遥感卫星接收系统故障诊断专家系统设计

针对遥感卫星接收系统故障诊断智能化、自动化的技术需求,分析了遥感卫星接收系统的故障特征,给出了故障诊断专家系统的架构。通过对系统设备监测信息及任务流程的分析、故障树的建立与分析,利用产生式的知识表示方式,建立了故障诊断专家系统的知识库;采用启发式的正向推理模式,实现故障的定位。该故障诊断专家系统已用于实际工程项目,提高了遥感卫星接收系统故障诊断的效率。     

基于安卓平台的电缆故障数据终端设计

为解决传统电缆故障定位设备体积庞大、操作复杂、且价格昂贵的问题。提出了利用手机处理系统分担一部分电缆故障测距数据处理显示任务。该系统以FPGA为测量仪下位机核心,完成故障数据的测量。基于App Inventor 2设计一个App,利用蓝牙模块将手机与电缆故障测距系统连接并接收其测量数据,对该数据进行处理及显示。实验结果表明,测量系统运行速度提高、操作简单、携带方便且人机界面友好。     

基于层次分析的火控系统故障诊断专家系统

火控系统是高科技的复杂系统，故障诊断的难度较大。通过对火控系统的功能结构与故障特性进行层次分析，在较小的功能结构范围内建立故障树层次诊断模型，然后以故障树表述专家知识，并通过故障树选取推理规则，以Windows为平台，以C＋＋Builder为编程语言，开发出具有友好的人机界面和解释功能并可进行二次开发的故障诊断专家系统。该专家系统的设计为火控系统的故障诊断带来便利。     

Fault Diagnosis of Smart Grid Distribution System by Using Smart Sensors and Symlet Wavelet Function

In today’s era of smart grid system scenario, the fault diagnosis is of utmost important task. Present distribution networks change drastically due to expansion and inclusion of large number of distributed generation units into power system at distribution level. To face the challenges of modernized girds, conventional fault diagnosis methodologies require drastic change by making use of advanced infrastructure and technologies. This will be helpful to achieve automation in fault diagnosis tasks, improved power quality, reliability, resilience and self healing property of the power system. This paper proposes the use of smart sensors and advanced communication technology that will be available in future smart grids to carry out automated fault diagnosis tasks using signal processing techniques. Methods of using Standard deviation features of fault transient signal and a fault location factors are proposed. Performance of various scaling levels, features and components of fault transient current signals extracted using the latest non conventional Symlet mother wavelet function are evaluated and compared. The attempt is made to select optimal features and components of fault transient currents to improve the performance of present limited types of available fault locators. The tests are taken on standard model of smart grid distribution system but can be applied for fault diagnosis of any other power equipment. Results show adequate accuracy to extend the use of proposed method for real time applications.     

基于六氟化硫气体分解物的高压设备专家诊断系统

本文采用小波神经网络的专家诊断方法,提出了一种基于六氟化硫气体分解物的高压设备专家诊断系统的思路和方法,并且将良好的软件和硬件协同应用于高压设备专家诊断中,用于分析气体分解物的含量并做出高压设备的故障判断与对故障的预测。介绍专家诊断系统的硬件组成和软件实现方式,并通过与其他业内常用方法的比较进而突出本方法的优势。最后,通过分析一些列实验数据证明专家诊断系统的可靠性和实用性。     

新型飞机的故障诊断维修体系研究

针对新型飞机航空电子系统结构复杂、维修保障难度大等问题,构建了一个高度信息化的故障诊断维修体系,通过网络资源传输故障数据和共享维修数据库信息,利用快速故障诊断、增强故障诊断与远程专家支持诊断三级工作模式,实现对飞机故障的诊断与排除,降低维修成本,提高飞行效率。     

