A method and apparatus for rapid plate load testing in space

Abstract

The present application relates to the technical field of load testing, and more particularly to a space fast flat plate load test method and device. The method comprises the following steps: connecting a depth-adjustable force transmission frame with a bearing flat plate through a magnetic adsorption structure and establishing a data transmission link between the bearing flat plate and a multi-source data acquisition module; obtaining different space target test depths and calculating splicing length error, and triggering a matching gap if the splicing length error exceeds; synchronously collecting strain data and calculating corresponding transmission load to construct a depth-load-settlement three-dimensional relationship surface; identifying and counting corresponding space depth mutation test points according to the depth-load-settlement three-dimensional relationship surface and regenerating load-settlement data; fusing the load-settlement data with corresponding strain data and performing space bearing visualization to generate mechanical property space bearing deformation distribution corresponding to different depth distribution. The present application can realize efficient and accurate testing of flat plate bearing force in different spaces.

Description

Technical Field

[0001] This invention relates to the field of load testing technology, and in particular to a method and apparatus for rapid space plate load testing. Background Technology

[0002] With the continuous development of modern engineering technology, especially in fields such as building structures and mechanical equipment, plate load testing has become an important method for evaluating the load-bearing capacity and safety of materials, structures, or components to ensure that these structures can operate normally under extreme conditions. However, in actual load tests, due to the special nature of the space environment, the test equipment and load application methods need to take into account the complexity and variable working conditions of the space structure. Currently, existing plate load testing methods mainly rely on fixed loading devices and load sensors. These devices often require a large amount of space to place and are not flexibly adjustable. In some confined and complex environments, the use of these traditional devices becomes very difficult, and their operation is mostly dependent on manual operation, which cannot be automated, resulting in low test efficiency and cumbersome operation. Especially in situations where it is necessary to quickly assess the load-bearing capacity of materials or components, existing technologies cannot meet the requirements for efficient, convenient, and accurate testing. Summary of the Invention

[0003] Therefore, it is necessary for the present invention to provide a method and apparatus for rapid space plate load testing to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a space rapid plate load testing device includes a bearing plate, a depth-adjustable force transmission frame, a jack load loading module, and a multi-source data acquisition module. The bearing plate is connected to the lower end of the depth-adjustable force transmission frame via a magnetic adsorption structure, and the upper end of the depth-adjustable force transmission frame is connected to the jack load loading module via a spherical hinge mechanism. The multi-source data acquisition module establishes wired or wireless data transmission links with the bearing plate, the depth-adjustable force transmission frame, and the jack load loading module, respectively. The depth-adjustable force transmission frame is composed of at least three modular force transmission rods spliced ​​together via electromagnetic coupling interfaces, wherein each modular force transmission rod incorporates a fiber optic strain sensor and a temperature compensation... The compensation module, the jack load loading module includes a multi-stage hydraulic cylinder group, a closed-loop control system, a jack, and concrete test blocks. A steel beam is set on the ground plane above the jack load loading module to place the concrete test blocks, applying load to measure the change in foundation settlement with load, and determining the bearing capacity and deformation of the spatial foundation soil. The multi-source data acquisition module includes a distributed sensor network that synchronously acquires load, displacement, and strain. The control signal of the jack load loading module is transmitted to the actuator of the bearing plate through a signal line inside the depth-adjustable force transmission frame to form a closed-loop control circuit. The electromagnetic coupling interface includes electromagnetic chucks and magnetic positioning pins located at both ends of the modular force transmission rod. The specific adsorption force of the electromagnetic chucks is... Where F c The electromagnetic chuck has the following properties: B represents the magnetic induction intensity of the electromagnetic chuck, M represents the effective adsorption area of ​​the electromagnetic chuck, μ0 represents the vacuum permeability, and the magnetic positioning pin has a taper of 1:50 with a fit clearance of <0.02mm to ensure that the coaxiality error of the modular force transmission rod to the stress transmission path is <0.05°.

[0005] Furthermore, the magnetic adsorption structure includes a permanent magnet chuck array disposed on the upper surface of the supporting plate and a magnetically conductive base disposed at the lower end of the depth-adjustable force transmission frame. The adsorption force of the permanent magnet chuck array is adjusted by an electronically controlled coil, and the current relationship between the adsorption force and the electronically controlled coil satisfies F y =k·I 2 , where F y The value represents the adsorption force of the permanent magnet chuck array, I represents the current of the electronic control coil, and k represents the material characteristic attenuation coefficient of the electronic control coil. The permanent magnet chuck array is distributed in a regular hexagonal shape, and the distance between adjacent chucks is 45-50 mm to ensure that the shear strength of the adsorption interface of the permanent magnet chuck array is >50 MPa under the maximum test load.

[0006] Furthermore, the fiber optic strain sensor is arranged along the axial direction of the modular force transmission rod, and each modular force transmission rod has at least three measuring points. The relationship between the center wavelength drift and strain of the fiber optic strain sensor satisfies... Where Δλ represents the wavelength shift of the fiber optic strain sensor, λ0 represents the center wavelength of the fiber optic strain sensor, and p e ε represents the fiber optic elastic coefficient of the fiber optic strain sensor, ε represents the strain of the modular force transmission rod, and the temperature compensation module corrects the wavelength drift caused by temperature in real time by means of a thermistor attached to the surface of the modular force transmission rod.

[0007] Furthermore, the modular force transmission member adopts a variable cross-section hollow tubular structure, whose outer diameter decreases linearly from D at the lower end to 0.8D at the upper end, where d is the length of the outer diameter of the cross-section, and the wall thickness is uniformly t. The moment of inertia of the cross-section of the variable cross-section hollow tubular structure is distributed along the axis I(x) and satisfies Where x represents the distance from the lower end of the modular force transmission rod, and L represents the length of the modular force transmission rod.

[0008] Furthermore, the present invention also provides a method for rapid space plate load testing, the method being implemented based on the space rapid plate load testing device described above, and the space rapid plate load testing method includes the following steps:

[0009] The depth-adjustable force transmission frame is connected to the bearing plate through a magnetic adsorption structure, and the jack load loading module is docked with the depth-adjustable force transmission frame through a spherical hinge mechanism to establish a data transmission link with the multi-source data acquisition module.

[0010] Different space target test depths H are obtained, and based on the space target test depth H, a corresponding number of modular force transmission rods are selected and automatically assembled using an electromagnetic coupling interface. After assembly, initial strain data ε0 is collected through a fiber optic strain sensor, and then processed using the formula... Calculate the splicing length error, where n represents the total number of modular force transmission members, specifically... l i E represents the length of the i-th modular force transmission member. i This represents the elastic modulus of the i-th modular force transmission member. If the splicing length error exceeds ±0.5mm, the electromagnetic coupling interface is triggered to adjust the corresponding fitting gap between the modular force transmission members.

[0011] The load is applied according to a preset loading sequence using the jack load loading module. Once the applied load stabilizes, the strain data ε of each modular force transmission member on the depth-adjustable force transmission frame is simultaneously acquired via the multi-source data acquisition module through the data transmission link. i And the settlement S of the supporting plate, and based on the strain data ε i and elastic modulus E i Through formula Calculate the transferred load at the corresponding space target test depth H, where A i Represents the cross-sectional area of ​​the i-th modular force transmission member; construct a three-dimensional relationship surface of depth-load-settlement based on the transmitted load at the corresponding spatial target test depth H and the settlement S of the bearing plate;

[0012] Based on the three-dimensional relationship surface of depth-load-settlement, the corresponding spatial depth change measurement points are identified and statistically analyzed, and the corresponding strain change rate is calculated through the strain data corresponding to the spatial depth change measurement points. When the strain change rate exceeds 0.5% / min, the loading rate of the applied load is automatically adjusted by the jack load loading module, and the load-settlement data corresponding to the spatial depth change measurement points are regenerated.

[0013] The load-settlement data of the space depth abrupt measurement point is fused with the corresponding strain data, and the mechanical parameters corresponding to the space target test are calculated through the inversion process. Based on the corresponding space target test depth, the space bearing capacity of the mechanical parameters corresponding to the space target test is visualized to generate the space bearing deformation distribution of mechanical properties corresponding to different depth distributions.

[0014] Furthermore, the step of identifying and statistically analyzing the corresponding spatial depth abrupt change measurement points based on the depth-load-settlement three-dimensional relationship surface includes the following steps:

[0015] The Gaussian curvature and average curvature at each point were calculated based on the three-dimensional relationship surface of depth-load-settlement.

[0016] The rate of curvature change at each point is calculated using the Gaussian curvature and the average curvature. When the rate of curvature change at a point is greater than 0.3 times the maximum Gaussian curvature within the depth-load-settlement three-dimensional relationship surface, the point is marked as a candidate point for curvature abrupt change.

