A Disaster Prediction Method and System Based on Horizontal Visual Network

Abstract

The invention discloses a horizontal visual network-based catastrophe prediction method and system. The method includes the following steps that: a section of vibration signals of an engineering system during its normal operation are acquired so as to form a discrete time sequence; the acquired discrete time sequence is adopted to reconstruct a horizontal visual virtual complex network according to a horizontal visual network conversion rule; the maximum node degree of the virtual visual complex network when the engineering system is in normal operation is calculated; real-time mechanical system vibration signals are collected, a corresponding horizontal visual network is established, and the maximum node degree of the horizontal visual network is calculated; and with the horizontal visualvirtual complex network adopted as a benchmark, the real-time catastrophe index of the engineering system is calculated, and the catastrophe of the system can be predicted based on the catastrophe index. According to the horizontal visual network-based catastrophe prediction method and system of the invention, a network catastrophe early warning mechanism in which a monitoring method and recognition are combined together, and therefore, the method and system do not depend on the dynamic equation of the system, and can be applied to high-dimensional complex systems. The method and system havethe advantages of no need for time sequence reconstruction, a small amount of calculation, good real-time monitoring, simplicity, easiness in implementation and high applicability.

Description

technical field [0001] The invention relates to the field of disaster prediction of complex engineering systems, in particular to a method and system for disaster prediction based on a horizontal visual network. Background technique [0002] Modern large-scale engineering systems are usually composed of multiple parts, and their structures are often complex. The subsystems are interconnected and interact with each other, showing complex nonlinear characteristics. Under certain special conditions, catastrophic collapse events (catastrophes) may occur in the system, such as the collapse of suspension bridges, the collapse of tower cranes, the collapse of dams, and the sudden increase in the vibration amplitude of floating platforms. The occurrence of catastrophic events is often sudden, and it is difficult to catch obvious signs before the catastrophe, which can easily cause extremely heavy economic and human losses. [0003] Catastrophe specifically refers to a sudden change...

AI Technical Summary

Problems solved by technology

Since it is difficult for the replacement model to fully inherit all the information of the original system, and the error is extremely sensitive to the bifurcation analysis, the theoretical research is limited to the low-dimensional system, and the catastrophe prediction of the high-dimensional complex engineering system is often invalid.

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