A Method for Estimating Abnormal Environmental Stress of Wear-out Products Assisted by Swarm Intelligence Algorithm

SHENG Pei; LI Wei; CUI Weicheng; GONG Jing

doi:10.7643/ issn.1672-9242.2026.02.014

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Equipment Environmental Engineering ›› 2026, Vol. 23 ›› Issue (2) : 123-129. DOI: 10.7643/ issn.1672-9242.2026.02.014

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A Method for Estimating Abnormal Environmental Stress of Wear-out Products Assisted by Swarm Intelligence Algorithm

SHENG Pei¹, LI Wei¹, CUI Weicheng¹, GONG Jing^2,*

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Abstract

The work aims to achieve high-precision estimation of reliability distribution parameters for wear-out products in dynamic environments and accurate localization of the start point of environmental stress anomalies, thereby enhancing product storage reliability and reducing failure risks. Firstly, a comparative analysis was conducted on the performance of four types of swarm intelligence algorithms of Artificial Bee Colony, Grey Wolf Optimizer, Particle Swarm Optimization, and Ant Colony Optimization in the task of estimating Weibull distribution parameters, leading to the selection of the optimal algorithm. Secondly, the sliding window method was employed to process the full-life-cycle cumulative failure probability data of the products segment by segment, constructing dynamic sequences of shape and scale parameters changing over time. Finally, based on the slope characteristics of line segments formed by parameters from adjacent windows, the K-means clustering algorithm was applied to identify mutation nodes in the parameter change patterns. Simulation data indicated that the Grey Wolf Optimizer performed best in Weibull parameter estimation. Application results with measured data showed that the classification method based on the sliding window and K-means could accurately identify the index point where the parameter slope mutated, and this point highly coincided with the actual start time of the environmental stress anomaly. The integrated scheme developed in the research effectively estimates product reliability parameters in dynamic environments and accurately locates environmental stress anomaly points, compensating for the shortcomings of traditional analytical models in adapting to dynamic parameter drift and establishing anomaly correlation mechanisms. It provides reliable technical support for the dynamic reliability analysis of wear-out products and the adjustment of storage management strategies.

Key words

swarm intelligence algorithm / wear-out products / parameter estimation / environmental anomaly / Weibull distribution / K-means algorithm / dynamic reliability / full-life-cycle data

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SHENG Pei, LI Wei, CUI Weicheng, GONG Jing. A Method for Estimating Abnormal Environmental Stress of Wear-out Products Assisted by Swarm Intelligence Algorithm[J]. Equipment Environmental Engineering. 2026, 23(2): 123-129 https://doi.org/10.7643/ issn.1672-9242.2026.02.014

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