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A Condition-Based Maintenance Method Through Control Charts Based on the Wavelet Energy Spectrum of Generators in Thermal Power Plants
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Type
Academic journal
Author
Suk Joo Bae (Hanyang University) Jin-ha Tae (Hanyang University) Chang-Sik Chung (Rozetatech) Youngjin Cho (Rozetatech) Hyung-Sool Oh (Kangwon National University) Sun Geu Chae (Hanyang University)
Journal
The Korean Reliability Society Journal of Applied Reliability Vol.22 No.4 KCI Accredited Journals
Published
2022.12
Pages
363 - 373 (11page)
DOI
10.33162/JAR.2022.12.22.4.363

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A Condition-Based Maintenance Method Through Control Charts Based on the Wavelet Energy Spectrum of Generators in Thermal Power Plants
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Abstract· Keywords

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Purpose: Failing power-plant equipment can cause significant harm to both human life and expensive infrastructure. Hence, both effective process-monitoring and failure-prediction techniques are needed to prevent catastrophic equipment failure. Existing time-based maintenance-methods are not enough to prevent catastrophic failures. In this work, a condition-based maintenance (CBM) method, which can predict failures using wavelet-based process-monitoring methods, is studied.
Methods: Both a wavelet spectrum analysis (with coefficients extracted from the wavelet transform) and a T² chart (with a slope and intercept based on a linear trend profile) are used in this study. The results are then embedded into a T² chart.
Results: The proposed methodology in this study is validated using data signals coming from thermoelectric power plants. Overall, the proposed monitoring method has a higher prediction performance using breakdown signals than the traditional T² chart-based maintenance method.
Conclusion: The investigated failure-prediction method is not only more successful but also more specific when abnormal signal patterns are detected before failures. Therefore, using the proposed method for condition-based maintenance can help save resources and prevent human losses.
#Condition Based Maintenance(CBM) #Control Chart #Power Plant #Wavelet Spectrum Analysis

Contents

1. Introduction
2. Wavelet Spectrum Analysis
3. T² Chart on the Monitoring of Linear Profile
4. Application to a Generator in a Power Plant
5. Conclusions and Future Research
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