Perception data driven rigid pavement multi-dimensional structure parameter analysis method and system

Abstract

The present application relates to a perception data driven rigid pavement multi-dimensional structure parameter analysis method and system, the method comprising the following steps: establishing a rigid pavement operating state perception system through multiple laser wheel track instruments and multiple spatial dynamic strain gauges, collecting field perception data of the pavement to be measured, calculating aircraft virtual prototype to obtain aircraft taxiing load parameters, establishing a rigid pavement simulation model based on the field perception data and the aircraft virtual prototype, calculating mechanical simulation data, constructing a rigid pavement full-condition fusion database based on the field perception data and the mechanical simulation data, training to obtain a rigid pavement multi-dimensional structure parameter mapping model, realizing perception data driven airport rigid pavement multi-dimensional structure parameter inversion analysis, and obtaining the analysis result of the pavement to be measured. Compared with the prior art, the present application realizes efficient mapping between perception data and pavement multi-dimensional structure parameters, has the advantages of high reliability, efficient information collection, high frequency, comprehensive accuracy, low cost, etc.

Description

Technical Field

[0001] This invention relates to the field of airport engineering, and in particular to a method and system for analyzing multi-dimensional structural parameters of rigid pavements driven by sensing data. Background Technology

[0002] Rigid pavement is the main pavement type for airport runways worldwide. The structural parameters of rigid pavement primarily include the elastic modulus of the pavement slab, the response modulus of the base course surface, and the load-bearing stiffness of the joints. Conducting reliable and accurate inversion analysis of these pavement structural parameters is fundamental for quantitative calculation of structural damage and accurate evaluation of airport rigid pavement performance. Traditional FWD (Fixed-Wave Deflection) tests are typically used for inversion calculations, requiring manual operation with the runway closed, causing significant interference with aircraft operations, incurring high technical costs, and requiring testing only once every few years with low update frequency.

[0003] Chinese patent application CN108416089B discloses a method for inverting parameters of rigid pavement structures. This method fully utilizes deflection information from various measuring points in the deflection basin, reducing the fitting error between the theoretical and measured deflection basins and improving the robustness and reliability of the inversion results. However, this invention is based on a hypothetical theoretical model and the traditional manual detection method for FWD deflection basins. It requires the closure of airport runways and cannot meet the comprehensive, accurate, efficient, and high-frequency monitoring and analysis requirements of intelligent runway structural parameters. Furthermore, it cannot be used to obtain the load-bearing stiffness of airport rigid pavement joints.

[0004] Therefore, existing methods cannot fully utilize the spatial dynamic strain gauge information of airport rigid runways under aircraft passage events, making it difficult to meet the technical requirements of no traffic interference, high efficiency and accuracy, full parameter analysis, and low cost, thus affecting the accuracy and reliability of pavement structure parameter analysis. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology, such as traffic interference, low accuracy, few analytical parameters, and high cost, and to provide a perception data-driven method and system for analyzing multi-dimensional structural parameters of rigid pavement.

[0006] The objective of this invention can be achieved through the following technical solutions: A perception data-driven method for analyzing multidimensional structural parameters of rigid pavement includes the following steps: S1: Establish a rigid pavement operation status perception system using multiple laser wheel trackers and multiple spatial dynamic strain gauges; S2: Collect on-site perception data of the pavement under test through the rigid pavement operation status perception system, including spatial dynamic strain data and aircraft taxiing characteristic data, establish a virtual prototype model of the aircraft to calculate the aircraft taxiing load parameters, and establish a rigid pavement simulation model based on the on-site perception data and the virtual prototype model of the aircraft. S3: Calculate mechanical simulation data through a rigid pavement simulation model, and construct a fusion database of all working conditions of rigid pavement based on field perception data and mechanical simulation data; S4: Based on the fusion database of all working conditions of rigid pavement, a multi-dimensional structural parameter mapping model of rigid pavement is trained; S5: Based on the multi-dimensional structural parameter mapping model of rigid pavement, realize the inversion and analysis of multi-dimensional structural parameters of airport rigid pavement driven by perception data, and obtain the analytical results of the pavement under test.

