Integrated Intelligent Analysis Method, System, Device and Medium for Vehicle Load Deflection

Abstract

The present invention relates to the technical field of data processing, and specifically relates to a vehicle load deflection integrated intelligent analysis method, system, device and medium, including: obtaining 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; obtaining a bridge state data set and an environmental data set of the bridge to be detected within a 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 environmental data set and the target vehicle distributed load data set; performing bridge damage assessment on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result. This application can obtain more accurate and comprehensive bridge damage assessment results, which is beneficial to improving the effectiveness of bridge maintenance management and the accuracy of bridge structure optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a vehicle load deflection integrated intelligent analysis method, system, device and medium. Background Art

[0002] Bridge damage analysis is crucial for timely discovering potential problems of bridges, formulating reasonable maintenance strategies, and extending the service life of bridges. Although various advanced detection technologies and devices are emerging continuously, such as non-destructive testing technologies, etc., 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 has complexity and diversity, and its damage mechanism is affected by a variety of factors, such as traffic load, environmental erosion, and material aging, etc. Therefore, how to achieve more accurate and comprehensive bridge damage assessment has become a hot issue to be solved urgently at present. 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 the first aspect, a vehicle load deflection integrated intelligent analysis method is provided, including:

[0005] Obtaining 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;

[0006] Obtaining a bridge state data set and an environmental data set of the bridge to be detected within a preset time period;

[0007] Determining a target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set;

[0008] Determining a bridge load deflection parameter set according to the bridge state data set, the environmental data set and the target vehicle distributed load data set;

[0009] Performing bridge damage assessment on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result.

[0010] In the second aspect, a vehicle load deflection integrated intelligent analysis system is provided. 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,

[0011] 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;

[0012] The bridge data acquisition module is used to acquire a bridge state data set and an environmental data set of the bridge to be detected within the preset time period;

[0013] The load distribution determination module is used to determine a target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set;

[0014] The load deflection parameter determination module is used to determine a bridge load deflection parameter set according to the bridge state data set, the environmental data set and the target vehicle distributed load data set;

[0015] 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.

[0016] 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. When the processor executes the computer program, the steps of the above-mentioned integrated intelligent analysis method for vehicle load and deflection are implemented.

[0017] In a fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned integrated intelligent analysis method for vehicle load and deflection are implemented.

[0018] In the solution implemented by the above-mentioned integrated intelligent analysis method and system for vehicle load and deflection, by acquiring 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, and acquiring a bridge state 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 further, a bridge load deflection parameter set can be determined according to the bridge state 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 to obtain a more accurate and comprehensive bridge damage assessment result, which is conducive to improving the effectiveness of bridge maintenance management and the accuracy of bridge structure optimization, and helps to extend the service life of the bridge. Description of the Drawings

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for the description of the embodiments of the present invention. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0020] Figure 1 It is a schematic structural diagram of an integrated intelligent analysis system for vehicle load deflection in an embodiment of the present invention;

[0021] Figure 2 It is a schematic flowchart of an integrated intelligent analysis method for vehicle load deflection in an embodiment of the present invention;

[0022] Figure 3 It is a schematic structural diagram of an integrated intelligent analysis device for vehicle load deflection in an embodiment of the present invention;

[0023] Figure 4 It is a schematic structural diagram of a computer device in an embodiment of the present invention;

[0024] Figure 5 It is another schematic structural diagram of a computer device in an embodiment of the present invention. Specific embodiments

[0025] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0026] The integrated intelligent analysis method for vehicle load deflection provided by the embodiments of the present invention can be applied in, for example 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. Exemplarily, taking the bridge damage assessment scenario as an example, the target user (such as a R & D personnel or a manager) can upload, through the client, the vehicle basic data set and the vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset period, as well as the bridge state data set and the environmental data set of the bridge to be detected within the preset period. Correspondingly, the server can obtain, through the client, the vehicle basic data set and the vehicle load data set corresponding to all vehicles on the bridge to be detected within the preset period, and obtain the bridge state data set and the environmental data set of the bridge to be detected within the preset 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 state data set, the environmental data set and the target vehicle distributed load data set, so that the bridge damage assessment can be carried out 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 feedback the bridge damage assessment result to the client. Correspondingly, 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 vehicle load deflection integrated intelligent analysis method provided by this application, it is beneficial to improve the effectiveness of bridge maintenance management and the accuracy of bridge structure optimization, and helps to extend the service life of the bridge.

[0027] Among them, the client can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers and portable wearable devices. The server can be implemented by an independent server or a server cluster composed of multiple servers. The present invention will be described in detail below through specific embodiments.

[0028] Please refer to Figure 2 as shown Figure 2 which is a schematic flow chart of the vehicle load deflection integrated intelligent analysis method provided by the embodiment of the present invention, and includes the following steps:

[0029] S10: Obtain the vehicle basic data set and the vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset period.

