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A compound fault integrated diagnosis method for rotating machinery base on dimensionless immune detector

机译:基于无因次免疫检测器的旋转机械复合故障综合诊断方法

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Real-time and accuracy fault diagnosis is the key technique to realize timely effective maintenance and health management for rotating machinery, most faults of which are compound under actual working conditions. Many compound faults are coupled with each other, fuzzy, object and some complex characteristics so it is a bottleneck problem which is very tough to break through in fault diagnosis field. Early research results indicate that diagnosis with dimensionless parameters have got good effects in single fault for rotating machinery, but under simulating actual working state of compound faults, there are obvious overlap in ranges of dimensionless parameters calculated by vibration monitoring data of each compound faults, that is to say, it is hard to distinguish the ranges of dimensionless parameters of each fault, causing complexity of diagnosis rise, and the existing method is hard to deal with this problem. To solve the difficult problem, an online fusion fault diagnosis method for rotating machinery based on dimensionless immune detector and evidence reasoning (ER) is proposed. Experimental result demonstrates that the method can realize effectively real-time fault diagnose for rotating machinery and has high potential applications in real project.
机译:实时,准确的故障诊断是对旋转机械进行及时有效的维护和健康管理的关键技术,在实际工作条件下,大多数故障是复合的。复合故障多,模糊,对象多,特征复杂等特点相互耦合,是一个瓶颈问题,在故障诊断领域很难突破。早期的研究结果表明,无量纲参数的诊断对旋转机械的单个故障有很好的效果,但在模拟复合故障的实际工作状态下,根据各复合故障的振动监测数据计算出的无量纲参数范围存在明显的重叠,即也就是说,难以区分每个故障的无量纲参数范围,导致诊断的复杂性上升,现有的方法难以解决。针对这一难题,提出了一种基于无量纲免疫检测器和证据推理(ER)的旋转机械在线融合故障诊断方法。实验结果表明,该方法可以有效地实现旋转机械实时故障诊断,在实际工程中具有很高的应用潜力。

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