水利学报2025，Vol.56Issue(4)：488-498,11.DOI:10.13243/j.cnki.slxb.20240396
基于SSA-BP的自压灌溉管网泄漏定位模型研究
Research on leakage positioning model of self-pressure irrigation pipe network based on SSA-BP
摘要
Abstract
Given the limitations of the existing self-pressure pipe network leakage location methods,this paper ana-lyzes the impact of the spatial distribution of leakage points on the pressure changes in the pipe network under various leakage conditions by constructing a hydraulic model of self-pressure irrigation pipe network.A self-pressure irriga-tion pipe network leakage location model based on the SSA-BP neural network is proposed.The nonlinear relationship between the leakage point position and the pressure change rate of the monitoring point is established and compared with the traditional BP neural network and GA-BP neural network.The results show that the SSA-BP model has higher prediction accuracy for the horizontal and vertical coordinates of the predicted leakage position,and the deter-mination coefficients R2 reach 0.991 and 0.993,respectively,which are 0.90％,1.71％and 3.32％,3.12％higher than those of the BP model and the GA-BP model,respectively.The root mean square error(RMSE)and the mean absolute percentage error(MAPE)are 29.45 and 0.88％,and 26.76 and 0.74％,respectively,obviously lower than those of the latter two.The prediction error is reduced dramatically,showing better generalization ability.In the random simulation leakage location of the case pipeline network,the average prediction deviation of the SSA-BP model under large-scale leakage conditions is only 39.93 m,which is 67.66％and 26.99％lower than that of the BP model and the GA-BP model,respectively.The average prediction deviation of the SSA-BP model under small-scale leakage conditions is only 66.17 m,which is 53.70％and 37.54％lower than that of the BP model and the GA-BP model,respectively,which further proves that the SSA-BP model has higher accuracy and stability.This paper is not only essential for studying the spatial distribution of leakage points in response to the pressure changes in the pipe net-work and for selecting pressure monitoring points reasonably,but also for providing a reliable basis for the leakage location of the self-pressure irrigation pipe network.关键词
自压灌溉管网/泄漏定位/SSA-BP神经网络/水力模型/压力变化率Key words
self-pressure irrigation pipe network/leak location/SSA-BP neural networks/hydraulic model/pres-sure change rate分类
农业工程引用本文复制引用
张辉,刘宁宁,王振华,张金珠,李淼,尹飞虎..基于SSA-BP的自压灌溉管网泄漏定位模型研究[J].水利学报,2025,56(4):488-498,11.基金项目
国家重点研发计划课题(2022YFD1900405) （2022YFD1900405）
兵团农业GG项目(2023AA305) （2023AA305）
石河子大学科技攻关计划项目(KJGG202405) （KJGG202405）
兵团科技成果转化引导计划项目(2023BA003) （2023BA003）
