Vehicle load deflection integrated intelligent analysis method, system, equipment and medium

Abstract

The invention relates to the technical field of data processing, in particular to a vehicle load deflection integrated intelligent analysis method, system and device and a medium, and the method comprises the steps: obtaining a vehicle basic data set and a vehicle load data set corresponding to all vehicles on a to-be-detected bridge within a preset time period; acquiring a bridge state data set and an environment data set of the to-be-detected bridge in a preset time period; determining a target vehicle distribution load data set according to the vehicle basic data set and the vehicle load data set; determining a bridge load deflection parameter set according to the bridge state data set, the environment data set and the target vehicle distribution load data set; and performing bridge damage evaluation on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage evaluation result. According to the method, a more accurate and more comprehensive bridge damage assessment result can be obtained, and the effectiveness of bridge maintenance management and the accuracy of bridge structure optimization can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an integrated intelligent analysis method, system, equipment and medium for vehicle load deflection. Background Art

[0002] Bridge damage analysis is crucial for timely detection of potential bridge problems, formulation of reasonable maintenance strategies, and extension of bridge service life. Although various advanced detection technologies and equipment continue to emerge, such as non-destructive testing technology, these technologies also have certain limitations. For example, non-destructive testing methods can only detect damage on the surface or near the surface of the bridge structure, and it is difficult to accurately identify deep internal damage. In addition, the bridge structure itself is complex and diverse, and its damage mechanism is affected by a combination of factors, such as traffic loads, environmental erosion, and material aging. Therefore, how to achieve more accurate and comprehensive bridge damage assessment has become a hot issue that needs to be solved urgently. Summary of the invention

[0003] The present invention provides a vehicle load-deflection integrated intelligent analysis method, system, device and medium to solve the technical problem of how to achieve more accurate and comprehensive bridge damage assessment.

[0004] In a first aspect, a vehicle load-deflection integrated intelligent analysis method is provided, comprising: Obtaining a vehicle basic data set and a vehicle load data set corresponding to all vehicles on the bridge to be inspected within a preset time period; Acquire a bridge status data set and an environment data set of a bridge to be inspected within a preset time period; Determine the target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set; Determine a bridge load deflection parameter set according to a bridge state data set, an environment data set, and a target vehicle distributed load data set; A bridge damage assessment is performed on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result.

[0005] In a second aspect, a vehicle load-deflection integrated intelligent analysis system is provided, the vehicle load-deflection integrated intelligent analysis system comprising a vehicle data acquisition module, a bridge data acquisition module, a load distribution determination module, a load-deflection parameter determination module and a bridge damage assessment module, wherein: The vehicle data acquisition module is used to acquire a vehicle basic data set and a vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset time period; The bridge data acquisition module is used to acquire a bridge status data set and an environment data set of the bridge to be detected within the preset time period; The load distribution determination module is used to determine a target vehicle distributed load data set based on the vehicle basic data set and the vehicle load data set; A load-deflection parameter determination module, used to determine a bridge load-deflection parameter set according to the bridge state data set, the environment data set and the target vehicle distributed load data set; The bridge damage assessment module is used to perform bridge damage assessment on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result.

[0006] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned vehicle load-deflection integrated intelligent analysis method when executing the computer program.

[0007] In a fourth aspect, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned vehicle load-deflection integrated intelligent analysis method are implemented.

[0008] In the scheme implemented by the above-mentioned vehicle load-deflection integrated intelligent analysis method and system, by obtaining the vehicle basic data set and vehicle load data set corresponding to all vehicles on the bridge to be inspected within a preset time period, and obtaining the bridge status data set and environmental data set of the bridge to be inspected within the preset time period, the target vehicle distributed load data set can be determined according to the vehicle basic data set and the vehicle load data set, and the bridge load-deflection parameter set can be further determined according to the bridge status data set, the environmental data set and the target vehicle distributed load data set, so that bridge damage assessment can be performed on each bridge load-deflection parameter in the bridge load-deflection parameter set, and more accurate and comprehensive bridge damage assessment results can be obtained, which is beneficial to improve the effectiveness of bridge maintenance management and the accuracy of structural optimization of bridges, and helps to extend the service life of bridges. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0010] Figure 1 It is a structural schematic diagram of a vehicle load-deflection integrated intelligent analysis system in one embodiment of the present invention; Figure 2 It is a schematic diagram of a process of an integrated intelligent analysis method of vehicle load deflection in one embodiment of the present invention; Figure 3 It is a structural schematic diagram of a vehicle load deflection integrated intelligent analysis device in one embodiment of the present invention; Figure 4 is a schematic diagram of a structure of a computer device in one embodiment of the present invention; Figure 5 It is another structural schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0011] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0012] The vehicle load deflection integrated intelligent analysis method provided by the embodiment of the present invention can be applied in the following aspects: Figure 1In the vehicle load-deflection integrated intelligent analysis system, the client of the vehicle load-deflection integrated intelligent analysis system communicates with the server of the vehicle load-deflection integrated intelligent analysis system through the network. For example, taking the bridge damage assessment scenario as an example, the target user (such as R&D personnel or management personnel) can upload the vehicle basic data set and vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset period of time through the client, as well as the bridge status data set and environmental data set of the bridge to be detected within the preset period of time. Accordingly, the server can obtain the vehicle basic data set and vehicle load data set corresponding to all vehicles on the bridge to be detected within the preset time period through the client, and obtain the bridge status data set and environmental data set of the bridge to be detected within the preset time period, so as to determine the target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set, and further determine the bridge load deflection parameter set according to the bridge status data set, the environmental data set and the target vehicle distributed load data set, so as to perform bridge damage assessment on each bridge load deflection parameter in the bridge load deflection parameter set, so as to obtain a more accurate and comprehensive bridge damage assessment result, and feed back the bridge damage assessment result to the client. Accordingly, the client can receive the bridge damage assessment result from the server, and can display the bridge damage assessment result on the client for the target user to query or browse. By adopting the integrated intelligent analysis method of vehicle load deflection provided by the present application, it can be beneficial to improve the effectiveness of bridge maintenance management and the accuracy of structural optimization of bridges, and help to extend the service life of bridges.

[0013] The client may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices. The server may be implemented by an independent server or a server cluster consisting of multiple servers. The present invention is described in detail below through specific embodiments.