[0017] Spatiotemporal neighborhood expansion is performed on candidate points of curvature abrupt change by selecting a spherical neighborhood with a radius of 0.5m centered on the candidate point and calculating the density of candidate points within this spherical neighborhood. When the density exceeds 5 points / m... 3 When this happens, the spherical neighborhood is identified as a candidate region for a spatial depth mutation point;

[0018] Based on the candidate regions of spatial depth mutation points, the corresponding spatial depth mutation measurement points are identified and statistically analyzed.

[0019] Furthermore, the step of identifying and statistically analyzing the corresponding spatial depth abrupt change measurement points based on the candidate regions of spatial depth abrupt change points includes the following steps:

[0020] The partial derivatives along the depth direction and the load direction are calculated for each spatial point in the candidate region of spatial depth mutation points to obtain the depth direction gradient and the load direction gradient of each spatial point in the candidate region.

[0021] Based on the spatial target test settings, corresponding depth direction gradient thresholds and load direction gradient thresholds are set. Based on the corresponding depth direction gradient thresholds and load direction gradient thresholds, abrupt change points are identified for the depth direction gradient and load direction gradient of each spatial point in the candidate region. If the absolute value of the depth direction gradient of the spatial point is greater than the depth direction gradient threshold and the absolute value of the load direction gradient is greater than the load direction gradient threshold, then it is determined as the corresponding spatial depth abrupt change measurement point.

[0022] Furthermore, the automatic adjustment of the applied load rate is calculated using a loading rate adjustment formula, wherein the loading rate adjustment formula is specifically as follows:

[0023]

[0024] Among them, v k+1 v represents the loading rate at time k+1. k Let δ represent the loading rate at time k, exp represent the exponential function, and δ d The value represents the strain change rate corresponding to the spatial depth abrupt change measurement point, α represents the adjustment coefficient, which ranges from 0.2 to 0.5, and β represents the preset threshold.

[0025] Furthermore, the specific implementation process of the inversion process is as follows:

[0026] The load data, settlement data and strain data corresponding to the measurement points with abrupt changes in spatial depth are acquired, and the corresponding load data, settlement data and strain data are timestamped by the dynamic time warping algorithm to eliminate the time offset caused by the difference in sampling frequency and ensure that the time synchronization error is <10ms, so as to obtain the load data, settlement data and strain data after time synchronization.

[0027] A corresponding spatial test mechanical response model was constructed by combining the elastic half-space theory with the Burgers viscoelastic model. The model parameters include the elastic modulus E, Poisson's ratio μ, and Kelvin bulk elastic modulus E. k Kelvin's volume viscosity coefficient η kand Maxwell's volume viscosity coefficient η m ;

[0028] The time-synchronized load, settlement, and strain data are input into the space test mechanical response model to derive the corresponding load-settlement and strain inversion calculation formulas. For the elastic stage, the relationship between settlement S and transferred load P is as follows: Where B represents the diameter of the supporting plate; for the viscoelastic stage, the integral form of the Burgers viscoelastic model is used to describe the change of strain data with time τ.

[0029] Based on the inversion calculation formula of load-settlement and strain, and combined with the space test mechanical response model, the model prediction inversion analysis is performed on the load data, settlement data and strain data after time synchronization. The relative error between the measured data and the model prediction data is set as the objective function, and the corresponding space test mechanical response model is optimized based on the objective function. The mechanical parameters corresponding to the space target test are then inverted and optimized to output.

[0030] Furthermore, the objective function is specifically:

[0031]

[0032] Where f represents the objective function, and q represents the total number of spatial depth abrupt change measurement points. This represents the predicted settlement value at the j-th spatial depth abrupt change measuring point. This represents the measured settlement value at the j-th spatial depth abrupt change measuring point. This represents the predicted strain value at the j-th spatial depth abrupt change measurement point. This represents the measured strain value at the j-th spatial depth abrupt change measurement point.

[0033] The beneficial effects of this invention are:

[0034] 1. The space rapid plate load testing device proposed in this invention consists of a bearing plate, a depth-adjustable force transmission frame, a jack load loading module, and a multi-source data acquisition module. It can use a magnetic adsorption structure to connect the bearing plate to the lower end of the depth-adjustable force transmission frame, providing a stable and convenient connection method, reducing friction and mechanical wear, and improving the long-term stability and reliability of the equipment. Magnetic adsorption facilitates quick installation and disassembly, avoiding the problems of loose or deformed fasteners in traditional connection methods, and ensuring the accuracy and repeatability of test data. Meanwhile, the magnetic adsorption structure extends the equipment's service life and reduces wear; the depth-adjustable force transmission frame, through modular design, allows for adjustment under load conditions, and its built-in fiber optic strain sensor and temperature compensation module ensure data accuracy and stability while maintaining good maintainability; the jack load loading module employs a multi-stage hydraulic cylinder group, a closed-loop control system, jacks, and concrete test blocks. A steel beam is installed on the ground plane above the jack load loading module to place the concrete test blocks, applying load to measure the change in foundation settlement with load, and determining the bearing capacity and deformation of the spatial foundation soil. Precise control of the loading force and direction improves loading accuracy and stability, reduces errors, and enhances automation; the multi-source data acquisition module synchronously collects key parameters through a distributed sensor network, ensuring data consistency and reliability, and supporting real-time monitoring and analysis; the electromagnetic coupling interface, through electromagnetic chucks and magnetic positioning pins, ensures the accuracy and stability of module connections, further improving the reliability and accuracy of experimental data.

[0035] 2. Compared with existing technologies, the space rapid plate load test method proposed in this invention has the following advantages: It connects the depth-adjustable force transmission frame to the bearing plate using a magnetic adsorption structure, and uses a spherical hinge mechanism to connect the jack load loading module to the depth-adjustable force transmission frame, thereby establishing a data transmission link with the multi-source data acquisition module. The key to this step is the combination of magnetic adsorption and spherical hinge technology, which makes the connection between the force transmission frame and the bearing plate more stable and efficient. The spherical hinge allows for flexible adjustment of the force transmission frame at multiple angles, improving the system's adaptability and stability. Furthermore, the established data transmission link ensures timely and accurate data exchange between different modules, providing a solid foundation for subsequent data acquisition and analysis. This technological innovation greatly improves the overall adjustability and accuracy, ensuring effective load testing under different spatial depths and test conditions, and further promoting the efficiency and reliability of multi-source data acquisition. Secondly, by acquiring different spatial target test depths and selecting the corresponding number of modular force transmission rods based on these depths, the assembly is automatically completed using electromagnetic coupling interfaces. This process enhances the flexibility and precision of the experimental setup. Initial strain data is collected using fiber optic strain sensors, and the splicing length error is calculated using formulas, ensuring precise fit between each modular force transmission rod. The application of fiber optic strain sensors enables real-time monitoring and recording of strain data, accurately reflecting changes and fit between modules, thereby optimizing the force transmission process. If the splicing length error exceeds ±0.5mm, the fit gap of the electromagnetic coupling interface is automatically adjusted, effectively avoiding the impact of splicing errors on force transmission and improving splicing accuracy. This automated splicing process not only reduces human error but also improves the accuracy and stability of the entire setup, thereby enhancing the reliability of experimental data and providing a more accurate foundation for subsequent load transfer tests. This enables automated adjustment in confined spaces and complex environments. The system also applies loads according to a preset loading sequence using a jack load loading module, while simultaneously collecting strain data of each modular force transmission member and settlement of the bearing plate through a multi-source data acquisition module. This provides ample data support for subsequent mechanical analysis. The combination of strain data and elastic modulus makes the calculation of the transmitted load more accurate, ensuring effective load assessment at different spatial target test depths. Furthermore, based on the relationship between strain data and settlement, a three-dimensional relationship surface of depth-load-settlement is constructed. The construction of this surface helps to comprehensively analyze and understand the mechanical properties of the test object. This not only accurately captures the load and settlement characteristics at different depths, but also provides visualization and scientific basis for subsequent depth load optimization and settlement monitoring, improving the operability and accuracy of the test.Then, the spatial depth abrupt change measurement points are identified and statistically analyzed using the depth-load-settlement three-dimensional relationship surface. The loading rate is adjusted according to the strain change rate of these measurement points to ensure precise control of the entire loading process. When the strain change rate exceeds 0.5% / min, the loading rate is automatically adjusted. This design effectively prevents data fluctuations or systematic errors caused by excessively fast loading rates. By automatically adjusting the loading rate, it ensures that the test at each spatial depth is conducted under the most suitable conditions, thereby optimizing the test results. The innovation of this step lies in its ability to monitor and adjust the loading rate in real time, providing extremely high real-time feedback capabilities. This not only improves the data accuracy during the test process but also meets the requirements for efficient, convenient, and accurate testing, responding promptly to sudden strain changes and preventing abnormal situations during the test. Finally, by fusing load-settlement data and strain data, and using the inversion process to calculate mechanical parameters, spatial bearing deformation distribution maps of mechanical properties at different depths are generated. This process achieves comprehensive coupling of depth and load, and by using multi-dimensional data fusion technology, the depth and breadth of mechanical analysis are improved. The mechanical parameters obtained through inversion calculation not only provide accurate physical parameter support for depth target testing, but also clearly present the bearing deformation characteristics at different spatial depths, providing effective visualization data support for subsequent engineering design and theoretical research, thereby improving experimental efficiency. Attached Figure Description

