Highway bridge damage assessment method based on specific traffic flow and structure monitoring response

Abstract

The invention discloses a highway bridge damage assessment method based on specific traffic flow and structure monitoring response, which comprises the following steps: firstly, capturing traffic flow information, acquiring real-time dynamic response data of a bridge structure under the action of environmental excitation, and carrying out space-time matching on the traffic flow information and structure response monitoring data to obtain a real-time dynamic response result; constructing a vehicle load-structure response association database; classifying the vehicles of the same type into the same layer for classification, sampling from a database by adopting an optimal distribution sampling method according to different vehicle types, and sampling from the database to obtain three-layer specific traffic flows of small cars, medium-sized trucks and heavy-duty trucks and corresponding structure monitoring response characteristic values; and carrying out weighted average on the specific traffic flow structure monitoring response characteristic values obtained by each layer, calculating the overall structure response under a single-day specific traffic flow load, and carrying out bridge safety evaluation through long-term monitoring. The method can replace a traditional bridge load test, and rapid and real-time safety assessment of the highway bridge is achieved under the condition that traffic is not interrupted.

Description

Technical Field

[0001] The present invention relates to the field of safety assessment of existing bridge structures under operating conditions, in particular to load testing of highway bridges, and specifically to a highway bridge damage assessment method based on specific traffic flow and structural monitoring responses. Background Art

[0002] China has become the world's center for civil engineering and bridge construction after Europe, the United States and Japan. China's large-scale bridge construction began in the late 1990s, and now has a service history of several decades. Its structural behavior and safety status urgently need to be evaluated in order to provide a scientific basis for decisions such as maintenance and reinforcement or demolition and decommissioning. China has entered a period of equal emphasis on construction and maintenance. With the rapid development of economic construction, traffic density and vehicle load have increased rapidly. Driven by economic interests, the trend of large-scale vehicles has intensified, and the number of overloaded trucks has continued to increase. The actual load is usually 100%-400% of the nuclear load. Under such severe traffic density and overloading, coupled with factors such as environmental erosion, material aging and long-term effects of loads, it is inevitable that bridge structures will experience damage accumulation and resistance attenuation.

[0003] Bridge load tests simulate the load conditions in actual use to conduct a comprehensive and systematic evaluation and verification of bridge structures. The test results can provide an important reference for bridge design and construction, help optimize structural design and material selection, improve the bearing capacity and safety of bridges, and provide an important basis for bridge maintenance and management. However, load tests require the closure of traffic, the use of specific types and numbers of trucks, the design of special loading schemes, and the deployment of sensor systems to collect bridge responses. This not only consumes a lot of manpower and material resources, but also has a low implementation frequency, making it difficult to timely grasp the evolution of bridge status. At the same time, closed traffic brings adverse economic and social impacts.

[0004] Bridges are subjected to load tests in the operational traffic at all times, and these operational traffic contains rich load test information. Under the current operational traffic, the automobile load response of bridges has reached or even exceeded the design expected value, which provides an important opportunity to carry out bridge load tests and status assessments using operational traffic under non-closed traffic conditions. With the in-depth research of digital technology, bridge monitoring technology with perception functions continues to develop and is widely used. Advanced intelligent perception equipment is used to obtain bridge structure response and load data, and research on online monitoring and data processing of bridges under random traffic, safety warning, status assessment, and maintenance decision-making is carried out based on big data-driven methods to achieve health and safety assessment and prediction of existing bridges. Summary of the invention

[0005] In view of the above technical problems existing in the prior art, the purpose of the present invention is to provide a highway bridge damage assessment method based on specific traffic flow and structural monitoring response. The present invention is based on the specific bridge deck traffic flow and its corresponding bridge structure monitoring response information, and uses massive monitoring data and big data drive to achieve bridge safety assessment. This method can effectively replace the traditional bridge load test and realize the rapid and real-time safety assessment of highway bridges without interrupting traffic.