[0030] Among them, the preset time period can be a pre-set period of time, which can be the period set by the system by default or the period pre-set by the target user. This application does not limit this. The bridge to be detected can be a bridge that needs to be detected and evaluated, such as a bridge that needs to be evaluated for damage. The bridge to be detected can be understood as the object targeted by the vehicle load deflection integrated intelligent analysis method provided by this application.

[0031] The vehicle basic data set can include one or more vehicle basic data, which can be the basic data corresponding to any vehicle on the bridge to be detected during the preset time period. The vehicle basic data can include but is not limited to the type of vehicle (such as a car, a large truck, etc.), vehicle dimensions (such as length, width, height), relevant data of the axles (such as axle position, wheelbase, etc.) and other data. The vehicle basic data set can help to understand the basic characteristics of each vehicle and the basic situation of the action of each vehicle on the bridge.

[0032] The vehicle load data set can include one or more vehicle load data, which can be the load data corresponding to any vehicle on the bridge to be detected during the preset time period. The vehicle load data can 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. This application does not limit this. The vehicle load data set can help to determine the relevant situation of the load generated by the vehicle on the bridge.

[0033] By obtaining the vehicle basic data set and vehicle load data set corresponding to all vehicles on the bridge to be detected during the preset time period, the traffic load characteristics on the bridge during this period can be better understood, such as the size of the traffic flow, the composition ratio of vehicle types, the distribution law of vehicle loads, etc., and the distributed load generated by the vehicle on the bridge can be calculated more accurately in the subsequent steps to more accurately evaluate the action of the vehicle on the bridge, thereby providing a more accurate and comprehensive data basis for the fatigue damage assessment of the bridge.

[0034] S20: Obtain the bridge state data set and environmental data set of the bridge to be detected during the preset time period.

[0035] The bridge state data set can include one or more bridge state data, which can be various data that can reflect the state of the bridge itself. The bridge state data can include but is not limited to data such as displacement, strain, vibration frequency, cracks at key positions of the bridge. Among them, the key positions of the bridge can be the mid-span position of the bridge girder, the top of the pier, the support position, both sides of the expansion joint, etc. This application does not limit this.

[0036] The environmental data set may include one or more pieces of environmental data, which may be relevant data of the environment where the bridge is located within a preset time period, as well as relevant data of the instruments or devices responsible for collecting bridge data within the preset time period. Among them, the relevant data of the environment where it is located may include, but are not limited to, temperature, humidity, wind speed, wind direction, etc. The relevant data of the instruments or devices may include, but are not limited to, power status data, working mode, calibration data, position and attitude data, fault warning data, and acquisition frequency data of the instruments or devices.

[0037] By obtaining the bridge status data set and the environmental data set of the bridge to be detected within a preset time period, the working status of the bridge can be comprehensively grasped, the impact of environmental data on the bridge can be analyzed, and further combined with the bridge status data and environmental data to estimate the performance change of the bridge in the next period of time, discover potential problems in advance and take corresponding measures, extend the service life of the bridge, and reduce the maintenance cost.

[0038] S30: Determine the target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set.

[0039] Among them, the target vehicle distributed load data set may include one or more target vehicle distributed load data, which can be obtained through calculation and processing based on the vehicle basic data set and the vehicle load data set, and can be used to describe the distribution of vehicle loads at different positions on the bridge to be detected within a preset time period. That is to say, 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 mentioned below), the load distribution data of each position on the bridge at all moments within the preset time period can be further obtained, that is, the above-mentioned target vehicle distributed load data set.

[0040] It should be understood that determining the target vehicle distributed load data set according to 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 for the external excitation of the bridge (such as vehicle load) to obtain the target vehicle distributed load data set.

[0041] Among them, in step S30, that is, determining the target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set, includes the following steps:

[0042] S31: Obtain the first vehicle basic data subset corresponding to the first acquisition moment and the second vehicle basic data subset corresponding to the second acquisition moment from the vehicle basic data set;

[0043] S32: Obtain a first subset of vehicle load data corresponding to the first acquisition moment and a second subset of vehicle load data corresponding to the second acquisition moment from the set of vehicle load data;

[0044] S33: Perform vehicle load distribution processing based on the first subset of vehicle basic data and the first subset of vehicle load data to obtain first vehicle distributed load data;

[0045] S34: Perform vehicle load distribution processing based on the second subset of vehicle basic data and the second subset of vehicle load data to obtain second vehicle distributed load data;

[0046] S35: Determine a set of target vehicle distributed load data based on the first vehicle distributed load data and the second vehicle distributed load data.

