Urban underground comprehensive pipe gallery risk management and control system and method based on neural network

Abstract

The invention relates to an urban underground comprehensive pipe gallery risk management and control system based on a neural network, and the system comprises an AI-based artificial intelligence server platform, a remote control terminal, an on-site detection node terminal, an on-site mobile device, and an internet-of-thing communication service network. The AI-based artificial intelligence server platform is in data connection with the remote control terminal, the on-site detection node terminal and the on-site mobile device through the internet-of-thing communication service network. The method specifically comprises the five steps: detection point determination, system networking, system presetting, pipe gallery maintenance and operation and system expansion and optimization. On one hand, the pipe gallery system and the surrounding environment can be effectively and comprehensively monitored, and data acquisition is comprehensive and high in precision; and on the other hand, the system is high in operation automation degree and intelligent degree, the risk event judgment efficiency and precision are greatly improved, and accurate information guidance and service can be providedfor daily management, emergency processing and future information tracing of risk events.

Description

technical field [0001] The invention relates to a pipe gallery positioning management system and method, in particular to a multi-source comprehensive field positioning system and method for an underground comprehensive pipe gallery. Background technique [0002] In the operation of the urban comprehensive utility corridor system, in order to improve the comprehensive supervision ability of operational risk events and improve the safety of utility corridor operation, a large number of risk monitoring system platforms based on manual functions are currently used in the supervision work, such as Wang Jianbo using the Delphi method Establish a risk evaluation index system for utility tunnel PPP projects with principal component analysis (PCA), and use the C-OWA operator to carry out index weighting, establish a risk evaluation model based on set pair analysis, and use the gray correlation degree to determine the coefficient of difference. The value of the connection degree judg...

AI Technical Summary

Problems solved by technology

[0002] In the operation of the urban comprehensive utility corridor system, in order to improve the comprehensive supervision ability of operational risk events and improve the safety of utility corridor operation, a large number of risk monitoring system platforms based on manual functions are currently used in the supervision work, such as Wang Jianbo using the Delphi method Establish a risk evaluation index system for utility tunnel PPP projects with principal component analysis (PCA), and use the C-OWA operator to carry out index weighting, establish a risk evaluation model based on set pair analysis, and use the gray correlation degree to determine the coefficient of difference. The value of the connection degree judges the risk level and development trend of the project, and provides a reference for the theory and practice of the risk assessment of the integrated utility tunnel PPP project. Although it can meet the needs of use to a certain extent, it is found in actual work that the currently used utility tunnel Risk monitoring and evaluation systems, on the one hand, have a complex system structure to varying degrees, are difficult to operate and maintain, and can only meet the evaluation and management of specific types of risk events, and the flexibility and convenience of use are relatively poor; and the risk The evaluation system’s efficiency and accuracy of risk evaluation calculations are relatively poor, and it lacks the necessary self-learning ability during the operation process, which makes it impossible to effectively evaluate the risk situation corresponding to sudden or individual accidental state data; another On the one hand, the current utility gallery risk maintenance system is in operation, and often lacks effective positioning and monitoring of the internal and external surrounding address environment of the utility gallery system, resulting in poor monitoring and comprehensiveness of the current utility gallery risk assessment system, and there are many security loopholes. The staff cannot accurately locate the risk occurrence point of the pipe gallery system, and it is easy to cause the staff and equipment to get lost or the path identification is difficult inside the pipe gallery, which seriously affects the efficiency and quality of risk event handling

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