[0014] See also Figure 2 As shown, Figure 2 A schematic flow chart of a vehicle load-deflection integrated intelligent analysis method provided by an embodiment of the present invention includes the following steps: S10: Obtaining a vehicle basic data set and a vehicle load data set corresponding to all vehicles on the bridge to be inspected within a preset time period.

[0015] The preset time period may be a pre-set period of time, which may be a system default period or a target user pre-set period, and the present application does not limit this. The bridge to be inspected may be a bridge that needs to be inspected and evaluated, such as a bridge that needs to be damaged. The bridge to be inspected may be understood as the object targeted by the vehicle load-deflection integrated intelligent analysis method provided in the present application.

[0016] The vehicle basic data set may include one or more vehicle basic data, which may be the basic data corresponding to any vehicle on the bridge to be detected within a preset period of time, and may include but is not limited to the type of vehicle (such as a sedan, a truck, etc.), vehicle size (such as length, width, height), axle-related data (such as axle position, wheelbase, etc.), etc. The vehicle basic data set can help understand the basic characteristics of each vehicle and the basic situation of each vehicle's effect on the bridge.

[0017] The vehicle load data set may include one or more vehicle load data, which may be the load data corresponding to any vehicle on the bridge to be detected within a preset period of time, and may include but is not limited to the total load of any vehicle, the axle load corresponding to each axle of any vehicle, and other data, which are not limited in this application. The vehicle load data set may help determine the relevant conditions of the load generated by the vehicle on the bridge.

[0018] By obtaining the basic vehicle data set and vehicle load data set corresponding to all vehicles on the bridge to be inspected within a preset time period, we can better understand the traffic load characteristics on the bridge during this period, such as the size of the traffic flow, the composition ratio of vehicle types, the distribution pattern of vehicle loads, etc., and can more accurately calculate the distributed load generated by vehicles on the bridge in subsequent steps, so as to more accurately evaluate the effect of vehicles on the bridge, and thus provide more accurate and comprehensive data basis for the fatigue damage assessment of the bridge.

[0019] S20: Acquire a bridge status data set and an environment data set of the bridge to be inspected within the preset time period.

[0020] The bridge status data set may include one or more bridge status data, which may be various data that can reflect the state of the bridge itself. The bridge status data may include, but are not limited to, data such as displacement, strain, vibration frequency, and cracks at key positions of the bridge. Among them, the key positions of the bridge may be the mid-span position of the bridge beam, the top of the pier, the support position, and both sides of the expansion joint, etc., which are not limited in this application.

[0021] The environmental data set may include one or more environmental data, which may be data related to the environment in which the bridge is located within a preset period of time, and data related to the instrument or device responsible for collecting bridge data within the preset period of time. The data related to the environment may include, but are not limited to, temperature, humidity, wind speed, wind direction, etc. The data related to the instrument or device may include, but are not limited to, power status data, working mode, calibration data, position and posture data, fault warning data, and collection frequency data of the instrument or device.

[0022] By obtaining the bridge status data set and environmental data set of the bridge to be inspected within a preset time period, the working status of the bridge can be fully understood, the impact of environmental data on the bridge can be analyzed, and the bridge status data and environmental data can be further combined to estimate the performance changes of the bridge in the future, discover potential problems in advance and take corresponding measures, thereby extending the service life of the bridge and reducing maintenance costs.

[0023] S30: Determine a target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set.

[0024] Among them, the target vehicle distributed load data set may include one or more target vehicle distributed load data, which may be obtained after calculation and processing based on the vehicle basic data set and the vehicle load data set, and may be used to describe the distribution of vehicle loads at different positions on the bridge to be detected within a preset period of time. In other words, by analyzing the load distribution data generated by different vehicle loads at different positions on the bridge at the same acquisition moment (such as the first acquisition moment and the second acquisition moment to be mentioned below), the load distribution data of each position of the bridge at all times within the preset period of time can be further obtained, that is, the above-mentioned target vehicle distributed load data set.

[0025] It should be understood that determining the target vehicle distributed load data set based on the vehicle basic data set and the vehicle load data set refers to the process of analyzing and calculating the distributed load generated by the bridge in response to external excitations of the bridge (such as vehicle load) to obtain the target vehicle distributed load data set.

[0026] Wherein, in step S30, namely, determining the target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set, comprises the following steps: S31: Acquire a first vehicle basic data subset corresponding to a first acquisition time and a second vehicle basic data subset corresponding to a second acquisition time from the vehicle basic data set; S32: Acquire, from the vehicle load data set, a first vehicle load data subset corresponding to the first acquisition time and a second vehicle load data subset corresponding to the second acquisition time; S33: performing vehicle load distribution processing according to the first vehicle basic data subset and the first vehicle load data subset to obtain first vehicle distributed load data; S34: performing vehicle load distribution processing according to the second vehicle basic data subset and the second vehicle load data subset to obtain second vehicle distributed load data; S35: Determine a target vehicle distributed load data set according to the first vehicle distributed load data and the second vehicle distributed load data.

[0027] Among them, the first acquisition moment can be any time point within the preset period, and the second acquisition moment can be any time point within the preset period except the first acquisition moment. Optionally, the first acquisition moment and the second acquisition moment can be adjacent moments or non-adjacent moments, and the present application does not limit this. It can be understood that the present application is illustrated by selecting the first acquisition moment and the second acquisition moment as an example, which does not constitute a limitation on the present application. Optionally, other moments within the preset period can be further selected, such as the third acquisition moment, the fourth acquisition moment, etc., and the present application does not limit this.

[0028] The first vehicle basic data subset may include one or more vehicle basic data corresponding to the first acquisition time (i.e., first vehicle basic data), and the first vehicle basic data may include but is not limited to the type, size, axle-related data, etc. of all vehicles on the bridge at the first acquisition time. The second vehicle basic data subset may include one or more vehicle basic data corresponding to the second acquisition time (i.e., second vehicle basic data), and the second vehicle basic data may include but is not limited to the type, size, axle-related data, etc. of all vehicles on the bridge at the second acquisition time.