[0047] Among them, the first acquisition moment can be any time point within a preset time period, and the second acquisition moment can be any time point within the preset time period other than the first acquisition moment. Optionally, the first acquisition moment and the second acquisition moment can be adjacent moments or non - adjacent moments, and this application does not limit this. It can be understood that this application takes the selection of the first acquisition moment and the second acquisition moment as an example for illustration, which does not constitute a limitation to this application. Optionally, other moments within the preset time period, such as the third acquisition moment, the fourth acquisition moment, etc., can also be further selected, and this application does not limit this.

[0048] The first subset of vehicle basic data may include one or more vehicle basic data (i.e., the first vehicle basic data) corresponding to the first acquisition moment. The first vehicle basic data may include, but is not limited to, the types, sizes, axle - related data, etc. of all vehicles on the bridge at the first acquisition moment. The second subset of vehicle basic data may include one or more vehicle basic data (i.e., the second vehicle basic data) corresponding to the second acquisition moment. The second vehicle basic data may include, but is not limited to, the types, sizes, axle - related data, etc. of all vehicles on the bridge at the second acquisition moment.

[0049] The first subset of vehicle load data may include one or more vehicle load data (i.e., the first vehicle load data) corresponding to the first acquisition moment. The first vehicle load data may include, but is not limited to, the total load of each vehicle on the bridge at the first acquisition moment, the axle load of each axle, and other related data. The second subset of vehicle load data may include one or more vehicle load data (i.e., the second vehicle load data) corresponding to the second acquisition moment. The second vehicle load data may include, but is not limited to, the total load of each vehicle on the bridge at the second acquisition moment, the axle load of each axle, and other related data.

[0050] The first vehicle distributed load data can be understood as the relevant data of the load distribution of vehicles on the bridge at the first acquisition moment after performing vehicle load distribution processing on the first subset of vehicle basic data and the first subset of vehicle load data. The second vehicle distributed load data can be understood as the relevant data of the load distribution of vehicles on the bridge at the second acquisition moment after performing vehicle load distribution processing on the second subset of vehicle basic data and the second subset of vehicle load data.

[0051] It should be understood that performing vehicle load distribution processing based on the first subset of vehicle basic data and the first subset of vehicle load data to obtain the first vehicle distributed load data refers to the process of analyzing and calculating the distributed load generated by vehicles on the bridge at the first acquisition moment to obtain the first vehicle distributed load data. Among them, in step S33, that is, performing vehicle load distribution processing based on the first subset of vehicle basic data and the first subset of vehicle load data to obtain the first vehicle distributed load data, includes the following steps:

[0052] S331: Obtain the axle position corresponding to each axle of each vehicle from the first subset of vehicle basic data to obtain the first set of axle position data;

[0053] S332: Obtain the axle load corresponding to each axle of each vehicle from the first subset of vehicle load data to obtain the first set of axle load data;

[0054] S333: Determine the distributed load at each position on the bridge to be detected at the first acquisition moment according to the first set of axle position data and the first set of axle load data;

[0055] S334: 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 moment.

[0056] Among them, the first set of axle position data may include one or more axle position data (that is, the first axle position data), and this first axle position data can 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 moment. The first set of axle load data may include one or more first axle load data, and this first axle load data can be used to indicate the relevant data of the load borne by each axle of each vehicle on the bridge to be detected at the first acquisition moment.

[0057] It should be noted that the axle position information can clarify the specific action points of the vehicle load on the bridge, and the axle load can determine the specific magnitude of the load at each action point. The combination of the two can accurately calculate the distributed load borne by each position on the bridge, thereby providing key data support for analyzing the stress state, deformation conditions of the bridge under vehicle load, and conducting structural safety assessments, etc., helping to more scientifically understand the actual working conditions of the bridge and providing a reliable basis for the maintenance management and structural optimization of the bridge.

[0058] Specifically, according to the first axle position data set and the first axle load data set, the distributed load at each position on the bridge to be detected 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.

[0059] Optionally, the process of determining the distributed load at each position on the bridge to be detected at the first acquisition moment according to the first axle position data set and the first axle load data set can refer to the following formula:

[0060]

[0061] Among them, can be used to represent the distributed load at the position on the bridge to be detected at the first acquisition moment; the position on the bridge to be detected; can be used to represent the number of vehicles on the bridge to be detected at the first acquisition moment; the position; can be used to represent the number of axles of the vehicle 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 represent the number of axles of this vehicle; can be used to represent the index of the axle; can be used to represent the axle load of the j-th axle of the i-th vehicle; can be used to represent the operation through the Dirac function; can be used to represent the axle position of the j-th axle of the i-th vehicle.

[0062] Furthermore, after determining the distributed load at each position on the bridge to be detected 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, which is used to analyze the stress and performance of the bridge in subsequent steps.

[0063] 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 moment can refer to the following formula:

[0064]

[0065] Among them, can be used to represent the first vehicle distribution load data; can be used to represent the distributed load at the position on the bridge to be detected at the first acquisition moment ; can be used to represent the distributed load at the position on the bridge to be detected at the first acquisition moment ; can be used to represent the distributed load at the position on the bridge to be detected at the first acquisition moment , and L can be used to represent the total length of the bridge to be detected.

