Abstract of Power Plant Equipment Defect Trend Analysis Method Based on Apriori Algorithm

Fanqi Huang, LingLing Ming, Qiang Liu, Chuanhe Sun, Lixue Liang

2025

Abstract

As an important supporting industry in the national economy, the stability of equipment operation in the power industry is extremely important. However, defects in power plant equipment will always constrain power productivity. In this paper, this paper proposes a method for analyzing the defect trend of power plant equipment based on Apriori algorithm. Based on the collection and preprocessing of important data such as maintenance records and fault reports of power plant equipment, the Apriori algorithm is used to complete the mining of the correlation rules between equipment defects, and carry out in-depth analysis of these rules, so as to find the common factors that cause equipment defects and predict future trends. Finally, certain countermeasures should be put forward to facilitate the scientific improvement of power plant equipment management, improve the reliability of its equipment operation, and ensure the safety and stability of power production.

Paper Citation

in Harvard Style

Huang F., Ming L., Liu Q., Sun C. and Liang L. (2025). Abstract of Power Plant Equipment Defect Trend Analysis Method Based on Apriori Algorithm. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 116-121. DOI: 10.5220/0013536500004664

in Bibtex Style

@conference{incoft25,
author={Fanqi Huang and LingLing Ming and Qiang Liu and Chuanhe Sun and Lixue Liang},
title={Abstract of Power Plant Equipment Defect Trend Analysis Method Based on Apriori Algorithm},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT},
year={2025},
pages={116-121},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013536500004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT
TI - Abstract of Power Plant Equipment Defect Trend Analysis Method Based on Apriori Algorithm
SN - 978-989-758-763-4
AU - Huang F.
AU - Ming L.
AU - Liu Q.
AU - Sun C.
AU - Liang L.
PY - 2025
SP - 116
EP - 121
DO - 10.5220/0013536500004664
PB - SciTePress