Basic Research on Machinery Fault Diagnosis—What is the Prescription
Basic Research on Machinery Fault Diagnosis—What is the Prescription
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DOI：
10.3901/jme.2013.01.063
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发表时间：
2013
影响因子：
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通讯作者：
Guobiao Wang
中科院分区：
文献类型：
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作者：
Guobiao Wang
(CID：0)自20世纪60年代以来，机械故障诊断作为一门新兴学科得到了迅速发展，其突出特点是理论研究与工程实际应用紧密结合。近半个世纪以来，机械故障诊断已发展到成熟阶段，在信号采集与传感技术、故障机理与征兆关系、信号处理与诊断方法以及智能决策与诊断系统等方面形成了较为完整的理论框架。本课题还取得了多项原创性的理论成果，如全息谱诊断、基于小波有限元的裂纹动态定量诊断等。同时，它在机械、冶金、石油化工、能源、航空等领域的工程应用中也得到了有效的应用，但仍存在一些不足之处，如故障机理研究空白、诊断方法有限、智能诊断设备薄弱等。因此，如何开展基础研究，探寻机械故障诊断的源头？未来的发展方向是什么？这些都是迫切需要解决的问题。在综述国内外机械故障诊断基础理论研究和工程实际应用现状的基础上，指出了机械故障诊断基础研究的不足和突破潜力。
(cid:0)From the 1960s, the machinery fault diagnosis has rapidly developed as an emerging subject, whose prominent feature lies in close combination of theoretical research and engineering practical application. Over the past half a century, the machinery fault diagnosis has been developed into its maturity, which results in relatively comprehensive theoretical framework on signal acquisition and sensing technology, fault mechanism and symptom relationship, signal processing and diagnosis method as well as intelligent decision and diagnosis system. This subject has also made several original theoretical achievements, such as holospectrum diagnosis and crack dynamic quantitative diagnosis with wavelet finite element. Meanwhile, it has been effectively implemented in a number of engineering applications, such as machinery, metallurgy, petrochemical industry, energy and aviation, etc. However, there still exist some shortcomings in this subject, such as research blanks in fault mechanism, limitation in diagnosis methods, weakness in intelligent diagnosis equipment. Therefore, how to develop the basic research and explore the source of machinery fault diagnosis? What are development directions in the future? These are urgent problems needed to be addressed. Based on the review of the recent researches on basic theory of machinery fault diagnosis and its engineering practical application at home and abroad, the deficiency of the basic research and the breakthrough potentials of machinery fault diagnosis are presented.