某型四余度舵机的神经网络故障诊断模型

某型四余度电液舵机是飞机平尾操纵系统的关键部件，是机、电、液高度耦合的复杂系统。本文根据实际需求，将系统分为元件、部件及系统三种不同层次的故障诊断问题，运用神经网络故障诊断理论，分别建立其BP神经网络诊断模型，并介绍了神经网络故障诊断系统的实现。     

基于小波包和支持向量机的滚动轴承故障模式识别

为了解决对故障轴承的特征提取和故障特征准确分类问题,提出了应用小波包变换和支持向量机相结合进行滚动轴承故障诊断的方法.小波包变换具有良好的时-频局部化特征,非常适于对瞬态或时变信号进行特征提取.而支持向量机可完成模式识别和非线性回归.利用上述原理根据轴承振动信号的频域变化特征,采用小波包变换对其提取频域能量特征向量,然后利用建立的支持向量机多故障分类器完成滚动轴承故障模式的识别.试验结果表明,支持向量机可以有效、准确地识别轴承的故障模式,为轴承故障诊断向智能化发展提供了新的途径.     

数控机床机械故障诊断

分析了数控机床故障诊断技术研究现状，阐述了数控机床故障诊断的原则、故障识别的方法以及故障的诊断与维修技巧。介绍了数控机床故障诊断技术的应用与发展。     

神经网络信息融合技术在岩石挖掘机系统故障诊断中的应用

将信息融合技术与神经网络结合起来，充分利用检测到的各种故障征兆信息准确诊断岩石挖掘机系统的故障。采用混合式数据融合方法，将数据级、特征级和决策级融合通过神经网络的方法综合在一起，解决输入信息不对称性问题，使得小数据量和大数据量的信息融合成为可能。     

液压系统齿轮泵故障树分析

介绍了故障树分析方法.以液压系统齿轮泵为例,通过分析系统故障形式、液压系统结构以及组件与系统之间的逻辑关系,绘制了系统的故障树,再通过最小割集的求解和重要度分析对其进行定性和定量的分析.此方法简便、直观、实用,应用于液压系统故障诊断中能够取得令人满意的效果.     

Mooring system diagnosis and structural reliability control for position moored vessels

Early diagnosis and fault-tolerant control are essential for safe operation of floating platforms where mooring systems maintain vessel position and must withstand environmental loads. This paper considers two critical faults, line breakage and loss of a buoyancy element and employs vector statistical change detection for timely diagnosis of faults. Diagnosis design is scrutinised and a procedure is proposed based on specified false alarm probability and estimation of the distribution of the test statistics on which change detection is based. A structural reliability index is applied for monitoring the safety level of each mooring line and a set-point chasing algorithm accommodates the effects of line failure, as an integral part of the reliability-based set-point chasing control algorithm. The feasibility of the diagnosis and of the fault-tolerant control strategy is verified in model basin tests.     

Exception handling analysis and transformation using fault injection: Study of resilience against unanticipated exceptions

ContextIn software, there are the error cases that are anticipated at specification and design time, those encountered at development and testing time, and those that were never anticipated before happening in production. Is it possible to learn from the anticipated errors during design to analyze and improve the resilience against the unanticipated ones in production?ObjectiveIn this paper, we aim at analyzing and improving how software handles unanticipated exceptions. The first objective is to set up contracts about exception handling and a way to assess them automatically. The second one is to improve the resilience capabilities of software by transforming the source code.MethodWe devise an algorithm, called short-circuit testing, which injects exceptions during test suite execution so as to simulate unanticipated errors. It is a kind of fault-injection techniques dedicated to exception-handling. This algorithm collects data that is used for verifying two formal contracts that capture two resilience properties w.r.t. exceptions: the source-independence and pure-resilience contracts. Then we propose a code modification technique, called “catch-stretching” which allows error-recovery code (of the form of catch blocks) to be more resilient.ResultsOur evaluation is performed on 9 open-source software applications and consists in analyzing 241 catch blocks executed during test suite execution. Our results show that 101/214 of them (47%) expose resilience properties as defined by our exception contracts and that 84/214 of them (39%) can be transformed to be more resilient.ConclusionOur work shows that it is possible to reason on software resilience by injecting exceptions during test suite execution. The collected information allows us to apply one source code transformation that improves the resilience against unanticipated exceptions. This works best if the test suite exercises the exceptional programming language constructs in many different scenarios.     

基于改进的无量纲指标信息融合故障诊断方法

针对无量纲指标信息的不确定会产生冲突证据的问题,提出一种基于改进证据理论的无量纲指标信息融合故障诊断方法.采用人工免疫算法构建原始证据;通过计算无量纲免疫检测器证据之间的相似度找出相似证据和冲突证据.保留相似证据,并利用可信度修正冲突证据,从而降低冲突证据对证据理论合成结果的影响.组合式旋转机械故障诊断试验验证本文方法有效.该方法能够明显提高故障诊断准确率.     

装备故障样本优化方法研究

测试性验证装备的故障样本往往相互关联,全部注入费用较高、代价较大.为了降低验证试验费用,采用适当方法对故障样本进行优化分析.为提高故障检测率,提出了一种等价样本的故障样本优化方法.方法在分析故障-测试关联矩阵及其扩展、故障模式功能等价集合和故障模式测试等价集合的基础上,构建了故障样本等价集合,并进行重要度特征分析和最大熵求解,确定了最小的故障样本集合.通过对某型试验台故障样本优化实例分析,并与传统的方法进行了试验结果对比分析,使得故障样本数量、试验费用大为减少,提高了测试性验证的经济性.