Adaptive Online Extraction Method of Slot Harmonics for Multiphase Induction Motor

Author:

Yu Jie,Zhang Youjun,Shen Hongyuan,Zheng Xiaoqin

Abstract

The accurate extraction and analysis of slot harmonics caused by slotting in an induction motor are important for the motor’s performance evaluation and state monitoring. However, the frequency distribution of rotor slot harmonics (RSHs) varies along with the operating states of the motor, such as motor speed and slip ratio, and the voltage and current signals of the motor only contain small-amplitude RSHs compared with other harmonics; both make it difficult to extract and analyze the RSHs accurately online. While offline extraction and filters with constant parameters are mainly utilized in available works, a novel adaptive extraction method for RSHs in a multiphase induction motor is proposed here to realize online RSH extraction under different speed and load conditions. In this paper, the RSHs in the multiphase induction motors are firstly modeled by using the magnetic potential permeability method, and the influence of a skewed rotor on RSHs is analyzed through a multisection method. Then, an adaptive extraction method of RSHs is proposed, which can effectively realize the online processing of RSHs of stator current. Finally, the experimental platform of a nine-phase induction motor has been used to verify the effectiveness of the proposed method under different speeds and load conditions, with a relative error of less than 1% in identifying the RSH frequency distribution.

Funder

Natural Science Foundation of Shandong Province

Key Project of Innovative Teaching Laboratory of Qingdao University in 2020

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. New Schemes of Induction Motor Electric Signature Analysis for Gear Fault Diagnosis: A Comparative Study;IEEE Transactions on Power Electronics;2024-03

2. Instantaneous speed estimation of induction motor by time-varying sinusoidal mode extraction from stator current;Mechanical Systems and Signal Processing;2023-10

3. Online Efficiency Prediction of Induction Motor using Model Reference Adaptvie Method;2022 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific);2022-10-28

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