| 引用本文: | 董深,吕谋,盛泽斌,李璞.基于遗传算法的供水管网反问题漏失定位[J].哈尔滨工业大学学报,2013,45(2):106.DOI:10.11918/j.issn.0367-6234.2013.02.019 |
| DONG Shen,L Mou,SHENG Zebin,LI Pu
.Inverse transient leakage location of water supply network based on genetic algorithm[J].Journal of Harbin Institute of Technology,2013,45(2):106.DOI:10.11918/j.issn.0367-6234.2013.02.019 |
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| 摘要: |
| 为有效减少城市供水管网漏失,快速、准确确定漏失点的位置及漏失水量,进而实现管网漏失的实时诊断,提出了基于遗传算法的供水管网反问题漏失定位方法．在构建基于反问题分析的微观基础水力模型的基础上,通过对管网漏失量与压力变化的相关性分析,以漏失点所在管网中的位置及漏失点相应的漏失水量为变量,以漏失发生时管网压力监测点的监测值与模拟值的差值最小为目标,建立了基于遗传算法的供水管网反问题漏失定位模型．通过3种工况下的漏失模拟计算,结果表明:所建立的反问题漏失定位模型可以有效地定位漏失点并优化预测漏失水量,可合理高效地制定漏失点检测与定位方案． |
| 关键词: 供水管网 漏失定位 漏失量优化分析 遗传算法 反问题分析 |
| DOI：10.11918/j.issn.0367-6234.2013.02.019 |
| 分类号: |
| 基金项目:国家自然科学基金资助项目(51078193);国家重大水专项课题(2009ZX7422-006). |
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| Inverse transient leakage location of water supply network based on genetic algorithm |
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DONG Shen, L Mou, SHENG Zebin, LI Pu
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(Institute of Environmental and Municipal Engineering, Qingdao Technologicl University, 266033 Qingdao, Shandong,China)
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| Abstract: |
| To reduce the network leakage effectively and determine the position of the leakage point or region and leakage volume quickly and exactly, the inverse transient leakage location technology based on genetic algorithm is proposed to realize the real-time leakage diagnosis of water supply network. First of all, the microscopic model is established as the basic hydraulic model based on inverse problem analysis. By correlation analysis of the network leakage and pressure variation, the inverse transient leakage location model of water supply network based on genetic algorithm is established. The model takes the position of the leakage point and the corresponding volume as variables, takes the minimum difference between the monitoring value and simulation value of pressure monitoring points when leakage occurs as target. By simulating three leakage modes, the practicality and effectiveness of the inverse transient leakage location model of water supply network are verified. The research provides important basis for making program of leakage detection and location effectively. |
| Key words: water supply network leakage location optimization analysis of leakage volume genetic algorithm inverse transient analysis
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