New fusion frameworks including explicit weighting functions for the remaining useful life prognostics

作者：

Highlights：

• An integrated fusion framework based on Gaussian process regression and IOWA operators has been introduced for assessing the remaining useful life;

• The combination procedure is built upon three weighting schemes including exponential, logarithmic and inverse functions;

• Extensive numerical simulations have been conducted with respect to various configurations;

• Outcomes of the proposed techniques have been evaluated with respect to the standard IOWA method and some related works in terms of error and computation time figures of merit.

摘要

•An integrated fusion framework based on Gaussian process regression and IOWA operators has been introduced for assessing the remaining useful life;•The combination procedure is built upon three weighting schemes including exponential, logarithmic and inverse functions;•Extensive numerical simulations have been conducted with respect to various configurations;•Outcomes of the proposed techniques have been evaluated with respect to the standard IOWA method and some related works in terms of error and computation time figures of merit.

论文关键词：Fusion,Gaussian process,Induced ordered weighted averaging,Analytical weighting function,Remaining useful life

论文评审过程：Received 4 March 2021, Revised 31 May 2021, Accepted 12 October 2021, Available online 16 October 2021, Version of Record 27 October 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116091