[0007] Furthermore, the aircraft virtual prototype model includes three-dimensional geometric models of the aircraft fuselage, landing gear, and wheels. It defines the fuselage aerodynamics, build mass, constraint mass, constraints, and communicators, and establishes the fuselage subsystem, nose landing gear subsystem, nose landing gear wheel subsystem, main landing gear system, and main landing gear wheel system. It also establishes communication connections between the subsystems and with the aircraft test bench.

[0008] Furthermore, the input values ​​of the rigid pavement multidimensional structural parameter mapping model are pavement geometric dimension parameters, aircraft taxiing load parameters, and spatial dynamic strain data. The output values ​​of the rigid pavement multidimensional structural parameter mapping model are pavement multidimensional structural parameters, which include the pavement panel elastic modulus, the base layer top surface reaction modulus, and the joint load transfer stiffness.

[0009] Furthermore, the rigid pavement full-condition fusion database includes pavement geometric parameters, aircraft taxiing load parameters, spatial dynamic strain data, and pavement multi-dimensional structural parameters.

[0010] Furthermore, the rigid pavement simulation model includes the Winkler foundation model, the nine-slab finite element model of the airport rigid pavement, and the aircraft virtual prototype model.

[0011] Furthermore, the inversion analysis includes a first-step inversion analysis and a second-step inversion analysis. The first-step inversion analysis analyzes the elastic modulus of the pavement slab and the response modulus of the base course top surface, with the input values ​​being pavement geometric parameters, aircraft runway load parameters, and dynamic strain response in the slab. The second-step inversion analysis analyzes the load transfer stiffness of the pavement slab joints, with the input values ​​being pavement geometric parameters, aircraft runway load parameters, dynamic strain response at the midpoint of the slab edge, elastic modulus of the pavement slab, and response modulus of the base course top surface.

[0012] In a second aspect of the present invention, a parameter analysis system based on any of the above-mentioned sensing data-driven multi-dimensional structural parameter analysis methods for rigid pavements is provided. The system includes a rigid pavement operation status sensing system, an aircraft virtual prototype model, a rigid pavement simulation model, a data processing module, and a parameter analysis module. The rigid pavement operation status perception system is used to collect on-site perception data during aircraft taxiing; a full-size virtual aircraft prototype model is used to simulate and calculate aircraft taxiing load parameters; the rigid pavement simulation model is used to simulate and calculate mechanical simulation data under aircraft passage events; the data processing module is used to verify and optimize the rigid pavement simulation model, and integrate on-site perception data, aircraft taxiing load parameters, and mechanical simulation data to obtain a rigid pavement full-condition fusion database, and then establish a multi-dimensional structural parameter mapping model for the rigid pavement; the parameter analysis module, based on the on-site perception data and the multi-dimensional structural parameter mapping model for the rigid pavement, inversely analyzes the multi-dimensional structural parameters of the airport rigid pavement.

[0013] Furthermore, the operational status perception system includes an aircraft transit event perception subsystem and a pavement space dynamic strain response perception subsystem.

[0014] Furthermore, the aircraft uses an event perception subsystem that includes multiple laser wheel trackers deployed in the same and opposite directions, and a pavement spatial dynamic strain response perception subsystem that includes multiple spatial dynamic strain gauges deployed in a double layer in the rigid pavement panel and at the midpoint of the panel edge.

[0015] Furthermore, the system includes a laser wheel tracker, an airport rigid pavement panel, multiple spatial dynamic strain gauges, an aircraft, a monitoring data transmission network, and a monitoring data demodulator. The laser wheel tracker is located on the airport ground surface outside the airport rigid pavement panel and is used to build an aircraft passage event sensing subsystem. The multiple spatial dynamic strain gauges are distributed in the middle and at the midpoint of the edges of the airport rigid pavement panel and are used to build a pavement dynamic strain sensing subsystem. The aircraft serves as the modeling target for the virtual aircraft prototype model. The monitoring data transmission network connects the laser wheel tracker and the monitoring data demodulator and is used to transmit the raw data from the laser wheel tracker and the spatial dynamic strain gauges. The monitoring data demodulator is used to collect and analyze the monitored data transmission data.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1) This invention constructs a method and system for analyzing multi-dimensional structural parameters of rigid pavement driven by sensing data. The pavement geometric dimension parameters, aircraft taxiing load parameters, and spatial dynamic strain are used as input values, and the pavement multi-dimensional structural parameters are used as output values. It realizes efficient mapping between on-site sensing data and pavement multi-dimensional structural parameters, with high reliability and technical advantages of high efficiency, high frequency, comprehensive accuracy, and low cost.

