Real-time data analysis method and device for water pipe network

Abstract

The invention discloses a data real-time analysis method and device of a water pipe network, wherein the method includes the following steps: obtaining the current flow data x to be identified i ;judgment x i and the previous identified traffic data x i‑1 Whether the first difference of is less than or equal to the preset threshold, if yes, wait for the output; otherwise, judge the next flow data x to be identified i+1 and x i‑1 Whether the second difference of is less than or equal to the preset threshold, if yes, wait for the output after correction; otherwise, judge x i with x i+1 Whether the third difference of is less than or equal to the preset threshold, if yes, wait for the output; otherwise, check x i‑1 、x i and x i+1 If the trend meets the preset conditions, wait for the output, otherwise wait for the output after correction, and after reaching the output cycle, obtain and output the analysis results. The method quickly and accurately identifies any abnormality in the operation status of the water pipe network through the real-time change law of the flow, thereby effectively improving the accuracy and real-time performance of data analysis, thereby effectively ensuring the safe operation of the water pipe network, and is simple and easy to implement.

Description

technical field [0001] The invention relates to the technical field of data analysis, in particular to a method and device for real-time data analysis of a water pipe network. Background technique [0002] At present, there are more and more technologies at home and abroad that use front-end sensors to monitor pipe network indicators. However, due to the complex change rules and large fluctuation range of flow indicators, it is impossible to quickly identify abnormal situations by setting threshold ranges. The abnormal fluctuation of the flow will inevitably cause the change of the pipeline pressure. However, the pressure fluctuation is relatively stable and the fluctuation range is not obvious. Most of the real-time monitoring technologies through the pipeline pressure index can only monitor the obvious pressure fluctuation caused by the abnormal flow. Frequent abnormal situations cannot be monitored and identified. [0003] However, most of the hidden dangers of the water...

AI Technical Summary

Problems solved by technology

[0002] At present, there are more and more technologies at home and abroad that use front-end sensors to monitor pipe network indicators. However, due to the complex change rules and large fluctuation range of flow indicators, it is impossible to quickly identify abnormal situations by setting threshold ranges.

The abnormal fluctuation of the flow will inevitably cause the change of the pipeline pressure. However, the pressure fluctuation is relatively stable and the fluctuation range is not obvious. Most of the real-time monitoring technologies through the pipeline pressure index can only monitor the obvious pressure fluctuation caused by the abnormal flow. Frequent abnormal situations cannot be monitored and identified

[0003] However, most of the hidden dangers of the water pipe network are caused by the long-term accumulation of such small and frequent abnormalities that cannot be monitored and identified in time. Once the structural strength cannot bear the pressure of the pipeline, accidents such as pipe bursts will occur, and even secondary derivative disasters will occur. happened

For example, abnormal flow fluctuations caused by large users’ irregular water use, switching valves, and large-flow flushing of pipelines generally last for a short time and have a small impact range. The existing pressure monitoring technology cannot monitor and identify all real abnormalities, and has low accuracy. , large error and other disadvantages

Images