY USING NEURAL NETWORKS

This paper proposes a neural network to implement the maximum likelihood bearingestimation algorithm in real time.We show both analytically and by simulation that this neuralnetwork is guaranteed to be stable and to provide the maximum likelihood bearing estimationwithin an elapsed time of only a few characteristic time constants of the network.As a result,this proposed neural network is satisfactory for real-time hearing estimation.     

An accurate classifier based on adaptive neuro-fuzzy and features selection techniques for fault classification in analog circuits

This paper presents a new approach for faults classification in analog integrated circuits using a multiclass adaptive neuro fuzzy inference system classifier. This is carried out to assist analog circuit's faults diagnosis suffering from inaccurate faults classification on one hand, and to lessen computational burden on the other hand. This has been achieved from features number reduction. These features serving as input feature vector are extracted from the selected circuits (CUT) frequency and transient responses under both fault free and faulty conditions. The considered faults are resistors and capacitors values variations of about 50% low and high from their nominal ones. The method accuracy has been validated with three experiment circuits, the Sallen Key band-pass, the four opamp biquad high-pass and the leapfrog filters. The obtained results reveal a high level of efficiency with an accuracy average reach to 99.76%. Hence, the proposed method has shown a good performance in term of fault classification accuracy when compared with those of both the Artificial Neural Networks (ANN) approach and the fractional Fourier transform (FRFT) method based on a statistical property.     

A fault detection sensor for circuit aging using double-edge-triggered flip-flop

In nanoscale technology, transistor aging is one of the most critical problems that impact on the reliability of circuits. Aging sensor is a good online way to detect the circuit aging, which performs during the operating time with no influence of the normal operation of circuits. In this paper, a Double-edge-triggered Detection Sensor for circuit Aging (DSDA) is proposed, which employs data signal of logic circuits as its clock to control the sampling process. The simulation is done by Hspice using 45 nm technology. The results show that this technique is not sensitive to the process variations. The worst case of the detection precision is more than 80% under the different process variations. It can detect aging fault effectively with the 8% power cost and 30% performance cost.     

The variant cycle-cover problem in fault detection and localization for mesh all-optical networks

With the soaring channel speed and density in all-optical networks (AONs), the risk of high data loss upon network faults increases quickly. To manage network faults efficiently, an m-cycle based fault detection and localization (MFDL) scheme has been introduced recently. This paper verifies the necessary and sufficient condition for achieving the complete fault localization (CFL) in MFDL, which is defined as the case that every single network fault can be located to a unique link. We model the m-cycle construction as a new mathematical problem: the variant version of the constrained cycle-cover problem (vCCCP) and explore its formal expression. The model includes the consideration of the cycle-length limit, cycle number, and wavelength cost, while also keeps the CFL achievable. A two-phase branch-and-bound (B&B) algorithm was developed for solving the vCCCP, which guarantees to find near-optimal solutions. This algorithm is then applied to four typical and four random network examples to validate and assess the performance. The results are analyzed and compared with some previously reported algorithms, in terms of fault localization degree, cycle number, wavelength overhead, and cost reduction. The performance evaluation and comparison reveal that the new model and algorithm could significantly reduce the MFDL cost, including both the cost of monitoring devices and reserved wavelengths.     

A NEW PROBABILISTIC APPROACH FOR ESTIMATING FAULT DETECTION PROBABILITY

A new approach to calculate fault detection probabilities is presented. Fault-free simulation is used in the approach. The quantities of controllability and observability are defined as probabilities of controlling and observing the nodes in the circuit. The probability distribution of random signals on the circuit nodes is analyzed, and it is proved that controllability is in normal distribution. Thus the unbiasing estimation of the fault detection probability can be obtained. According to the concept of observability, we deal with the fan-out nodes. The fault coverages for actual circuits obtained from this approach agree favorably with the fault simulation results.     