[0017] 2) By using a high-precision simulation model of airport rigid pavement based on on-site perception data and a full-size virtual aircraft prototype model, the spatial dynamic strain response of airport rigid pavement under aircraft load is analyzed. Mechanical simulation methods are used to supplement the full-condition data of airport operation, and data fusion is used to expand the sample database used for training and verification of the mapping model, thereby improving the rationality, accuracy, practicality and robustness of the mapping model. 3) This invention is adapted to intelligent runway structures and can perform monitoring without interfering with airport runway operations, reducing the risk of personnel operation. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the process of the present invention.

[0019] Figure 2 This is a schematic diagram of the system structure of the present invention.

[0020] The labels in the diagram are as follows: 1. Laser wheel tracker; 2. Airport rigid pavement panel; 3. Space dynamic strain gauge; 4. Aircraft; 5. Monitoring data transmission network; 6. Monitoring data demodulator. Detailed Implementation

[0021] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0022] Example 1 like Figure 1 As shown, this invention provides a method for analyzing multi-dimensional structural parameters of rigid pavement driven by sensing data, comprising the following steps: S1: Establish a rigid pavement operation status perception system using multiple laser wheel trackers and multiple spatial dynamic strain gauges; S2: Collect on-site perception data of the pavement under test through the rigid pavement operation status perception system, including spatial dynamic strain data and aircraft taxiing characteristic data, establish a virtual prototype model of the aircraft to calculate the aircraft taxiing load parameters, and establish a rigid pavement simulation model based on the on-site perception data and the virtual prototype model of the aircraft. S3: Calculate mechanical simulation data through a rigid pavement simulation model, and construct a fusion database of all working conditions of rigid pavement based on field perception data and mechanical simulation data; S4: Based on the fusion database of all working conditions of rigid pavement, a multi-dimensional structural parameter mapping model of rigid pavement is trained; S5: Based on the multi-dimensional structural parameter mapping model of rigid pavement, realize the inversion and analysis of multi-dimensional structural parameters of airport rigid pavement driven by perception data, and obtain the analytical results of the pavement under test.

[0023] As a preferred embodiment of the present invention, in step S1 above, this embodiment establishes an airport rigid pavement operation status perception system based on a laser wheel track meter and a space dynamic strain gauge. The aforementioned system includes an aircraft transit event perception subsystem and a pavement space dynamic strain response perception subsystem; The aircraft uses multiple laser wheel trackers to analyze the event perception subsystem. The laser trackers are deployed in opposite directions to analyze the aircraft type and lateral offset, and in the same direction to analyze the taxiing speed. The aircraft taxiing characteristic data are analyzed together. The pavement spatial dynamic strain response sensing subsystem is deployed in two layers at the pavement panel center and the midpoint of the panel edge (including longitudinal and transverse joints). It is matched according to spatial location and time window to analyze and extract the peak value of the pavement dynamic strain response under aircraft passage events. The dynamic strain response at the center of the panel is used to invert and analyze the elastic modulus of the pavement panel and the reaction modulus of the base layer top surface, while the dynamic strain response at the midpoint of the panel edge is used to invert and analyze the load transfer stiffness of the pavement panel joints.

[0024] Safety should be the primary consideration in the deployment of sensors in the aforementioned sensing system. While ensuring the safety of flight operations and the stable operating range of the laser, the deployment distance of the laser wheel trackers on the soil surface areas on both sides of the runway should be optimized, with a horizontal distance of 50 to 100 meters from the runway centerline. Considering the thickness of the pavement concrete safety protection layer and the range of strain response amplitude, the installation location of the spatial dynamic strain gauges should be optimized. The core location parameters are the installation depth from the top and bottom of the slab and the horizontal distance from the edge of the slab. Load data of the rigid pavement during aircraft taxiing are collected, including aircraft taxiing characteristics and spatial dynamic strain response. Anomalies are identified using a data distribution hypothesis discrimination method. Robust regression is used to fill in missing and outlier data. Kalman filtering is used to reduce data volatility and improve the quality of sensing data utilization.