[0066] It should be noted that the above method can be further adopted (that is, according to the first vehicle basic data subset and the first vehicle load data subset, the implementation logic of obtaining the first vehicle distribution load data through vehicle load distribution processing), so as 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 distribution load data, so as to obtain the relevant data on the load distribution of the vehicle on the bridge at the second acquisition moment. For the relevant content, please refer to the detailed description of the above steps, and this application will not elaborate here.

[0067] By selecting the vehicle basic data subset and the vehicle load data subset corresponding to different time points within a preset time period (two time points are taken as an example in the embodiments of this application), the vehicle data at different times can be analyzed and processed respectively, so as to more carefully understand the change of the vehicle load distribution on the bridge over time, and thus obtain a target vehicle distribution load data set including all times within the preset time period. Specifically, the first vehicle distribution load data, the second vehicle distribution load data, and the vehicle distribution load data at other times are integrated, such as sorting and integrating in chronological order, etc., to further obtain a target vehicle distribution load data set including all times within the preset time period. This application does not limit this.

[0068] S40: Determine a bridge load deflection parameter set according to the bridge state data set, the environmental data set, and the target vehicle distribution load data set.

[0069] Among them, the bridge load deflection parameter set may include one or more bridge load deflection parameters. The bridge load deflection parameter can be obtained by comprehensively analyzing and processing the bridge state data set, the environmental data set, and the target vehicle distribution load data set, and can be used to reflect the load deflection change of the bridge under the action of different factors.

[0070] It should be understood that determining the bridge load deflection parameter set according to the bridge state data set, the environmental data set, and the target vehicle distributed load data set refers to the 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, in step S40, that is, determining the bridge load deflection parameter set according to the bridge state data set, the environmental data set, and the target vehicle distributed load data set, includes the following steps:

[0071] S41: Obtain the first bridge state data subset corresponding to the first analysis moment and the second bridge state data subset corresponding to the next moment of the first analysis moment from the bridge state data set;

[0072] S42: Perform adjacent moment bridge state change analysis processing 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;

[0073] S43: Perform dynamic deflection analysis on the bridge state data corresponding to each moment in the bridge state data set to obtain the bridge dynamic deflection data set;

[0074] S44: Perform input-output change analysis processing according to the first bridge dynamic deflection data subset, the first bridge state data subset corresponding to the first analysis moment in the bridge dynamic deflection data set, and the environmental data set to obtain the first bridge output load deflection parameter;

[0075] S45: Determine the bridge load deflection parameter set according to the first bridge input load deflection parameter and the first bridge output load deflection parameter.

[0076] Among them, 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 are not limited to, data such as the position and strain of the key positions of the bridge at the first analysis moment 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 are not limited to, data such as the position and strain of the key positions of the bridge at the next moment of the first analysis moment that can reflect the bridge state.

[0077] 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 the preset time period, and this application does not limit this. By obtaining subsets of bridge state data corresponding to adjacent moments, the changes between the state at the previous moment and the state at the next moment can be better clarified, so as to obtain more accurate bridge load deflection parameters. It should be noted that the first analysis moment, the aforementioned first acquisition moment, and the second acquisition moment are all time points within the preset time period. The different naming methods adopted in this application can be used to distinguish the acquisition moments and analysis moments as time points in different steps, and do not constitute a limitation to this application.

[0078] The first bridge input load deflection parameter can be understood as the relevant parameter obtained 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, which can reflect the change in load deflection of the bridge state due to external inputs (such as vehicle loads, environmental factors) between adjacent moments. This first bridge input load deflection parameter can be the bridge input load deflection parameter at the first analysis moment. It can be understood that the bridge state data, vehicle distributed load data, and environmental data at other moments can be further analyzed as above to obtain the bridge input load deflection parameters at other moments, and this application will not elaborate further here.

[0079] It should be understood that obtaining the first bridge input load deflection parameter through the analysis and processing of the change in the bridge state between 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 refers to the process of how to obtain the first bridge input load deflection parameter. Among them, in step S42, that is, obtaining the first bridge input load deflection parameter through the analysis and processing of the change in the bridge state between 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, includes the following steps:

[0080] S421: Obtain the first environmental data subset corresponding to the first analysis moment from the environmental data set;

[0081] S422: Determine the first environmental error data according to the first environmental data subset;

[0082] S423: Perform analysis and processing on the change in bridge eigenvalue based on the first bridge state data subset, the second bridge state data subset, and the first environmental error data to determine the reference bridge eigenvalue load deflection parameter;

[0083] S424: Perform bridge input response analysis processing based on the reference bridge characteristic value load deflection parameter, the first vehicle distribution load data in the target vehicle distribution 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 parameter;

[0084] S425: Adjust 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;

[0085] 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.

