AN ACCURATE METHOD OF FAULT ANALYSIS FOR RESPONSE OF FAULTY DISTANT TRANSMISSION LINE

本文应用分布参数故障传输线复频域布参数节点导纳方程和另一种数值拉普拉斯反变换方法 ,对故障传输线首末端电压响应进行了分析。基于 matlab的分析结果显示 ,与应用 pade有理函数近似的拉普拉斯反变换方法相比较 ,该方法更易于分析 。

CANONICAL PIECEWISE-LINEAR ANALYSIS FOR NONLINEAR DC FAULT CIRCUITS

This paper uses canonical piecewise-linear analysis method to analyze nonlinear DC fault circuitsand solve for the values of the test port voltages which are selected beforehand .The method needs lessmemory storages,obtains the results in finite steps and has high efficiency in computation.It can be appliedto the circuits containing multiport nonlinear elements.It is a good method of pre-test analysis for fault cir-cuits in simulation-before-test aproach in analogue circuit diagnosis.

Feature evaluation and extraction based on neural network in analog circuit fault diagnosis

Choosing the right characteristic parameter is the key to fault diagnosis in analog circuit. The feature evaluation and extraction methods based on neural network are presented. Parameter evaluation of circuit features is realized by training results from neural network; the superior nonlinear mapping capability is competent for extracting fault features which are normalized and compressed subsequently. The complex classification problem on fault pattern recognition in analog circuit is transferred into feature processing stage by feature extraction based on neural network effectively, which improves the diagnosis efficiency. A fault diagnosis illustration validated this method.

Wavelet neural network based fault diagnosis in nonlinear analog circuits

The theories of diagnosing nonlinear analog circuits by means of the transient response testing are studled. Wavelet analysis is made to extract the transient response signature of nonlinear circuits and compress the signature dada. The best wavelet function is selected based on the between-category total scatter of signature. The fault dictionary of nonlinear circuits is constructed based on improved back-propagation（BP） neural network. Experimental results demonstrate that the method proposed has high diagnostic sensitivity and fast fault identification and deducibility.

Analog circuit intelligent fault diagnosis based on GKPCA and multi-class SVM approach

Analog circuits fault diagnosis is essential for guaranteeing the reliability and maintainability of electronic systems. In this paper, a novel analog circuit fault diagnosis approach is proposed based on greedy kernel principal component analysis (KPCA) and one-against-all support vector machine (OAASVM). In order to obtain a successful SVM-based fault classifier, eliminating noise and extracting fault features are very important. Due to the better performance of nonlinear fault features extraction and noise elimination as compared with PCA, KPCA is adopted in the proposed approach. However, when we adopt KPCA to extract fault features of analog circuit, a drawback of KPCA is that the storage required for the kernel matrix grows quadratically, and the computational cost for eigenvector of the kernel matrix grows linearly with the number of training samples. Therefore, GKPCA, which can approximate KPCA with small representation error, is introduced to enhance computational efficiency. Based on the statistical learning theory and the empirical risk minimization principle, SVM has advantages of better classification accuracy and generalization performance. The extracted fault features are then used as the inputs of OAASVM to solve fault diagnosis problem. The effectiveness of the proposed approach is verified by the experimental results.

Fault diagnosis method of track circuit based on KPCA-SAE

At present,ZPW-2000 track circuit fault diagnosis is artificially analyzed and monitored.Its discrimination method not only is low efficient and takes a long period,but also requires highly experienced personnel to analyze the data.Therefore,we introduce kernel principal component analysis and stacked auto-encoder network(KPCA-SAD)into the fault diagnosis of ZPW-2000 track circuit.According to the working principle and fault characteristics of track circuit,a fault diagnosis model of KPCA-SAE network is established.The relevant parameters of key components recorded in the data collected by field staff are used as the fault feature parameters.The KPCA method is used to reduce the dimension and noise of fault document matrix to avoid information redundancy.The SAE network is trained by the processed fault data.The model parameters are optimized overall by using back propagation(BP)algorithm.The KPCA-SAE model is simulated in Matlab platform and is finally proved to be effective and feasible.Compared with the traditional method of artificially analyzing fault data and other intelligent algorithms,the KPCA-SAE based classifier has higher fault identification accuracy.