[0006] The technical solution adopted by the present invention is as follows:

[0007] A highway bridge damage assessment method based on specific traffic flow and structure monitoring response includes the following steps:

[0008] S1. Traffic flow information capture: Use bridge deck monitoring equipment and image recognition algorithms to capture the traffic flow information of random vehicles, and classify the random vehicles on a single day into three types: small cars, medium-sized trucks, and heavy-duty trucks, to obtain data on traffic flow information;

[0009] S2. Structural response monitoring: Dynamic response monitoring sensing equipment is installed on the bridge to obtain real-time dynamic response data of the bridge structure under environmental excitation;

[0010] S3. Data matching: performing spatiotemporal matching of the vehicle flow information in step S1 with the data of the structural response monitoring in step 2 to construct a vehicle load-structural response association database;

[0011] S4. Classification sampling: vehicles of the same type are classified into the same classification layer, and the optimal allocation sampling method is used to sample from the database according to different vehicle types. The sampling ratio of the layer with small internal variation of the bridge structure is small, and the sampling ratio of the layer with large internal variation of the bridge structure is large (that is, the sampling ratio of the layer where "large" vehicles are located is the largest, the sampling ratio of the layer where "medium" vehicles are located is the second largest, and the sampling ratio of the layer where "small" vehicles are located is the smallest);

[0012] S5: Acquisition of structural response monitoring characteristic values: adopting the classification sampling method of step S4, sampling and acquiring three layers of specific traffic flows of small cars, medium-sized trucks and heavy-duty trucks from the database of step S3, and acquiring structural monitoring response characteristic values ​​corresponding to the specific traffic flows;

[0013] S6. Data model establishment: Take the weighted average of the specific traffic flow structure monitoring response characteristic values ​​obtained from each layer (the layers here are three different vehicle types, representing "large", "medium" and "small" vehicles respectively), and calculate the weighted average of the overall structural response under the specific traffic flow load on a single day;

[0014] S7. Bridge safety assessment: After long-term monitoring on a daily basis, according to the process of steps S1-S6 above, a data model of the change of the weighted average value of the overall structural response of the bridge under the specific traffic load monitored over multiple days is established to effectively reflect the health status of the bridge and achieve safety assessment.

[0015] Furthermore, in step S2, the dynamic response monitoring sensing equipment includes a bridge deck vehicle image acquisition device, a vibration acceleration sensor and a displacement sensor, and the displacement sensor includes at least one of a dynamic displacement optical sensor and a laser displacement sensor. The bridge deck vehicle image acquisition device, the vibration acceleration sensor, the dynamic displacement optical sensor and the laser displacement sensor are respectively used to obtain vehicle apparent identity information of vehicles randomly passing through the bridge deck, bridge vibration data, dynamic deflection data of the bridge main beam and dynamic rotation angle data of the bridge main beam.

[0016] Furthermore, in step S3, according to the vehicle passing time obtained by the bridge deck vehicle image acquisition equipment, the dynamic response data of the bridge structure when the vehicle load passes is obtained with time as the link, and a vehicle load-structure response database is constructed.

[0017] Further, the bridge structure dynamic response data includes one of the following: mid-span vertical displacement of the bridge main beam, vibration acceleration of the bridge main beam, and longitudinal displacement of the expansion joint at the end of the bridge;

[0018] When the dynamic response data of the bridge structure is the vertical displacement at the mid-span of the bridge main beam or the longitudinal displacement of the expansion joint at the end of the bridge, the structural monitoring response characteristic value is the maximum displacement value;

[0019] When the dynamic response data of the bridge structure is the vibration acceleration of the bridge main beam, the structural monitoring response characteristic value is the first-order natural frequency of the structure.

[0020] Furthermore, in step S4, the sampling goal is to minimize the sampling error, and the number of samples in each layer n i The following relationship should be satisfied:

[0021]

[0022] Among them, N i is the total number of the i-th layer, σ i is the standard deviation of the structural monitoring response eigenvalue corresponding to the vehicle type in the i-th layer, n is the total sample size, and L is the total number of layers.

[0023] Furthermore, the process of establishing the S6 data model is to first monitor and obtain the structural monitoring response characteristic values ​​related to the vehicle type, and then perform weighted averaging according to the sampling ratios of the three types of vehicles; the sampling ratio of each vehicle type reflects the degree of its influence on the bridge structure response. Through this weighted calculation method, the impact of different vehicle flow combinations on the overall safety of the bridge can be more accurately evaluated. The calculation formula for weighted averaging the specific vehicle flow structure monitoring response characteristic values ​​obtained at each layer is as follows:

[0024]

[0025] Where: r i is the structural monitoring response characteristic value of the i-th vehicle type;

[0026] n i is the number of the i-th vehicle type during the observation period, where the unit of the observation period is day;

[0027] w i =n i / N i , reflecting the degree of its influence on the response of the bridge structure;

[0028] R represents the weighted average of the structural monitoring response eigenvalues.

