| 引用本文: | 高金良,陈健勋,郑成志,邓立群,李建宇.应用改进ICA-R算法的供水管网漏失量估计[J].哈尔滨工业大学学报,2021,53(5):42.DOI:10.11918/201906060 |
| GAO Jinliang,CHEN Jianxun,ZHENG Chengzhi,DENG Liqun,LI Jianyu.Leakage estimation of water supply network by improved ICA-R algorithm[J].Journal of Harbin Institute of Technology,2021,53(5):42.DOI:10.11918/201906060 |
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| 应用改进ICA-R算法的供水管网漏失量估计 |
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高金良1,陈健勋1,郑成志2,邓立群3,李建宇1
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(1.哈尔滨工业大学 环境学院,哈尔滨 150090; 2.广东粤港供水有限公司,广东 深圳 518021; 3.深圳市拓安信计控仪表有限公司,广东 深圳 518100)
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| 摘要: |
| 漏失量作为城市供水管网漏损量的主要组成成分,可作为管网漏损控制的重要参考指标.现有漏失量计算方法存在准确度不高,计算过程复杂等问题,而盲源分离法具有数据需求量少,分析结果准确特点.针对盲源分离中约束独立成分分析（CICA）算法在漏失量估计中存在误收敛,限制盲源分离法进一步应用的问题,提出利用改进的带参考信号的独立成分分析（改进ICA-R）算法进行供水管网漏失量估计思路.对目标函数选取、信号处理过程进行分析说明,同时设计算例管网模型并搭建漏失实验平台验证算法分离效果,并与快速独立成分分析（FastICA）算法处理效果进行对比.采用皮尔逊相关系数评价漏失量分离效果,利用平均相对误差评价改进ICA-R分离精度.结果证明,使用改进ICA-R算法分离漏失量所得相关系数维持在90%附近,平均相对误差维持在15%以内,优于FastICA算法,该方法避免加装大量计量仪表,降低了漏失量计算成本,可为漏失量计算提供参考,便于各水司有针对性地采取漏损控制措施. |
| 关键词: 供水管网 漏失量分离 盲源分离 改进算法 快速独立成分分析（FastICA） |
| DOI：10.11918/201906060 |
| 分类号:TU991 |
| 文献标识码:A |
| 基金项目:国家重点研发计划(2016YFC2,8YFC0406201-3)；国家自然科学基金(51778178)；黑龙江省自然科学基金(LH2019E044)；深圳市科技计划项目(JSGG20170823140113498,KJYY20170413170501147) |
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| Leakage estimation of water supply network by improved ICA-R algorithm |
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GAO Jinliang1,CHEN Jianxun1,ZHENG Chengzhi2,DENG Liqun3,LI Jianyu1
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(1.School of Environment, Harbin Institute of Technology, Harbin 150090, China; 2.Guangdong GDH Water Co., Ltd., Shenzhen 518021, Guangdong, China; 3.Shenzhen ANSO Measurement & Control Instrument Co., Ltd., Shenzhen 518100, Guangdong, China)
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| Abstract: |
| As the main component of the loss quantity of urban water supply network, the leakage quantity can be used as an important reference index for pipe network loss control. The existing calculation method of leakage is not accurate and the calculation process is complicated, whereas the blind source separation method needs less data and can achieve more accurate analysis results. However, the constrained independent component analysis (CICA) algorithm in blind source separation has the problem of misconvergence in the estimation of leakage quantity, which limits the further application of the blind source separation method. To solve this problem, an improved ICA-R algorithm was proposed to estimate the leakage of water supply network. The selection of objective function and signal processing were analyzed. An example pipe network was designed and the leakage experimental platform was built to verify the separation effect of the algorithm, and results were compared with the treatment effect of fast independent component analysis (FastICA). Pearson correlation coefficient was adopted to evaluate the effect of leakage separation, and average relative error was used to evaluate the separation accuracy of the improved ICA-R. Results show that the improved ICA-R algorithm could maintain the correlation coefficient of separation leakage at around 90% and the average relative error was within 15%, which was better than the FastICA algorithm. Instead of adding a large number of meters, the proposed method reduces the cost of calculation, and can provide reference for the calculation of leakage, so as to facilitate the water department to take targeted measures to control loss. |
| Key words: water supply pipe network leakage separation blind source separation improved algorithm fast independent component analysis (FastICA) |
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