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基于压力波相位特征的给水管网漏损识别及定位

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鉴于现有管网漏损检测方法在实际应用中存在的各种局限性,提出将管网瞬变频率响应的压力波相位,作为训练神经网络样本参数的漏损检测方法.通过阀门主动扰动产生漏损特征信号,利用瞬变流水力模型模拟潜在漏损工况,以此获取ANN检测模型训练所需的漏损样本.为提高检测准确率,采用遗传算法优化ANN模型结构;将所述理论及方法应用于小区典型供水管网的漏损检测,结果表明,该方法在单点漏损流量达到5%以上时,检测准确率普遍大于80%,且在管网规模较小、用水节点较少的情况下,检测精度更高.
Leakage identification and localization in water supply networks based on pressure wave phase characteristics
Considering the various limitations of existing pipeline leakage detection methods in practical applications,this paper proposes a leakage detection method that uses the phase of pres-sure waves from the transient frequency response of the pipeline network as the sample parameters for training a neural network.By actively disturbing the valves to generate leakage characteristic signals and simulating potential leakage conditions using a transient flow hydraulic model,the leak-age samples required for training the ANN detection model are obtained.To improve the detection accuracy,a genetic algorithm is employed to optimize the structure of the ANN model.The theory and methods described are applied to leakage detection in typical water supply networks of residen-tial areas.The results show that when the single-point leakage flow rate reaches more than 5%,the detection accuracy is generally greater than 80%,and the detection accuracy is higher in cases where the pipeline network scale is smaller and there are fewer water use nodes.

Water supply networkLeakage detectionFrequency responseValve disturbancePhase spectrum

李江云、罗靖苡、周飞

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武汉大学土木建筑工程学院,武汉 430072

供水管网 漏损检测 频率响应 阀门扰动 相位谱

2024

给水排水
亚太建设科技信息研究院,中国建筑设计研究院,中国土木工程学会

给水排水

CSTPCD北大核心
影响因子:0.8
ISSN:1002-8471
年,卷(期):2024.50(12)