Role diagnostic system for bridge structural state

Abstract

The invention discloses a role diagnostic system for a bridge structural state, which is characterized in that: the role diagnostic system is inserted between a data storage unit and a software evaluation unit in a safety evaluation link of the conventional bridge structural state monitoring system; data acquired from an information acquisition link of the conventional bridge structural state monitoring system is processed by the data storage unit so as to acquire data to be analyzed; the data to be analyzed is input in the role diagnostic system; the role diagnostic system distinguishes the structure information, the interference information and the role failure information of the data to be analyzed; and the role diagnostic system performs role position and role maintenance on the source of the interference information and / or the role failure information and only transmits the structure information to the software evaluation unit. The role diagnostic system for the bridge structural state has the advantages of providing a new method for solving the problems of the original data distortion and variance of the bridge structural state information from the height of the system.

Description

technical field [0001] The invention relates to a bridge structure state monitoring, fault diagnosis and early warning technology, in particular to a bridge structure state role diagnosis system. Background technique [0002] Bridge structure monitoring, fault diagnosis and early warning technology is to use the means of information technology to monitor various state information of bridge structure, and carry out structural analysis and fault diagnosis. However, since the bridge is recognized as the most complex engineering structure in the structural engineering field, and the bridge structure monitoring, fault diagnosis and early warning technology has the characteristics of a high degree of cross-discipline, this determines that there must be a lot of in-depth research for this emerging technology that has just started. Distortion and variation of original data is one of the key core issues that is extremely important but lies in the weak point of cross-discipline and di...

AI Technical Summary

Problems solved by technology

Improving the reliability, environmental adaptability, and service life of the sensor system is the fundamental way to solve the distortion and variation of the original data, and it is also the duty-bound responsibility of workers in the field of information science. However, it not only involves many different types of sensors, instruments and equipment, but also Involves the on-site installation process technology of the system, so this will be a very long process

Increasing the hardware and software redundancy of the system is the most conventional method, but it will greatly increase the complexity and cost of the system, so it is difficult to be accepted by the bridge industry

However, using conventional signal processing methods such as filtering to preprocess the original signal is a relatively effective and low-cost method. However, due to the limitation of professional background, technicians in the field of structural engineering only consider problems from the perspective of mechanics and structure. Technicians in the information discipline only consider problems from the perspective of sensors and instrument systems, and cannot solve such a large interdisciplinary problem at all.

What's more serious is that researchers in bridge structure monitoring and fault diagnosis technology generally have not realized the seriousness of this problem; especially the vast majority of researchers who focus on structural engineering take it for granted that all the systems acquired are Real, effective, and undistorted original data, all data variations are caused by the bridge structure

This kind of understanding has caused the damage identification and fault diagnosis technology of bridge structures to fall into a "data disaster" dilemma in practical application. For example, the state monitoring system of a bridge in Hong Kong, which invested tens of millions of It was the most advanced hardware system in the world at that time, but there were still large fluctuations in raw data caused by various hardware, and a considerable proportion of abnormal fluctuations exceeded the data changes in structural damage, making most algorithms and software for damage identification and fault diagnosis useless. Frequent false alarms and the new problem of "data disaster" have caused the bridge to spend huge sums of money every year to attract talents in the field of structural engineering from all over the world to conduct structural identification and processing algorithm research. However, the impact of data distortion and variation has never been considered. , so more than ten years of hard work have not yielded substantive breakthroughs. Even after the hardware system of the bridge has been greatly updated recently, this "data disaster" problem still plagues the bridge and related researchers around the world.

[0007] Since the data distortion and variation of the bridge structure monitoring and fault diagnosis system are completely mixed with the abnormal information generated by the fault of the bridge structure itself, the technical basis it involves spans different professional fields, so it only relies on a certain professional personnel , It is difficult to achieve the goal only by starting from a certain aspect and using a certain method of treatment

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