转子断条故障难以检测的原因在于工频分量与边频分量在频率上相隔较近且边频信号微弱，这一影响在低转差率时尤为严重。这种情况下，具有高频率分辨率的旋转不变信号参数估计技术(estimation of signal parameters via rotational invariance technique，ESPRIT)的估计效果也失去意义。因此，引入复调制技术，将工频分量搬移至0 Hz并予以滤除。同时，引入hilbert变换构成解析信号，利用其单边频谱性解决负频率分量问题。进而，提出了基于复调制滤波与ESPRIT的异步电动机转子断条故障检测新方法。仿真与实验验证了此方法的有效性。
英文摘要:
Broken rotor bars is difficult to detect the onset of failure because of the frequency components and frequency components separated in frequency closer, and this effect is particularly at low slip serious. In this case, even ESPRIT is ineffective. Therefore, the complex modulation techniques is introduced.the complex modulation techniques can remove the f1 component by shifting it to 0 Hz in frequency domain. And Hilbert Transform is introduced ,so the negative frequencies can exist and be meaningful. . Finally, a new BRB detection method is presented by combining complex modulation techniques and ESPRIT seamlessly, and then tested on an induction motor showing promising results.