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The Application of Lifting Wavelet Transform in the Fault Diagnosis of Reciprocating Air Compressor

机译:提升小波变换在往复式空气压缩机故障诊断中的应用

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Lifting algorithm gives a simple and effective method for the construction of orthogonal wavelet, which is no longer the Fourier transformation completely, but the obtained wavelet has all the advantages of the first generation. This article makes use of lifting wavelet transformation to de-noise the vibration signals of the air compressor sensor, and to diagnose effectively the fault of reciprocating compressor's rotor dynamic balance fault, bearings, blade and other faults due to wear and tear, then to extract the failure symptom. The results show that using the lifting wavelet to decompose and reconstruct the fault signals, the reconstructed low-frequency signals can reflect the fault signal mutation or the transient characteristics of dynamic balance effectively, and extraction of rotor dynamic balance and blade's characteristic frequency are evident, which provides a way to solve the engineering problems of incipient fault feature.
机译:提升算法给出了一个简单有效的施工正交小波的方法,这不再完全傅里叶变换,但是所获得的小波具有第一代的所有优点。本文利用提升小波变换来解除空气压缩机传感器的振动信号,并有效地诊断往复式压缩机转子动态平衡故障,轴承,叶片等由于磨损而导致的故障,然后提取失败症状。结果表明,使用提升小波分解和重建故障信号,重建的低频信号可以有效地反映动态平衡的故障信号突变或瞬态特性,以及转子动态平衡和刀片的特征频率是明显的,显而易见,这提供了解决初始故障特征的工程问题的方法。

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