[0029] Furthermore, in step S7, the method for assessing the health status of the bridge is that the weighted average value of the overall structural response under the specific traffic load monitored for multiple days is within the range of ±5% with the date. If it exceeds ±5%, it is determined that the bridge may be damaged.

[0030] The beneficial effects achieved by the present invention are:

[0031] 1) The vehicle load data obtained by the method proposed in the present invention only need to be the apparent information data of the traffic flow, and there is no need to obtain the vehicle load data. Through a large number of large, medium and small vehicle groups corresponding to the structural response data set, a probability distribution model of the structural response is established based on the law of large numbers. There is a certain corresponding relationship between the bridge stiffness and the characteristic value of the structural monitoring response, and then the change of the bridge stiffness is evaluated. If the bridge structure is healthy, the model established by the present invention will not change significantly in daily monitoring.

[0032] 2) The present invention relates to a method for real-time assessment of bridge safety based on a specific proportion of bridge deck traffic load and structural monitoring response information. This method can effectively replace the traditional bridge load test and achieve rapid and real-time safety assessment of highway bridges without interrupting traffic. Through the present invention, based on the big data of specific traffic and structural monitoring responses, the big data driven method can be used to efficiently assess the health status of highway bridges, replacing the traditional road closure bridge load test. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a text flow diagram of the method of the present invention.

[0034] Figure 2 The method of the present invention adopts a set of lightweight monitoring hardware systems suitable for highway bridges.

[0035] Figure 3 Schematic diagram of three vehicle types of the present invention.

[0036] Figure 4 This is an example of a data model based on multi-day monitoring response changes of a highway bridge of the present invention. DETAILED DESCRIPTION

[0037] The present invention will be further described below in conjunction with specific embodiments, but the protection scope of the present invention is not limited thereto.

[0038] Embodiment 1:

[0039] A bridge damage assessment method based on structural dynamic rotation angle monitoring under random traffic flow includes the following steps:

[0040] S1. Traffic flow information capture: Use bridge deck monitoring equipment and image recognition algorithms to capture the appearance and license plate information of randomly traveling vehicles, and classify the random vehicles of a single day into three types: small cars, medium-sized trucks, and heavy-duty trucks, to obtain data on traffic flow information.

[0041] The built-in target detection algorithm in the bridge monitoring equipment is used to automatically obtain the appearance and license plate information of the vehicles on the bridge. The random vehicles on a single day are divided into three types: small cars (2-axle cars, including SUVs, MPVs, etc.), medium trucks (2-axle trucks) and heavy trucks (3-axle and above trucks), that is, three "layers".

[0042] S2. Structural response monitoring: The structural dynamic response monitoring sensor is used to obtain the real-time dynamic response of the bridge under load excitation, including the dynamic deflection of the main beam, the vibration of the main beam and the displacement of the expansion joint.

[0043] The characteristics of S2 are: a set of lightweight monitoring hardware systems suitable for small and medium-sized bridges has been built to obtain bridge dynamic response data, including: bridge deck vehicle image acquisition equipment (mandatory), vibration acceleration sensor (mandatory), dynamic displacement optical sensor and laser displacement sensor (optional, choose one of the two), which can respectively obtain the appearance and license plate information of vehicles randomly passing through the bridge deck, dynamic deflection of the main beam, main beam vibration or expansion joint displacement data.

[0044] The characteristic value in the present invention is the real-time dynamic response data generated when a vehicle passes through a bridge, selected from one of the following: the mid-span vertical displacement (deflection) of the bridge main beam, the vibration acceleration of the bridge main beam, and the longitudinal displacement of the expansion joint at the end of the bridge.

[0045] When the mid-span vertical displacement (deflection) of the bridge main beam or the longitudinal displacement of the expansion joint at the end of the bridge is selected, the structural monitoring response characteristic value is the maximum displacement value. When the vibration acceleration of the bridge main beam is selected, the structural monitoring response characteristic value is the first-order natural frequency (bending mode) of the structure.

[0046] S3. Data matching: Match the traffic information with the structural monitoring response in time and space to build a vehicle load-structure response correlation database.

[0047] The characteristics of S3 are: based on the vehicle passing time obtained by the bridge deck vehicle image acquisition equipment, using time as a link, the dynamic response data of the bridge structure when the vehicle load passes by is obtained, and a vehicle load-structure response database is constructed.

