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基于CUSUM方法的集中供热管网泄漏故障诊断 被引量:1

Fault diagnosis leakage of district heating pipelines based on CUSUM method
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摘要 为了有效降低集中供热管网泄漏故障发生率,减轻大量管内介质泄漏导致的经济损失和环境破坏,文章基于变点理论中的累积和(Cumulative Sum,CUSUM)方法以及集中供热管网泄漏仿真模型,提出了一种新的集中供热管网泄漏故障诊断方法。针对实验室现有的集中供热实验管网,开发了相应的算法程序,并诊断分析了供热实验管网的泄漏工况。结果表明:在所有工况条件下,管网泄漏发生后2.2 s即可触发报警信号;最大泄漏流量的计算值与实验值相对误差为1.6%,对应计算所得泄漏流量最大的时刻也接近实际时间;泄漏位置诊断准确率随着误差距离增大而升高,当误差距离≤6 m时,其准确率为73.1%。 In order to effectively reduce the incidence of leakage fault of district heating pipelines,and reduce the economic loss and environmental damage caused by the leakage of a large number of pipeline mediums,based on the CUSUM method in the change point theory and the leakage simulation model disctrict heating pipelines,a new method for fault diagnosis of leakage of district heating pipelines is proposed.Based on the existing district heating experimental pipelines in the laboratory,this paper developes the corresponding algorithm program,and diagnoses and analyzes the leakage conditions of the heating experimental pipelines.The result shows,under all working conditions,the alarm signal can be triggered 2.2 s after the leakage of the pipe network.The relative error between the calculated value of the maximum leakage flow rate and the experimental value is 1.60%.And the experimental time when the calculated leakage flow is the largest is also close to the actual time.The accuracy of leakage location diagnosis increases as the error distance increases,and when the error distance≤6 m,the accuracy rate is 73.1%.
作者 周守军 张国正 刘臣 林旭东 曹长红 ZHOU Shoujun;ZHANG Guozheng;LIU Chen;LIN Xudong;CAO Changhong(School of Thermal Energy Engineering,Shandong Jianzhu University,Jinan 250101,China;Baiyanghe Power Plant,Huaneng Shandong Power Generation Co.,Ltd.,Zibo 255200,China;Zibo Boshan District Heating Company,Zibo 255200,China)
出处 《山东建筑大学学报》 2023年第5期48-57,共10页 Journal of Shandong Jianzhu University
基金 山东省重点研发计划项目(2019GSF111037) 山东省自然科学基金项目(ZR2020ME189)。
关键词 集中供热 CUSUM方法 泄漏仿真模型 实验管网 故障诊断 district heating CUSUM method leakage simulation model experimental pipeline fault diagnosis
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