基于小波分析的蜗轮蜗杆减速器故障诊断系统

随着蜗轮蜗杆减速器的广泛应用，其故障类型表现为复杂化和隐蔽化，这不仅会带来巨大的经济损失，甚至威胁工人的生命安全。为解决这一问题，提出了基于小波分析的蜗轮蜗杆减速器故障诊断系统，系统在模拟减速器真实工作情况的基础上，采用LabView编写故障诊断系统，实现对振动信号进行采集与显示、小波分析以及离线故障诊断，实验结果表明，文中提出基于小波分析的蜗轮蜗杆减速器故障诊断系统，能够较好地实现蜗轮蜗杆减速器故障的实时诊断，适用于蜗轮蜗杆减速器技术研究和安全应用等领域。     

故障模糊诊断方法及其应用

现代系统一般都采用模块化设计,功能层次比较明显,利用这种功能特点可加速系统的故障诊断。据此,综合层次法和模糊识别法,本文给出了一种基于层次分析和模糊识别的故障诊断方法。该方法根据系统功能特点划分故障模块,使故障具有一定的层次结构,从而加速了故障的定位;再结合模糊识别法进行故障定位,有效地解决了故障状态识别的不确定性问题。最后结合实例分析,验证了此方法的有效性,并具有故障诊断快速、准确的特点。     

Fault diagnosis algorithm based on switching function for boost converters

A fault diagnosis algorithm, which is necessary for constructing a reliable power conversion system, should detect fault occurrences as soon as possible to protect the entire system from fatal damages resulting from system malfunction. In this paper, a fault diagnosis algorithm is proposed to detect open- and short-circuit faults that occur in a boost converter switch. The inductor voltage is abnormally kept at a positive DC value during a short-circuit fault in the switch or at a negative DC value during an open-circuit fault condition until the inductor current becomes zero. By employing these abnormal properties during faulty conditions, the inductor voltage is compared with the switching function to detect each fault type by generating fault alarms when a fault occurs. As a result, from the fault alarm, a decision is made in response to the fault occurrence and the fault type in less than two switching time periods using the proposed algorithm constructed in analogue circuits. In addition, the proposed algorithm has good resistivity to discontinuous current-mode operation. As a result, this algorithm features the advantages of low cost and simplicity because of its simple analogue circuit configuration.     

基于神经网络与专家系统的压路机智能故障诊断

针对压路机发生故障时,故障原因与故障征兆之间复杂的对应关系,提出了一种基于神经网络与专家系统相结合的新方法,充分发挥了神经网络与专家系统各自的特点。介绍了系统的构成、功能及实现。利用该系统可大大提高压路机故障诊断的准确性和实时性。     

基于改进LSSVM的城市轨道交通供电故障诊断方法

小样本条件下供电系统故障快速诊断是保证城市轨道交通安全稳定运行的保证。文中提出了一种基于量子粒子群优化最小二乘支持向量机(LSSVM)的供电系统故障诊断方法。该方法首先基于主成分分析提取能够表征系统运行状态的特征参数,并降低数据维数。然后利用LSSVM构建小样本故障诊断模型,通过量子粒子群算法对LSSVM模型参数进行优化,设计了自适应检测机制和自适应扰动操作,提高优化算法的全局搜索能力。实验结果表明,该方法能够有效提取故障特征,具有更高的全局搜索能力,对供电系统故障的诊断正确率更高。     

激光冲击强化声学诊断系统研究

为了开发一种有效的激光冲击强化工艺故障诊断系统,基于声学诊断原理,对激光冲击强化过程中采集到的声信号进行小波包分析,提取出能够指示故障状态的声学特征信息,并验证了其有效性。最后将提取的特征信息结合人工神经网络,建立了激光冲击强化的故障诊断系统模型。     

Intelligent fault diagnosis system of induction motor based on transient current signal

This paper presents a method for induction motor fault diagnosis based on transient signal using component analysis and support vector machine (SVM). The start-up transient current signal is selected as features source for fault diagnosis. Preprocessing of transient current signal is performed using smoothing and discrete wavelet transform to highlight the salient features of faults. In this work, independent component analysis, principal component analysis and their kernel are performed to reduce the dimension of features and to extract the optimal features for classification process. In this work, the influence of the number of component analysis towards diagnosis accuracy is also studied. SVM multi-class classification using one against all strategy is selected for classification tool due to good generalization properties. Performance of the system is validated by applying the system to induction motor faults diagnosis. According to the result, the system has potential to serve an intelligent fault diagnosis system in real application.     

