Analysis Of Water Use Law And Leakage Of Residential Districts Based On Internet Of Things

Through the Internet of Things system to monitor the water supply network of a residential district in a city,this paper obtains the water consumption and flow data of multiple communities.According to the current situation of water use in different communities,this paper analyzes the water use patterns and leakage of residential communities.First,this paper analyzes the impact of holidays,seasons and temperature factors on residents’domestic water use.In addition to the Spring Festival,the water use situation of residential districts during the working days and holidays is basically the same,but the morning peak hours of the holidays will be delayed by 2 hours,and the overall water consumption will increase by about 5%.The effect of seasons on water consumption is mainly reflected in the highest average water consumption in summer and the lowest in winter.Temperature is the main manifestation of seasonal changes,so this paper curves the relationship between temperature and water consumption to establish a predictive model.By analyzing the R~2 and F values of different fitting curves,the highest quadratic curve model of matching degree is obtained,and the prediction accuracy of the curve model is tested by using the water quantity and temperature data for one year.The results confirmed that the model has high accuracy with an average error of 3.46%and a standard deviation of 0.035.Subsequently,this paper analyzes the water use patterns of residential communities of different scales.The peak hours of water use in residential communities are not much different,and there is similarity.The differences are mainly concentrated in the following three aspects:the degree of sudden change in water peaks and valleys;the duration of water peaks;and the water flow from 9:00 to 16:00.In addition,the distribution of the occurrence time of the maximum hourly flow is greatly affected by the conditions of the residential district itself,but it is mainly concentrated in the morning and evening of the two water peak periods,and its probability of occurrence exceeds 80%.As the daily water consumption scale increases,the hourly variation coefficient of change gradually decreases,and water consumption tends to be stable.In addition,the hourly variation coefficient can help determine the leakage situation and qualitative leakage.The per capita water consumption of most residential communities in the city is lower than the city’s water quota standard.Therefore,this paper optimizes the pumping combination of the pumping station for a residential area.Finally,this paper uses the nighttime minimum flow analysis method to estimate the leakage flow of different residential quarters.According to the flow data of each minute of the residential district,the time range of the minimum flow of the district is determined to be 0:00-4:00.and then the high daily water consumption data is selected to draw the nighttime flow distribution curve,and the normal distribution curve is fitted.The nighttime approximate leakage flow and leakage water volume of the residential area are analyzed by selecting different confidence levels.After testing,when the confidence level is 95.5%,the estimated leakage flow rate of the residential district is the most accurate,the error rate is 2.6%,and the amount of data has little effect on the analysis results,thus increasing the applicability of the method.At the same time,this paper summarizes the leakage form of the water supply pipe network and the causes of leakage.