New “Intellectual Networks” (Smart Grid) for Detecting Electrical Equipment Faults, Defects and Weaknesses

The most important elements of “intellectual networks” (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which described in this paper, were proposed to use together with rapid digital protection against short-circuit regimes in transformer windings. This paper presents an application’s experience of LVI-testing, some results of the use of Frequency Response Analysis (FRA) to check the condition of transformer windings and infra-red control results of electrical equipment. The LVI method and short-circuit inductive reactance measurements are sensitive for detecting such faults as radial, axial winding deformations, a twisting of low-voltage or regulating winding, a losing of winding’s pressing and others.

fault500 kV变电站35 kV串联电抗器故障分析及建议

某500kV变电站主变35kV侧发生一起电容器组串联电抗器短路故障,通过对事故现场检查,结合故障录波器记录,对本次事故发生的过程进行了分析并得出结论。针对本次故障暴露出的问题,从串联电抗器安装位置、在线监测等方面提出了事故防范措施,对于变电站电容器组安全运行具有一定参考价值。

Worst-Case Finish Time Analysis for DAG-Based Applications in the Presence of Transient Faults

Tasks in hard real-time systems are required to meet preset deadlines, even in the presence of transient faults and hence the analysis of worst-case finish time （WCFT） must consider the extra time incurred by re-executing tasks that were faulty. Existing solutions can only estimate WCFT and usually result in significant under- or over-estimation. In this work, we conclude that a sufficient and necessary condition of a task set experiencing its WCFT is that its critical task incurs all expected transient faults. A method is presented to identify the critical task and WCFT in O（IVI ＋ IEI） where IVI and IEI are the number of tasks and dependencies between tasks, respectively. This method finds its application in testing the feasibility of directed acyclic graph （DAG） based task sets scheduled in a wide variety of fault-prone multi-processor systems, where the processors could be either homogeneous or heterogeneous, DVS-capable or DVS-incapable, etc. The common practices, which require the same time complexity as the proposed critical-task method, could either underestimate the worst case by up to 25%, or overestimate by 13%. Based on the proposed critical-task method, a simulated-annealing scheduling algorithm is developed to find the energy efficient fault-tolerant schedule for a given DAG task set. Experimental results show that the proposed critical-task method wins over a common practice by up to 40% in terms of energy saving.

基于Simulink的三段比相式距离保护仿真研究

距离保护因其不受系统运行方式的影响,在输电线路保护中得到广泛的应用,对此了解其工作原理并借助计算机做仿真研究显得很有意义。通过查阅相关文献资料并以Matlab软件为仿真平台,对三段比相式距离保护的原理进行了仿真研究。在Matlab环境下建立了阻抗继电器、时间继电器、中间继电器的数学仿真模型,在此基础上搭建了一个110k V输电线路的三段比相式距离保护模型,并结合某一110k V输电线参数完成了输电线距离保护整定值计算,通过Simulink模拟短路来验证模型动作的正确性。通过仿真研究验证了三段比相式距离保护原理的正确性,并得出接地短路和相间短路时的整定方式具有差异性,在仿真模块连接时需要信号类型匹配等结论。

基于核主成分分析-SoftMax的高压断路器机械故障诊断技术研究

高压断路器是保证电力系统安全、可靠运行的重要设备,对于高压断路器机械故障定位和诊断成为近年来重要的研究课题。本文针对高压断路器典型工况的振动信号,提出了一种基于核主成分分析(KPCA)的SoftMax故障诊断模型。首先,通过小波包分解计算振动信息的时频能量比,定义高压断路器六种典型机械工况下的特征描述。然后,利用KPCA对原始特征空间进行压缩,重构低维、高识别度的特征空间,采用SoftMax分类算法对高压断路器典型工况进行诊断定位。最后,对比原始特征空间下、主成分分析特征空间下和KPCA特征空间下的SoftMax分类结果以及KPCA特征下多种典型分类诊断算法,诊断结果表明结合KPCA特征空间重构的SoftMax诊断模型的优越性,为高压断路器机械故障诊断与定位提供新思路。

