Academic Journal of Engineering and Technology Science, 2024, 7(2); doi: 10.25236/AJETS.2024.070225.
Mei Yuqing1, Zeng Hui1, Yang Jin1, Lei Haiwei1, Shi Puyue2
1China Yangtze Power Co., Ltd, No.1 Xiba Jianshe Road, Yichang City, Hubei Province, 443002, China
2Boya Gongdao(Beijing)Robot Technology Co., Ltd, Tongzhou District, Beijing, 101100, China
In order to accurately locate the leakage location of hydropower gates, an automatic location of multiple leakage points of hydropower gates based on approximate kernel density estimation algorithm is proposed. Based on the location structure of multiple leakage points of hydropower station gates, the early warning indicators for these leakage points have been determined. The abnormal warning features have been extracted and combined with the approximate kernel density estimation algorithm. The data execution database indicators have been set, and an automatic location normal processing structure has been built. The approximate kernel density estimation algorithm is dynamically processed to analyze the proportion of the consistency coefficient of the load distribution form of the inlet ball valve of the hydraulic turbine, so as to realize the automatic location of multiple leakage points of the hydropower station gate. The experimental results show that the flow at the starting point of valve control is gradually increasing, and the flow direction at the end point is gradually decreasing, which has good clustering effect. It can complete the clustering of different types of leakage point data, and the automatic positioning effect is good.
Approximate kernel density estimation algorithm; Gate of hydropower station; Multiple leakage points; Automatic location of leakage point
Mei Yuqing, Zeng Hui, Yang Jin, Lei Haiwei, Shi Puyue. Automatic location of multiple leakage points of hydropower station gate based on approximate kernel density estimation algorithm. Academic Journal of Engineering and Technology Science (2024) Vol. 7, Issue 2: 170-177. https://doi.org/10.25236/AJETS.2024.070225.
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