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张西宁

教授 博士生导师 硕士生导师

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  • 学历: 博士研究生毕业
  • 学位: 博士
  • 职称: 教授
  • 毕业院校: 西安交通大学
  • 学科: 机械工程

论文成果

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

发布时间:2025-04-30
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发布时间:
2025-04-30
论文名称:
Predictability assessment of machine performance using an integrated signal redundancy and bootstrap
发表刊物:
International Conference on Sensing, Computing and Automation( Chongqing, PEOP)
摘要:
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.
合写作者:
Wen, Guangrui; Zhang, Xining; Qu, Liangsheng
是否译文:
发表时间:
2006-05-08