[0048] S4. Classification sampling: vehicles of the same type are classified into the same classification layer, and the optimal allocation sampling method is used to sample from the database according to different vehicle types. The sampling ratio of the layer with small internal variation of bridge structure response is small, and the sampling ratio of the layer with large internal variation of bridge structure response is large;

[0049] The sampling proportion of each stratum is determined based on the number of observations and the standard deviation to minimize the sampling error. This means that the number of samples in each stratum, n i The following relationship should be satisfied:

[0050]

[0051] Among them, N i is the total number of the i-th layer, σ i is the standard deviation of the structural monitoring response characteristic value corresponding to the i-th layer vehicle type, n is the total sample size, L is the total number of layers, L = 3.

[0052] S5 Structural response monitoring characteristic value acquisition: adopt the classification sampling method of step S4, sample and obtain three layers of specific traffic flows of small cars, medium-sized trucks and heavy-duty trucks from the database of step S3, and obtain the structural monitoring response characteristic values ​​corresponding to the specific traffic flows.

[0053] S6 data model establishment: The specific traffic flow structure monitoring response characteristic values ​​obtained at each layer are weighted averaged to calculate the weighted average value of the overall structural response under the specific traffic flow load of a single day.

[0054] The characteristics of S6 are: a data model is established to analyze and calculate the overall structural response of the bridge under a specific traffic flow load on a single day. The model first obtains the structural monitoring response characteristic values ​​related to the vehicle type from each monitoring level, and then performs weighted averaging based on the sampling ratio of three vehicle types (small cars, medium-sized trucks and heavy-duty trucks). The sampling ratio of each vehicle type reflects its degree of influence on the structural response of the bridge. Through this weighted calculation method, the impact of different traffic combinations on the overall safety of the bridge can be more accurately evaluated. The calculation formula for weighted averaging the specific traffic structure monitoring response characteristic values ​​obtained at each layer is as follows:

[0055]

[0056] Where: r i is the structural monitoring response eigenvalue of the i-th vehicle type.

[0057] n i is the number of the i-th vehicle type in the observation period. The unit of the observation period is day, and one observation period is one day.

[0058] w i =n i / N i , reflecting its influence on the response of the bridge structure.

[0059] R represents the weighted average of the structural monitoring response eigenvalues.

[0060] S7. Bridge safety assessment: After long-term monitoring on a daily basis, according to the process of steps S1-S6 above, a data model of the change of the weighted average value of the overall structural response of the bridge under the specific traffic load monitored over multiple days is established to effectively reflect the health status of the bridge and achieve safety assessment.

[0061] The characteristic of S7 is that through long-term monitoring of highway bridges, a data model of the changes in the multi-day monitoring response of the bridge is established. This model is used to analyze the changing trend of the bridge structure response. If the "weighted average value of the structural monitoring response characteristic value" shows overall stability with the changing trend of the monitoring date, without significant mutations, it can be considered that the bridge structure remains safe. On the contrary, if the monitoring data shows a mutation in the structural response trend, this may indicate that the bridge structure has been damaged. In this application, it can be determined that the "weighted average value of the structural monitoring response characteristic value" should be stable within the range of ±5% with the changing trend of the monitoring date. If it exceeds ±5%, it is determined that the bridge may be damaged.

[0062] According to the method of Example 1 of the present invention, the results of the data model based on the multi-day monitoring response change of a highway bridge are shown in Figure 4 ,from Figure 4It can be seen that the characteristic values ​​of the bridge structure monitoring response under daily traffic flow change steadily, reflecting the structural health of the bridge within the measurement time period.

[0063] The contents described in this specification are merely an enumeration of implementation forms of the inventive concept, and the protection scope of the present invention should not be regarded as being limited to the specific forms described in the embodiments.

