个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:西北工业大学
学位:博士
所在单位:机械工程学院
学科:测试计量技术及仪器. 精密仪器及机械. 机械制造及其自动化. 机械电子工程
电子邮箱:duanfh@dlut.edu.cn
Novel algorithms for sequential fault diagnosis based on greedy method
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论文类型:期刊论文
发表时间:2021-01-10
发表刊物:PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
卷号:234
期号:6
页面范围:779-792
ISSN号:1748-006X
关键字:D-matrix; greedy algorithm; information entropy; sequential fault diagnosis; test sequence
摘要:Test sequencing for binary systems is a nondeterministic polynomial-complete problem, where greedy algorithms have been proposed to find the solution. The traditional greedy algorithms only extract a single kind of information from the D-matrix to search the optimal test sequence, so their application scope is limited. In this study, two novel greedy algorithms that combine the weight index for fault detection with the information entropy are introduced for this problem, which are defined as the Mix1 algorithm and the Mix2 algorithm. First, the application scope for the traditional greedy algorithms is demonstrated in detail by stochastic simulation experiments. Second, two new heuristic formulas are presented, and their scale factors are determined. Third, an example is used to show how the two new algorithms work, and four real-world D-matrices are employed to validate their universality and stability. Finally, the application scope of the Mix1 and Mix2 algorithms is determined based on stochastic simulation experiments, and the two greedy algorithms are also used to improve a multistep look-ahead heuristic algorithm. The Mix1 and Mix2 algorithms can obtain good results in a reasonable time and have a wide application scope, which also can be used to improve the multistep look-ahead heuristic algorithm.