针对舰船电机轴承故障诊断技术难点,采用基于振动加速度共振解调频谱分析方法,通过不同程度外圈故障的对比实验,验证以振动加速度峭度系数和振动速度有效值为指标,可以提高异步电动机轴承故障诊断的有效性。
Aiming at the technical difficulties of motor bearing fault diagnosis, using resonant demodulated spectrum analysis in frequency domain of vibration acceleration, bearing outer race fault comparison tset with different severity, verify the effectiveness indicators of kurtosis for vibration acceleration and root mean square of vibration velocity, and improve the diagnosic effectiveness of bearing fault in induction motors.
2023,45(24): 128-131 收稿日期:2022-12-01
DOI:10.3404/j.issn.1672-7649.2023.24.023
分类号:TM307
基金项目:国家自然科学基金资助项目(51407193)
作者简介:周智勇(1972-),男,博士,教授,研究方向为电机的状态监测与故障诊断
参考文献:
[1] OLAV VAAG T, MAGNUS D. A survey of faults on induction motors in offshore oil industry, petrochemical industry, gas terminals, and oil refineries[J]. IEEE Transactions on Industry Applications, 1995, 31(5): 1186-1196
[2] CERRADA M, SÁNCHEZ R V, LI C, et al. A review on data-driven fault severity assessment in rolling bearings[J]. Mechanical Systems and Signal Processing, 2018, 99: 169-196
[3] 韩睿. 基于振动信号的电机轴承故障诊断方法研究[D]. 合肥: 合肥工业大学, 2020.
[4] 梅宏斌. 滚动轴承振动监测与诊断——理论·方法·系统[M]. 北京: 机械工业出版社, 1996.