Pipe network leakage warning method based on water consumption optimization prediction model

Abstract

The invention provides a pipe network leakage warning method based on a water consumption optimization prediction model. The pipe network leakage warning method comprises the following steps of obtaining original data; preprocessing historical water consumption sequences; analyzing mutual information between the preprocessed historical water consumption sequences; establishing a water consumptionprediction model when a support vector returns; and using a test set residual sequence to establish an isolated forest model, and judging the anomaly based on the real-time residual. According to thewater consumption optimization prediction model and the pipe network leakage warning method, the historical water consumption is processed based on L1 norm singular spectrum analysis interpolation, and the original sequence is restored as much as possible to improve the prediction accuracy; and the isolated forest algorithm is adopted for conducting abnormality identification, and fast and efficient online pipe network leakage warning can be achieved.

Description

technical field [0001] The invention relates to a pipeline network leakage alarm method, in particular to a pipeline network leakage alarm method based on a water consumption optimization prediction model. Background technique [0002] With the acceleration of urbanization, the scale and population of cities are increasing, and the few available water resources are also facing environmental pollution and other problems. The pressure and challenges on water supply companies are constantly escalating. According to expert statistics, 669 cities across the country are short of more than 7 billion cubic meters of water. If groundwater is not over-exploited, the urban water resource gap will reach more than 10 billion cubic meters. Phenomena have emerged one after another, and have become the biggest bottleneck restricting urban development. In contrast, the average leakage rate in major cities is as high as 15.7% (some organizations also say 17.92%), among which the underdevelop...

AI Technical Summary

Problems solved by technology

However, the existing technologies and methods have not been able to efficiently solve the above situation

Images