Original scientific paper

https://doi.org/10.17559/TV-20240315001399

A Complex Device State Feature Selection Method based on Improved Hybrid Algorithm

Zhiyong Liu ; Department of Computer Technology, Hebei Vocational University of Industry and Technology, Shijiazhuang Hebei 050091, China
Liqing Rong ; Shijiazhuang Campus, Army Engineering University, Shijiazhuang 050003, China
Yu Zhang ; Shijiazhuang Campus, Army Engineering University, Shijiazhuang 050003, China, No.32181 Unit of PLA, Xian710032, China *
Bing Hao ; Shijiazhuang Campus, Army Engineering University, Shijiazhuang 050003, China

* Corresponding author.

Abstract

In this study, the authors aim to analyze how to improve equipment health state prediction by reducing the dimensionality of complex equipment condition monitoring features. In this paper, a hybrid algorithm that improves Filter and Wrapper based on mutual information is used, and simulated annealing and immunization algorithms are added to the search strategy for implementation. Experimental results show that the hybrid algorithm has advantages over the Filter and Wrapper algorithms alone, which not only improves the efficiency of feature selection while solving the feature redundancy problem well, but also improves the accuracy of state prediction greatly. This study is an effective means of fault prediction and health management intelligence, which can solve the problems of low accuracy and long delay of complex equipment health state prediction, and has a reference role in cost reduction and efficiency improvement for maintenance management departments.

Keywords

feature selection; health state prediction; hybrid algorithms; maintenance management; redundant features

Hrčak ID:

330535

URI

https://hrcak.srce.hr/330535

Publication date:

1.5.2025.

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