[0025] As a preferred embodiment of the present invention, in step S2 above, this embodiment establishes an airport rigid pavement simulation model based on on-site perception data and a full-size aircraft virtual prototype model. For the target slab of the rigid pavement of the airport, the foundation adopts the Winkler foundation model based on the elastic base plate theory, and the finite element model of the nine slabs of the rigid pavement of the airport is built on the Winkler foundation and considers the load transfer at the joints. The concrete of the pavement slab is an elastic material, and the load transfer at the joints is simulated using the spring element method. The structural parameters that determine the above simulation model are the elastic modulus of the pavement slab, the reaction modulus of the top surface of the base layer, and the load transfer stiffness of the pavement slab joints. The process of establishing a virtual prototype model of the aircraft includes: creating three-dimensional geometric models of the fuselage, landing gear, and wheels; defining fuselage aerodynamics, build mass, constraint mass, constraints, and communication devices; establishing fuselage subsystems, nose landing gear subsystems, nose landing gear wheel systems, main landing gear systems, and main landing gear wheel systems; establishing communication devices between each subsystem and with the aircraft test bench; and completing the assembly of the virtual prototype model of the aircraft.

[0026] Based on aircraft taxiing characteristic perception data and aircraft virtual prototype model, the aircraft taxiing load parameters are calculated.

[0027] Based on actual measurements of aircraft passing events on airport runways, the geometric parameters of the airport pavement and various aircraft taxiing load parameters are input to simulate and analyze the pavement structure response. The simulated values ​​of dynamic strain response at multiple measuring points are linked with the monitored values, and the calculation is iteratively performed to finally obtain a high-precision simulation numerical model.

[0028] As a preferred embodiment of the present invention, in step S3 above, this embodiment constructs a full-condition fusion database of airport rigid pavement based on on-site perception data and mechanical simulation data. There are three main categories of parameters affecting the full working conditions of airport rigid pavement: pavement geometric parameters, including pavement side length and thickness; aircraft taxiing load parameters, including aircraft type, lateral offset, taxiing speed, and ground contact wheel pressure; and pavement structural parameters, including pavement panel elastic modulus, base course top surface reaction modulus, and pavement panel joint load transfer stiffness. The horizontal range of the above parameters is analyzed based on historical statistical data. To address the numerous operational conditions missing from the airport rigid pavement sensing data, the aforementioned influencing parameters were substituted into the S2 airport rigid pavement simulation model. Spatial dynamic strain response data of airport rigid pavement monitoring point locations under complex operational conditions were calculated, and mechanical simulation methods were used to supplement a large number of operational conditions beyond the airport rigid pavement sensing data.

[0029] The strain data from the center sensing and simulation of the pavement panel is used to invert and analyze the elastic modulus of the pavement panel and the reaction modulus of the top surface of the base layer; based on this, the strain data from the midpoint sensing and simulation of the edge of the panel is used to analyze and invert the load transfer stiffness of the pavement panel joint. By integrating on-site perception data and mechanical simulation data, a full-condition fusion database is reconstructed and established, with pavement geometric dimensions, aircraft taxiing load parameters, and spatial dynamic strain response as input values ​​and pavement multi-dimensional structural parameters as output values, covering all operating conditions of airport rigid pavement.

[0030] As a preferred embodiment of the present invention, in step S4 above, this embodiment constructs a perception data-driven method for analyzing multi-dimensional structural parameters of rigid pavement at airports. Based on the airport rigid pavement full-condition database in S3 above, machine learning models such as neural networks and deep learning are used, combined with parameter estimation methods such as maximum likelihood estimation, to train an efficient mapping algorithm for multi-dimensional structural parameters of airport rigid pavement, taking into account both high accuracy and generalization ability. The first step is to invert and analyze the elastic modulus of the pavement panel and the reaction modulus of the base layer top surface, where the input values ​​are pavement geometric parameters, aircraft taxiing load parameters, and dynamic strain response in the slab. On this basis, the second step is to invert and analyze the load transfer stiffness of the pavement panel joints, where the input values ​​are pavement geometric parameters, aircraft taxiing load parameters, dynamic strain response at the midpoint of the slab edge, elastic modulus of the pavement panel, and reaction modulus of the base layer top surface.

