Bridge dynamic weighing method based on long-gauge fiber grating sensing technology and dynamic weighing system thereof

Abstract

The invention discloses a bridge dynamic weighing method based on the long-gauge fiber grating sensing technology and a bridge dynamic weighing system thereof. The dynamic weighing method comprises the steps that long-gauge sensors are arranged: the long-gauge sensors are arranged on the initial entering and final exiting side span units of a vehicle and the part between the two side span units along the length direction of the bridge; load condition monitoring of a vehicle to be identified and load condition monitoring of a standard vehicle are performed: the vehicle of which various parameters are known acts as the standard vehicle, the strain response data of each sensing unit under the load condition of the standard vehicle are acquired, and the maximum strain of each sensing unit only caused by the axle load is calculated; and vehicle load identification under the load condition of the vehicle to be identified is performed. The maximum bending strain value only caused by the axle load under the load condition of the standard vehicle is analyzed and compared with the corresponding value under the load condition of the standard value so that the total weight of the driving load on the bridge and the load of each vehicle can be identified, the overload vehicle can be effectively pre-warned and thus damage to the big long-span bridges can be avoided.

Description

technical field [0001] The invention relates to a bridge dynamic weighing system based on long-gauge optical fiber grating sensing technology, which can realize real-time monitoring of the load of moving vehicles on the bridge and effectively warn overloaded vehicles. Background technique [0002] Bridges are an essential part of road and rail networks. In recent years, with the continuous development of social economy, vehicle overload has become one of the main reasons for bridge collapse. The repeated driving of overloaded vehicles seriously threatens the infrastructure safety of the bridge deck, and significantly accelerates the fatigue degradation of the bridge. Especially the old bridges, which account for a large proportion of the bridges in the country, will be seriously damaged or even collapsed under the action of overloaded vehicles due to the continuous decline of resistance. At the same time, considering the ever-increasing maintenance and management costs of ...

AI Technical Summary

Problems solved by technology

The first type of method, the number of axles, wheelbase and vehicle speed are all necessary data to calculate the axle load; the early B-WIM needs to install at least two sensors with a certain distance in the middle of the road to detect the axles, then calculate the vehicle speed, and at the same time Used for vehicle classification and axle load calculations, but its main disadvantages are that installation and maintenance interfere with traffic and are not durable

Later, the method of using the strain peak generated by the strain history under the action of the axle to identify the axle proposed the B-WIM without the axle detection device, but it could not effectively identify all vehicles

For the second type of method, scholars at home and abroad have proposed force balance method, modal superposition method, time domain method and frequency time domain method, etc. Although these methods can effectively identify the moving axle of the bridge, due to the complexity of the vehicle-bridge coupling vibration and the The ill-posed nature of the inverse problem of structural dynamics, etc., this method is still a long way from practical application

The introduction of the new non-pavement B-WIM method has greatly enhanced the durability of the B-WIM system. However, the accuracy of the bridge strain influence line and axle information seriously affects the test accuracy of the B-WIM. harder to identify

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