CN115510724A - Bridge damage identification method based on mobile vehicle test - Google Patents

Bridge damage identification method based on mobile vehicle test Download PDF

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CN115510724A
CN115510724A CN202211323911.9A CN202211323911A CN115510724A CN 115510724 A CN115510724 A CN 115510724A CN 202211323911 A CN202211323911 A CN 202211323911A CN 115510724 A CN115510724 A CN 115510724A
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area
damage
vehicle
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CN115510724B (en
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熊亮
程华才
贺文宇
王阔昌
黎骏飞
李子兵
束冬林
崔珊珊
沈阳超
张静
胡志祥
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Anhui Expressway Engineering Test And Research Center LLC
Hefei University of Technology
Anhui Transportation Holding Group Co Ltd
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Anhui Expressway Engineering Test And Research Center LLC
Hefei University of Technology
Anhui Transportation Holding Group Co Ltd
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Abstract

The invention discloses a bridge damage identification method based on mobile vehicle testing, which is characterized in that a displacement sensor is arranged on a vehicle to obtain the displacement response of the vehicle when the vehicle passes through a bridge at a constant speed, and the bridge damage is identified by using the difference value of the actual displacement response and the theoretical model displacement response. According to the invention, the displacement response of the vehicle is obtained by arranging the displacement sensor on the vehicle, and the damage of the bridge is identified, so that the problems that the sensor needs to be arranged on the bridge for identifying the damage of the bridge in the prior art can be effectively solved.

