基于小样本学习的工业过程复合故障诊断方法综述

Liang Ma, Fuzhong Shi, Zijing Wu, Kai-xiang Peng
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引用次数: 0

摘要

在工业生产过程中,一旦发生故障,故障往往是复合故障,复合故障在不同的位置、不同的形式、不同的程度上发生。如何对具有耦合和传播特性的多故障进行诊断,提高系统的可靠性,保证工业过程的可靠运行,具有十分重要的意义。本文综述了复合故障的机理和症状表现。同时,分析和讨论了复合故障诊断方法的难点和研究现状,特别是基于少采样学习的复合故障诊断方法。并对其优缺点及研究方向进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey of Few-shot Learning-based Compound Fault Diagnosis Methods for Industrial Processes
Once the fault occurs in the industrial processes, the fault maybe always compound faults which take place in different locations, forms, and degrees. How to diagnose the multiple faults with coupling and propagation characteristics, enhance the reliability of the system, and ensure the reliable operation of industrial processes is very important. In this paper, a survey on mechanism and manifestation of symptoms for compound faults is given. Meanwhile, difficulties and research status of compound fault diagnosis methods, especially the few-shot learning-based methods are analyzed and discussed. Moreover, the advantages, disadvantages, and research directions are mentioned.
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