[0029] The first vehicle load data subset may include one or more vehicle load data corresponding to the first acquisition time (i.e., first vehicle load data), and the first vehicle load data may include, but are not limited to, the total load of each vehicle on the bridge at the first acquisition time, the axle load of each axle, and other related data. The second vehicle load data subset may include one or more vehicle load data corresponding to the second acquisition time (i.e., second vehicle load data), and the second vehicle load data may include, but are not limited to, the total load of each vehicle on the bridge at the second acquisition time, the axle load of each axle, and other related data.

[0030] The first vehicle distributed load data can be understood as the relevant data of the load distribution of the vehicle on the bridge at the first acquisition moment obtained after the vehicle load distribution processing is performed on the first vehicle basic data subset and the first vehicle load data subset. The second vehicle distributed load data can be understood as the relevant data of the load distribution of the vehicle on the bridge at the second acquisition moment obtained after the vehicle load distribution processing is performed on the second vehicle basic data subset and the second vehicle load data subset.

[0031] It should be understood that, according to the first vehicle basic data subset and the first vehicle load data subset, performing vehicle load distribution processing to obtain the first vehicle distributed load data refers to the process of analyzing and calculating the distributed load generated by the vehicle on the bridge at the first acquisition time to obtain the first vehicle distributed load data. Among them, step S33, that is, according to the first vehicle basic data subset and the first vehicle load data subset, performing vehicle load distribution processing to obtain the first vehicle distributed load data, includes the following steps: S331: Acquire the axle position corresponding to each axle of each vehicle from the first vehicle basic data subset to obtain a first axle position data set; S332: acquiring the axle load corresponding to each axle of each vehicle from the first vehicle load data subset to obtain a first axle load data set; S333: determining the distributed load at each position on the bridge to be inspected at the first acquisition time according to the first axle position data set and the first axle load data set; S334: Obtain first vehicle distributed load data according to the distributed load at each position on the bridge to be inspected at the first acquisition time.

[0032] The first axle position data set may include one or more axle position data (i.e., first axle position data), and the first axle position data may be used to indicate the relevant data of the corresponding position of each axle of each vehicle on the bridge to be detected at the first acquisition time. The first axle load data set may include one or more first axle load data, and the first axle load data may be used to indicate the relevant data of the load size borne by each axle of each vehicle on the bridge to be detected at the first acquisition time.

[0033] It should be noted that the axle position information can clarify the specific points of action of the vehicle load on the bridge, and the axle load can determine the specific size of the load at each point of action. The combination of the two can accurately calculate the distributed load borne by each position on the bridge, and then provide key data support for analyzing the stress state and deformation of the bridge under the action of vehicle loads, as well as conducting structural safety assessments. This helps to understand the actual working conditions of the bridge more scientifically and provide a reliable basis for bridge maintenance management and structural optimization.

[0034] Specifically, based on the first axle position data set and the first axle load data set, the distributed load at each position on the bridge to be inspected at the first acquisition moment can be further determined, that is, the load conditions acting on different positions of the bridge at the first acquisition moment.

[0035] Optionally, the process of determining the distributed load at each position on the bridge to be detected at the first acquisition time according to the first axle position data set and the first axle load data set may refer to the following formula: in, It can be used to indicate the bridge to be detected at the first acquisition time. Distributed loads at locations; Can be used to indicate the bridge to be inspected Location; It can be used to indicate the number of vehicles on the bridge to be detected at the first acquisition moment; Can be used to represent the index of the vehicle; Can be used to indicate the number of axles of the vehicle; Can be used to indicate the index of an axle; It can be used to represent the axle load of the jth axle of the i-th vehicle; Can be used to represent operations through Dirac functions; It can be used to represent the axle position of the j-th axle of the i-th vehicle.

[0036] Furthermore, after determining the distributed load at each position on the bridge to be inspected at the first acquisition moment, the distributed load at each position can be integrated to obtain the first vehicle distributed load data including all positions, so as to be used for analyzing the stress and performance of the bridge in subsequent steps.

[0037] Optionally, the process of obtaining the first vehicle distributed load data according to the distributed load at each position on the bridge to be detected at the first acquisition time can be referred to the following formula: in, Can be used to represent the first vehicle distributed load data; It can be used to indicate the bridge to be detected at the first acquisition time. Distributed loads at locations; It can be used to indicate the bridge to be detected at the first acquisition time. Distributed loads at locations; It can be used to indicate the bridge to be detected at the first acquisition time. The distributed load at the location, L can be used to represent the total length of the bridge to be inspected.

[0038] It should be noted that the above-mentioned method (that is, the implementation logic of performing vehicle load distribution processing according to the first vehicle basic data subset and the first vehicle load data subset to obtain the first vehicle distributed load data) can be further adopted to perform vehicle load distribution processing according to the second vehicle basic data subset and the second vehicle load data subset to obtain the second vehicle distributed load data, thereby obtaining relevant data on the load distribution of the vehicle on the bridge at the second acquisition time. The relevant content can be found in the detailed description of the above steps, and this application will not repeat them here.

[0039] By selecting the vehicle basic data subsets and vehicle load data subsets corresponding to different time points within the preset time period (the embodiment of the present application takes two time points as an example), the vehicle data at different times can be analyzed and processed respectively, so as to have a more detailed understanding of the changes in the load distribution of the vehicle on the bridge over time, thereby obtaining a target vehicle distributed load data set that includes all times within the preset time period. Specifically, the first vehicle distributed load data, the second vehicle distributed load data, and the vehicle distributed load data at other times are integrated, such as sorting and integrating in chronological order, etc., to further obtain a target vehicle distributed load data set that includes all times within the preset time period, and the present application does not limit this.

[0040] S40: Determine a bridge load deflection parameter set according to the bridge state data set, the environment data set and the target vehicle distributed load data set.

[0041] Among them, the bridge load deflection parameter set may include one or more bridge load deflection parameters, which can be obtained after comprehensive analysis and processing of the bridge status data set, the environmental data set and the target vehicle distributed load data set, and can be used to reflect the load deflection changes of the bridge under the influence of different factors.