[0036] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0037] Figure 1 This is a schematic diagram of the steps of the rapid plate load test method in space according to the present invention;

[0038] Figure 2 This is a detailed flowchart illustrating the steps of identifying and statistically analyzing corresponding spatial depth abrupt change measurement points based on the three-dimensional relationship surface of depth-load-settlement as described in this invention. Detailed Implementation

[0039] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0040] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0041] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0042] To achieve the above objectives, please refer to Figures 1 to 2 The load test in this invention is an on-site test in which loads are applied to the foundation in stages through a bearing plate of a certain area, and the change in foundation settlement with load is measured to determine the bearing capacity and deformation characteristics of the foundation soil.

[0043] This invention provides a space rapid plate load testing device, comprising a bearing plate, a depth-adjustable force transmission frame, a jack load loading module, and a multi-source data acquisition module. The bearing plate is connected to the lower end of the depth-adjustable force transmission frame via a magnetic adsorption structure, and the upper end of the depth-adjustable force transmission frame is connected to the jack load loading module via a spherical hinge mechanism. The multi-source data acquisition module establishes wired or wireless data transmission links with the bearing plate, the depth-adjustable force transmission frame, and the jack load loading module, respectively. The depth-adjustable force transmission frame is composed of at least three modular force transmission rods spliced ​​together via electromagnetic coupling interfaces, wherein each modular force transmission rod incorporates a fiber optic strain sensor and temperature compensation. The module, the jack load loading module, includes a multi-stage hydraulic cylinder group, a closed-loop control system, a jack, and concrete test blocks. A steel beam is set on the ground plane above the jack load loading module to place the concrete test blocks, applying load to measure the change in foundation settlement with load, and to determine the bearing capacity and deformation of the spatial foundation soil. The multi-source data acquisition module includes a distributed sensor network that synchronously acquires load, displacement, and strain. The control signal of the jack load loading module is transmitted to the actuator of the bearing plate through a signal line inside the depth-adjustable force transmission frame to form a closed-loop control circuit. The electromagnetic coupling interface includes electromagnetic chucks and magnetic positioning pins located at both ends of the modular force transmission rod. The specific adsorption force of the electromagnetic chucks is... Where F c The electromagnetic chuck has the following properties: B represents the magnetic induction intensity of the electromagnetic chuck, M represents the effective adsorption area of ​​the electromagnetic chuck, μ0 represents the vacuum permeability, and the magnetic positioning pin has a taper of 1:50 with a fit clearance of <0.02mm to ensure that the coaxiality error of the modular force transmission rod to the stress transmission path is <0.05°.

[0044] In this embodiment of the invention, in the construction of the space rapid plate load testing device, the connection between the bearing plate and the depth-adjustable force transmission frame adopts a magnetic adsorption structure. The bearing plate is made of high-strength aluminum alloy, with dimensions of 1200mm×800mm×50mm. Twenty electromagnetic adsorption units are evenly distributed on its surface, each unit having a diameter of 50mm and a height of 20mm, and an excitation coil is installed inside. The same number of magnetic adsorption plates, made of high-permeability pure iron with a thickness of 15mm, are installed at the corresponding positions at the lower end of the depth-adjustable force transmission frame. During the connection operation, the depth-adjustable force transmission frame is first aligned with the top of the bearing plate, and initial positioning is achieved using positioning pins to ensure that the center deviation between the two does not exceed 0.5mm. Then, the electromagnetic adsorption units on the bearing plate are energized, according to the formula... Where F cLet B represent the attraction force of the electromagnetic chuck, M represent the effective attraction area of ​​the electromagnetic chuck, and μ0 represent the vacuum permeability. When the magnetic induction intensity B of the electromagnetic chuck is set to 1.2T, the effective attraction area M is 0.002m². 2 Vacuum permeability μ0 = 4π × 10 -7 N / A 2Calculations show that the adsorption force of each electromagnetic adsorption unit is approximately 11465N. The combined action of 20 units generates a strong adsorption force, firmly attaching the depth-adjustable force transmission frame to the supporting plate, ensuring the stability and reliability of the connection during the experiment. The depth-adjustable force transmission frame is composed of five modular force transmission rods, each a hollow cylindrical structure with an outer diameter of 80mm, an inner diameter of 60mm, and a length of 500mm, made of TC4 titanium alloy. Electromagnetic coupling interfaces are located at both ends of the rods; one end is an electromagnetic chuck, and the other end is a magnetic positioning pin. The electromagnetic chuck is internally wound with 2000 turns of enameled wire and connected to an external DC power supply. The magnetic induction intensity is controlled by adjusting the current, and the magnetic positioning pin is used for magnetic guidance. The pin head taper is strictly machined to 1:50, with a surface roughness Ra≤0.8μm. The clearance between the pin and the adjacent rod's pin hole is controlled within 0.015mm. During assembly, the first rod is placed vertically, and the second rod is lifted by a crane. The magnetic positioning pin is aligned with the pin hole of the first rod and inserted under the initial action of gravity and magnetic force. When the insertion depth reaches 80% of the pin length, the electromagnetic chuck is energized to generate an attraction force that tightly connects the two rods. This process is repeated to complete the assembly of 5 rods. Due to the high-precision fit of the magnetic positioning pin, the coaxiality error of the entire force transmission frame stress transmission path is controlled within 0.03°, meeting the high-precision requirements of the test. The internal axis of each modular force transmission rod is... Two fiber optic strain sensors, each 0.1 mm in diameter, are embedded along the linear direction. A semiconductor temperature sensor is also installed for real-time temperature compensation to ensure accurate strain measurement. The upper end of the depth-adjustable force transmission frame is connected to the jack load loading module via a spherical hinge mechanism. This mechanism consists of a ball head and a socket; the ball head has a diameter of 60 mm, and the socket has an inner diameter of 62 mm. Both are hard chrome plated to a hardness of HV800. The ball head is mounted on the top of the force transmission frame, and the socket is fixed to the connecting seat of the jack load loading module. During connection, the ball head is aligned with the socket, and a pressure of 500 N is applied using a hydraulic auxiliary device to fully embed the ball head into the socket, forming a flexible and stable connection. This allows the force transmission frame to... The jack's load loading module, capable of oscillating within a defined range to adapt to different loading directions, comprises a three-stage hydraulic cylinder assembly. The first-stage cylinder has an inner diameter of 100mm, the second-stage cylinder 80mm, and the third-stage cylinder 60mm, with strokes of 200mm, 150mm, and 100mm respectively. The closed-loop control system, centered on a PLC controller, uses a pressure sensor (accuracy 0.1% FS) to monitor the hydraulic cylinder pressure in real time and a displacement sensor (resolution 0.01mm) to measure the piston stroke. When loading the support plate, the PLC controller, according to a preset loading program, adjusts the proportional valve to control the oil supply and pressure of the hydraulic cylinder, transmitting the load to the support plate through a spherical hinge mechanism and a depth-adjustable force transmission frame. Simultaneously, signal lines within the force transmission frame transmit control signals to the actuators on the support plate. The actuators adjust the fixed state of the support plate or the operation of auxiliary devices based on the signals, forming a closed-loop control circuit.A multi-source data acquisition module constructs a distributed sensor network to achieve synchronous data acquisition. Four high-precision load sensors (range 0-500kN, accuracy 0.2%FS) are arranged on the load-bearing plate, located at the four corners of the plate, to measure the load on the plate. Fiber grating strain sensors are installed in the middle of each modular force transmission member of the depth-adjustable force transmission frame to monitor the strain of the members in real time. Simultaneously, laser displacement sensors (range 0-500mm, resolution 0.005mm) are installed below the steel beams on the jack load loading module to measure the load displacement of the load-bearing plate. The corresponding steel beams are also used to place concrete test blocks to apply loads and determine the foundation settlement as a function of the load. The system monitors changes and determines the bearing capacity and deformation of the foundation soil in the space. All sensors are connected to the data acquisition unit via shielded cables or wireless transmission modules. The data acquisition unit has a built-in high-precision A / D converter and a sampling frequency set to 1000Hz. The data acquisition unit preprocesses the collected load, displacement, strain, and other data, including filtering, noise reduction, and normalization, and then transmits them to the computer for storage and analysis via an Ethernet interface. For example, in a loading test, when the hydraulic cylinder is loaded at a speed of 5mm / min, the data acquisition module simultaneously collects data from each sensor. The computer plots load-displacement curves and strain-time curves in real time, providing accurate data support for test data analysis and result evaluation.

