Failure Prediction and Life Cycle Management of Power Equipment Based on Big Data Analysis
DOI:
https://doi.org/10.71222/4ptjr081Keywords:
failure prediction, life cycle management, power equipment, big data analysisAbstract
With the continuous development of China's industrial process, the social demand for electricity is increasing. Under the influence of new energy grid connection to build smart grid, the stability and security of the power grid system are particularly affected by the unstable characteristics of new energy. In view of the protection of the safe and stable operation of power, it is very necessary to monitor the information of power equipment, especially for the unpredictable power failure analysis is the key to ensure the safety of electricity use. However, due to the wide variety and huge quantity of power equipment and the frequent fluctuation of monitoring data affected by the natural environment, the amount of data of equipment information will grow rapidly in a short time, which has exceeded the ability of ordinary computers to handle. With the increasing size and complexity of power equipment, its fault prediction and life cycle management become very important. The emergence of big data analysis technology provides a new way to solve this problem. This paper first expounds the importance and status quo of power equipment fault prediction and life cycle management, then introduces the application principle and related technologies of big data analysis in this field, and then discusses the power equipment fault prediction method and life cycle management strategy based on big data analysis in detail. Finally, the effectiveness of this method is verified through practical cases. The future development is also prospected.
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Copyright (c) 2025 Kang Zhang, Joan Lazaro (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