Description

Bridge damage identification method based on mobile vehicle test
Technical Field
The invention relates to the field of bridge safety detection, in particular to a bridge damage identification method based on mobile vehicle test.
Background
Bridges are important infrastructures and important hubs in traffic networks. As times develop, the center of gravity of bridge engineering will shift from bridge construction to bridge maintenance, assessment and reinforcement. The bridge can receive the influence of multiple adverse factors at the operation in-process, and then appears damage and disease, has caused potential hidden danger for the safe operation of bridge. Frequent safety accidents in various places highlight the importance and the urgency of bridge evaluation.
The damage identification method based on dynamic characteristics is a mainstream method in the field of damage identification at present, and usually takes modal frequency, modal shape, compliance matrix, modal strain energy and curvature mode as damage indexes. However, the methods have some problems, for example, the structural damage identification based on the modal shape has the problems of more measuring point arrangement, expensive sensor, large noise disturbance and the like; the structural damage identification based on the flexibility matrix has the problems of low vibration mode precision, difficult vibration mode quality normalization and the like.
Disclosure of Invention
The invention provides a bridge damage identification method based on mobile vehicle test, aiming at avoiding the defects of the bridge damage identification method, so as to rapidly acquire the damage of the bridge, thereby determining the safety state of the bridge structure.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention relates to a bridge damage identification method based on a mobile vehicle test, which is characterized by comprising the following steps of:
step 1, determining parameters of a two-axis vehicle, comprising the following steps: total weight m 0 Front wheel base d 1 Rear wheel base d 2 Front wheel suspension spring stiffness k 1 Rear wheel suspension spring stiffness k 2 Moment of inertia J and travel speed v;
step 2, mounting a displacement sensor at the bottom of the vehicle, so that when the vehicle drives across the bridge at a constant speed v, the dynamic response of the vehicle in a time period from an upper bridge to a lower bridge is obtained, and s (t) represents the displacement of the bridge at the position of the vehicle at the t moment;
step 3, performing spectrum analysis on the displacement s (t) through Fourier transform, and extracting a quasi-static component y (t) at the t-th moment;
step 4, equally dividing the quasi-static component y (t) into N sections, so that the bridge is also divided into N areas; calculating the ith segment y of y (t) by using the formula (1) i (t) area D enclosed by ith area of bridge i ：
Figure BDA0003911438270000011
In the formula (1), the reaction mixture is,
Figure BDA0003911438270000012
respectively representing the left and right boundaries of the ith area;
step 5, calculating the shape curvature RSMC of the ith area of the bridge by using the formula (2) i ：
Figure BDA0003911438270000021
In formula (2), D i-1 I-1 st section y of y (t) i-1 (t) the area enclosed by the i-1 th area of the bridge; d i+1 Segment i +1 y of y (t) i+1 (t) the area enclosed by the (i + 1) th area of the bridge;
step 6, based on the difference value of the vibration mode curvatures of the areas before and after the damage, the damage positioning index DLI of the ith area of the bridge is established by using the formula (3) i ：
Figure BDA0003911438270000022
In the formula (3), the reaction mixture is,
Figure BDA0003911438270000023
respectively representing the region mode curvature before and after the damage of the ith region of the bridge;
and 7, drawing the damage positioning indexes of all areas of the bridge into a histogram, and taking the peak area in the histogram as the damage position of the corresponding area of the bridge, thereby realizing damage identification.
The electronic device comprises a memory and a processor, and is characterized in that the memory is used for storing a program for supporting the processor to execute the bridge damage identification method, and the processor is configured to execute the program stored in the memory.
The invention relates to a computer-readable storage medium, on which a computer program is stored, wherein the computer program is executed by a processor to perform the steps of the bridge damage identification method.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the vehicle runs through the bridge at a uniform speed, only one displacement sensor is arranged on the vehicle for testing, the bridge damage index is calculated by combining the collected displacement response and the displacement response of the theoretical model, the bridge damage is well identified by using the dynamic test, the workload and the test cost are reduced, and the bridge detection is rapid and efficient.
2. According to the invention, the displacement response of the vehicle is obtained only by arranging one displacement sensor on the vehicle, and the damage of the bridge is identified, so that the problems of large quantity of sensors, large noise interference, large data processing capacity and the like existing in the conventional bridge damage method can be effectively solved.
3. The invention adopts the two-axle vehicle for testing, is consistent with the model of the vehicle for actual bridge detection, and can be better applied to the actual bridge detection.
Drawings
FIG. 1 is a diagram of a numerically simulated uniform-section simply supported beam bridge according to the present invention;
FIG. 2 is a response diagram of the bridge of the present invention under the damaged and non-damaged conditions;
FIG. 3 is a graph of a numerical simulation response spectrum analysis of the present invention;
FIG. 4 is a diagram of quasi-static components of a damaged or non-damaged bridge in a numerical simulation of the present invention;
FIG. 5 is a DLI index diagram of a numerical simulation bridge according to the present invention.
Detailed Description
In the embodiment, a simple supported bridge with an equal cross section is selected, the span length of the bridge is 30m, the elastic modulus of the bridge is 32Gpa, and the inertia moment of the bridge is 0.2m 4 The mass per linear meter is 2000kg/m, the bridge damping is not considered, and the unevenness grade of the bridge deck is good. A20% rigidity reduction is arranged at a 13-16m position of the bridge to simulate a damaged state of the bridge. Limit based on Newmark-beta integrationAnd performing element simulation, namely calculating the dynamic response of the vehicle when the vehicle passes through a bridge by adopting a separation iteration method, wherein the sampling frequency of the displacement sensor is 1000Hz, and the signal-to-noise ratio is 30dB. A bridge damage identification method based on a mobile vehicle test, as shown in fig. 1, includes the following steps:
step 1, determining parameters of a two-axis vehicle, comprising the following steps: total weight m 0 =3000kg, front wheel base d 1 =2, rear wheel base d 2 =1 front wheel suspension spring rate k 1 =230kN/m, rear wheel suspension spring stiffness k 2 =230kN/m, moment of inertia J v ＝2300kg·m 2 And a travel speed v =10m/s;
step 2, mounting a displacement sensor at the bottom of the vehicle, so that when the vehicle drives through the bridge at a constant speed v, the dynamic response s of the vehicle in the time period from the bridge to the bridge under the state of the damaged bridge and the state of the undamaged bridge is respectively obtained d (t) and s (t), as shown in FIG. 2;
step 3, responding to the dynamic response s in the loss state through Fourier transform d (t) and the dynamic response s (t) in the lossless state, as shown in FIG. 3, filtering the non-moving load frequency component, and extracting the quasi-static component y in the lossy state d (t) and quasi-static component y (t) in a lossless state, as shown in FIG. 4;
step 4, mixing y d (t) and y (t) are equally divided into N =300 segments, so that the bridge is also divided into 300 regions, and the area surrounded by the ith region when the bridge is damaged is calculated
Figure BDA0003911438270000031
And area D surrounded by ith area when no damage occurs i . Wherein the ith segment y of y (t) is calculated by using the formula (1) i (t) area D enclosed by ith area of bridge i ：
Figure BDA0003911438270000032
In the formula (1), the reaction mixture is,
Figure BDA0003911438270000033
respectively representing the left and right boundaries of the ith area;
step 5, calculating the area vibration mode curvature under the bridge damage state
Figure BDA0003911438270000034
And regional vibration mode curvature RSMC under bridge nondestructive state i . Wherein, the mode shape curvature RSMC of the ith area of the bridge is calculated by using the formula (2) i ：
Figure BDA0003911438270000041
In the formula (2), D i-1 I-1 st section y of y (t) i-1 (t) the area enclosed by the i-1 th area of the bridge; d i+1 Segment i +1 y of y (t) i+1 (t) the area enclosed by the (i + 1) th area of the bridge;
and 6, establishing a damage positioning index DLI of the ith area of the bridge by using a formula (3) based on the difference value of the area vibration mode curvatures before and after damage i ：
Figure BDA0003911438270000042
In the formula (3), the reaction mixture is,
Figure BDA0003911438270000043
respectively representing the region mode curvature before and after the damage of the ith region of the bridge;
and 7, identifying the damage according to the damage positioning index DLI.
Will DLI i The index is plotted as a bar chart when DLI i When the index graph has obvious peak value, the damage exists in the peak value area, and when the index DLI appears i The larger the value, the larger the damage value of the region. As shown in FIG. 5, it can be seen that the damage index has a distinct peak at 13-16m of the bridge, indicating that the bridge has damage in this area. Therefore, the bridge damage can be well identified based on the mobile vehicle test.
In this embodiment, an electronic device includes a memory and a processor, where the memory is used to store a program that supports the processor to execute the bridge damage identification method, and the processor is configured to execute the program stored in the memory.
In this embodiment, a computer-readable storage medium is a computer program stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the bridge damage identification method are executed.