[0045] Furthermore, the magnetic adsorption structure includes a permanent magnet chuck array disposed on the upper surface of the supporting plate and a magnetically conductive base disposed at the lower end of the depth-adjustable force transmission frame. The adsorption force of the permanent magnet chuck array is adjusted by an electronically controlled coil, and the current relationship between the adsorption force and the electronically controlled coil satisfies F y =k·I 2 , where F y The value represents the adsorption force of the permanent magnet chuck array, I represents the current of the electronic control coil, and k represents the material characteristic attenuation coefficient of the electronic control coil. The permanent magnet chuck array is distributed in a regular hexagonal shape, and the distance between adjacent chucks is 45-50 mm to ensure that the shear strength of the adsorption interface of the permanent magnet chuck array is >50 MPa under the maximum test load.

[0046] In this embodiment of the invention, the construction of the magnetic adsorption structure in the space rapid plate load testing device strictly follows the design standards. The upper surface of the bearing plate is precisely milled with regular hexagonal array grooves for mounting permanent magnet chucks. The permanent magnet chuck consists of neodymium iron boron permanent magnets and an electronically controlled coil wound around them. The permanent magnets are 30mm in diameter and 20mm in height. The electronically controlled coils are made of 0.5mm diameter enameled wire, evenly wound with 800 turns. Through precision machining, the lower end of the depth-adjustable force transmission frame is fabricated. The magnetic base is made of DT4E electrical pure iron, with a surface flatness error controlled within 0.01mm to ensure a tight fit with the permanent magnet chucks. The permanent magnet chuck array is arranged in a regular hexagonal pattern at 48mm intervals on the support plate, totaling 18 chucks. During installation, a high-precision laser positioning instrument is used to calibrate the position of each chuck, ensuring the array distribution accuracy is within ±0.2mm. During connection, the magnetic base of the force transmission frame is aligned with the permanent magnet chuck array on the support plate, and initial fixation is achieved using auxiliary positioning pins. Subsequently, power is supplied to the electronic control coil via DC power, according to formula F... y =k·I 2 , where F y The value represents the adsorption force of the permanent magnet chuck array, I represents the current of the electronic control coil, and k represents the material characteristic attenuation coefficient of the electronic control coil (e.g., k = 50 N / A). When the current I is set to 10 A, a single permanent magnet chuck generates an adsorption force of 5000 N, and the 18 chucks work together to form a total adsorption force of 90000 N. According to actual testing, under the maximum test load condition, the shear strength of the adsorption interface reaches 55 MPa, far exceeding the design requirement of 50 MPa, effectively ensuring the stability of the connection between the bearing plate and the force transmission frame, and preventing relative displacement during loading.

[0047] Furthermore, the fiber optic strain sensor is arranged along the axial direction of the modular force transmission rod, and each modular force transmission rod has at least three measuring points. The relationship between the center wavelength drift and strain of the fiber optic strain sensor satisfies... Where Δλ represents the wavelength shift of the fiber optic strain sensor, λ0 represents the center wavelength of the fiber optic strain sensor, and p e ε represents the fiber optic elastic coefficient of the fiber optic strain sensor, ε represents the strain of the modular force transmission rod, and the temperature compensation module corrects the wavelength drift caused by temperature in real time by means of a thermistor attached to the surface of the modular force transmission rod.

[0048] In this embodiment of the invention, the arrangement and calibration of fiber optic strain sensors for strain monitoring of modular force transmission rods strictly follow standard procedures. For each 500mm long modular force transmission rod, three fiber optic strain sensors are precisely installed along its axis using a special fixture. The sensor installation positions are 100mm, 250mm, and 400mm above the lower end of the rod, respectively. Epoxy resin adhesive is used for bonding, with the bonding thickness controlled between 0.1-0.2mm to ensure a tight bond between the sensor and the rod without affecting the rod's mechanical properties. The center wavelength of the fiber optic strain sensor is 1550nm, and the fiber elastic-optic coefficient p... e =0.22. After installation, the sensor is initially calibrated, and the center wavelength under no-stress conditions is recorded. When the rod is subjected to external force and strain occurs, the wavelength is calculated according to the formula... If the rod experiences a strain of 1000με, the wavelength drift can be calculated. The temperature compensation module uses a negative temperature coefficient thermistor (NTC) for real-time correction. A 10kΩ NTC thermistor is attached near each fiber optic strain sensor. The temperature change is converted into a voltage signal through a bridge circuit. When the ambient temperature changes, the NTC resistance changes. After circuit calculation, the wavelength drift caused by temperature is compensated in reverse to ensure that the strain measurement accuracy is controlled within ±10με, providing a reliable guarantee for the accuracy of the test data.

[0049] Furthermore, the modular force transmission member adopts a variable cross-section hollow tubular structure, whose outer diameter decreases linearly from D at the lower end to 0.8D at the upper end, where D is the length of the outer diameter of the cross-section, and the wall thickness is uniformly t. The moment of inertia of the cross-section of the variable cross-section hollow tubular structure is distributed along the axis I(x) and satisfies... Where x represents the distance from the lower end of the modular force transmission rod, and L represents the length of the modular force transmission rod.

[0050] In this embodiment of the invention, a modular force transmission rod is fabricated as a variable cross-section hollow tubular structure using a CNC machining center. The outer diameter of the lower end of the rod is set to 80mm, decreasing linearly upwards at a constant slope. At a distance of 400mm from the lower end, the outer diameter decreases to 64mm (i.e., 0.8 times the lower end outer diameter), while the wall thickness remains uniformly 10mm. During machining, a five-axis CNC system precisely controls the tool path, and the outer diameter is checked every 1mm of machining to ensure that the outer diameter error is controlled within 0.1mm, according to the formula... (Where D is the length of the outer diameter of the cross section, the wall thickness is uniform (t), x represents the distance from the lower end of the modular force transmission rod, and L represents the length of the modular force transmission rod). Through this variable cross section design, the rod can reduce its weight by up to 15% while meeting the strength requirements. Furthermore, when subjected to bending loads, the stress distribution is more uniform, and the maximum stress value is reduced by 20%, effectively improving the mechanical properties of the force transmission rod and the overall efficiency of the test device.

[0051] Furthermore, the present invention also provides a method for rapid space plate load testing, which is implemented based on the rapid space plate load testing device described above. In the embodiments of the present invention, please refer to... Figure 1 The diagram shown is a flowchart illustrating the steps of the rapid space plate load testing method of the present invention. In this example, the rapid space plate load testing method includes the following steps:

[0052] S10: The depth-adjustable force transmission frame is connected to the bearing plate through a magnetic adsorption structure, and the jack load loading module is docked with the depth-adjustable force transmission frame through a spherical hinge mechanism to establish a data transmission link with the multi-source data acquisition module.

[0053] In this embodiment of the invention, during the construction of the space rapid plate load testing device, the components are first connected and the data link is established. The bearing plate is made of high-strength aluminum alloy with hexagonal array grooves on the surface for mounting permanent magnet chucks. Each permanent magnet chuck is 50mm in diameter and 20mm in height, with a built-in excitation coil. Precision positioning ensures that the distance between adjacent chucks is 48mm. A magnetic base is installed at the lower end of the depth adjustable force transmission frame. The base is made of high-permeability pure iron with a thickness of 15mm, and the surface flatness error is controlled within 0.01mm. The force transmission frame is hoisted above the bearing plate, and the center deviation between the two is ensured to be no more than 0.5mm using a laser positioning system. After the auxiliary positioning pins are initially fixed, a 10A current is applied to the electrical control coil of the permanent magnet chuck, according to formula F. y =k·I 2 , where F yLet I represent the adsorption force of the permanent magnet chuck array, I represent the current of the electronic control coil, and k represent the material characteristic attenuation coefficient of the electronic control coil (e.g., k = 50 N / A). This will generate an adsorption force of 5000 N. The combined action of the 18 chucks will create a total adsorption force of 90000 N, achieving a secure connection. The jack load loading module connects to the force transmission frame via a spherical hinge mechanism. The spherical hinge has a ball head diameter of 60 mm and a socket inner diameter of 62 mm, with a hard chrome plated surface. A hydraulic device applies 500 N of pressure, causing the ball head to fully embed into the socket, forming a flexible connection that can rotate 360°. Angle deviation control is also possible. Within ±0.1°, the multi-source data acquisition module includes a distributed sensor network and a data acquisition instrument. Load sensors (range 500kN, accuracy 0.1%FS) are installed at the four corners of the load-bearing plate. Fiber optic strain sensors are arranged on each member of the force transmission frame. Displacement sensors (resolution 0.01mm) are installed on the jack load loading module. All sensors are connected to the data acquisition instrument through shielded cables or wireless transmission modules. The data acquisition instrument uses a 16-bit A / D converter with a sampling frequency of 1000Hz. A data transmission link is established with the industrial control computer through an Ethernet interface to ensure real-time and accurate data transmission.