[0086] Among them, the first environmental data subset may include environmental data at one or more first analysis times, and the environmental data at the first analysis time may include, but are not limited to, environmental data such as temperature, humidity, and wind speed at the first analysis time. The first environmental error data can be understood as the error data that may be generated by environmental factors on bridge state measurement or analysis determined according to the first environmental data subset. For example, in the case of strong wind speed, it may affect the displacement monitoring of key positions of the bridge. Therefore, by considering the environmental error, a more accurate bridge input load deflection parameter can be determined.

[0087] 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. When the first environmental data in the first environmental data subset exceeds each environmental data threshold, specifically, the look-up table method can be used to determine the corresponding first environmental error data. By setting multiple environmental data thresholds, different environmental change scenarios can be better adapted, and the impact of environmental changes on the bridge can be captured quickly and effectively. Optionally, in the case where multiple environmental factors affect the bridge interactively, 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.

[0088] The reference bridge characteristic value load deflection parameter can be understood as the parameter used to indicate the preliminary change situation of the relevant characteristic values (such as natural frequency, mode, etc., parameters reflecting the bridge structure characteristics) of the bridge at adjacent times determined after preliminary analysis of the first bridge state data subset, the second bridge state data subset, and the first environmental error data.

[0089] Further, after determining the reference bridge eigenvalue load deflection parameters, the bridge input response analysis and processing can be further performed based on the reference bridge eigenvalue load deflection parameters, the first vehicle distribution load data in the target vehicle distribution load data set, the first bridge state data subset, the second bridge state data subset, and the first environmental error data, so as to obtain the bridge input response load deflection parameters and the updated and adjusted target bridge eigenvalue load deflection parameters.

[0090] It should be noted that since the reference bridge eigenvalue load deflection parameter is the reference value of the bridge eigenvalue load deflection parameter obtained after preliminary analysis of the first bridge state data subset, the second bridge state data subset, and the first environmental error data; this reference bridge eigenvalue load deflection 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 eigenvalue load deflection parameter can be further calculated based on this bridge input response load deflection parameter to obtain the target bridge eigenvalue load deflection parameter that matches this bridge input response load deflection parameter.

[0091] Optionally, the process of performing bridge input response analysis and processing based on the reference bridge eigenvalue load deflection parameter, the first vehicle distribution load data in the target vehicle distribution 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 parameter, and adjusting the reference bridge eigenvalue load deflection parameter according to the bridge input response load deflection parameter to obtain the target bridge eigenvalue load deflection parameter can be seen in the following formula:

[0092]

[0093]

[0094] Among them, can be used to represent the second bridge state data subset; can be used to represent the reference bridge eigenvalue load deflection parameter; can be used to represent the first bridge state data subset; can be used to represent the first environmental error data; can be used to represent the target bridge eigenvalue load deflection parameter; can be used to represent the bridge input response load deflection parameter; can be used to represent the first vehicle distribution load data in the target vehicle distribution load data set; It can be used to represent an operation of adjusting the reference bridge eigenvalue load deflection parameter according to the bridge input response load deflection parameter to obtain the target bridge eigenvalue load deflection parameter.

[0095] It should be noted that It can describe the dynamic characteristics of the vehicle load deflection integrated intelligent analysis system itself. In the embodiments of the present application, it can reflect the inherent properties such as the stiffness and damping of the bridge structure, and can determine the response mode of the vehicle load deflection integrated intelligent analysis system to the input; while It can describe the action relationship of external input on the vehicle load deflection integrated intelligent analysis system, such as how the input such as vehicle distributed load acts on the bridge. When the structural state of the bridge changes (i.e., changes), the action effect of the vehicle load on the bridge (related to ) will also be different; conversely, the change of the vehicle load (affecting ) will in turn affect the dynamic response of the bridge, and then affect the estimation of .

[0096] In the initial stage of the vehicle load deflection integrated intelligent analysis system or in some specific situations (such as when there is no vehicle on the bridge), the initial conditions of the system and some prior information can be used to estimate according to the input and output data of the system, which helps to provide a basis for determining subsequently. Optionally, and can also be alternately updated according to the subsequent input and output data and the iterative algorithm to continuously improve the accuracy of the parameters.

[0097] By integrating the bridge input response load deflection parameter and the target bridge eigenvalue load deflection parameter, the first bridge input load deflection parameter can be determined, so as to realize the extraction of the parameters of the bridge state change caused by external input at adjacent moments, and then key data can be provided for subsequent bridge state analysis. Specifically, the bridge input response load deflection parameter and the target bridge eigenvalue load deflection parameter can be integrated to form the first bridge input load deflection parameter. Then, in the subsequent bridge damage assessment process, by querying the corresponding parameters from the first bridge input load deflection parameter, the bridge damage assessment in a certain aspect (such as the target bridge eigenvalue load deflection parameter is more helpful for reflecting the inherent properties such as the stiffness and damping of the bridge structure, and the bridge input response load deflection parameter is more helpful for reflecting the action relationship of external input on the system) can be realized. The present application does not limit this.