[0042] It should be understood that determining the bridge load deflection parameter set based on the bridge state data set, the environment data set and the target vehicle distributed load data set refers to a process of analyzing the state of the bridge itself and further analyzing it in combination with the environment and vehicle distributed load to obtain the bridge load deflection parameter set. Among them, step S40, that is, determining the bridge load deflection parameter set based on the bridge state data set, the environment data set and the target vehicle distributed load data set, includes the following steps: S41: Acquire, from the bridge status data set, a first bridge status data subset corresponding to the first analysis moment and a second bridge status data subset corresponding to a moment next to the first analysis moment; S42: performing bridge state change analysis at adjacent moments according to the first bridge state data subset, the second bridge state data subset, the environmental data set, and the target vehicle distributed load data set to obtain a first bridge input load deflection parameter; S43: performing dynamic disturbance analysis on the bridge state data corresponding to each moment in the bridge state data set to obtain a bridge dynamic deflection data set; S44: performing input-output change analysis processing according to the first bridge dynamic deflection data subset corresponding to the first analysis moment in the bridge dynamic deflection data set, the first bridge state data subset and the environmental data set to obtain the first bridge output load deflection parameter; S45: Determine a bridge load deflection parameter set according to the first bridge input load deflection parameter and the first bridge output load deflection parameter.

[0043] The first bridge state data subset may include one or more bridge state data corresponding to the first analysis moment, and the bridge state data corresponding to the first analysis moment may include but not limited to the position of the key position of the bridge at the first analysis moment, strain, and other data that can reflect the bridge state. The second bridge state data subset may include one or more bridge state data corresponding to the next moment of the first analysis moment, and the bridge state data corresponding to the next moment of the first analysis moment may include but not limited to the position of the key position of the bridge at the next moment of the first analysis moment, strain, and other data that can reflect the bridge state.

[0044] It should be noted that the first analysis moment and the next moment of the first analysis moment can be two adjacent moments within a preset time period. Optionally, the first analysis moment can be the aforementioned first acquisition moment, or the aforementioned second acquisition moment, or other moments within a preset time period, and the present application does not limit this. By acquiring a subset of bridge status data corresponding to adjacent moments, the change between the state at the previous moment and the state at the next moment can be better clarified, thereby obtaining more accurate bridge load deflection parameters. It should be noted that the first analysis moment and the aforementioned first acquisition moment and second acquisition moment are all time points within a preset time period. The present application uses different naming methods to distinguish the acquisition moment and the analysis moment as time points in different steps, which does not constitute a limitation to the present application.

[0045] The first bridge input load deflection parameter can be understood as a related parameter that can reflect the change in load deflection caused by changes in the bridge state at adjacent moments due to changes in external inputs (such as vehicle loads, environmental factors) after analyzing and processing the first bridge state data subset, the second bridge state data subset, the environmental data set, and the target vehicle distributed load data set. The first bridge input load deflection parameter can be the bridge input load deflection parameter at the first analysis moment. It is understandable that the above analysis can be further performed on the bridge state data, vehicle distributed load data, and environmental data at other moments to obtain the bridge input load deflection parameters at other moments, which will not be repeated in this application.

[0046] It should be understood that, according to the first bridge state data subset, the second bridge state data subset, the environmental data set and the target vehicle distributed load data set, the bridge state change analysis and processing at adjacent moments to obtain the first bridge input load deflection parameter refers to the process of how to obtain the first bridge input load deflection parameter. Among them, in step S42, that is, according to the first bridge state data subset, the second bridge state data subset, the environmental data set and the target vehicle distributed load data set, the bridge state change analysis and processing at adjacent moments to obtain the first bridge input load deflection parameter includes the following steps: S421: Acquire a first environment data subset corresponding to the first analysis moment from the environment data set; S422: Determine first environmental error data according to the first environmental data subset; S423: performing bridge characteristic value change analysis processing according to the first bridge state data subset, the second bridge state data subset and the first environmental error data to determine a reference bridge characteristic value load deflection parameter; S424: performing bridge input response analysis processing according to the reference bridge characteristic value load deflection parameter, the first vehicle distributed load data in the target vehicle distributed load data set, the first bridge state data subset, the second bridge state data subset and the first environmental error data to obtain a bridge input response load deflection parameter; S425: adjusting the reference bridge characteristic value load-deflection parameter according to the bridge input response load-deflection parameter to obtain the target bridge characteristic value load-deflection parameter; S426: Determine the first bridge input load deflection parameter according to the bridge input response load deflection parameter and the target bridge characteristic value load deflection parameter.

[0047] The first environmental data subset may include one or more environmental data at the first analysis time, and the environmental data at the first analysis time may include but are not limited to environmental data such as temperature, humidity, wind speed, etc. at the first analysis time. The first environmental error data can be understood as error data that may be generated by environmental factors in the measurement or analysis of the bridge state determined according to the first environmental data subset. For example, when the wind speed is very high, it may affect the displacement monitoring of the key position of the bridge. Therefore, by considering the environmental error, a more accurate bridge input load deflection parameter can be determined.

[0048] Specifically, since the change of environmental data has a small impact on the bridge within a certain range, and the impact on the bridge increases significantly after exceeding the corresponding threshold, multiple environmental data thresholds can be set so that when the first environmental data in the first environmental data subset exceeds each environmental data threshold, the corresponding first environmental error data can be determined by a table lookup method. By setting multiple environmental data thresholds, it is possible to better adapt to different environmental change scenarios and quickly and effectively capture the impact of environmental changes on bridges. Optionally, in the case where multiple environmental factors affect the bridge mutually, the environmental error data caused by environmental changes can be comprehensively considered in combination with multiple environmental factors, and this application does not limit this.

[0049] The reference bridge eigenvalue load-deflection parameters can be understood as parameters that are determined after a preliminary analysis of the first bridge state data subset, the second bridge state data subset and the first environmental error data to indicate the preliminary changes in relevant eigenvalues ​​of the bridge at adjacent moments (such as natural frequency, mode and other parameters reflecting the structural characteristics of the bridge).

[0050] Furthermore, after determining the eigenvalue load-deflection parameters of the reference bridge, bridge input response analysis and processing can be further performed based on the eigenvalue load-deflection parameters of the reference bridge, the first vehicle distributed load data in the target vehicle distributed load data set, the first bridge state data subset, the second bridge state data subset and the first environmental error data to obtain the bridge input response load-deflection parameters and the updated and adjusted target bridge eigenvalue load-deflection parameters.

