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Incipient Feature extraction based on singular value decomposition and undecimated lifting scheme packet

机译:基于奇异值分解和未传定提升方案包的初期特征提取

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Vibration signal measured from machinery is often heavily interfered with by various noises. This paper puts forward a joint method to reduce noises, acquire the enhanced signals from the decomposed subbands and extract the incipient fault features. First, the signals are denoised by the method of singular value decomposition (SVD). Then, the denoised signal is decomposed into four layers by undecimated lifting scheme packet (ULSP). Finally, all 16 subbands of the fourth layer are plotted and the rich-fault-information subbands are used to extract incipient features. The effectiveness of the proposed method is validated with simulated data. Furthermore, in the processing of engineering signal, the weak feature caused by the fault of a valve in reciprocating compressor is bulged and the early failure of spring is detected.
机译:由机械测量的振动信号通常由各种噪声严重干扰。本文提出了一个接合方法来减少噪声,从分解的子带中获取增强的信号并提取初始故障特征。首先,通过奇异值分解(SVD)的方法来解析信号。然后,通过未传定的提升方案分组(ULSP)将去噪信号分解成四层。最后,绘制了第四层的所有16个子带,并且富有故障信息子带用于提取初期特征。提出方法的有效性验证了模拟数据。此外,在工程信号的处理中,由往复式压缩机中的阀故障引起的弱特征被凸出,并且检测到弹簧的早期失效。

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