Pipeline Leakage Identification and Location Method Based on Line Spectrum Pairs and Cubic Interpolation Search

Abstract

The disclosure is a method for identifying and locating urban water supply pipe network leakage based on line spectrum pairs and cubic interpolation search, including: collection and transmission of leakage data; establishment of a random forest leakage identification model based on line spectrum pairs, and using The random forest leakage identification model identifies whether the urban water supply network is leaking; establishes a cubic interpolation search leakage location model based on the topology of the pipe network, and uses the leakage location model to determine the location of the urban water supply network leakage. The disclosure combines leakage signal processing technology, linear prediction technology, and heuristic search and positioning technology, so that leakage accidents of water supply pipe networks can be identified more accurately, and leakage points can be located with high precision. This method has high computational efficiency and strong practicability, and is suitable for use in large-scale and complex pipeline networks. The disclosure expands the research content of the existing pipeline network leakage identification and location method, and provides a basis for water companies to make scientific and reasonable decisions.

Description

technical field [0001] The disclosure relates to the technical field of leakage detection of urban water supply pipe networks, in particular to a method for identifying and locating leakage of urban water supply pipe networks based on line spectrum pairs and cubic interpolation search. Background technique [0002] With the impact of global climate change, as well as the acceleration of urbanization in my country and the development of high water-consuming industries, my country is facing more and more severe challenges of water resources, mainly manifested in the small amount of water resources per capita, uneven temporal and spatial distribution, and Resource allocation is difficult in these three aspects. The total amount of water resources in my country is about 2.8 trillion m 3 , according to my country's total population in 2015, the per capita water resources are only 2034m 3 , which is only 1 / 4 of the world's per capita water resources. The water supply network is ...

AI Technical Summary

Problems solved by technology

However, due to the complex topological structure of the actual water supply network, the leakage signal is easily affected by interference noise, which limits the practical application of existing pipeline leakage detection methods, and the accuracy of leakage identification is low.

Especially when there are various fixed interference noises at the detection site, the leakage flow rate is small, or the pipeline network structure is complex, and the pipeline information is unknown, the false alarm rate of leakage identification is high

At the same time, the existing detection methods do not fully consider the diversity and complexity of the pipeline network topology, resulting in low leakage location accuracy, high computational load, and a waste of limited computational resources.

[0004] Chinese patent CN109555979B discloses a water supply pipe network leakage monitoring method. This technical method uses a deep neural network model and a local search positioning model for leakage detection, but this technical method has a high computational load, and the search process is a kind of heuristic method. , the search efficiency is low, and it is not suitable for use in large-scale and complex pipe networks

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