[0051] It should be noted that since the reference bridge characteristic value load disturbance parameter is a reference value of the bridge characteristic value load disturbance parameter obtained after preliminary analysis of the first bridge state data subset, the second bridge state data subset and the first environmental error data; the reference bridge characteristic value load disturbance parameter can be further used to assist in determining the bridge input response load deflection parameter. Therefore, after determining the bridge input response load deflection parameter, the reference bridge characteristic value load disturbance parameter can be further calculated based on the bridge input response load deflection parameter to obtain the target bridge characteristic value load deflection parameter that matches the bridge input response load deflection parameter.

[0052] Optionally, according to the reference bridge characteristic value load deflection parameter, the first vehicle distributed load data in the target vehicle distributed load data set, the first bridge state data subset, the second bridge state data subset and the first environmental error data, a bridge input response analysis is performed to obtain a bridge input response load deflection parameter, and according to the bridge input response load deflection parameter, the reference bridge characteristic value load deflection parameter is adjusted to obtain the target bridge characteristic value load deflection parameter. The process can be seen in the following formula: in, can be used to represent a second subset of bridge status data; It can be used to represent the eigenvalue load-deflection parameters of the reference bridge; can be used to represent a first bridge status data subset; Can be used to represent first environmental error data; It can be used to represent the characteristic value load-deflection parameters of the target bridge; It can be used to represent the load-deflection parameters of bridge input response; can be used to represent the first vehicle distributed load data in the target vehicle distributed load data set; It can be used to represent the operation of adjusting the reference bridge characteristic value load-deflection parameters according to the bridge input response load-deflection parameters to obtain the target bridge characteristic value load-deflection parameters.

[0053] It should be noted that The dynamic characteristics of the vehicle load deflection integrated intelligent analysis system itself can be described. In the embodiment of the present application, the inherent properties of the bridge structure such as stiffness and damping can be reflected, and the response mode of the vehicle load deflection integrated intelligent analysis system to the input can be determined; and It can describe the effect of external input on the vehicle load deflection integrated intelligent analysis system, such as how the input of vehicle distributed load acts on the bridge. The effect of vehicle load on the bridge (with related) will also be different; conversely, changes in vehicle load (affecting ) will in turn affect the dynamic response of the bridge, thus affecting the Estimates.

[0054] In the initial stage of the vehicle load-deflection integrated intelligent analysis system or in certain specific situations (such as when there are no vehicles on the bridge), the input and output data of the system can be used to estimate the load deflection of the vehicle based on the initial conditions of the system and some prior information. , which will help to determine the Optionally, the following input and output data and iterative algorithms can be used to and Alternate updates are performed to continuously improve the accuracy of parameters.

[0055] By combining the bridge input response load deflection parameters and the target bridge characteristic value load deflection parameters, the first bridge input load deflection parameters can be determined, thereby realizing the extraction of parameters of the state change of the bridge due to external input at adjacent moments, and thus providing key data for subsequent bridge state analysis. Specifically, the bridge input response load deflection parameters and the target bridge characteristic value load deflection parameters can be integrated to form the first bridge input load disturbance parameters, and then in the subsequent bridge damage assessment process, the corresponding parameters can be queried from the first bridge input load disturbance parameters to realize a certain aspect (such as the aforementioned target bridge characteristic value load deflection parameters). It is more helpful to reflect the inherent properties of the bridge structure such as stiffness and damping. The bridge input response load deflection parameters This is more helpful for bridge damage assessment that reflects the relationship between external inputs and the system, and this application does not impose any restrictions on this.

[0056] It should be noted that the first bridge input load deflection parameter can be the bridge input load deflection parameter at the first analysis moment. Optionally, the bridge input load deflection parameter at other moments can also be analyzed and determined by the above method to obtain a more comprehensive set of bridge load deflection parameters. This application does not impose any restrictions on this.

[0057] The bridge dynamic deflection data set may include one or more bridge dynamic disturbance data, and the bridge dynamic deflection data set may be used to indicate a data set on the change of bridge deflection over time obtained after dynamic deflection analysis of the bridge status data at each moment in the bridge status data set. The bridge dynamic deflection data set may reflect the change of bridge deflection at different moments.

[0058] Specifically, the sensor measurement method can be used to implement the above process of obtaining the dynamic deflection data set of the bridge, such as installing displacement sensors at key positions of the bridge (such as mid-span, support points, etc.) to measure the distance change between the bridge surface and the sensor in real time, so as to obtain the bridge disturbance data; or the fiber grating sensor is pasted or buried inside or on the surface of the bridge structure to monitor the deformation of the bridge by monitoring the wavelength change of the fiber grating, and the wavelength change can be monitored and demodulated by a fiber optic demodulator to obtain the strain data of the bridge, and then the strain data is converted into deflection data; or an acceleration sensor can be installed on the bridge to measure the vibration acceleration of the bridge, so that the vibration acceleration can be integrated to obtain the displacement data, that is, the disturbance data of the bridge.

[0059] Optionally, a computer vision measurement method may be used to implement the above process of obtaining a dynamic deflection data set of a bridge, such as photographing the bridge with a high-speed camera, so that the images taken at different times may be processed by a digital image correlation algorithm to calculate the displacement changes of multiple preset positions on the bridge surface in the image, so as to further obtain the deflection data of the bridge; or a fixed camera installed around the bridge may be used to continuously photograph the bridge, so that the contour information of the bridge may be extracted by analyzing the video image, and the deflection data of the bridge may be further calculated based on the changes in the contour. This application does not impose any restrictions on this.

[0060] The first bridge output load deflection parameter can be understood as the relevant parameter obtained after the input-output change analysis and processing of the first bridge dynamic deflection data subset, the first bridge state data subset and the environmental data set, which is used to reflect the change of the bridge state at the output level (such as observable indicators such as deflection change) and the change of load deflection. It should be noted that the present application uses the change of the output level as the change of the bridge disturbance data as an example for explanation, which does not constitute a limitation on the present application. Optionally, other observable indicators (such as the dynamic curve of the deflection distribution along the span of the bridge, or the bridge deformation, etc.) can be selected for output level change analysis, and the present application does not limit this. The first bridge output load deflection parameter can be the bridge output load deflection parameter at the first analysis moment. It can be understood that the above analysis can be further performed on the bridge state data and environmental data at other moments to obtain the bridge output load deflection parameter at other moments, and the present application will not repeat it here.

