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Performance evaluation of decomposition methods to diagnose leakage in a reciprocating compressor under limited speed variation

机译:诊断有限速度变化下往复式压缩机泄漏的分解方法的性能评估

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Reciprocating compressors (RCs) are used in pressure based applications to achieve high-pressure ratio. An efficient detection of a leakage in a RC by vibration based signal processing techniques can avoid high energy losses. Conventional signal processing methods used to examine the faults in non-stationary vibration signals have been proved to be inefficient. This paper aims to detect valve leakage in a RC by evaluating the performance of signal decomposition techniques i.e. empirical mode decomposition (EMD) and recently developed variational mode decomposition (VMD). These non-stationary signal processing techniques have been widely applied for condition monitoring of mechanical systems. In the present study, the vibration signals of RC at different levels of leaks under limited speed variation were acquired, decomposed and compared. To detect the fault features exhibiting leakage, the vibration signals were decomposed by EMD and VMD respectively. Post decomposition, FFT analysis along with RMS and kurtosis were evaluated from decomposed signals. The characteristics frequencies were clearly exhibited by VMD and the responses of kurtosis were also better with VMD. The fault detection performance of VMD was found better than EMD. (C) 2018 Elsevier Ltd. All rights reserved.
机译:往复式压缩机(RCs)用于基于压力的应用中,以实现高压比。通过基于振动的信号处理技术对RC中的泄漏进行有效检测可以避免高能量损失。已经证明,用于检查非平稳振动信号中故障的常规信号处理方法效率低下。本文旨在通过评估信号分解技术(即经验模式分解(EMD)和最近开发的变异模式分解(VMD))的性能来检测RC中的阀门泄漏。这些非平稳信号处理技术已广泛应用于机械系统的状态监视。在本研究中,获得,分解和比较了在有限速度变化下不同泄漏水平下的钢筋混凝土的振动信号。为了检测表现出泄漏的故障特征,分别通过EMD和VMD对振动信号进行分解。从分解后的信号评估后分解,FFT分析以及RMS和峰度。 VMD清楚地显示了特征频率,VMD的峰度响应也更好。发现VMD的故障检测性能优于EMD。 (C)2018 Elsevier Ltd.保留所有权利。

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