[0054] S20: Obtain different space target test depths H, and based on the space target test depth H, select the corresponding number of modular force transmission rods and automatically complete the splicing using an electromagnetic coupling interface. After splicing, collect initial strain data ε0 through a fiber optic strain sensor, and then use the formula... Calculate the splicing length error, where n represents the total number of modular force transmission members, specifically... l i E represents the length of the i-th modular force transmission member. i This represents the elastic modulus of the i-th modular force transmission member. If the splicing length error exceeds ±0.5mm, the electromagnetic coupling interface is triggered to adjust the corresponding fitting gap between the modular force transmission members.

[0055] In this embodiment of the invention, assuming the space target test depth H is 2300mm and the standard length L of each modular force transmission rod is 500mm, the number of rods that need to be spliced ​​is... The system employs a robotic arm to grasp the rods, using a vision positioning system to ensure that the deviation between the magnetic positioning pin and the pin hole does not exceed 0.05mm. When the insertion depth reaches 80% of the pin length, the electromagnetic chuck is energized to generate an adsorption force, and adjacent rods are tightly connected through an electromagnetic coupling interface. After splicing, the fiber optic strain sensors inside each rod collect the initial strain data ε0. Assuming the initial strains of the first to fifth rods are 20με, 25με, 18με, 22με, and 21με, respectively, and the elastic modulus E... i Both are 110 GPa, length l i Both are 500mm, according to the formula If the splicing length error ΔL = 0.523 mm is calculated, and this error exceeds the ±0.5 mm threshold, the electromagnetic coupling interface adjustment will be automatically triggered. By finely adjusting the electromagnetic chuck current, the adjacent rods will be displaced by ±0.01 mm. The strain data will be re-acquired and the error will be calculated until the error is controlled within ±0.5 mm.

[0056] S30: Apply load according to a preset loading sequence using the jack load loading module. Simultaneously, after the applied load stabilizes, synchronously acquire strain data ε of each modular force transmission member on the depth-adjustable force transmission frame using the multi-source data acquisition module via the data transmission link. i And the settlement S of the supporting plate, and based on the strain data ε i and elastic modulus E i Through formula Calculate the transferred load at the corresponding space target test depth H, where A i Represents the cross-sectional area of ​​the i-th modular force transmission member; construct a three-dimensional relationship surface of depth-load-settlement based on the transmitted load at the corresponding spatial target test depth H and the settlement S of the bearing plate;

[0057] In this embodiment of the invention, a load is applied by a jack load loading module according to a preset loading sequence. The loading sequence is set as follows: 0-50kN at a rate of 10kN / min, 50-100kN at a rate of 15kN / min, and 100-150kN at a rate of 20kN / min. Each load level is maintained for 5 minutes. When the load fluctuation does not exceed ±1%, the load is considered stable. After the load stabilizes, a multi-source data acquisition module synchronously acquires data. Assuming that at a depth H = 2300mm, the strain data ε of each member is... i They are 100με, 120με, 110με, 130με, and 125με respectively, and the cross-sectional area of ​​the rod is A. i Both are 2198mm 2 Elastic modulus E i Both are 110 GPa, according to the formula At the test depth H of the space target, the corresponding transmitted load is calculated to be approximately 121.9 kN. Meanwhile, the settlement S of the bearing plate is measured to be 4.2 mm by a displacement sensor. By changing the test depth H (e.g., 1800 mm, 2800 mm) and the load p (e.g., 80 kN, 160 kN), the above process is repeated to obtain multiple sets of depth-load-settlement data points. Using a three-dimensional interpolation algorithm, these discrete data points are fitted into a continuous three-dimensional relationship surface of depth-load-settlement. The surface accuracy is controlled within ±0.1 mm to ensure that it can accurately reflect the settlement characteristics under different depth and load conditions.

[0058] S40: Based on the three-dimensional relationship surface of depth-load-settlement, identify and statistically analyze the corresponding spatial depth change measurement points, and calculate the corresponding strain change rate using the strain data corresponding to the spatial depth change measurement points; when the strain change rate exceeds 0.5% / min, automatically adjust the loading rate of the applied load through the jack load loading module, and regenerate the load-settlement data corresponding to the spatial depth change measurement points.

[0059] In this embodiment of the invention, after obtaining the three-dimensional relationship surface of depth-load-settlement, a curvature analysis algorithm is used to identify spatial depth abrupt change measurement points. The surface is then meshed, with the mesh size set to 10mm × 10mm. The Gaussian curvature at each mesh node is calculated. When the absolute value of the Gaussian curvature at a node exceeds 0.05mm... -1 When this occurs, it is identified as a point of abrupt change. For example, at a depth of 2100 mm and a load of 130 kN, the Gaussian curvature of the mesh node is 0.065 mm. -1 The point was identified as a sudden change measurement point. Strain data corresponding to this point was extracted, and the strain change rate was calculated through time series analysis. Strain data was collected at a sampling frequency of 10Hz within one minute, yielding 60 data points. Assuming the initial strain was 150με and changed to 152.25με after one minute, the strain change rate was: (152.25-150) / 150×100%÷1min=1.5% / min. This value exceeds the threshold of 0.5% / min, triggering the automatic adjustment of the jack load loading module. That is, the jack load loading module activates the loading rate adjustment mechanism, setting the adjustment coefficient α=0.3 and the preset threshold β=0.5% / min. The current loading rate v k =15kN / min, adjusted according to the loading rate formula The calculation yields 8.235 kN / min. The jack load loading module adjusts the loading rate from 15 kN / min to 8.235 kN / min and continues to apply the load at the new loading rate. At the same time, the load-settlement data of the spatial depth change measurement point are re-acquired during the subsequent loading process. The settlement is recorded every 2 kN increase to ensure that the data acquisition accuracy is within ±0.02 mm.

[0060] S50: The load-settlement data of the space depth abrupt measurement point is fused with the corresponding strain data, and the mechanical parameters corresponding to the space target test are calculated through the inversion process; based on the corresponding space target test depth, the space bearing capacity of the mechanical parameters corresponding to the space target test is visualized to generate the mechanical property space bearing deformation distribution corresponding to different depth distributions.

[0061] In this embodiment of the invention, load-settlement data and strain data from abrupt measurement points are fused to establish a three-dimensional coordinate system with depth as the Z-axis, load as the X-axis, and settlement as the Y-axis. Strain data is mapped to color attributes; for example, blue corresponds to a strain of 150 με, and red corresponds to 200 με. Gradient colors represent continuous changes in strain values. Mechanical parameters are calculated using an inversion algorithm, and a load-settlement-strain relationship model is established based on elasticity theory. Where μ is Poisson's ratio and B represents the diameter of the bearing plate, the measured data is fitted using the least squares method, and iterative calculations are performed until the error is less than 1%. For example, for the abrupt change test point at a depth of 2100 mm, after 10 iterations, the elastic modulus E = 115 GPa and the Poisson's ratio μ = 0.32 are obtained. Based on the spatial target test depth, the spatial bearing capacity of the mechanical parameters is visualized. The test space is divided into 5 mm × 5 mm × 5 mm cubic units using a voxelization method, and each unit is assigned a mechanical parameter value corresponding to the depth. A 3D scene is rendered using a ray casting algorithm. The elastic modulus is represented by color saturation, and the deformation is presented by the degree of mesh distortion. For example, areas with high elastic modulus are displayed as bright red, and areas with low elastic modulus are displayed as dark blue; for areas with deformation exceeding 5 mm, the mesh distortion is increased by 20%, ultimately generating a realistic spatial bearing capacity deformation distribution with a spatial resolution of 5 mm, ensuring that even minute changes in mechanical properties can be clearly presented.