[0061] It should be noted that when performing input-output change analysis and processing, the relevant data of the instrument or equipment responsible for collecting bridge data during the corresponding preset time period in the environmental data set can be used as a reference. For example, the instrument (or equipment) error data at each moment can be determined based on the environmental data set, and then the input-output change analysis and processing can be further performed based on the bridge dynamic deflection data, bridge status data and environmental data to obtain the bridge output load deflection parameters.

[0062] Optionally, the process of performing input-output change analysis and processing to obtain the first bridge output load deflection parameter according to the first bridge dynamic deflection data subset corresponding to the first analysis time in the bridge dynamic deflection data set, the first bridge state data subset and the first instrument (or equipment) error data corresponding to the first analysis time in the environmental data set can be referred to the following formula: in, It can be used to represent the first bridge dynamic deflection data subset corresponding to the first analysis time k in the bridge dynamic deflection data set; It can be used to represent the first bridge output load deflection parameter; can be used to represent a first bridge status data subset; It can be used to represent the first instrument (or equipment) error data corresponding to the first analysis time k in the environmental data set. It should be noted that, The load-deflection parameters outputted in response to a certain characteristic value of the bridge can be characterized, such as the load-deflection parameters of the bridge disturbance data outputted in response to the displacement of a key position of the bridge.

[0063] Furthermore, after obtaining the first bridge input load deflection parameter and the first bridge output load deflection parameter at the first analysis moment, and after obtaining the bridge input load deflection parameter and the bridge output load deflection parameter at other moments, each bridge input load deflection parameter and each bridge output load deflection parameter can be further integrated to obtain a set of bridge load deflection parameters that can comprehensively reflect the state changes of the bridge under the influence of different factors, thereby providing a basis for subsequent bridge damage assessment.

[0064] S50: Performing bridge damage assessment on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result.

[0065] The bridge damage assessment result can be understood as the relevant data of the damage assessment result obtained after judging and evaluating whether the bridge is damaged and the degree of damage according to each bridge load-deflection parameter set in the bridge load-deflection parameter set. Specifically, the bridge damage assessment result may include relevant assessment data such as whether the bridge is damaged at various locations, the degree of damage, the type of damage, the prevention of damage, and the repair of damage, and this application does not limit this.

[0066] Specifically, based on each bridge load-deflection parameter in the bridge load-deflection parameter set, a damage index corresponding to each bridge load-deflection parameter can be established, so as to perform a comprehensive damage assessment on each damage index. For example, a weighted average method can be used to assign different weights according to the importance of each damage to obtain a comprehensive damage assessment result; or a fuzzy relationship matrix can be established to obtain a comprehensive damage assessment result through fuzzy transformation. This application does not impose any restrictions on this.

[0067] Optional, bridge input response load deflection parameters to describe the relationship between external input and vehicle load deflection integrated intelligent analysis system For example, when a bridge is damaged, its response characteristics to external loads will change, thus affecting By analyzing The changes at different times are compared with the input response load deflection parameters of the bridge under normal conditions (such as ) for comparison; for example, one can calculate The magnitude of changes in some key elements in With standard distance metric between them (such as Euclidean distance, etc.) to further obtain The present application does not impose any limitation on this.

[0068] It can be seen that in the above scheme, by obtaining the vehicle basic data set and vehicle load data set corresponding to all vehicles on the bridge to be inspected within a preset time period, and obtaining the bridge status data set and environmental data set of the bridge to be inspected within the preset time period, the target vehicle distributed load data set can be determined according to the vehicle basic data set and the vehicle load data set, and the bridge load deflection parameter set can be further determined according to the bridge status data set, the environmental data set and the target vehicle distributed load data set, so that bridge damage assessment can be performed on each bridge load deflection parameter in the bridge load deflection parameter set, and more accurate and comprehensive bridge damage assessment results can be obtained, which is beneficial to improve the effectiveness of bridge maintenance management and the accuracy of structural optimization of bridges, and helps to extend the service life of bridges.

[0069] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0070] In one embodiment, a vehicle load-deflection integrated intelligent analysis device is provided, and the vehicle load-deflection integrated intelligent analysis device corresponds one-to-one to the vehicle load-deflection integrated intelligent analysis method in the above embodiment. Figure 3 As shown, the vehicle load deflection integrated intelligent analysis device includes a first acquisition module 101, a second acquisition module 102, a first determination module 103, a second determination module 104 and a processing module 105. The functional modules are described in detail as follows: The first acquisition module 101 is used as a vehicle data acquisition module, which is used to acquire a vehicle basic data set and a vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset period of time; The second acquisition module 102 is used to acquire a bridge state data set and an environment data set of the bridge to be detected within the preset time period; A first determination module 103, configured to determine a target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set; A second determination module 104 is used to determine a bridge load deflection parameter set according to the bridge state data set, the environment data set and the target vehicle distributed load data set; The processing module 105 is used to perform bridge damage assessment on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result.

[0071] In one embodiment, the first determination module 103 is used to determine the target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set, specifically for: Acquire, from the vehicle basic data set, a first vehicle basic data subset corresponding to a first acquisition time and a second vehicle basic data subset corresponding to a second acquisition time; Acquire, from the vehicle load data set, a first vehicle load data subset corresponding to the first acquisition time and a second vehicle load data subset corresponding to the second acquisition time; According to the first vehicle basic data subset and the first vehicle load data subset, vehicle load distribution processing is performed to obtain first vehicle distributed load data; According to the second vehicle basic data subset and the second vehicle load data subset, vehicle load distribution processing is performed to obtain second vehicle distributed load data; A target vehicle distributed load data set is determined according to the first vehicle distributed load data and the second vehicle distributed load data.

[0072] In one embodiment, the first determination module 103 is used to perform vehicle load distribution processing according to the first vehicle basic data subset and the first vehicle load data subset to obtain first vehicle distributed load data, specifically for: Acquire the axle position corresponding to each axle of each vehicle from the first vehicle basic data subset to obtain a first axle position data set; Acquire the axle load corresponding to each axle of each vehicle from the first vehicle load data subset to obtain a first axle load data set; Determine the distributed load at each position on the bridge to be inspected at the first acquisition time according to the first axle position data set and the first axle load data set; The first vehicle distributed load data is obtained according to the distributed load at each position on the bridge to be detected at the first acquisition time.