[0031] Among them, the pavement geometric dimension parameters are the static parameters of the airport rigid pavement; the aircraft taxiing load parameters and spatial dynamic strain response are the dynamic parameters, which are determined by the airport rigid pavement operation status perception system in S1. The three categories of parameters, namely the pavement geometric dimension parameters, aircraft taxiing load parameters, and spatial dynamic strain response, are input into the efficient mapping model of the above-mentioned airport rigid pavement multidimensional structural parameters. First, the elastic modulus of the pavement panel and the reaction modulus of the base layer top surface are determined, and then the load transfer stiffness of the pavement panel joint is determined, forming a perception data-driven analytical method for airport rigid pavement multidimensional structural parameters.

[0032] like Figure 2 As shown, as a second aspect of the present invention, in step S5 above, this embodiment constructs a perception data-driven multi-dimensional structural parameter analysis system for rigid pavement, the system comprising: Airport rigid pavement simulation model is used to simulate and calculate the spatial dynamic strain response data of airport rigid pavement under aircraft passage events; A full-size virtual prototype model of the aircraft, used to simulate and calculate the aircraft's taxiing load parameters; The data acquisition module is used to collect dynamic strain response data of the pavement space during the aircraft's takeoff and landing process; The data processing module is used to combine field perception data to verify and optimize the airport rigid pavement simulation model, integrate field perception data and mechanical simulation data, construct a full-condition fusion database of airport rigid pavement, and train a multi-dimensional structural parameter mapping model of rigid pavement. The parameter parsing module is used to realize the inversion and parsing of multi-dimensional structural parameters of airport rigid pavement driven by perception data based on on-site perception data and the multi-dimensional structural parameter mapping model of rigid pavement.

[0033] As a preferred embodiment of this system, the hardware components used in the system include: Laser wheel tracker 1: Installed in the airport dirt area to build an aircraft passage event perception subsystem; Airport rigid pavement panel 2: The target pavement panel for inverting and analyzing structural parameters; Spatial dynamic strain gauge 3: installed in the pavement panel 2 of the aircraft virtual prototype model and at the midpoint of the panel edge (including the transverse and longitudinal seams) to build the pavement spatial dynamic strain response sensing subsystem; Aircraft 4: The aircraft passing over the target runway panel, serving as the modeling target for the virtual prototype model of the aircraft; Monitoring data transmission network 5: used to transmit raw data from the laser wheel tracker and the space dynamic strain gauge; Monitoring data demodulator 6: Used to collect and analyze monitoring transmission data.

[0034] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for analyzing multi-dimensional structural parameters of rigid pavement driven by perception data, characterized in that, Includes the following steps: S1: Establish a rigid pavement operation status perception system using multiple laser wheel trackers and multiple spatial dynamic strain gauges; S2: Collect on-site perception data of the pavement under test through the rigid pavement operation status perception system, including spatial dynamic strain data and aircraft taxiing characteristic data, establish a virtual prototype model of the aircraft to calculate the aircraft taxiing load parameters, and establish a rigid pavement simulation model based on the on-site perception data and the virtual prototype model of the aircraft. S3: Calculate mechanical simulation data through a rigid pavement simulation model, and construct a fusion database of all working conditions of rigid pavement based on field perception data and mechanical simulation data; S4: Based on the fusion database of all working conditions of rigid pavement, a multi-dimensional structural parameter mapping model of rigid pavement is trained; S5: Based on the multi-dimensional structural parameter mapping model of rigid pavement, realize the inversion and analysis of multi-dimensional structural parameters of airport rigid pavement driven by perception data, and obtain the analytical results of the pavement under test; The inversion analysis includes a first-step inversion analysis and a second-step inversion analysis. The first-step inversion analysis analyzes the elastic modulus of the pavement slab and the reaction modulus of the base course top surface, with the input values ​​being pavement geometric parameters, aircraft runway load parameters, and dynamic strain response in the slab. The second-step inversion analysis analyzes the load transfer stiffness of the pavement slab joints, with the input values ​​being pavement geometric parameters, aircraft runway load parameters, dynamic strain response at the midpoint of the slab edge, elastic modulus of the pavement slab, and reaction modulus of the base course top surface.

