Application for Analysis of the Multiple Coherence Function in Diagnostic Signal Separation Processes

Q4 Engineering
Mariusz Wądołowski, J. Pankiewicz, D. Markuszewski
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引用次数: 4

Abstract

Diagnosing the condition of the machine during its operation by non-invasive methods is most often reduced to measuring the acceleration of vibrations occurring on the housing, as close as possible to the observed element or changes in sound pressure in the immediate vicinity of the machine. For proper inference about the condition of a given machine element, the registered signals should be undisturbed by signals coming from other components and free from external interference. In the case of simple stationary machines, it is quite simple, but in the case of more complex systems, such as a car, which in addition is in motion, things get complicated In the available literature we find examples of the effectiveness of using ordinary coherence function to separate signals from two independent sources[1,2,3]. This work presents attempt to build an algorithm that uses signals from a multi-point measurement system to analyze multiple coherence functions, which allows to separate signals from various sources. It can then get diagnostic information from the signal thus separated. The effectiveness of the algorithm was tested on a model simulating signal mixing, and then using signal coherence function and knowledge of the transmittance function, the signals were separated.
多重相干函数分析在诊断信号分离过程中的应用
在机器运行过程中,通过非侵入性方法诊断机器的状况,通常被简化为测量外壳上发生的振动加速度,尽可能接近观察到的元件或机器附近声压的变化。为了正确推断给定机器元件的状态,所记录的信号应该不受来自其他元件的信号的干扰,并且不受外部干扰。在简单的固定机器的情况下,这是相当简单的,但在更复杂的系统的情况下,如汽车,除了运动,事情变得复杂。在现有的文献中,我们发现使用普通相干函数从两个独立的源分离信号的有效性的例子[1,2,3]。本研究尝试建立一种算法,该算法使用来自多点测量系统的信号来分析多个相干函数,从而可以分离来自不同来源的信号。然后,它可以从这样分离的信号中获得诊断信息。在模拟信号混频的模型上验证了该算法的有效性,然后利用信号相干函数和透光函数知识对信号进行分离。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Vibrations in Physical Systems
Vibrations in Physical Systems Engineering-Mechanics of Materials
CiteScore
0.70
自引率
0.00%
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0
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