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国外文献 > 1.轴承 > 5. 监测与诊断 > 状态监测

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标 题： A Comparative Analysis of Monitoring Signals for Bearing Wear Detection in VSI-fed Induction Motors During Startup Transient
在启动瞬态期间，基于VSI供电感应电机轴承磨损检测的监测信号比较分析
作 者： T. A. Garcia-Calva
D. Morinigo-Sotelo
A. Garcia-Perez
R. J. Romero-Troncoso
关键词： Acoustic emissions  [声发射]
Bearing faults  [ 轴承故障]
Condition monitoring  [ 状态监测]
Fault detection  [ 故障检测]
Fault diagnosis  [ 故障诊断]
Induction motors  [ 感应电动机]
Spectral analysis  [ 光谱分析]
Time-frequency  [ 时频]
Transient analysis  [ 瞬态分析]
Vibration signals  [ 振动信号]
出版年： 2022
文集名： 2022 International Conference on Electrical Machines (ICEM 2022)
2022年国际电机会议（ICEM 2022）
会议名： 2022 International Conference on Electrical Machines (ICEM 2022)
2022年国际电机会议（ICEM 2022）
届 次：
摘 要： Bearing faults account for the great majority of failures in induction motors. Therefore, the academy and industry have placed a lot of importance on their detection to improve the efficiency of the motors and ensure the reliable operation of industrial systems. Recently, different approaches based on transient analysis have been proposed for improving diagnostic robustness and reducing false indicators of conventional steady-state analysis. This paper presents a comparative study of vibration, stator current, speed, and sound monitoring for bearing wear detection by using transient analysis. A high-resolution spectral analysis technique is applied to the monitoring signals in order to decompose them into the time-frequency plane. The decompositions are examined to evaluate and compare the transient features in each monitored variable for bearing fault detection. The obtained results have shown the feasibility of the startup transient analysis for bearing wear detection in induction motors using time-frequency characteristics.

轴承故障是感应电机失效的主要原因。因此，学术界和工业界高度重视轴承故障的检测，以提高电机效率并确保工业系统的可靠运行。近年来，为增强诊断鲁棒性并减少传统稳态分析中的误报指标，已提出多种基于瞬态分析的方法。本文通过瞬态分析对振动、定子电流、转速和声音等参数进行监测，用于轴承磨损检测，并开展对比研究。采用高分辨率频谱分析技术对监测信号进行处理，将其分解至时频平面。通过对各监测变量在瞬态过程中的特征进行分析与比较，评估其在轴承故障检测中的应用潜力。研究结果表明，利用时频特性对感应电机轴承磨损进行启动瞬态分析是可行的。
中文内容为网络AI翻译，专业术语未必准确，仅供参考。

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