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故障诊断视角在智能化要求下的转变

CHANGE OF VIEW ANGLE OF FAULT DIAGNOSIS UNDER INTELLIGENTIZE
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摘要 故障诊断的背景是从预防事故开始,从事后事故反向倒推进入到对故障阶段的分析而产生的。通过对单一故障和耦合故障的分别研究,论证目前故障诊断的理论是在故障阶段介入和发展起来的,是对故障模型各自对立、并层层故障细分的规则方法,这种方法使研究对象成为一个发散的系统,并不可求解。采取实验室实验和现场故障的全过程跟踪,利用数据分析证明了故障是在转子系统内相互构建的动态环节,并随着故障状态时间“正进”的阶段变化而表现出相应的“同质”特征,并层层展开的过程。所以故障诊断理论的应用都应该还原于其所产生的统一整体并全过程的系统之中,要求转变故障诊断的方向,视界倒转,基于时间历程“正进”和故障性质“同质”的方法,在统一整体并全过程中掌握故障的主要发展规律,奠定智能诊断更坚实的理论基础。 The background of fault diagnosis is from the prevention of accidents, and from the reverse progression of accidents to the fault subdivision of the failure stage.By studying the single fault and the coupled fault separately, this paper demonstrates that the current theory of fault diagnosis has been intervened and developed in the fault stage, and it is a rule method of subdividing the fault models into opposite and parallel layers. This method makes the research object a divergent system and cannot be solved.The whole process of laboratory experiments and field failures is tracked, and data analysis proves that failures are dynamic links that build each other in the rotor system, and show the corresponding “homogeneous”characteristics with the change of the “forward” phase of the fault state time, and expand the process layer by layer.Therefore, the application of fault diagnosis theory should be restored to the unified whole and the whole process system, which requires changing the direction of fault diagnosis, reversing the horizon, and mastering the main law of fault development in the unified whole and the whole process based on the "forward" and "homogeneous" methods of time history and fault nature, so as to lay a more solid theoretical basis for intelligent diagnosis.
作者 胡军 HU Jun(School of Mechanical Engineering,University of Science and Technology,Bejing 100083,China;Angang Steel Company Limited Equipment Engineering Department,Anshan 114021,China)
出处 《机械强度》 CAS CSCD 北大核心 2022年第3期531-540,共10页 Journal of Mechanical Strength
关键词 反向倒推 故障细分 正进 同质 智能诊断 Reverse backwards Fault subdivision Forward Homogeneity Intelligent diagnosis
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