基于PCA的电机顺序加速老化熵分析

T. Senguler, E. Karatoprak, E. Ayaz, S. Gullulu, S. Seker
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引用次数: 3

摘要

本文的目的是通过测量感应电机轴承槽纹老化的振动信号来监测轴承损伤的发展。采用主成分分析(PCA)对加速度计振动信号进行分析,并计算出振动信号的谱图来表征老化的进程。同时,利用主成分分析结果,计算主成分评分的熵值,并采用指数法和多项式法建立老化过程模型。因此,确定最大熵值来表示临界老化水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Entropy Approach Using PCA for Sequential Accelerated Aging Processes in Electrical Motors
The aim of this paper is to monitor the bearing damage developing by vibration signals measured from induction motors subjected to bearing fluting aging. The vibration signals taken from the accelerometers were analyzed by principal component analysis (PCA) and computed their spectra to denote the progressing of the aging. Meanwhile, using the principal component (PC) results, the entropy values based on the PC scores were computed and aging process models were established by the exponential and polynomial approach. Hence, maximum entropy value was determined to indicate the critical aging level.
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