Journal
MACHINES
Volume 10, Issue 12, Pages -Publisher
MDPI
DOI: 10.3390/machines10121174
Keywords
capacitor monitoring; electrolytic capacitors; advanced learning intelligence
Funding
- National Research Foundation of Korea (NRF) - Korea government (MSIT)
- Korea Electric Power Corporation
- [2020R1A2C1013413]
- [R21XA01-3]
Ask authors/readers for more resources
The reliability of electronic converters in industrialized areas is crucial, with capacitors being a critical component. This study proposes an estimation scheme using source current to assess capacitor health status and employs various advanced techniques to achieve this.
The reliability of the electronic converter is a vital concern in an industrialized area. Capacitors are critical in electronic converters and are more likely to fail than other electronic gears. Due to aging, the capacitor progressively loses its original quality and capacitance, and the equivalent series resistance escalates. Hence, condition monitoring is a fundamental procedure for evaluating capacitor health that affords prognostic repairs to guarantee stability in power networks. The ESR and capacitance of the capacitor are commonly employed to estimate the condition grade. This study proposes an estimation scheme that utilizes the source current to assess the health condition of an aluminum capacitor. Several advanced intelligence techniques are adopted to estimate the parameters of an AEC in a three-phase inverter system. First, different signals used as inputs, such as input power, capacitor current, voltage, and power, output current, voltage, and power, are analyzed using fast Fourier transform and discrete wavelet transform analysis. Then, various indexes of the analyzed signals, such as RMS, average, median, and variance, are used as the inputs in learning models to monitor the AEC's parameters. In addition, various input signals are combined to obtain the best combinations for capacitor monitoring. The estimated results prove that utilizing the source current combined with selected indexes improves the monitoring accuracy of the AEC's health status.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available