[0098] 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 parameters at other moments can also be analyzed and determined in the above manner to obtain a more comprehensive set of bridge load deflection parameters. This application does not limit this.

[0099] The bridge dynamic deflection data set can include one or more bridge dynamic deflection data. This bridge dynamic deflection data set can be used to indicate the data set of the bridge deflection changing with time obtained after performing dynamic deflection analysis on the bridge state data at each moment in the bridge state data set. The bridge dynamic deflection data set can reflect the deflection change of the bridge at different moments.

[0100] Specifically, the above process of obtaining the bridge dynamic deflection data set can be achieved by using the sensor measurement method. For example, displacement sensors can be installed at key positions of the bridge (such as the mid-span, supports, etc.) to measure the distance change between the bridge surface and the sensors in real time, so as to obtain the bridge deflection data; or fiber Bragg grating sensors can be 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 Bragg grating. 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 can be converted into deflection data; or acceleration sensors can be installed on the bridge to measure the vibration acceleration of the bridge, and then the vibration acceleration can be integrated to obtain the displacement data, that is, the bridge deflection data.

[0101] Optionally, the above process of obtaining the bridge dynamic deflection data set can be achieved by using the computer vision measurement method. For example, a high-speed camera can be used to take pictures of the bridge, and then the images taken at different moments can be processed by digital image correlation algorithms to calculate the displacement changes of multiple preset positions on the bridge surface in the images, so as to further obtain the deflection data of the bridge; or fixed cameras installed around the bridge can be used to continuously take pictures of the bridge, and then the contour information of the bridge can be extracted through the analysis of the video images, and the deflection data of the bridge can be further calculated according to the change of the contour. This application does not limit this.

[0102] The first bridge output load deflection parameter can be understood as the result of input-output change analysis and processing on the subset of the first bridge dynamic deflection data, the subset of the first bridge state data, and the environmental data set, and is used to reflect the change of the bridge state at the output level (such as observable indicators such as deflection change), and the related parameters of the load deflection change generated thereby. It should be noted that this application takes the change at the output level as an example of the change of the bridge deflection data for illustration, which does not constitute a limitation to this application. Optionally, other observable indicators (such as the dynamic curve of the deflection distribution along the span of the bridge, or the deformation amount of the bridge, etc.) can be selected for the change analysis at the output level, and this 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 parameters at other moments, which will not be elaborated here in this application.

[0103] It should be noted that when performing the input-output change analysis and processing, the relevant data of the instrument or device responsible for collecting bridge data within the corresponding preset time period in the environmental data set can be used as a reference. For example, the instrument (or device) error data at each moment can be determined according to the environmental data set, and then, based on the bridge dynamic deflection data, bridge state data, and environmental data, the input-output change analysis and processing can be performed to obtain the bridge output load deflection parameter.

[0104] Optionally, the process of performing input-output change analysis and processing on the subset of the first bridge dynamic deflection data corresponding to the first analysis moment in the bridge dynamic deflection data set, the subset of the first bridge state data, and the first instrument (or device) error data corresponding to the first analysis moment in the environmental data set to obtain the first bridge output load deflection parameter can be seen in the following formula:

[0105]

[0106] Among them, can be used to represent the subset of the first bridge dynamic deflection data corresponding to the first analysis moment k in the bridge dynamic deflection data set; can be used to represent the first bridge output load deflection parameter; can be used to represent the subset of the first bridge state data; can be used to represent the first instrument (or device) error data corresponding to the first analysis moment k in the environmental data set. It should be noted that can characterize the load deflection parameter for the bridge to output in response to a certain characteristic value, such as the load deflection parameter of the bridge deflection data output in response to the displacement at the key position of the bridge.

[0107] Further, 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 parameters and the bridge output load deflection parameters at other moments, the various bridge input load deflection parameters and the various bridge output load deflection parameters can be further integrated to obtain a set of bridge load deflection parameters that can comprehensively reflect the state change of the bridge under the action of different factors, and further provide a basis for subsequent bridge damage assessment.

[0108] S50: Perform bridge damage assessment on each bridge load deflection parameter in the set of bridge load deflection parameters to obtain a bridge damage assessment result.

[0109] Among them, the bridge damage assessment result can be understood as the relevant data of the damage assessment result obtained by judging and evaluating whether the bridge is damaged and the degree of damage according to each bridge load deflection parameter in the set of bridge load deflection parameters. Specifically, the bridge damage assessment result may include whether there is damage at each different position of the bridge, as well as relevant assessment data such as the degree of damage, the type of damage, the prevention of damage, and the repair of damage. This application does not limit this.

