Model selection for degradation modeling and prognosis with health monitoring data

作者：Nguyen Khanh T P^*; Fouladirad Mitra; Grall Antoine

来源：Reliability Engineering & System Safety, 2018, 169: 105-116.

DOI：10.1016/j.ress.2017.08.004

• Model selection
• Prognostic prediction
• Residual life prediction
• Degradation process
• Levy process

Health monitoring data are increasingly collected and widely used for reliability assessment and lifetime prediction. They not only provide information about degradation state but also could trace failure mechanisms of assets. The selection of a deterioration model that optimally fits in with health monitoring data is an important issue. It can enable a more precise asset health prognostic and help reducing operation and maintenance costs. Therefore, this paper aims to address the problem of degradation model selection including goals, procedure and evaluation criteria. Focusing on continuous degradation modeling including some currently used Levy processes, the performance of classical and prognostic criteria are discussed through numerous numerical examples. We also investigate in what circumstances which methods perform better than others. The efficiency of a new hybrid criterion is highlighted that allows to take into account the information of goodness-of-fit of observation data when evaluating prognostic measure.

• 出版日期2018-1