[0062] Furthermore, such as Figure 2 As shown, the process of identifying and statistically analyzing the corresponding spatial depth abrupt change measurement points based on the three-dimensional relationship surface of depth-load-settlement includes the following steps:

[0063] S401: Calculate the Gaussian curvature and average curvature at each point based on the three-dimensional relationship surface of depth-load-settlement;

[0064] In this embodiment of the invention, after obtaining the three-dimensional relationship surface of depth-load-settlement, the curvature of the points on the surface is calculated. The three-dimensional relationship surface is discretized into a grid with a spacing of 10mm×10mm×10mm, and the intersection of each grid is a calculation point. The entire surface forms a total of 100×100×80 calculation points. The Gaussian curvature and mean curvature at each point are calculated using the finite difference method. For a certain calculation point, the depth, load, and settlement data of its six surrounding adjacent points (front-back, left-right, and up-down directions) are obtained to construct a local quadratic surface fitting equation. For example, at the calculation point with a depth of 2000mm, a load of 100kN, and a settlement of 3mm, the quadratic surface equation z=ax is fitted using the data of its surrounding points (such as adjacent points with a depth of 1990mm, a load of 90kN, and a settlement of 2.5mm). 2 +bxy+cy 2Given the equations +dx + ey + f, according to differential geometry formulas, we can obtain a system of six equations: Solving this system of equations using the least squares method yields the values ​​of coefficients a, b, c, d, e, and f, thus determining the local quadratic surface fitting equation. Next, the Gaussian curvature K and mean curvature C are calculated using differential geometry formulas. First, the partial derivatives are calculated, including the first partial derivative z. x =2ax + by + d, z y =bx + 2cy + e; second partial derivative z xx =2a,z xy =b,z yy =2c, calculate the coefficients of the first basic form: The coefficients of the second basic form: Then, calculate the Gaussian curvature according to the formula. Mean curvature By substituting the previously calculated coefficient values ​​into the corresponding formulas, the Gaussian curvature and average curvature values ​​of the calculation point can be obtained. By performing the above steps on all calculation points on the entire surface, the curvature data corresponding to each point can be obtained, laying the foundation for subsequent identification of spatial depth abrupt change measurement points through curvature changes.

[0065] S402: Calculate the rate of change of curvature at each point using the Gaussian curvature and the average curvature. If the rate of change of curvature at a point is greater than 0.3 times the maximum Gaussian curvature within the depth-load-settlement three-dimensional relationship surface, then mark that point as a candidate point for curvature abrupt change.

[0066] In this embodiment of the invention, the rate of change of curvature at each point is calculated based on the previously calculated Gaussian curvature and average curvature. For each calculation point, nine points (a 3×3×1 neighborhood) are selected around that point, and the difference ΔK between the Gaussian curvature of that point and the curvature of each point in the neighborhood is calculated. i The difference between the mean curvature and ΔC i Take the maximum absolute value of the Gaussian curvature difference, max|ΔK i |Maximum absolute value of the difference between the mean curvature and the mean curvature|ΔC i For example, the Gaussian curvature at a certain point is 0.02 mm. -1 The maximum Gaussian curvature in its neighborhood is 0.03 mm. -1 The minimum is 0.01mm. -1 The change in Gaussian curvature at that point is 0.02 mm. -1 The average curvature at this point is 0.015 mm. -1 The maximum average curvature within the neighborhood is 0.02 mm. -1 The minimum is 0.01mm. -1The average curvature change is 0.01 mm. -1 The Gaussian curvature change and the mean curvature change are weighted and summed with weights of 0.6 and 0.4, respectively, to obtain the comprehensive curvature change ΔQ = 0.6 × max|ΔK. i |+0.4×max|ΔC i Then, divide the total curvature change by the time interval (assuming each data acquisition interval is 1 minute) to obtain the curvature change rate at that point. Simultaneously, find the maximum Gaussian curvature within the entire depth-load-settlement three-dimensional relationship surface, assumed to be 0.08 mm. -1 When the rate of change of curvature at a certain point is greater than 0.3 times the maximum Gaussian curvature (i.e., greater than 0.024 mm), -1 When the curvature change rate is calculated to be 0.026 mm / min, the point is marked as a candidate point for curvature abrupt change. -1 Points with a curvature abrupt change exceeding a certain threshold are marked as candidate points for curvature abrupt changes. This method is used to filter out points with spatial depth abrupt changes.

[0067] S403: Expand the spatiotemporal neighborhood of candidate points for curvature abrupt changes by selecting a spherical neighborhood with a radius of 0.5m centered on the candidate point and calculating the density of candidate points within this spherical neighborhood. When the density exceeds 5 points / m... 3 When this happens, the spherical neighborhood is identified as a candidate region for a spatial depth mutation point;

[0068] In this embodiment of the invention, a spatiotemporal neighborhood expansion analysis is performed on the marked curvature abrupt change candidate points. A spherical neighborhood with a radius of 0.25m is constructed centered on each curvature abrupt change candidate point. For example, for a curvature abrupt change candidate point located at a depth of 2100mm, a load of 110kN, and a settlement of 3.5mm, a spherical spatial range with a radius of 0.5m and centered on this point is established. The number of all curvature abrupt change candidate points within this spherical neighborhood is counted, and the candidate point density is calculated using the formula: Candidate point density = Number of candidate points in the spherical neighborhood / Volume of the spherical neighborhood. Assuming there are 8 curvature abrupt change candidate points in a certain spherical neighborhood, according to the sphere volume formula... The volume of the spherical neighborhood is approximately 0.0654 m. 3 The candidate point density is approximately 15.286 / m. 3 More than 5 / m 3 The threshold for determining the spherical neighborhood is used to identify it as a candidate region for spatial depth abrupt change. By traversing all curvature abrupt change candidate points, the analysis of the entire surface is completed, and multiple candidate regions for spatial depth abrupt change are determined.

[0069] S404: Identify and statistically analyze the corresponding spatial depth mutation measurement points based on the candidate regions of spatial depth mutation points.

[0070] In this embodiment of the invention, after determining the candidate region for spatial depth abrupt change points, partial derivatives are calculated for each spatial point within the region along the depth and load directions. The spatial points within the candidate region are then arranged in a grid according to the depth and load directions, with a grid spacing of 5mm × 5kN. For each spatial point, its gradient along the depth direction and its gradient along the load direction are calculated, thereby obtaining the depth and load direction gradient data for each spatial point within the entire candidate region. Then, based on the characteristics of spatial target testing, a depth direction gradient threshold of 0.008mm / mm and a load direction gradient threshold of 0.003mm / kN are set. Abrupt change points are identified for the depth and load direction gradients of each spatial point within the candidate region. For example… For a spatial point at a depth of 2100 mm and a load of 110 kN, the depth gradient is 0.01 mm / mm and the load gradient is 0.004 mm / kN. Their absolute values ​​are calculated and compared with the corresponding gradient thresholds. Since 0.01 mm / mm > 0.008 mm / mm and 0.004 mm / kN > 0.003 mm / kN, both conditions are met, and this point is identified as a spatial depth abrupt change measurement point. This method is applied to all spatial points within the candidate region, accurately identifying all spatial depth abrupt change measurement points within the candidate region, providing precise data support for subsequent mechanical parameter analysis and spatial load visualization.

[0071] Furthermore, the step of identifying and statistically analyzing the corresponding spatial depth abrupt change measurement points based on the candidate regions of spatial depth abrupt change points includes the following steps:

[0072] The partial derivatives along the depth direction and the load direction are calculated for each spatial point in the candidate region of spatial depth mutation points to obtain the depth direction gradient and the load direction gradient of each spatial point in the candidate region.

[0073] In this embodiment of the invention, after determining the candidate region for spatial depth abrupt change points, partial derivatives are calculated for each spatial point within the region along the depth and load directions. This allows the spatial points within the candidate region to be arranged in a grid according to the depth and load directions, with a grid spacing of 5mm × 5kN. For each spatial point, the central difference method is used to calculate the partial derivative. For example, for a spatial point located at a depth of 2100mm and a load of 110kN, two adjacent points are selected along the depth direction, each 5mm before and after the point (depth 2095mm, load 110kN and depth 2105mm, load 110kN), and two adjacent points along the load direction, each 5kN to the left and right (depth 2100mm, load 105kN and depth 2100mm, load 115kN). When calculating the depth gradient, the settlement data of these two adjacent points is obtained. Assuming the settlement at depth 2095mm is 3.45mm and the settlement at depth 2105mm is 3.55mm, the depth gradient at this point is: When calculating the load directional gradient, the settlement data of the corresponding adjacent points are obtained. Assuming the settlement at a load of 105 kN is 3.48 mm and the settlement at a load of 115 kN is 3.52 mm, then the load directional gradient at that point is: The above calculation process is repeated for each spatial point within the candidate region to obtain the depth direction gradient and load direction gradient data of each spatial point in the entire candidate region, providing a basis for subsequent abrupt change point identification.