A Comparative Evaluation of Test Coverage Techniques Effectiveness

Software systems have become complex and challenging to develop and maintain because of the large size of test cases with increased scalability issues. Test case prioritization methods have been successfully utilized in test case management. However, the prohibitively exorbitant cost of large test cases is now the mainstream in the software industry. The growth of agile test-driven development has increased the expectations for software quality. Yet, our knowledge of when to use various path testing criteria for cost-effectiveness is inadequate due to the inherent complexity in software testing. Existing researches attempted to address the issue without effectively tackling the scalability of large test suites to reduce time in regression testing. In order to provide a more accurate way of fault detection in software projects, we introduced novel coverage criteria, called Incremental Cluster-based test case Prioritization (ICP), and investigated its potentials by making a comparative evaluation with three un-clustered traditional coverage-based criteria: Prime-Path Coverage (PPC), Edge-Pair Coverage (EPC) and Edge Coverage (EC) based on mutation analysis. By clustering test suites, based on their dynamic run-time behavior, the number of pair-wise comparisons is reduced significantly. To compare, we analyzed 20 functions from 25 C programs, instrumented faults into the programs, and used the Mull mutation tool to generate mutants and perform a statistical analysis of the results. The experimental results show that ICP can lead to cost-effective improvements in fault detection.

基于相位差的轴向磁通无铁心电机早期轻微匝间短路故障诊断

针对轴向磁通定子无铁心电机早期匝间短路故障问题,提出一种基于零序分量和定子电流分量相位差的轴向磁通定子无铁心电机的早期匝间短路故障诊断和定位方法。首先,根据定子绕组电感极小的特点建立了匝间短路故障数学模型;其次,对故障前后的短路电流、相电流、零序分量等进行了傅里叶分析,通过零序电压基波幅值变化对匝间短路故障进行识别;最后,通过对比零序电压基波与定子三相电流初相位差来进行故障相定位。结果表明,匝间短路故障相的相电流基波初始相位与零序电压基波初相位差的绝对值近似180°,而健康相的相位差与180°相差较大。基于相位差可以实现轴向磁通无铁心电机早期匝间短路故障的诊断与定位,为永磁电机的匝间短路故障诊断提供了参考。

逆变型电源场站故障稳态电流实用化计算方法

单机倍乘法常用于逆变型电源场站的故障稳态建模,可简单估算场站短路电流水平,但计算精度有待提升。文中首先分析了低电压穿越控制策略约束下,有功出力、电压跌落程度对发电单元输出的稳态电流的决定性作用,得出故障稳态电流输出特性曲线,基于此分析了场站电气距离及有功出力差异对单机倍乘法计算误差的影响。在误差分析的基础上,提出了计及发电单元分布特性的改进单机倍乘法。该方法在发电单元接入点电压计算中,利用等值阻抗来等效发电单元与并网点的电气距离;将场站分群等值为两台机组,减小发电单元间有功出力差异对短路特性的影响。不同场景下的仿真分析表明,改进方法计算精度较单机倍乘法有着较大的提升。所提方法仅需通过简单计算即可实现场站分群和短路电流聚合,有较好的工程实用性。

基于改进主元分析的锂离子电池内短路故障诊断方法

锂离子电池储能技术是建设我国以新能源为主体的新型电力系统的关键。因挤压针刺等强外力作用,生产时混入金属碎屑和析锂导致锂枝晶等容易造成锂离子电池出现内短路故障,但内短路的故障特征不明显,隐蔽性强,诊断难度大。为了灵敏有效地诊断出内短路故障,构建锂离子电池的等效电路模型,并基于递归最小二乘来辨识模型参数,提出扩展卡尔曼滤波方法以准确估计内短路故障电池的荷电状态;基于主元分析方法对电池的电压、电流和荷电状态进行关键信息提取,并在常规主元分析方法的基础上,提出一种综合指标来提高故障诊断的灵敏性。实验平台的测试结果验证了所提方法的可行性和有效性,系统可以灵敏且可靠地诊断出锂离子电池的内短路故障,保障了电池安全运行。

