Determination method and device of bridge reinforcing target bearing capacity

Abstract

The invention discloses a determination method and device of bridge reinforcing target bearing capacity, and relates to the field of safety of bridges. The determination method of bridge reinforcing target bearing capacity comprises the step of measuring the parameters of each car passing through a target bridge within a set time threshold value, the step of processing the parameters to obtain the load effect value when each car passes through the most adverse position of the target bridge, wherein the most adverse position is the position corresponding to the highest point of a load effect influence line corresponding to the target bridge, the step of processing all the load effect values to obtain a sample space satisfying generalized Paratore distribution and further determine a load effect representative value of the target bridge according to the generalized Paratore distribution rule, and the step of obtaining the target bearing capacity of reinforcing the target bridge according to the load effect representative value. The determination method of bridge reinforcing target bearing capacity can accurately deduce bridge load effect extreme values under the condition of a small calculation cost and reinforce the bridge by utilizing the bridge load effect extreme values.

Description

technical field [0001] The invention relates to the field of bridge safety, in particular to a method and device for confirming the target bearing capacity of bridge reinforcement. Background technique [0002] With the rapid development of my country's transportation industry, there is a trend of gradually increasing the size of vehicles, especially the appearance of overloaded trucks on some traffic arteries, which poses a huge threat to the safety of bridges in service along the lines. In recent years, bridges collapsed by overloaded trucks have occurred frequently. The truck was seriously overloaded and collapsed. People urgently need to know how much the daily traffic flow has on the bridge. The management department also hopes to know whether there are potential safety hazards in the bridge in service under the influence of the current traffic flow in the future service period, so that the bridge can be reinforced or formulated. More scientific management measures. ...

AI Technical Summary

Problems solved by technology

However, when studying the load effect of a specific service bridge under the actual traffic flow, such an assumption seems too arbitrary

[0012] Two problems enumerated above: the inaccuracy of the random parameter model of the MCS method, the inaccuracy of the high score point during the extrapolation of the load effect, are the most important two problems encountered when studying the actual measured automobile load effect, and are also the results of the present invention. Two issues to focus on

[0023] (1) The technology only focuses on the effect of a single vehicle on the bridge, and cannot solve the situation of multiple vehicles on the bridge at the same time, so it is not suitable for refined load analysis

[0024] (2) The assumption of technology 1 on the normal distribution of vehicle load effects is too simple and lacks theoretical basis

[0025] (3) The extrapolation method of technology 1 to determine the representative value of the evaluation cycle load effect assumes in practice that "replace the number of vehicles in a year with the number of vehicles in one day", which lacks theoretical basis

Since the traffic flow parameter model is often complex, such as figure 1 As shown, there is a certain degree of deviation between the simulated traffic flow and the actual traffic flow

[0036] (2) Technology 2 is difficult to complete long-term simulation

Due to the existence of the problem of "probability distribution is not accurate at high quantile points" and the unreasonable assumption of "one day represents one year", the extrapolation results are often not accurate enough

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