Open Access

ARTICLE

Application of the CatBoost Model for Stirred Reactor State Monitoring Based on Vibration Signals

Xukai Ren^1,2,*, Huanwei Yu², Xianfeng Chen², Yantong Tang², Guobiao Wang^1,*, Xiyong Du²

1 School of Mechanical Engineering, Tianjin University, Tianjin, 300354, China
2 Quality Department, Shaoxing Key Laboratory of Special Equipment Intelligent Testing and Evaluation, Shaoxing, 312071, China

* Corresponding Authors: Xukai Ren. Email: ; Guobiao Wang. Email:

(This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)

Computer Modeling in Engineering & Sciences 2024, 140(1), 647-663. https://doi.org/10.32604/cmes.2024.048782

Received 18 December 2023; Accepted 20 February 2024; Issue published 16 April 2024

Abstract

Stirred reactors are key equipment in production, and unpredictable failures will result in significant economic losses and safety issues. Therefore, it is necessary to monitor its health state. To achieve this goal, in this study, five states of the stirred reactor were firstly preset: normal, shaft bending, blade eccentricity, bearing wear, and bolt looseness. Vibration signals along x, y and z axes were collected and analyzed in both the time domain and frequency domain. Secondly, 93 statistical features were extracted and evaluated by ReliefF, Maximal Information Coefficient (MIC) and XGBoost. The above evaluation results were then fused by D-S evidence theory to extract the final 16 features that are most relevant to the state of the stirred reactor. Finally, the CatBoost algorithm was introduced to establish the stirred reactor health monitoring model. The validation results showed that the model achieves 100% accuracy in detecting the fault/normal state of the stirred reactor and 98% accuracy in diagnosing the type of fault.

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Keywords

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