新型同步调相机匝间短路故障机理分析

随着新型同步调相机大规模投入运行,调相机的安全问题逐渐凸显。绕组匝间短路故障是调相机1种典型故障,对调相机长期运行和电网稳定都有严重影响。该文从两种故障发生后对气隙磁场磁动势的影响出发,建立转子总电流、定子绕组相电流、支路电流及电磁转矩的统一数学表征,从幅值、相位、谐波含量等多方面对两种故障进行深入的对比分析,揭示新型同步调相机绕组匝间短路故障机理。该文基于已投入使用的TTS-300-2型新型同步调相机,开发有限元软件的仿真程序,搭建调相机模拟机的实验平台。理论分析结果分别得到了仿真与实验结果的验证。

基于IWOA-ELM的模拟电路故障诊断方法

针对模拟电路故障诊断中非线性和高维度输出信号带来的诊断困难问题,提出一种基于改进鲸鱼算法(IWOA)优化极限学习机(ELM)的模拟电路故障诊断方法。首先,采用主成分分析(PCA)法对初始故障电路特征进行降维;其次,在鲸鱼算法的基础上引入Tent映射来初始化种群,并且加入了非线性时变因子、自适应权重以及随机差分变异策略;再利用改进后的鲸鱼算法对ELM进行优化;最后将降维后的故障特征向量输入ELM中得到故障诊断结果。通过Sallen-Key带通滤波器电路以及CSTV滤波器电路仿真测试实例表明:IWOA优化ELM的故障诊断方法具有更优的故障诊断性能,故障诊断准确率高达99.41%。

基于小波分析的空心电抗器匝间短路磁场探测方法研究

为了解决目前干式空心电抗器匝间短路检测方法灵敏度和准确度不足的问题,根据故障发展期探测线圈感应电压的异常变化,提出一种新的基于小波分析的空心电抗器匝间短路磁场探测方法。首先,对电抗器故障发展期探测线圈电压信号进行仿真分析,得到电抗器不同位置匝间短路时探测线圈信号变化特征。再基于信号分解小波系数中有用信号与噪声相对比值最大的原则,逐层自适应选取最优小波基函数,利用小波变换对信号进行阈值去噪,提取故障特征量从而实现对电抗器匝间短路发展期及时准确地判断,避免故障进一步发展。通过搭建电抗器匝间短路故障检测系统实验平台,验证了基于小波分析磁场探测法的灵敏度和可靠性,为电抗器的安全稳定运行提供有效保障。

基于端部漏磁场分析的集成式电机驱动系统在线匝间短路故障诊断

基于宽禁带器件的变频器具有高功率密度和耐高温工作的优势,通过小型化和轻薄化设计可以将变频器置于电机端盖与端绕组之间,构成结构紧凑的集成式电机驱动系统。该系统发生匝间短路故障时,短路绕组电流增大不仅会使电机内部温度升高导致电机绝缘性能降低,还将引起磁场变化影响变频器的正常工作。以一台1.5 kW的交流感应电机为例,搭建基于宽禁带器件的集成式电机驱动系统三维物理模型,利用数学解析法分析并计算匝间短路故障前后的端部漏磁场,并提取电机内端部印制电路板(printed circuit board,PCB)表面与轴心距离相等、机械角度相差45°的两点处磁感应强度在直角坐标系下椭圆曲线的离心率反映端部漏磁场的对称性,以此为特征指标判断电机是否出现匝间短路故障。仿真与实验结果验证了所提方法的正确性和有效性。

飞利浦V60无创呼吸机故障图像分析与解决方案研究

我院重症监护室V60无创呼吸机在使用期间频发故障,本课题组经对2023年3月—7月期间的故障图像、数据、工作原理及系统组成进行深入分析,发现“主报警失败”和“100A”故障报警代码的具体原因。针对故障问题,本课题采取更换隔音棉材料、固定通讯电缆线的方式,并实施预防性维护计划。改进措施实施后,同类型故障报修率大幅下降,显著提升了呼吸机的稳定性和可靠性。此外,本课题组的研究成果还为生产厂家提供了产品改良建议,为未来无创呼吸机的设计和管理提供了新思路。