2025-04-30

Predictability assessment of machine performance using an integrated signal redundancy and bootstrap

International Conference on Sensing, Computing and Automation( Chongqing, PEOP)

Predicting machine performance based on current states and historical data has been a challenging issue in a predictive maintenance. Traditional methods mainly focused on developing prediction algorithms, rather than pay attention to the understanding of the data. This paper presents an innovative method to quantitatively evaluate the predictability of machinery performance based on information redundancy and a statistical simulation technique. The predictability of a series of simulated signals and practical vibration data were analyzed and a high-precision prediction was achieved by computing the redundancies of these sample sequences. The results show that evaluation tool can present a clear indication of machine performance predictability and therefore can guide the development and selection of prediction algorithms for predictive maintenance.

Wen, Guangrui; Zhang, Xining; Qu, Liangsheng

No

2006-05-08