機械系統性能衰退預測與故障診斷之研究

A Study of Performance Degradation Predictions and Fault Diagnoses for Mechanical Systems

蔡有藤(Yuo-Tern Tsai) ； 陳宗傑(Chung-Chieh Chen) ； 廖哲賢(Zhe-Xian Liao)

《技術學刊》 27卷3期 (2012/09) Pp. 121-129

https://doi.org/10.29507/JT.201209.0002

摘要

機械在運轉情況下會發生漸進式的故障，初期出現異常徵兆時，若未及時處理可能造成後續嚴重故障，為及早偵測故障問題，宜建立預兆式維護作業。本文分析機械系統故障種類、故障問題，建立機台振動總量估算法及性能劣化管理方法，利用迴歸分析建立性能衰退預測模式，從機台振動變化預測機台性能劣化趨勢。此外，探討故障診斷層級，建立振動訊號量測診斷平台，發展振動時域訊號特徵擷取及故障診斷方法，提供機台性能出現劣化訊息時，進行性能評估及故障識別。實驗結果顯示，指數模型和量測數據具高關聯性，適合用於預估性能衰退；透過本文建立的相關軟硬體技術，可用於發展系統預兆式維護之基礎。

關鍵字

預兆式維護 ； 衰退預測 ； 故障診斷

並列摘要

Gradually induced faults may occur while machinery is running for a long time. This kind of fault may cause serious damage if the potential faults aren't remedied in time. To avoid a serious breakdown, prognostic maintenance is commonly adopted to treat this kind of problem. In this paper, the general types of faults of mechanical systems are first introduced. The predicted model of performance degradation is proposed based on the trend of the over-all values of vibration. The model was constructed using a regression analysis method in cooperation with measured vibration signals. The techniques of vibration-based diagnosing are also reported for identifying the fault sources when machinery is at the degraded condition. Fault identification is done by comparing time-domain signal characteristics with the set of fault patterns. A rotational test device is designed to implement signal measuring, performance degradation prediction and fault diagnosis. The experimental results show that the exponential model and the measured data have a high correlation, indicating that they can be used to predict the performance of a machine. Moreover, the studied results can be used as the basis for developing prognostic maintenance for a system.

並列關鍵字

prognostic maintenance ； degradation prediction ； fault diagnosis