| As a part of urban public facilities,urban water supply system plays an important role in ensuring the steady development of the urban economy and in improving the quality of life for the residents.However,due to the mismatch between the planning along with construction and maintenance of urban water supply system in the early stage and the rapid development of urbanization,as well as the impact of worn water pipelines and external environment,the leakage of urban water supply system is serious in China.As an old area of Shenyang,Shenhe District is facing an issue that its underground water supply system is severely aging.The leakage of water pipelines not only leads to the huge difference between production and sales for Shenhe Water Company,but also causes continuous complaints of pollution of drinking water and water supply shutdown due to pipeline rupture.Aiming at the present situation of water supply system in Shenhe District and the urgent requirement of improving leakage control,this paper makes some analysis and research about the leakage of residential areas which measure water supply independently,and strives to apply this leakage analysis method to the whole Shenhe District.Through the combination of pressure management and intelligent water supply system,the leakage control of water supply network for Shenhe Water Supply Company is strengthened.In this article,the author randomly selects four residential areas which measure independently in Shenhe District for research,acquires the data of the four residential areas by using intelligent tele-transmission system and analyzes it with data mining.Firstly,2:00 a.m to 4:00 a.m.is identified as the period of minimum flow rate at night through the analysis of daily water consumption data,and then the flow data of four residential areas during that period is recorded in 7 consecutive days.After processing the data by mathematical statistics,it is found that the night flow distribution of the selected residential area is approximately normal distribution.Based on the principle of normal distribution in statistics,the author chooses the best confidence level and confidence interval.Five confidence levels between 68.2% and 99.74% are selected for this analysis,and the corresponding confidence intervals are(μ-kσ,μ+kσ,k takes 1,1.5,2,2.5,3 respectively).Compared with the actual flow range,the best confidence level is 95.5% and confidence interval is(μ-2σ,μ+2σ).Thus,the minimum flow rate at night is calculated to determine the real leakage of the district,which provides forceful evidence for the following detection and maintenance of pipeline leakage.The author determines the pipeline leakage of DMA district through theanalysis above,and then finds and repairs the leak by using dichotomy method combining the minimum flow rate at night with the closing valve regionally.Based on the analysis of the leakage maintenance data from 2017 to 2018 of Shenhe Water Company,it concludes that material,diameter and age of the pipeline are the main factors affecting the leakage.According to the analysis results,Shenhe Water Company has formulated the transformation scheme of pipeline network.After implementation,the number of leakage maintenance cases has decreased by 45%.By digging into the pressure data from the water supply data,it is proved that the water leakage increases with the increase of the pressure in the pipeline network.After optimizing the Pressure of Water Supply Network with Intelligent Large Data,the pressure of Shunfa Complex is adjusted from 0.327 to 0.267 MPa through data analysis,actual operation and feedback from water supply user service center.It not only effectively controls the leakage of the pipeline network,but also reduces the energy consumption of water supply and the gap between production and sales in this area. |
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