[0073] In one embodiment, the second determination module 104 is used to determine a bridge load deflection parameter set according to the bridge state data set, the environment data set and the target vehicle distributed load data set, specifically for: Acquire, from the bridge state data set, a first bridge state data subset corresponding to the first analysis moment and a second bridge state data subset corresponding to a moment next to the first analysis moment; According to the first bridge state data subset, the second bridge state data subset, the environmental data set and the target vehicle distributed load data set, performing bridge state change analysis processing at adjacent moments to obtain a first bridge input load deflection parameter; Performing dynamic disturbance analysis on the bridge state data corresponding to each moment in the bridge state data set to obtain a bridge dynamic deflection data set; According to the first bridge dynamic deflection data subset corresponding to the first analysis moment in the bridge dynamic deflection data set, the first bridge state data subset and the environmental data set, input and output change analysis processing is performed to obtain the first bridge output load deflection parameter; A bridge load deflection parameter set is determined according to the first bridge input load deflection parameter and the first bridge output load deflection parameter.

[0074] In one embodiment, the second determination module 104 is used to perform bridge state change analysis at adjacent moments according to the first bridge state data subset, the second bridge state data subset, the environmental data set and the target vehicle distributed load data set to obtain the first bridge input load deflection parameter, specifically for: Acquire a first subset of environmental data corresponding to the first analysis moment from the environmental data set; determining first environmental error data according to the first environmental data subset; Performing bridge characteristic value change analysis processing according to the first bridge state data subset, the second bridge state data subset and the first environmental error data to determine a reference bridge characteristic value load deflection parameter; According to the reference bridge eigenvalue load deflection parameter, the first vehicle distributed load data in the target vehicle distributed load data set, the first bridge state data subset, the second bridge state data subset and the first environmental error data, a bridge input response analysis process is performed to obtain a bridge input response load deflection parameter, and the reference bridge eigenvalue load deflection parameter is adjusted to obtain a target bridge eigenvalue load deflection parameter; The first bridge input load deflection parameter is determined according to the bridge input response load deflection parameter and the target bridge characteristic value load deflection parameter.

[0075] The present invention provides an integrated intelligent analysis device for vehicle load deflection. By acquiring a vehicle basic data set and a vehicle load data set corresponding to all vehicles on a bridge to be detected within a preset time period, and acquiring a bridge status data set and an environmental data set of the bridge to be detected within the preset time period, a target vehicle distributed load data set can be determined according to the vehicle basic data set and the vehicle load data set, and a bridge load deflection parameter set can be further determined according to the bridge status data set, the environmental data set and the target vehicle distributed load data set, so that bridge damage assessment can be performed on each bridge load deflection parameter in the bridge load deflection parameter set, and a more accurate and comprehensive bridge damage assessment result can be obtained, which is beneficial to improving the effectiveness of bridge maintenance management and the accuracy of structural optimization of bridges, and helps to extend the service life of bridges.

[0076] For the specific definition of the integrated intelligent analysis device for vehicle load deflection, please refer to the definition of the integrated intelligent analysis method for vehicle load deflection above, which will not be repeated here. Each module in the above-mentioned integrated intelligent analysis device for vehicle load deflection can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0077] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client through a network connection. When the computer program is executed by the processor, it realizes the functions or steps of a service-side integrated intelligent analysis method for vehicle load deflection.

[0078] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as follows: Figure 5As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, the functions or steps on the client side of a vehicle load deflection integrated intelligent analysis method are implemented.

[0079] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Obtaining a vehicle basic data set and a vehicle load data set corresponding to all vehicles on the bridge to be inspected within a preset time period; Acquire a bridge state data set and an environment data set of the bridge to be detected within the preset time period; Determining a target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set; Determining a bridge load deflection parameter set according to the bridge state data set, the environment data set and the target vehicle distributed load data set; A bridge damage assessment is performed on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result.

[0080] The present invention provides a computer device, which obtains a vehicle basic data set and a vehicle load data set corresponding to all vehicles on a bridge to be detected within a preset time period, and obtains a bridge status data set and an environmental data set of the bridge to be detected within the preset time period. The target vehicle distributed load data set can be determined according to the vehicle basic data set and the vehicle load data set, and the bridge load deflection parameter set can be further determined according to the bridge status data set, the environmental data set and the target vehicle distributed load data set, so that bridge damage assessment can be performed on each bridge load deflection parameter in the bridge load deflection parameter set, and a more accurate and comprehensive bridge damage assessment result can be obtained, which is beneficial to improving the effectiveness of bridge maintenance management and the accuracy of structural optimization of bridges, and helps to extend the service life of bridges.

[0081] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Obtaining a vehicle basic data set and a vehicle load data set corresponding to all vehicles on the bridge to be inspected within a preset time period; Acquire a bridge state data set and an environment data set of the bridge to be detected within the preset time period; Determining a target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set; Determining a bridge load deflection parameter set according to the bridge state data set, the environment data set and the target vehicle distributed load data set; A bridge damage assessment is performed on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result.

[0082] The present invention provides a computer-readable storage medium, which can obtain a vehicle basic data set and a vehicle load data set corresponding to all vehicles on a bridge to be detected within a preset time period, and obtain a bridge status data set and an environmental data set of the bridge to be detected within the preset time period. According to the vehicle basic data set and the vehicle load data set, a target vehicle distributed load data set can be determined, and further according to the bridge status data set, the environmental data set and the target vehicle distributed load data set, a bridge load deflection parameter set can be determined, so that bridge damage assessment can be performed on each bridge load deflection parameter in the bridge load deflection parameter set, and a more accurate and comprehensive bridge damage assessment result can be obtained, which is beneficial to improving the effectiveness of bridge maintenance management and the accuracy of structural optimization of bridges, and helps to extend the service life of bridges.

[0083] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0084] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0085] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0086] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A vehicle load deflection integrated intelligent analysis method, characterized in that: The method comprises: Obtaining a vehicle basic data set and a vehicle load data set corresponding to all vehicles on the bridge to be inspected within a preset time period; Acquire a bridge state data set and an environment data set of the bridge to be detected within the preset time period; Determining a target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set; Determining a bridge load deflection parameter set according to the bridge state data set, the environment data set and the target vehicle distributed load data set; A bridge damage assessment is performed on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result.

