Additive hazard model based on equipment age and health index

Autor: Yan-Guang Hu, Jian-Ping Chen, Kun-Yun Wang, Zhi-Jun Xu, Xiang-Kun Liu
Rok vydání: 2016
Předmět:
Zdroj: 2016 Prognostics and System Health Management Conference (PHM-Chengdu).
DOI: 10.1109/phm.2016.7819921
Popis: When describing the influence of equipment state to failure rate, traditional additive hazard model (AHM) has certain defects. Therefore, an improved AHM with equipment age and health index (HI) as variables is established, in which HI is used to describe the equipment state. In order to fit out the model's five parameters, a nonlinear constrained optimization problem was posed. A sampling algorithm based on Monte Carlo method was also proposed to obtain parameter ranges and initial values. When the sample data are complete, the parameters can be fitted out by Trust Region algorithm. Historical data of most equipment lack HI time series at present, so non-sequential Monte Carlo method is applied in the section of example analysis to obtain approximate solution of parameters. Fitting results of the example show that an AHM with practical significance can be acquired through the parameter fitting method. Compared with the results of two models with age as the only variable, sum of squares due to error (SSE) of the AHM decreases by at least 10%.
Databáze: OpenAIRE