Claims

1. A highway bridge damage assessment method based on specific traffic flow and structural monitoring response, characterized in that The following steps are involved: S1. Traffic flow information capture: Use bridge deck monitoring equipment and image recognition algorithms to capture the traffic flow information of random vehicles, and classify the random vehicles on a single day into three types: small cars, medium-sized trucks, and heavy-duty trucks, to obtain data on traffic flow information; S2. Structural response monitoring: Dynamic response monitoring sensing equipment is installed on the bridge to obtain real-time dynamic response data of the bridge structure under environmental excitation; S3. Data matching: performing spatiotemporal matching of the vehicle flow information of step S1 and the data of the structural response monitoring of step S2 to construct a vehicle load-structural response association database; S4. Classification sampling: vehicles of the same type are classified into the same classification layer, and the optimal allocation sampling method is used to sample from the database according to different vehicle types. The sampling ratio of the layer with small internal variation of bridge structure response is small, and the sampling ratio of the layer with large internal variation of bridge structure response is large; S5: Acquisition of structural response monitoring characteristic values: adopting the classification sampling method of step S4, sampling and acquiring three layers of specific traffic flows of small cars, medium-sized trucks and heavy-duty trucks from the database of step S3, and acquiring structural monitoring response characteristic values ​​corresponding to the specific traffic flows; S6. Data model establishment: weighted average the specific traffic flow structure monitoring response characteristic values ​​obtained at each layer, and calculate the weighted average value of the overall structural response under the specific traffic flow load of a single day; S7. Bridge safety assessment: After long-term monitoring on a daily basis, according to the process of steps S1-S6 above, a data model of the change of the weighted average value of the overall structural response of the bridge under the specific traffic load monitored over multiple days is established to effectively reflect the health status of the bridge and achieve safety assessment.

2. A highway bridge damage assessment method based on specific traffic flow and structural monitoring response as claimed in claim 1, characterized in that The monitoring sensing equipment in step S2 includes a bridge deck vehicle image acquisition device, a vibration acceleration sensor and a displacement sensor, wherein the displacement sensor includes at least one of a dynamic displacement optical sensor and a laser displacement sensor, and the bridge deck vehicle image acquisition device, the vibration acceleration sensor, the dynamic displacement optical sensor and the laser displacement sensor are respectively used to obtain vehicle apparent identity information of vehicles randomly passing through the bridge deck, bridge vibration data, dynamic deflection data of the bridge main beam and dynamic rotation angle data of the bridge main beam.

3. A highway bridge damage assessment method based on specific traffic flow and structural monitoring response as claimed in claim 1, characterized in that In step S3, according to the vehicle passing time obtained by the bridge deck vehicle image acquisition equipment, the dynamic response data of the bridge structure when the vehicle load passes is obtained with time as the link, and a vehicle load-structure response database is constructed.

4. A highway bridge damage assessment method based on specific traffic flow and structural monitoring response as claimed in claim 3, characterized in that The bridge structure dynamic response data includes one of the following: the mid-span vertical displacement of the bridge main beam, the vibration acceleration of the bridge main beam, and the longitudinal displacement of the expansion joint at the end of the bridge; When the dynamic response data of the bridge structure is the vertical displacement at the mid-span of the bridge main beam or the longitudinal displacement of the expansion joint at the end of the bridge, the structural monitoring response characteristic value is the maximum displacement value; When the dynamic response data of the bridge structure is the vibration acceleration of the bridge main beam, the structural monitoring response characteristic value is the first-order natural frequency of the structure.

5. A highway bridge damage assessment method based on specific traffic flow and structural monitoring response as claimed in claim 1, characterized in that In step S4, the sampling goal is to minimize the sampling error, and the number of samples in each layer is n i The following relationship should be satisfied: Among them, N i is the total number of the i-th layer, σ i is the standard deviation of the structural monitoring response eigenvalue corresponding to the vehicle type in the i-th layer, n is the total sample size, and L is the total number of layers.

6. A highway bridge damage assessment method based on specific traffic flow and structural monitoring response as claimed in claim 1, characterized in that The process of establishing the S6 data model is to first monitor and obtain the structural monitoring response characteristic values ​​related to the vehicle type, and then perform weighted averaging according to the sampling ratios of the three types of vehicles; the sampling ratio of each vehicle type reflects the degree of its influence on the bridge structure response. Through this weighted calculation method, the impact of different vehicle flow combinations on the overall safety of the bridge can be more accurately evaluated. The calculation formula for weighted averaging the specific vehicle flow structure monitoring response characteristic values ​​obtained at each layer is as follows: Where: r i is the structural monitoring response characteristic value of the i-th vehicle type; n i is the number of the i-th vehicle type during the observation period, where the unit of the observation period is day; w i =n i / N i , reflecting the degree of its influence on the response of the bridge structure; R represents the weighted average of the structural monitoring response eigenvalues.

7. A highway bridge damage assessment method based on specific traffic flow and structural monitoring response as claimed in claim 1, characterized in that The method for evaluating the health status of the bridge in step S7 is that the weighted average value of the overall structural response under the specific traffic load monitored for multiple days is within the range of ±5% with the date. If it exceeds ±5%, it is determined that the bridge may be damaged.

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