2. The vehicle load-deflection integrated intelligent analysis method according to claim 1, characterized in that: The step of determining the target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set comprises: Acquire, from the vehicle basic data set, a first vehicle basic data subset corresponding to a first acquisition time and a second vehicle basic data subset corresponding to a second acquisition time; Acquire, from the vehicle load data set, a first vehicle load data subset corresponding to the first acquisition time and a second vehicle load data subset corresponding to the second acquisition time; According to the first vehicle basic data subset and the first vehicle load data subset, vehicle load distribution processing is performed to obtain first vehicle distributed load data; According to the second vehicle basic data subset and the second vehicle load data subset, vehicle load distribution processing is performed to obtain second vehicle distributed load data; A target vehicle distributed load data set is determined according to the first vehicle distributed load data and the second vehicle distributed load data.

3. The vehicle load-deflection integrated intelligent analysis method according to claim 2, characterized in that: The step of performing vehicle load distribution processing according to the first vehicle basic data subset and the first vehicle load data subset to obtain first vehicle distributed load data includes: Acquire the axle position corresponding to each axle of each vehicle from the first vehicle basic data subset to obtain a first axle position data set; Acquire the axle load corresponding to each axle of each vehicle from the first vehicle load data subset to obtain a first axle load data set; Determine the distributed load at each position on the bridge to be inspected at the first acquisition time according to the first axle position data set and the first axle load data set; The first vehicle distributed load data is obtained according to the distributed load at each position on the bridge to be detected at the first acquisition time.

4. The vehicle load-deflection integrated intelligent analysis method according to claim 3, characterized in that: Determining a bridge load deflection parameter set according to the bridge state data set, the environment data set and the target vehicle distributed load data set includes: Acquire, from the bridge state data set, a first bridge state data subset corresponding to a first analysis moment and a second bridge state data subset corresponding to a moment next to the first analysis moment; According to the first bridge state data subset, the second bridge state data subset, the environmental data set and the target vehicle distributed load data set, performing bridge state change analysis processing at adjacent moments to obtain a first bridge input load deflection parameter; Performing dynamic disturbance analysis on the bridge state data corresponding to each moment in the bridge state data set to obtain a bridge dynamic deflection data set; According to the first bridge dynamic deflection data subset corresponding to the first analysis time in the bridge dynamic deflection data set, the first bridge state data subset and the environmental data set, input and output change analysis processing is performed to obtain the first bridge output load deflection parameter; A bridge load deflection parameter set is determined according to the first bridge input load deflection parameter and the first bridge output load deflection parameter.

5. The vehicle load-deflection integrated intelligent analysis method according to claim 4, characterized in that: The step of analyzing and processing bridge state changes at adjacent moments based on the first bridge state data subset, the second bridge state data subset, the environmental data set, and the target vehicle distributed load data set to obtain the first bridge input load deflection parameter includes: Acquire a first subset of environmental data corresponding to the first analysis moment from the environmental data set; determining first environmental error data according to the first environmental data subset; Performing bridge characteristic value change analysis processing according to the first bridge state data subset, the second bridge state data subset and the first environmental error data to determine a reference bridge characteristic value load deflection parameter; According to the reference bridge characteristic value load-deflection parameter, the first vehicle distributed load data in the target vehicle distributed load data set, the first bridge state data subset, the second bridge state data subset and the first environmental error data, a bridge input response analysis process is performed to obtain a bridge input response load-deflection parameter; The reference bridge characteristic value load-deflection parameter is adjusted according to the bridge input response load-deflection parameter to obtain the target bridge characteristic value load-deflection parameter; The first bridge input load deflection parameter is determined according to the bridge input response load deflection parameter and the target bridge characteristic value load deflection parameter.

6. A vehicle load deflection integrated intelligent analysis system, characterized in that: The vehicle load-deflection integrated intelligent analysis system includes a vehicle data acquisition module, a bridge data acquisition module, a load distribution determination module, a load-deflection parameter determination module and a bridge damage assessment module, wherein: The vehicle data acquisition module is used to acquire a vehicle basic data set and a vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset time period; The bridge data acquisition module is used to acquire a bridge status data set and an environment data set of the bridge to be detected within the preset time period; The load distribution determination module is used to determine a target vehicle distributed load data set based on the vehicle basic data set and the vehicle load data set; The load-deflection parameter determination module is used to determine a bridge load-deflection parameter set according to the bridge state data set, the environment data set and the target vehicle distributed load data set; The bridge damage assessment module is used to perform bridge damage assessment on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result.

7. The vehicle load-deflection integrated intelligent analysis system according to claim 6, characterized in that: in, The vehicle data acquisition module is used to acquire a first vehicle basic data subset corresponding to a first acquisition time and a second vehicle basic data subset corresponding to a second acquisition time from the vehicle basic data set; The vehicle data acquisition module is used to acquire, from the vehicle load data set, a first vehicle load data subset corresponding to the first acquisition moment and a second vehicle load data subset corresponding to the second acquisition moment; The load distribution determination module is used to perform vehicle load distribution processing according to the first vehicle basic data subset and the first vehicle load data subset to obtain first vehicle distributed load data; The load distribution determination module is used to perform vehicle load distribution processing according to the second vehicle basic data subset and the second vehicle load data subset to obtain second vehicle distributed load data; The load distribution determination module is used to determine a target vehicle distributed load data set based on the first vehicle distributed load data and the second vehicle distributed load data.

8. The vehicle load-deflection integrated intelligent analysis system according to claim 7, characterized in that: in, The vehicle data acquisition module is used to acquire the axle position corresponding to each axle of each vehicle from the first vehicle basic data subset to obtain a first axle position data set; The vehicle data acquisition module is used to acquire the axle load corresponding to each axle of each vehicle from the first vehicle load data subset to obtain a first axle load data set; The load distribution determination module is used to determine the distributed load at each position on the bridge to be detected at the first acquisition time according to the first axle position data set and the first axle load data set; The load distribution determination module is used to obtain the first vehicle distributed load data according to the distributed load at each position on the bridge to be detected at the first acquisition time.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the vehicle load-deflection integrated intelligent analysis method as described in any one of claims 1 to 5 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the vehicle load-deflection integrated intelligent analysis method as described in any one of claims 1 to 5 is implemented.

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