Claims (3)

1. A bridge damage identification method based on a mobile vehicle test is characterized by comprising the following steps:
step 1, determining parameters of a two-axis vehicle, comprising: total weight m 0 Front wheel base d 1 Rear wheel base d 2 Front wheel suspension spring stiffness k 1 Rear wheel suspension spring stiffness k 2 Moment of inertia J and travel speed v;
step 2, mounting a displacement sensor at the bottom of the vehicle, so that when the vehicle drives across the bridge at a constant speed v, the dynamic response of the vehicle in a time period from an upper bridge to a lower bridge is obtained, and s (t) represents the displacement of the bridge at the position of the vehicle at the t moment;
step 3, performing spectrum analysis on the displacement s (t) through Fourier transform, and extracting a quasi-static component y (t) at the t-th moment;
step 4, equally dividing the quasi-static component y (t) into N sections, so that the bridge is also divided into N areas; calculating the ith segment y of y (t) by using the formula (1) i (t) area D enclosed by ith area of bridge i ：
Figure FDA0003911438260000011
In the formula (1), the reaction mixture is,
Figure FDA0003911438260000012
respectively representing the left and right boundaries of the ith area;
step (ii) of5. Calculating the shape curvature RSMC of the ith area of the bridge by using the formula (2) i ：
Figure FDA0003911438260000013
In formula (2), D i-1 Section i-1 y of y (t) i-1 (t) the area enclosed by the i-1 th area of the bridge; d i+1 Segment i +1 y of y (t) i+1 (t) the area enclosed by the (i + 1) th area of the bridge;
and 6, establishing a damage positioning index DLI of the ith area of the bridge by using a formula (3) based on the difference value of the area vibration mode curvatures before and after damage i ：
Figure FDA0003911438260000014
In the formula (3), the reaction mixture is,
Figure FDA0003911438260000015
respectively representing the region mode curvature before and after the damage of the ith region of the bridge;
and 7, drawing the damage positioning indexes of all areas of the bridge into a histogram, and taking the peak area in the histogram as the damage position of the corresponding area of the bridge, thereby realizing damage identification.
2. An electronic device comprising a memory and a processor, wherein the memory is configured to store a program that enables the processor to execute the bridge damage identification method of claim 1, and the processor is configured to execute the program stored in the memory.
3. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the bridge damage identification method according to claim 1.
CN202211323911.9A 2022-10-27 2022-10-27 Bridge damage identification method based on moving vehicle test Active CN115510724B (en)

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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109839440A (en) * 2019-03-20 2019-06-04 合肥工业大学 A kind of bridge damnification localization method based on standing vehicle testing
CN112461358A (en) * 2020-11-23 2021-03-09 合肥工业大学 Bridge modal parameter identification method based on instantaneous frequency of vehicle-bridge system
CN112484839A (en) * 2020-12-14 2021-03-12 湖南大学 Bridge movement detection method and system based on two-axis vehicle response
WO2021179350A1 (en) * 2020-03-13 2021-09-16 Dalian University Of Technology Method of damage detection for decks of girder bridges using an actively excited vehicle
CN113960165A (en) * 2021-10-09 2022-01-21 大连理工大学 Method for detecting damage of hinge joint of plate girder bridge by using vibration mode extracted from response of moving vehicle
CN115081277A (en) * 2022-06-14 2022-09-20 武汉理工大学 Bridge damage identification method and device based on double-shaft vehicle contact point response

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109839440A (en) * 2019-03-20 2019-06-04 合肥工业大学 A kind of bridge damnification localization method based on standing vehicle testing
WO2021179350A1 (en) * 2020-03-13 2021-09-16 Dalian University Of Technology Method of damage detection for decks of girder bridges using an actively excited vehicle
CN112461358A (en) * 2020-11-23 2021-03-09 合肥工业大学 Bridge modal parameter identification method based on instantaneous frequency of vehicle-bridge system
CN112484839A (en) * 2020-12-14 2021-03-12 湖南大学 Bridge movement detection method and system based on two-axis vehicle response
CN113960165A (en) * 2021-10-09 2022-01-21 大连理工大学 Method for detecting damage of hinge joint of plate girder bridge by using vibration mode extracted from response of moving vehicle
CN115081277A (en) * 2022-06-14 2022-09-20 武汉理工大学 Bridge damage identification method and device based on double-shaft vehicle contact point response

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
YILIN LI 等: "Modal identification of time-varying vehicle-bridge system using a single sensor", SMART STRUCTURES AND SYSTEMS, vol. 30, no. 1, pages 107 - 119 *
王珊珊 等: "基于车辆传感识别简支梁桥损伤的位移曲率法研究", 特种结构, vol. 39, no. 2, pages 79 - 85 *
贺文宇 等: "基于车辆静置的桥梁模态参数识别方法", 土木工程学报, pages 1 - 13 *

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