A Method of Abnormal/Fault Location Detection Based on Binary Tree Model

Abstract

The invention discloses an abnormality / fault location detection method based on a binary tree model. First, the physical layout of the industrial pipe network is transformed into a binary tree structure model, and the detected data is stored in a corresponding node of the binary tree; secondly, according to the properties of the binary tree , and the correlation of information between each detection node, using the flow conservation property of the industrial pipe network data flow, the calculation of the data flow of the undeployed sensor node is realized; thirdly, according to the actual measurement value and calculation of the sensor deployed at the detection point of the industrial pipe network The relationship between values, analyze the operating conditions of the industry, and judge its abnormal / fault type; finally, use the structural characteristics of the binary tree model to analyze the abnormal / fault location of the industrial pipe network and give an early warning. The inventive system is simple in design and low in cost, breaks through the detection of abnormalities / faults by traditional manual inspection methods, and realizes real-time detection of industrial pipe network working conditions in real time under the condition of limited detection points.

Description

technical field [0001] The invention relates to an abnormal / fault location detection method based on a binary tree model. According to the data detected by deployed limited sensors, using the properties of a binary tree, the data values ​​of undeployed sensor nodes are inverted and calculated; according to the flow conservation characteristics of industrial pipeline data streams , the relationship between the actual detection data and the calculated data value of the deployment detection point, online judgment of the fault type, and the corresponding location of the fault. This technology breaks through the limitations of the traditional manual inspection method for fault detection and the time lag of data, and realizes the monitoring of pipeline operating conditions under the condition of limited detection points, which belongs to the technical field of fault detection for industrial pipeline network conditions. Background technique [0002] Pipes are widely used in residen...

AI Technical Summary

Problems solved by technology

The negative pressure wave method is more effective in detecting sudden large-scale leaks, but for persistent and small-scale leaks, negative pressure waveforms are not easy to identify and detect

In a multi-branch pipeline network, the negative pressure wave method is difficult to distinguish the difference between the pressure fluctuation caused by the instantaneous diversion of the branch or node and the pressure fluctuation caused by the real leakage; therefore, it is not suitable for the leakage detection of the pipeline

The soft sensing method developed in recent years has been initially applied to detect and locate faults, but a mature application technology system has not yet been formed in China

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