2. The method for analyzing multi-dimensional structural parameters of rigid pavement driven by perception data according to claim 1, characterized in that, The virtual prototype model of the aircraft includes a three-dimensional geometric model of the aircraft fuselage, landing gear and wheels. It defines the fuselage aerodynamics, build mass, constraint mass and communicator, and establishes the fuselage subsystem, nose landing gear subsystem, nose landing gear wheel system, main landing gear system and main landing gear wheel system, and establishes communication connections between each subsystem and with the aircraft test bench.

3. The method for analyzing multi-dimensional structural parameters of rigid pavement driven by perception data according to claim 1, characterized in that, The input values ​​of the rigid pavement multidimensional structural parameter mapping model are pavement geometric dimension parameters, aircraft taxiing load parameters, and spatial dynamic strain data. The output values ​​of the rigid pavement multidimensional structural parameter mapping model are pavement multidimensional structural parameters, which include the pavement panel elastic modulus, the base layer top surface reaction modulus, and the joint load transfer stiffness.

4. The method for analyzing multi-dimensional structural parameters of rigid pavement driven by perception data according to claim 1, characterized in that, The rigid pavement full-condition fusion database includes pavement geometric parameters, aircraft taxiing load parameters, spatial dynamic strain data, and pavement multi-dimensional structural parameters.

5. The method for analyzing multi-dimensional structural parameters of rigid pavement driven by perception data according to claim 1, characterized in that, The rigid pavement simulation model includes a Winkler foundation model, a nine-slab finite element model of the airport rigid pavement, and a virtual aircraft prototype model.

6. A parameter analysis system based on the sensor data-driven method for analyzing multi-dimensional structural parameters of rigid pavement as described in any one of claims 1-5, characterized in that, The system includes a rigid pavement operation status perception system, an aircraft virtual prototype model, a rigid pavement simulation model, a data processing module, and a parameter analysis module. The rigid pavement operation status perception system is used to collect on-site perception data during aircraft taxiing; a full-size virtual aircraft prototype model is used to simulate and calculate aircraft taxiing load parameters; the rigid pavement simulation model is used to simulate and calculate mechanical simulation data under aircraft passage events; the data processing module is used to verify and optimize the rigid pavement simulation model, and to integrate on-site perception data, aircraft taxiing load parameters, and mechanical simulation data to obtain a rigid pavement full-condition fusion database, and then establish a rigid pavement multi-dimensional structural parameter mapping model; the parameter analysis module, based on on-site perception data and the rigid pavement multi-dimensional structural parameter mapping model, inversely analyzes the multi-dimensional structural parameters of the airport rigid pavement.

7. The system according to claim 6, characterized in that, The rigid pavement operation status perception system includes an aircraft passage event perception subsystem and a pavement space dynamic strain response perception subsystem.

8. The system according to claim 7, characterized in that, The aircraft via event perception subsystem includes multiple laser wheel trackers deployed in the same direction and opposite directions, and the pavement spatial dynamic strain response perception subsystem includes multiple spatial dynamic strain gauges deployed in two layers in the rigid pavement panel and at the midpoint of the panel edge.

9. The system according to claim 8, characterized in that, The system includes a laser wheel tracker (1), an airport rigid pavement panel (2), multiple spatial dynamic strain gauges (3), an aircraft (4), a monitoring data transmission network (5), and a monitoring data demodulator (6). The laser wheel tracker (1) is set in the airport ground area outside the airport rigid pavement panel (2) to build an aircraft passage event perception subsystem. The multiple spatial dynamic strain gauges (3) are distributed in the middle and at the midpoint of the edge of the airport rigid pavement panel (2) to build a pavement dynamic strain perception subsystem. The aircraft (4) is the modeling target of the aircraft virtual prototype model. The monitoring data transmission network (5) connects the laser wheel tracker (1) and the spatial dynamic strain gauges (3) to transmit the raw data of the laser wheel tracker and the spatial dynamic strain gauges. The monitoring data demodulator (6) is used to collect and analyze the monitoring transmission data.

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