Research on failure prediction of industrial mechanical equipment based on decision tree model

Linjun Zhang

doi:10.1117/12.3054648

20 January 2025 Research on failure prediction of industrial mechanical equipment based on decision tree model

Linjun Zhang

Author Affiliations +

Proceedings Volume 13515, Fourth International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2024); 135150V (2025) https://doi.org/10.1117/12.3054648
Event: 4th International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2024), 2024, Chongqing, China

Abstract

This paper proposes a decision tree model for the failure prediction of industrial machinery and equipment, with the aim of addressing the various failure problems caused by the inevitable wear and aging that occurs during the operation of such machinery and equipment. In order to optimize the model, tuning parameters are also included. First, the characteristics of industrial machinery and equipment are examined for potential correlations, and appropriate indicators are identified for fault prediction. Subsequently, a decision tree-based machine learning method is employed to construct a fault prediction model for industrial machinery and equipment. The confusion matrix is utilized as an evaluation index to assess the model's efficacy, and the developed model is employed for prediction. Ultimately, the primary causes of each category of failure are investigated with the objective of effectively preventing industrial machinery and equipment failures, thereby enhancing the safety of the equipment. In comparison to the logistic regression model and the decision tree model prior to optimization, the prediction accuracy of the optimized decision tree model in this paper has been significantly enhanced, reaching up to 98.28%. Furthermore, the training speed of the proposed model is more rapid, which is anticipated to be utilized for actual industrial machinery and equipment failure prediction.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Linjun Zhang "Research on failure prediction of industrial mechanical equipment based on decision tree model", Proc. SPIE 13515, Fourth International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2024), 135150V (20 January 2025); https://doi.org/10.1117/12.3054648

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KEYWORDS

Decision trees

Data modeling

Instrument modeling

Mathematical optimization

Matrices

Education and training

Failure analysis

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