PCB湿法设备泵故障检测与预防技术的应用探索

随着经济全球化和科学技术迅猛发展,PCB企业要保持自身的竞争力,就必须改变企业现有的设备计划维修管理模式。文章以PCB生产企业中的湿法设备为例,阐述湿法设备的泵故障检测与预防技术的应用,从而提高设备维修效率和节省维护费用;缩短了维修时间,保证生产过程的连续性,提高PCB企业的生产效益。     

以观测器为基础的量化网络化系统故障检测

文中针对具有未知输入和不确定扰动信号的系统,研究一类以观测器为基础的量化网络化系统故障检测问题。首先,引入时变量化器,对输出信号进行量化处理,在此基础上,对原系统建立故障检测滤波器,通过比较原系统与观测器的输出,建立故障检测滤波器误差系统。最后,基于H∞稳定性理论,将故障检测滤波器问题转化为问题。在论证过程中结合LMI有关定理,给出仿真实例,验证文中方法的有效性。     

Anomaly detection for IGBTs using Mahalanobis distance

In this study, a Mahalanobis distance (MD)-based anomaly detection approach has been evaluated for non-punch through (NPT) and trench field stop (FS) insulated gate bipolar transistors (IGBTs). The IGBTs were subjected to electrical–thermal stress under a resistive load until their failure. Monitored on-state collector–emitter voltage and collector–emitter currents were used as input parameters to calculate MD. The MD values obtained from the healthy data were transformed using a Box–Cox transform, and three standard deviation limits were obtained from the transformed data. The upper three standard deviation limits of the transformed MD healthy data were used as a threshold for anomaly detection. The anomaly detection times obtained by using the MD approach were compared to the detection times obtained by using a fixed percentage change threshold for the on-state collector–emitter voltage.     

浅析电力系统继电保护及故障检测

电力系统继电保护装置是电力系统安全稳定运行的重要基础,更是电力系统故障的第一道防线。随着近年来电力系统的加速发展,电力系统中出现的故障问题也日益严重。本文结合相关资料和文献分析电力系统继电保护及故障检测的重要作用,并对故障检测方法进行了简单介绍。     

基于小波包和Hilbert包络分析的滚动轴承故障诊断方法

滚动轴承故障诊断是机械故障检测中的一个重要方面。本文提出了一种小波包分析和Hilbert包络分析相结合的方法对轴承进行故障诊断。首先利用小波包分析将滚动轴承的振动信号分解到不同的节点上。然后求出各频段的能量,根据频带能量的变化情况,找出滚动轴承的故障所在的频带,对故障频带的重构信号做包络谱分析,将谱峰处的频率与滚动轴承的故障特征频率进行对比。诊断出滚动轴承的故障。通过对实验中采集到的滚动轴承振动信号进行分析,证明了该方法在滚动轴承故障诊断中的有效性。     

一种指纹锁电量智能检测及充电装置的设计

随着科学技术与经济的快速发展,以及智能家居的不断升级,这种在打开方式上完全不同于机械锁的集指纹、密码与人脸识别于一体的智能锁逐渐得到了现代人们的青睐。文章论述了一种指纹锁电量智能检测及充电装置的设计,首先通过磁性触点机构的闭合来连通充电电路,接着利用电量检测芯片检测可充电电池的电量,然后将检测结果与低电压阈值比较判断是否需要智能充电,从而解决指纹锁长久稳定供电的问题。     

Data-driven design of robust fault detection system for wind turbines

In this paper, a robust data-driven fault detection approach is proposed with application to a wind turbine benchmark. The main challenges of the wind turbine fault detection lie in its nonlinearity, unknown disturbances as well as significant measurement noise. To overcome these difficulties, a data-driven fault detection scheme is proposed with robust residual generators directly constructed from available process data. A performance index and an optimization criterion are proposed to achieve the robustness of the residual signals related to the disturbances. For the residual evaluation, a proper evaluation approach as well as a suitable decision logic is given to make a correct final decision. The effectiveness of the proposed approach is finally illustrated by simulations on the wind turbine benchmark model.     

基于雷达测量的多目标联合检测、跟踪与分类方法

利用雷达测量中的目标速度、加速度等属性信息, 基于跳转马尔科夫系统模型高斯混合概率假设密度滤波算法, 提出了一种多目标联合检测、跟踪与分类方法.该方法在进行雷达多目标测量信息处理的多模型混合高斯概率假设密度滤波过程中, 对各高斯项编号, 进行航迹提取, 在滤波处理的同时形成带有航迹编号的明确航迹, 并进行航迹管理; 同时, 根据目标运动模型, 联合利用目标加速度控制输入与速度估计进行多目标分类.仿真试验验证了该方法能够在检测、跟踪的同时, 对目标航迹进行有效类型识别.     