[0074] Preferably, the corresponding depth direction gradient threshold and load direction gradient threshold are set according to the spatial target test, and the abrupt change points of the depth direction gradient and load direction gradient of each spatial point in the candidate area are identified based on the corresponding depth direction gradient threshold and load direction gradient threshold. If the absolute value of the depth direction gradient of the spatial point is greater than the depth direction gradient threshold and the absolute value of the load direction gradient is greater than the load direction gradient threshold, then it is determined as the corresponding spatial depth abrupt change test point.

[0075] In this embodiment of the invention, based on the characteristics of space target testing, a depth direction gradient threshold of 0.008 mm / mm and a load direction gradient threshold of 0.003 mm / kN are set. Abrupt change points in the depth direction gradient and load direction gradient of each space point within the candidate region are identified. For example, for a space point at a depth of 2100 mm and a load of 110 kN, its depth direction gradient is 0.01 mm / mm and its load direction gradient is 0.004 mm / kN. The absolute values ​​of these values ​​are calculated and compared with their corresponding direction gradient thresholds. Since 0.01 mm / mm > 0.008 mm / mm and 0.004 mm / kN is not explicitly stated in the original text, abruptly changing the threshold values ​​is necessary. The point is determined to be a spatial depth abrupt change measurement point because it satisfies both conditions ( / kN > 0.003 mm / kN). All spatial points within the candidate region are judged using the same method. For example, if a point has a depth gradient of 0.007 mm / mm and a load gradient of 0.005 mm / kN, although the absolute value of the load gradient is greater than the threshold, the absolute value of the depth gradient is less than the threshold, thus not satisfying the condition of being simultaneously greater than the threshold. Therefore, it is not judged as an abrupt change measurement point. This rigorous dual-threshold judgment method accurately identifies all spatial depth abrupt change measurement points within the candidate region, providing precise data support for subsequent mechanical parameter analysis and spatial load visualization.

[0076] Furthermore, the automatic adjustment of the applied load rate is calculated using a loading rate adjustment formula, wherein the loading rate adjustment formula is specifically as follows:

[0077]

[0078] Among them, v k+1 v represents the loading rate at time k+1. k Let δ represent the loading rate at time k, exp represent the exponential function, and δ d The value represents the strain change rate corresponding to the spatial depth abrupt change measurement point, α represents the adjustment coefficient, which ranges from 0.2 to 0.5, and β represents the preset threshold.

[0079] This invention, through the use of a specific mathematical model and verification, derives a loading rate adjustment formula for automatically adjusting the loading rate of the applied load. This formula fully considers the loading rate v at time k+1. k+1 The loading rate v at time k k The exponential function exp represents the strain change rate δ corresponding to the abrupt change in spatial depth at the measuring point. d The adjustment coefficient α ranges from 0.2 to 0.5, and the preset threshold β is determined based on the loading rate v at time k+1. k+1 The interrelationships between the above parameters constitute a functional relationship. This formula dynamically adjusts the loading rate based on the real-time strain change rate. By introducing the strain change rate as a feedback variable, this process achieves adaptive control of the applied load, ensuring that the loading rate can be reduced promptly when large changes occur to avoid potential material damage or experimental errors, which is crucial for safety in engineering practice. The design of the adjustment coefficient α and threshold β used in the formula ensures the sensitivity of the loading rate adjustment to strain changes. When the strain change rate exceeds 0.5% / min, the loading rate will decrease significantly. This rapid response effectively prevents strain abrupt changes caused by excessively rapid loading, maintaining the stability and reliability of the testing process. The loading rate adjustment formula adopts an exponential decay form, which means that when the strain change rate approaches the preset threshold β, the loading rate adjustment will decrease rapidly. This approach avoids drastic changes while making the loading process smoother. The exponential function treatment mitigates large load variations, making it suitable for many practical application scenarios. In addition, the adjustment coefficient α can be selected from 0.2 to 0.5, which provides flexibility and adjustability to the formula. Researchers can adjust this coefficient according to experimental needs or material properties to optimize various strain response conditions. This degree of freedom makes this adjustment scheme widely applicable to different materials and loading conditions.

[0080] Furthermore, the specific implementation process of the inversion process is as follows:

[0081] The load data, settlement data and strain data corresponding to the measurement points with abrupt changes in spatial depth are acquired, and the corresponding load data, settlement data and strain data are timestamped by the dynamic time warping algorithm to eliminate the time offset caused by the difference in sampling frequency and ensure that the time synchronization error is <10ms, so as to obtain the load data, settlement data and strain data after time synchronization.

[0082] In this embodiment of the invention, after identifying the spatial depth abrupt change measuring points, the load data, settlement data, and strain data corresponding to each measuring point are obtained. Assuming that a total of 10 spatial depth abrupt change measuring points are identified, the load data of each measuring point is collected by the jack load loading module at a frequency of 1Hz, the settlement data is collected by the displacement sensors at the four corners of the bearing plate at a frequency of 2Hz, and the strain data is collected by the fiber optic strain sensor at a frequency of 5Hz. Since the sampling frequencies of each data are different, there is a time offset. A dynamic time warping algorithm is used for timestamp synchronization. Taking the first spatial depth abrupt change measuring point as an example, the load data, settlement data, and strain data of this measuring point are respectively organized into time series arrays. The dynamic time warping algorithm finds the optimal time alignment path by calculating the similarity distance between different time series. The algorithm first constructs a distance matrix, and the matrix elements represent the differences between data at different time points, such as the square of the difference between the load data at a certain time and the settlement data at the corresponding time. Then, a dynamic programming method is used to find the path with the minimum cumulative distance from the top left corner to the bottom right corner by calculating the cumulative distance, starting from the top left corner of the matrix. This path is the basis for time alignment. After calculation, the timestamps of each data are adjusted to align them in time. The above operation is repeated for all 10 measuring points. Calibration is performed using a high-precision time synchronization device to ensure that the time synchronization error between any two sets of data is <10ms. For example, the time difference between the load data and strain data of the 5th measuring point was 150ms before synchronization. After synchronization, the time difference was reduced to 8ms. Accurate load data, settlement data and strain data after time synchronization are obtained, providing a reliable basis for subsequent analysis.

[0083] Preferably, a corresponding spatial test mechanical response model is constructed by combining the elastic half-space theory with the Burgers viscoelastic model, wherein the model parameters include the elastic modulus E, Poisson's ratio μ, and Kelvin bulk elastic modulus E. k Kelvin's volume viscosity coefficient η k and Maxwell's volume viscosity coefficient η m ;

[0084] In this embodiment of the invention, a spatial test mechanical response model is constructed based on the elastic half-space theory combined with the Burgers viscoelastic model. The supporting plate is a circular aluminum plate with a diameter of B = 800 mm. According to the characteristics of the test material and the actual working conditions, the model parameters are initially set: the initial value of the elastic modulus E is set to 70 GPa (the common elastic modulus range of aluminum plates), the Poisson's ratio μ is set to 0.33, and the Kelvin volume elastic modulus E is set to... k Set at 50 GPa, Kelvin volume viscosity coefficient η k Set to 1×10 8 Pa·s, Maxwell viscosity coefficient η m Set to 2×109 In the process of building the model, the interaction between the bearing plate and the test space is regarded as a circular load on an elastic half-space. For the viscoelastic part, the Burgers model consists of a Maxwell model and a Kelvin model connected in series, which respectively describe the instantaneous elastic response, viscous flow characteristics and delayed elastic response of the material. Through the secondary development interface of the finite element analysis software, the theoretical formula of the elastic half-space and the constitutive equation of the Burgers model are embedded into the calculation program to build a complete space test mechanical response model. This model can comprehensively consider the mechanical behavior of the material in the elastic and viscoelastic stages.

[0085] Preferably, the time-synchronized load data, settlement data, and strain data are input into the space test mechanical response model to derive the corresponding load-settlement and strain inversion calculation formulas. For the elastic stage, the relationship between settlement S and transferred load P is as follows: Where B represents the diameter of the supporting plate; for the viscoelastic stage, the integral form of the Burgers viscoelastic model is used to describe the change of strain data with time τ.

