关键词: 数据驱动, 性能退化, 趋势预测, l1趋势滤波, 预测性维修

Abstract: It is difficult to track the occurrence and development of the performance degradation of rotating machinery by the conventional fixed threshold alarm method in the in-service condition monitoring system.To solve this problem,a data-driven rotating equipment performance degradation trend prediction model was constructed by using the raw normal vibration monitoring data and real-time monitoring data,and a method for predicting performance degradation trend based on the spectral distance index operating reliability curve l1 trend filtering was proposed.By dynamically tracking the point-by-point slope change of the trend filtering curve,the occurrence and development of performance degradation of rotating equipment could be detected.Using the Cincinnati Intelligent Maintenance Information System (IMS) center bearing experimental data and the rotor unbalance fault case data of a Chinese petrochemical company's centrifugal compressor to verify the model,the results showed that the data-driven performance degradation prediction model of rotating equipment only needed raw vibration data in normal operating conditions without relying on the prior knowledge of external experts,and could accurately predict and track the occurrence and development of the performance degradation trend of rotating equipment.

Key words: data-driven, performance degradation, trend prediction, l1 trend filtering, predictive maintenance