[0110] Specifically, based on each bridge load deflection parameter in the set of bridge load deflection parameters, damage indicators corresponding to each bridge load deflection parameter can be established, and then comprehensive damage assessment of each damage indicator can be performed. For example, the 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 relation matrix can be established to obtain a comprehensive damage assessment result through fuzzy transformation. This application does not limit this.

[0111] Optionally, taking the bridge input response load deflection parameter that describes the action relationship of external input on the vehicle load deflection integrated intelligent analysis system as an example, when the bridge is damaged, its response characteristics to external loads will change, thus affecting the value of. By analyzing the change situation of at different moments and comparing it with the bridge input response load deflection parameter in the normal state (such as called ); for example, the change amplitude of some key elements in can be calculated, or the distance metric (such as Euclidean distance, etc.) between and the standard can be established to further obtain a damage indicator based on . This application does not limit this.

[0112] It can be seen that in the above solution, by obtaining the vehicle basic data set and the vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset time period, and obtaining the bridge state data set and the 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 further, according to the bridge state data set, the environmental data set and the target vehicle distributed load data set, the bridge load deflection parameter set can be determined, so that the bridge damage assessment can be carried out 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. Furthermore, it is beneficial to improve the effectiveness of bridge maintenance management and the accuracy of bridge structure optimization, and help to extend the service life of the bridge.

[0113] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0114] 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 with the vehicle load deflection integrated intelligent analysis method in the above embodiment. As Figure 3 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 detailed description of each functional module is as follows:

[0115] The first acquisition module 101, used as a vehicle data acquisition module, is configured to acquire the vehicle basic data set and the vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset time period;

[0116] The second acquisition module 102 is configured to acquire the bridge state data set and the environmental data set of the bridge to be detected within the preset time period;

[0117] The first determination module 103 is configured to determine the target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set;

[0118] The second determination module 104 is configured to determine the bridge load deflection parameter set according to the bridge state data set, the environmental data set and the target vehicle distributed load data set;

[0119] The processing module 105 is configured 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.

[0120] In one embodiment, the first determination module 103 is configured to determine a target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set, specifically:

[0121] Obtain 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;

[0122] Obtain 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 from the vehicle load data set;

[0123] 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;

[0124] 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;

[0125] Determine a target vehicle distributed load data set according to the first vehicle distributed load data and the second vehicle distributed load data.

[0126] In one embodiment, the first determination module 103 is configured 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:

[0127] Obtain 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;

[0128] Obtain 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;

[0129] 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;

[0130] Obtain first vehicle distributed load data according to the distributed load at each position on the bridge to be detected at the first acquisition time.

[0131] In one embodiment, the second determination module 104 is configured to determine a bridge load deflection parameter set according to the bridge state data set, the environmental data set, and the target vehicle distributed load data set, specifically:

[0132] Obtain a first subset of bridge state data corresponding to the first analysis moment and a second subset of bridge state data corresponding to the next moment of the first analysis moment from the set of bridge state data;

[0133] Perform an analysis and processing of the bridge state change at adjacent moments based on the first subset of bridge state data, the second subset of bridge state data, the set of environmental data, and the set of target vehicle distributed load data to obtain a first bridge input load deflection parameter;

[0134] Perform a dynamic deflection analysis on the bridge state data corresponding to each moment in the set of bridge state data to obtain a set of bridge dynamic deflection data;

[0135] Perform an analysis and processing of the input-output change based on the first subset of bridge dynamic deflection data corresponding to the first analysis moment in the set of bridge dynamic deflection data, the first subset of bridge state data, and the set of environmental data to obtain a first bridge output load deflection parameter;

[0136] Determine a set of bridge load deflection parameters based on the first bridge input load deflection parameter and the first bridge output load deflection parameter.

[0137] In one embodiment, the second determination module 104 is configured to perform an analysis and processing of the bridge state change at adjacent moments based on the first subset of bridge state data, the second subset of bridge state data, the set of environmental data, and the set of target vehicle distributed load data to obtain a first bridge input load deflection parameter, and specifically configured to:

[0138] Obtain a first subset of environmental data corresponding to the first analysis moment from the set of environmental data;

[0139] Determine a first environmental error data based on the first subset of environmental data;

[0140] Perform an analysis and processing of the bridge eigenvalue change based on the first subset of bridge state data, the second subset of bridge state data, and the first environmental error data to determine a reference bridge eigenvalue load deflection parameter;

[0141] Perform an analysis and processing of the bridge input response based on the reference bridge eigenvalue load deflection parameter, the first vehicle distributed load data in the set of target vehicle distributed load data, the first subset of bridge state data, the second subset of bridge state data, and the first environmental error data to obtain a bridge input response load deflection parameter, and adjust the reference bridge eigenvalue load deflection parameter to obtain a target bridge eigenvalue load deflection parameter;

[0142] 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.