基于多元数据融合的课堂表现智能检测系统设计

为了评估学生的上课行为,文章采用最新的头部姿态估计技术。此项技术能够捕捉当前人头部所做的各种动作与角度,例如低头、转头、仰头等。低头是大多数学生课堂上使用手机的惯用姿势,可以利用此项技术来监测其头部姿态从而进行评估。考虑到人脸检测的定位准确度问题,以及学生低头的动作不一定是使用手机,文章同时引入了无线信号侦测技术,捕获并检测当前教室里由于学生使用手机造成信号频繁收发的终端位置,与人脸检测的定位相结合,交叉定位,从而获得更精准的定位效果。     

Extension of the bond graph causality inversion method for fault detection and isolation

Controlled systems can be subjected to faults that may affect the performance of the system, and unable its objectives to be achieved. Fault detection and isolation algorithms are then used to study these faults. The bond graph tool can be used for modeling purposes and then its structural, and causal properties can be exploited for automatic generation of analytical redundancy relations (ARRs) through a procedure named causality inversion method, which are used for diagnosis applications. These ARRs are mathematical constraints that are used to verify the coherence between the process measurements and the system model. This paper proposes an extension of the causality inversion method by different versions of the same ARR. The goal is to increase the number of isolable faults. Moreover, structural conditions are given in order to avoid the generation of redundant ARRs. To validate the obtained structural procedure, a fault is imposed in a traction of an omnidirectional mobile robot.     

实现白细胞五分类的光电检测电路设计

为了实现白细胞的五分类,提高识别异常细胞的能力,可通过激光照射通过库尔特微孔的白细胞粒子,并由光电探测器接收细胞粒子对激光的前向和后向散射信号,达到对细胞内部结构的测定[1]。文中设计的光电检测电路可将细胞粒子散射的光信号转换成电信号,并对电信号进行放大,与后面的检测和运算系统对接。实验结果表明,该电路具有输出信噪比大、检测精度高等特点,并在实际应用中取得了良好的效果。     

调制识别算法及性能分析

为了提高信号调制识别的性能,以信号的六阶和四阶累积量作为识别特征,研究了一种基于高阶累积量的调制识别算法.分析了最大似然调制识别算法和高阶累积量调制识别算法的性能.并在高斯信道和平衰落信道下对其性能进行了仿真,仿真表明,在一般通信环境下,基于累积量的调制识别算法具有较强的稳健性和实用性.     

导弹火控设备信号检测与故障诊断系统设计

介绍了基于VXI总线信号检测与故障诊断系统的硬件组成和系统集成方案，提出了火控设备分级检测与组合测试相结合的技术途径，讨论了测试系统软件层次化设计思想及故障诊断系统结构设计和软件实现。     

Distributed fault detection for modular and reconfigurable robots with joint torque sensing: A prediction error based approach

A distributed fault detection scheme for modular and reconfigurable robots (MRRs) with joint torque sensing is proposed in this paper. With the proposed scheme, the joint torque command is filtered and compared with a filtered torque estimate derived from the nonlinear dynamic model of MRR with joint torque sensing. Common joint actuator faults are considered with fault detection being performed independently for each joint module. The proposed fault detection scheme for each module does not require motion states of any other module making it an ideal modular approach for fault detection of modular robots. Experimental results have confirmed the effectiveness of the proposed fault detection scheme.     

数据驱动二次相关滤波器红外目标检测

针对传统红外目标检测算法易受目标和背景先验样本质量、目标姿态和视角及噪声等的影响,提出了一种新的基于稀疏编码的数据驱动二次相关滤波器目标检测算法,其中给出了目标自相关矩阵基字典的概念,该数据驱动滤波器模型能包容多种姿态和视角的目标,并能抑制噪声和样本质量的影响,同时可以舍弃对无规律背景样本的依赖,通过对行人和车辆的实验验证了该算法的有效性.所提算法的设计思想对诸多滤波器算法的改进具有很好的借鉴意义.