基于MCSA的异步电机测速系统研究

Research of induction motor speed measurement systems based on MCSA

在满足实时测速的前提下,直接对电机定子电流使用离散傅里叶变换,会带来频谱分辨率差、能量泄漏等问题,从而不能准确获取电机转速信息.为此,提出一种结合快速傅里叶变换、加窗函数、频谱细分和信号识别的综合算法.即将经过调理采样之后的信号加上布莱克曼窗或者凯塞窗,再对其进行复调制高分辨率的快速傅里叶变换,最后有效获取转子信号频率并求出电机速度.实验结果表明,本测速系统测量时间较短且具有较高的测量精度.

On the premise of measuring the real-time speed, the direct use of the discrete Fourier transform to motor stator current will bring the problems of a poor resolution of spectrum, energy leakage and so on, which will result in inaccurate motor speed information. Therefore, a combination algorithm which consisted of fast Fourier transform, window function, spectrum subdivision algorithm and signal recognition was proposed. Blackman window or Kaiser window was added to the conditioning sampling signal. It was then made to go through the fast fourier transform with high resolution zoom. Finally, we obtained the rotor signal frequency and calculated the motor speed. The experimental results show that the velocity measurement system is time- saving and accurate.