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Modulation Signal Bispectrum Analysis of Motor Current Signals for Condition Monitoring of Electromechanical Systems

机译:电机电流信号的调制信号BISPectrum分析机电系统状态监测

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Induction motor is one of the most widely used prime drivers and electric energy consuming devices in industry. Accurate and timely diagnosis of faults in motors will help to maintain their operating under optimal status and avoid excessive energy consumption and severe damages to systems. In this study, instantaneous motor current and voltage signals (IMCVS) is analyzed by an advanced Modulation Signal Bispectrum (MSB) method to achieve accurate demodulations of Frequency Modulation (FM) and Amplitude Modulation (AM) by minimizing noise influence and enhancing modulation characteristics simultaneously. Firstly, the modulation effects due to motor faults and downstream mechanical components were modelled, thus finding the interaction between AM and FM effect and hence developed a scheme to use the signature of AM and FM jointly for accurate fault diagnosis. Then experimentations were carried out to verify the performance of the proposed scheme in detecting and diagnosing common mechanical faults including Shaft Misalignments (SM), Motor Rotor Broken Bar (BRB), Stator Resistance Imbalance (SRI) and compound BRB with SRI
机译:异步电动机是业界最广泛使用的主要驱动和电动耗能设备之一。在电机故障的准确和及时的诊断将有助于保持他们在最佳状态运行,并避免过多的能量消耗和严重损坏系统。在这项研究中,瞬时马达电流和电压信号(IMCVS)由高级调制信号双谱(MSB)方法分析通过同时最小化噪声的影响和提高调制特性以实现频率调制(FM)和调幅(AM)的精确解调。首先,由于电机故障和下游的机械部件的调制效果进行建模,从而找到的AM和FM效果,因此开发了一种方案使用AM和FM的共同签名进行准确的故障诊断之间的相互作用。然后性实验进行了验证在检测和诊断常见机械故障,包括轴未对准(SM),电机转子断条(BRB),定子电阻失衡(SRI)中并用SRI化合物BRB所提出的方案的性能

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