A Diagnosability-Integrated Design Approach Based on Graph Theory

IF 2.5 4区 综合性期刊 Q2 CHEMISTRY, MULTIDISCIPLINARY Applied Sciences-Basel Pub Date : 2023-09-07 DOI:10.3390/app131810080
Jiapeng Lv, Xianjun Shi
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Abstract

In order to take into account the influence of both system structure and diagnosis algorithm in the diagnosability design of the system, a diagnosability-integrated design method based on graph theory was proposed in this paper. Firstly, based on the diagnosability evaluation results, the difficulty of fault diagnosis was qualitatively analyzed using the K-means method, and the diagnosis plot of measurement point was drawn based on the analysis results. Secondly, the Bron–Kerbosch algorithm was used to extract the maximal cliques from the diagnosis plot of measurement point and determine the set of maximal cliques that can diagnose faults in the system based on the hypergraph edge coverage theorem. Finally, a cascade classifier was set on the maximal clique set to classify and identify faults in the system, and the performance of the diagnosis scheme was evaluated using the posterior probabilities of the classifier outputs combined with the Shannon entropy. At the same time, the method incorporated a measurement point update mechanism, which can decide whether to add additional measurement point according to the evaluation results of Shannon entropy to ensure better diagnosis effect. The results of simulation experiments showed that the fault diagnosis scheme designed by the method of this paper improved the correct rate of diagnosis results by 3.25 percentage points compared with other diagnosis schemes due to the simultaneous consideration of the structure of the system and the diagnosis method, and the diagnosis results of this paper were relatively stable in repeated experiments, which proved the practicality and effectiveness of the method of this paper.
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基于图论的可诊断性集成设计方法
为了兼顾系统结构和诊断算法对系统可诊断性设计的影响,提出了一种基于图论的可诊断性集成设计方法。首先,根据可诊断性评价结果,采用k均值法对故障诊断难度进行定性分析,并根据分析结果绘制测点诊断图;其次,利用brown - kerbosch算法从测点诊断图中提取最大团块,并基于超图边缘覆盖定理确定可诊断系统故障的最大团块集合;最后,在最大团集上设置级联分类器对系统故障进行分类和识别,并利用分类器输出的后验概率结合香农熵对诊断方案的性能进行评价。同时,该方法引入了测点更新机制,根据香农熵的评价结果来决定是否增加额外的测点,以保证更好的诊断效果。仿真实验结果表明,由于同时考虑了系统结构和诊断方法,采用本文方法设计的故障诊断方案与其他诊断方案相比,诊断结果的正确率提高了3.25个百分点,并且在重复实验中,本文的诊断结果相对稳定,证明了本文方法的实用性和有效性。
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来源期刊
Applied Sciences-Basel
Applied Sciences-Basel CHEMISTRY, MULTIDISCIPLINARYMATERIALS SCIE-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
5.30
自引率
11.10%
发文量
10882
期刊介绍: Applied Sciences (ISSN 2076-3417) provides an advanced forum on all aspects of applied natural sciences. It publishes reviews, research papers and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files and software regarding the full details of the calculation or experimental procedure, if unable to be published in a normal way, can be deposited as supplementary electronic material.
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