A new bearing fault diagnosis method based on modified convolutional neural networks

Fault diagnosis is vital in manufacturing system. However, the first step of the traditional fault diagnosis method is to process the signal, extract the features and then put the features into a selected classifier for classification. The process of feature extraction depends on the experimenters’ experience, and the classification rate of the shallow diagnostic model does not achieve satisfactory results. In view of these problems, this paper proposes a method of converting raw signals into two-dimensional images. This method can extract the features of the converted two-dimensional images and eliminate the impact of expert’s experience on the feature extraction process. And it follows by proposing an intelligent diagnosis algorithm based on Convolution Neural Network (CNN), which can automatically accomplish the process of the feature extraction and fault diagnosis. The effect of this method is verified by bearing data. The influence of different sample sizes and different load conditions on the diagnostic capability of this method is analyzed. The results show that the proposed method is effective and can meet the timeliness requirements of fault diagnosis.     

超声速低声爆布局分层优化方法

声爆抑制是发展新一代超声速民机必须突破的关键技术。总体布局参数的合理设计可以使飞行器具有良好的声爆特性。为了提高全局进化算法在布局设计中的优化效率,提出一种基于数据挖掘的分层优化方法,利用数据挖掘中的决策树算法提取设计知识,获得设计变量分层信息,指导低声爆布局分层优化;针对某超声速低声爆飞行器,选取后掠角、上反角、展弦比、梢根比、长细比五个总体布局参数作为设计变量,开展分层优化数值实验,并与一体化优化形成对比验证。结果表明：分层优化方法能够搜索到与一体化优化高度吻合的最优解,分层优化的收敛速度显著高于一体化优化,且对随机寻优历程的表现更稳健。     

Neural network-based fault diagnosis for spacecraft with single-gimbal control moment gyros

This paper proposes a neural network-based fault diagnosis scheme to address the problem of fault isolation and estimation for the Single-Gimbal Control Moment Gyroscopes(SGCMGs) of spacecraft in a periodic orbit. To this end, a disturbance observer based on neural network is developed for active anti-disturbance, so as to improve the accuracy of fault diagnosis.The periodic disturbance on orbit can be decoupled with fault by resorting to the fitting and memory ability of neural network. Subsequ...     

SAR performance-based fault diagnosis for electro-hydraulic control system: A novel FDI framework for closed-loop system

Model-based fault diagnosis serves as an efficient and powerful technique in addressing fault detection and isolation (FDI) issues for control systems. However, the standard methods and their modifications still encounter some difficulties in algorithm design and application for complex higher-order systems. To avoid these difficulties, a novel fault diagnosis framework based on multiple performance indicators of closed-loop control system is proposed. Under this framework, a so-called performance residual vector is constructed to measure the differences between the real system and the nominal model in terms of system stability, accuracy, and rapidity (SAR) respectively. The criteria for quantification, normalization of the SAR residuals and the explicit mappings between the thresholds and the required performance are given. FDI can be easily achieved simultaneously by monitoring the normalized residual vector length and direction in the SAR performance residual space. A case study on electro-hydraulic servo control system of turbofan engine is adopted to demonstrate the effectiveness of the proposed method.     

基于故障树和神经网络模型的航天器智能诊断研究

提出基于故障树和神经网络模型的诊断方法,提出面向故障树的基于框架和广义规则的知识表示方法及相应的确定性和可能性推理策略,对于可能性推理的结果,通过基于神经网络模型的学习诊断来进一步确定其状态。在Ｗｉｎｄｏｗｓ环境下,用Ｂｏｒｌａｎｄ Ｃ＋＋实现了一个原型系统。通过对“实践４号”卫星能源系统故障模拟实验台的诊断验证了系统的有效性。     

外测系统突发性故障的诊断方法研究

外测系统突发性故障的检测与诊断在航天测控中有十分重要的意义。基于动态测量数据的容错处理技术, 建立了三组实用的过程故障诊断方法： 无须建模的容错平滑器方法; 基于模型拟合的容错辨识方法; 基于状态空间模型的有界影响滤波方法。这些方法既可用于对测控网跟踪质量的事后分析也可用于（准） 实时在线处理。仿真计算结果显示, 这些方法不但能够以１００％ 的准确率检测出脉冲型故障, 还可快速有效地检测出任何形式的关联型故障, 准确率达９８％以上。     

用最小割集有效系数法确定航炮系统故障的诊断程序

本文提出用最小割集有效系数法确定航炮系统故障的诊断程序,以改进底事件有效系数法没有充分考虑底事件对系统故障发生的影响的缺点。     

一种模块级可降级重组双机系统的系统管理程序实现方法

分析了模块级可降级重组双机系统的有效组态数,并与双机系统级备份进行了比较。分析结果表明,随着冗余级别的降低,系统的可靠性有所改善,但系统的有效组态数将大大增加,这将导致系统管理程序的复杂化。文章介绍了该系统管理程序的设计准则,并对其中几个有特点的子程序作了简要说明。     

反作用控制系统推力器失效的外部检测与诊断

通过推进系统外部可测的姿态信息,利用强跟踪滤波器和多模预报估计器,研究了一类非线性系统常值阶跃型故障和间歇性故障的检测与分离问题。对关机失效,利用强跟踪滤波器获得故障效应的估计,检测逻辑采用改进的贝叶斯分类方法,依据推力器失效效应的方向性进行故障单元的分离;对开机失效,采用多模预报,根据相应残差向量范数的比较进行故障的即时无阈值判别,同时完成了故障后系统状态的重构问题。以一类大型航天器的反作用姿态控制系统为例,对其中出现的推力器失效进行了故障识别仿真研究,表明所提方法是有效的。     

液体火箭发动机故障数据库的设计与实现

讨论了液体火箭发动机故障数据库的设计思路及实现途径,以国内２１种液体火箭发动机试车及发射数据为基准,建立了初步的故障数据库,重点介绍了故障数据库的功能设计,结构设计和开发环境等内容。