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Application of Self-Adaptive Wavelet Ridge Demodulation Method Based on LCD to Incipient Fault Diagnosis

机译:基于LCD的自适应小波脊线解调方法在早期故障诊断中的应用

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When a local defect occurs in gearbox, the vibration signals present as the form of multicomponent amplitude modulation and frequency modulation (AM-FM). Demodulation analysis is an effective way for this kind of signal. A self-adaptive wavelet ridge demodulation method based on LCD is proposed in this paper. Firstly, multicomponent AM-FM signal is decomposed into series of intrinsic scale components (ISCs) and the special intrinsic scale component is selected in order to decrease the lower frequency background noise. Secondly, the genetic algorithm is employed to optimize wavelet parameters according to the inherent characteristics of signal; thirdly, self-adaptive wavelet ridge demodulation wavelet for the selected ISC component is performed to get instantaneous amplitude (IA) or instantaneous frequency (IF). Lastly, the characteristics frequency can be obtained to identify the working state or failure information from its spectrum. By two simulation signals, the proposed method was compared with various existing demodulation methods; the simulation results show that it has higher accuracy and higher noise tolerant performance than others. Furthermore, the proposed method was applied to incipient fault diagnosis for gearbox and the results show that it is simple and effective.
机译:当齿轮箱中出现局部缺陷时,振动信号以多分量振幅调制和频率调制(AM-FM)的形式出现。解调分析是处理此类信号的有效方法。提出了一种基于液晶显示器的自适应小波脊解调方法。首先,将多分量AM-FM信号分解为一系列固有标度分量(ISC),并选择特殊的固有标度分量以降低低频背景噪声。其次,根据信号的固有特性,采用遗传算法对小波参数进行优化。第三,对选定的ISC分量进行自适应小波脊解调小波,得到瞬时幅度(IA)或瞬时频率(IF)。最后,可以获得特征频率以从其频谱中识别工作状态或故障信息。通过两个仿真信号,将该方法与现有的各种解调方法进行了比较。仿真结果表明,该算法具有较高的精度和较高的抗噪性能。将该方法应用于齿轮箱的早期故障诊断,结果表明该方法简单有效。

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