Fault location in multi-modular redundant systems

This paper describes a systematic design of a general m-order fault location network to detect and locate all possible subcritical faults in a multi-modular redundant system using decision elements. The fault distribution pattern propagating through various levels of the fault location network of a multi-modular redundant system is presented. The conditions for fault detection and location are also developed.     

基于案例推理的航天测控设备故障诊断

针对航天测控设备故障诊断难度日益增大的问题,将基于案例推理方法应用于设备故障诊断中.首先提出用故障信息规范描述、特征属性集和属性字典的三元组合结构来表示案例的方法,利用数据库管理系统建立故障案例库;然后通过对目标案例的特征属性集元素进行删补及位序调整,构造出与源案例特征属性集同构的特征属性阵列,以此计算案例的局部相似度;最后利用最近邻搜索策略计算案例间的全局相似度,完成对目标案例的搜索和问题的求解过程.应用实例表明,该方法案例表示结构清晰,易于建立案例库,能快速获得故障问题的解决方案,且诊断精度较高,有效提高了设备故障诊断效率.     

一种基于神经网络的模拟电路故障诊断方法

提出了一种基于模拟电路故障诊断的神经网络方法。这种方法利用小波分解、数据标准化、主成分分析对输入数据进行预处理,采用k个神经元输出的前馈神经网络结构进行有效训练。该方法检测和识别故障准确率高,系统的鲁棒性和稳定性强。     

基于神经网络的TD-LTE移动通信网络故障诊断系统的设计与实现

针对网络优化中的故障诊断工作,设计并实现了一种TD-LTE网络故障诊断系统。该系统采用神经网络来构建故障诊断模型,进行故障诊断,输出诊断结果和解决方案,实现了网络故障诊断智能化。最后根据系统的运行结果论证了设计的可行性和可实现性,可以有效地减轻网络优化人员的工作负担,降低网络运行商的网络维护成本。     

基于阻抗的匝间故障早期诊断系统设计与实现

提出了一种使用输入阻抗来诊断无刷直流电动机（brushless dc motors,BLDC）定子绕组匝间故障（inter-turn fault,ITF）的算法,并设计了相应的故障检测系统进行了实现。该系统的优势在于具有早期检测能力以及适用于各种速度范围检测。提出的故障检测技术通过使用输入电压和输入电流来计算输入阻抗,并将其与数据库中的数值比较。相比传统的方法,由于不需要快速傅里叶变换（FFT）,因此提出的算法更加迅速且简单。实验测试结果表明提出的检测方法在各种转速条件下均具有较高的精确度。     

Improved Shamir's CRT‐RSA Algorithm: Revisit with the Modulus Chaining Method

RSA signature algorithms using the Chinese remainder theorem (CRT‐RSA) are approximately four‐times faster than straightforward implementations of an RSA cryptosystem. However, the CRT‐RSA is known to be vulnerable to fault attacks; even one execution of the algorithm is sufficient to reveal the secret keys. Over the past few years, several countermeasures against CRT‐RSA fault attacks have tended to involve additional exponentiations or inversions, and in most cases, they are also vulnerable to new variants of fault attacks. In this paper, we review how Shamir's countermeasure can be broken by fault attacks and improve the countermeasure to prevent future fault attacks, with the added benefit of low additional costs. In our experiment, we use the side‐channel analysis resistance framework system, a fault injection testing and verification system, which enables us to inject a fault into the right position, even to within 1 μs. We also explain how to find the exact timing of the target operation using an Atmega128 software board.