[0143] The present invention provides a vehicle load deflection integrated intelligent analysis device. By obtaining the vehicle basic data set and the vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset time period, and obtaining the bridge state data set and the 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 further, according to the bridge state data set, the environmental data set and the target vehicle distributed load data set, the bridge load deflection parameter set can be determined. Thus, bridge damage assessment can be carried out on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a more accurate and comprehensive bridge damage assessment result, which is conducive to improving the effectiveness of bridge maintenance management and the accuracy of bridge structural optimization, and helps to extend the service life of the bridge.

[0144] For the specific limitations of the vehicle load deflection integrated intelligent analysis device, reference can be made to the limitations of the vehicle load deflection integrated intelligent analysis method in the above text, which will not be elaborated here. Each module in the above vehicle load deflection integrated intelligent analysis device can be implemented in whole or in part by software, hardware and their combination. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or 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.

[0145] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 4 shown. The computer device includes a processor, a memory, a network interface and a database connected through 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 non-volatile and / or volatile storage media and 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 on the server side of a vehicle load deflection integrated intelligent analysis method.

[0146] In one embodiment, a computer device is provided. The computer device can be a client, and its internal structure diagram can be as Figure 5As shown in the figure. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected through 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 through a network connection. When the computer program is executed by the processor, it realizes the functions or steps on the client side of a vehicle load deflection integrated intelligent analysis method.

[0147] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0148] Obtain the vehicle basic data set and the vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset time period;

[0149] Obtain the bridge state data set and the environmental data set of the bridge to be detected within the preset time period;

[0150] Determine the target vehicle distributed load data set according to the vehicle basic data set and the vehicle load data set;

[0151] Determine the bridge load deflection parameter set according to the bridge state data set, the environmental data set, and the target vehicle distributed load data set;

[0152] Perform bridge damage assessment on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a bridge damage assessment result.

[0153] The present invention provides a computer device. By obtaining the vehicle basic data set and the vehicle load data set corresponding to all vehicles on the bridge to be detected within a preset time period, and obtaining the bridge state data set and the 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 further, the bridge load deflection parameter set can be determined according to the bridge state data set, the environmental data set, and the target vehicle distributed load data set. Thus, bridge damage assessment can be performed on each bridge load deflection parameter in the bridge load deflection parameter set to obtain a more accurate and comprehensive bridge damage assessment result, which is beneficial to improving the effectiveness of bridge maintenance management and the accuracy of bridge structure optimization, and helps to extend the service life of the bridge.

[0154] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0155] Obtain a set of vehicle basic data and a set of vehicle load data corresponding to all vehicles on the bridge to be detected within a preset time period;

[0156] Obtain a set of bridge state data and a set of environmental data of the bridge to be detected within the preset time period;

[0157] Determine a set of target vehicle distributed load data according to the set of vehicle basic data and the set of vehicle load data;

[0158] Determine a set of bridge load deflection parameters according to the set of bridge state data, the set of environmental data, and the set of target vehicle distributed load data;

[0159] Perform bridge damage assessment on each bridge load deflection parameter in the set of bridge load deflection parameters to obtain a bridge damage assessment result.

[0160] The present invention provides a computer-readable storage medium. By obtaining a set of vehicle basic data and a set of vehicle load data corresponding to all vehicles on the bridge to be detected within a preset time period, and obtaining a set of bridge state data and a set of environmental data of the bridge to be detected within the preset time period, a set of target vehicle distributed load data can be determined according to the set of vehicle basic data and the set of vehicle load data, and further, a set of bridge load deflection parameters can be determined according to the set of bridge state data, the set of environmental data, and the set of target vehicle distributed load data. Thus, bridge damage assessment can be performed on each bridge load deflection parameter in the set of bridge load deflection parameters to obtain a more accurate and comprehensive bridge damage assessment result, which is conducive to improving the effectiveness of bridge maintenance management and the accuracy of bridge structure optimization, and helps to extend the service life of the bridge.

[0161] It should be noted that for the functions or steps that can be realized by the above computer-readable storage medium or computer device, reference can be made to the relevant descriptions on the server side and the client side in the foregoing method embodiments. To avoid repetition, they will not be described in detail here.

[0162] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. 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 methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0163] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, 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.

[0164] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate 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; 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; Determining a bridge load deflection parameter set according to the first bridge input load deflection parameter and the first bridge output load deflection parameter; 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 any one of claims 1 to 3, 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.

5. 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 obtain, 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; Determining a bridge load deflection parameter set according to the first bridge input load deflection parameter and the first bridge output load deflection parameter; 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.

6. The vehicle load-deflection integrated intelligent analysis system according to claim 5, 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.

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 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.

8. 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 4 is implemented.

9. 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 4 is implemented.

Images