[0086] In this embodiment of the invention, by inputting the time-synchronized load data, settlement data, and strain data into the constructed space test mechanical response model, during the elastic stage, for the third space depth abrupt change measurement point, the known transmitted load P = 120kN, the diameter of the bearing plate B = 800mm, and the Poisson's ratio μ = 0.33, these data are substituted into the formula. Assuming the elastic modulus E is taken as the initial value of 70 GPa set in the model, the settlement S can be calculated to be approximately 1.23 mm. In the viscoelastic stage, taking the 7th spatial depth abrupt change measurement point as an example, at a certain moment τ = 60 s, the transmitted load P = 150 kN. According to the integral form of the Burgers viscoelastic model... Substitute the initially set model parameters E k =50GPa, η k =1×10 8 Pa·s,η m =2×10 9 Pa·s, E=70GPa, the calculated strain value ε(60)≈4.98×10 -6 Through the derivation of these formulas, a quantitative relationship between load, settlement, and strain is established, providing a theoretical basis for subsequent inversion analysis.

[0087] Preferably, the load-settlement and strain inversion calculation formulas are used in conjunction with the space test mechanical response model to perform model prediction inversion analysis on the load data, settlement data and strain data after time synchronization. The relative error between the measured data and the model prediction data is set as the objective function, and the corresponding space test mechanical response model is optimized based on the objective function. The mechanical parameters corresponding to the space target test are then inverted and optimized to output the results.

[0088] In this embodiment of the invention, based on the derived load-settlement and strain inversion calculation formulas and combined with the space test mechanical response model, model prediction inversion analysis is performed on the measured data of 10 space depth abrupt change measurement points after time synchronization. The relative error between the measured data and the model prediction data is set as the objective function. Where f represents the objective function, and q represents the total number of spatial depth abrupt change measurement points. This represents the predicted settlement value at the j-th spatial depth abrupt change measuring point. This represents the measured settlement value at the j-th spatial depth abrupt change measuring point. This represents the predicted strain value at the j-th spatial depth abrupt change measurement point. This represents the measured strain value at the j-th spatial depth abrupt change measuring point. Taking the second spatial depth abrupt change measuring point as an example, it is assumed that the model predicts the settlement value. Measured settlement value Predicted strain values Measured strain value Substituting these values ​​into the objective function, the same calculation is performed for all 10 measuring points, and the results are summed to obtain the current value of the objective function. Then, a genetic algorithm is used to refine the parameters of the spatial test mechanical response model (elastic modulus E, Poisson's ratio μ, E0). k η k η m The optimization process involves selecting, crossing, and mutating parameter combinations based on the objective function value in each iteration to generate new parameter combinations. After 500 iterations, the iteration stops when the objective function value no longer changes significantly. Finally, the inverse optimization outputs the mechanical parameters corresponding to the space target test, providing accurate parameters for space mechanical performance evaluation.

[0089] Furthermore, the objective function is specifically:

[0090]

[0091] Where f represents the objective function, and q represents the total number of spatial depth abrupt change measurement points. This represents the predicted settlement value at the j-th spatial depth abrupt change measuring point. This represents the measured settlement value at the j-th spatial depth abrupt change measuring point. This represents the predicted strain value at the j-th spatial depth abrupt change measurement point. This represents the measured strain value at the j-th spatial depth abrupt change measurement point.

[0092] This invention derives an objective function through a specific mathematical model and verification, which is used to optimize the corresponding space test mechanical response model. This function fully considers the total number q of space depth abrupt change measurement points and the predicted settlement value of the j-th space depth abrupt change measurement point. Measured settlement value at the j-th spatial depth abrupt change measuring point Predicted strain value at the j-th spatial depth abrupt change measurement point Measured strain value at the j-th spatial depth abrupt change measurement point A functional relationship is established between the objective function f and the above parameters. This objective function effectively evaluates the model's fitting performance by calculating the relative error between predicted and measured values. By minimizing the objective function, the optimization algorithm adjusts the model parameters to make the predicted results as close as possible to the actual observation data. This feedback mechanism ensures the model's applicability and accuracy under different conditions, thereby improving the reliability of the space test mechanical response model. The sum-of-squares form of the relative error increases the model's sensitivity to larger errors; larger deviations significantly affect the value of the objective function. Therefore, during optimization, the model prioritizes data points with larger prediction errors. This effect helps identify and correct problems in the model, improving its applicability. Furthermore, this objective function considers not only the error in settlement data but also the error in strain data. This multi-dimensional evaluation system promotes the model's comprehensiveness in describing complex physical phenomena, ensuring that conditions at different measurement points are reasonably reflected. Therefore, it can more comprehensively capture the response characteristics of materials or structures under load. In practical applications, the testing environment and material properties change over time. By using relative error feedback, the parameters in the model (such as elastic modulus, Poisson's ratio, etc.) can be adjusted in a timely manner, so that the model can better adapt to new measurement data. This dynamic updating capability is of great significance for long-term monitoring and maintenance.

[0093] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0094] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method of spatially rapid plate loading test, characterized by, The method is based on the implementation of a spatial rapid plate loading test device, which includes a bearing plate, a depth-adjustable force transmission frame, a jack load loading module, and a multi-source data acquisition module. The bearing plate is connected to the lower end of the depth-adjustable force transmission frame through a magnetic adsorption structure. The upper end of the depth-adjustable force transmission frame is connected to the jack load loading module through a spherical hinge mechanism. The multi-source data acquisition module establishes a wired or wireless data transmission link with the bearing plate, the depth-adjustable force transmission frame, and the jack load loading module. The depth-adjustable force transmission frame is composed of at least three modular force transmission rods connected by electromagnetic coupling interfaces. Each modular force transmission rod has an optical fiber grating strain sensor and a temperature compensation module built-in. The jack load loading module includes a multi-stage hydraulic cylinder group, a closed-loop control system, a jack, and a concrete test block. A steel beam is set on the ground surface above the jack load loading module to stack the concrete test block to apply load and measure the change of foundation settlement with load. The bearing capacity and deformation of the spatial foundation soil are determined. The multi-source data acquisition module includes a distributed sensor network that synchronously acquires load, displacement, and strain. The control signal of the jack load loading module is transmitted to the actuator of the bearing plate through the signal line inside the depth-adjustable force transmission frame to form a closed-loop control circuit. The electromagnetic coupling interface includes electromagnetic suction cups and magnetic positioning pins set at both ends of the modular force transmission rod. The adsorption force of the electromagnetic suction cup is where represents the adsorption force of the electromagnetic suction cup, represents the magnetic induction intensity of the electromagnetic suction cup, represents the adsorption effective area of the electromagnetic suction cup, represents the vacuum permeability. The taper of the magnetic positioning pin is 1:50, and the fitting gap is <0.02mm to ensure that the coaxiality error of the corresponding stress transmission path of the modular force transmission rod is <0.05°. The spatial rapid plate loading test method includes the following steps: The deep-adjustable force transmission frame is connected with the bearing plate through a magnetic adsorption structure, and the jack load loading module is connected with the deep-adjustable force transmission frame through a spherical hinge mechanism to establish a data transmission link with a multi-source data acquisition module; Acquiring different spatial target test depths and selecting a corresponding number of modular force transmission rods combined with an electromagnetic coupling interface to automatically complete splicing based on the spatial target test depth Collect initial strain data through fiber Bragg grating strain sensors after splicing and calculate the splicing length error through the formula wherein represents the total number of modular force transmission rods, specifically , represents the length of the th modular force transmission rod, represents the elastic modulus of the th modular force transmission rod, represents the length of the modular force transmission rod, and if the splicing length error exceeds ±0.5 mm, the electromagnetic coupling interface adjustment module adjusts the corresponding fit gap between the modular force transmission rods. The load is applied according to a preset loading sequence using the jack load loading module. Once the applied load stabilizes, strain data of each modular force transmission member on the depth-adjustable force transmission frame is simultaneously acquired via the multi-source data acquisition module through the data transmission link. and the settlement of the supporting plate And based on strain data and elastic modulus Through formula Calculate the test depth of the target in the corresponding space. The amount of transmitted load, of which Indicates the first The cross-sectional area of ​​each modular force transmission member; based on the test depth of the corresponding spatial target. The amount of load transferred below, combined with the settlement of the supporting plate. Construct a three-dimensional surface relating depth, load, and settlement; According to the deep-load-settlement three-dimensional relationship surface, corresponding spatial depth mutation measuring points are identified and calculated, and the strain change rate corresponding to the spatial depth mutation measuring points is calculated; when the strain change rate exceeds 0.5% / min, the loading rate of the applied load is automatically adjusted through the jack load loading module, and the load-settlement data corresponding to the spatial depth mutation measuring points is regenerated; The load-settlement data and corresponding strain data of the spatial depth mutation measuring points are fused, and the mechanical parameters corresponding to the spatial target test are calculated through the inversion process; based on the corresponding spatial target test depth, the mechanical parameters corresponding to the spatial target test are visualized to generate mechanical property spatial bearing deformation distribution corresponding to different depth distribution.

2. The spatial quick plate loading test method according to claim 1, characterized in that: The magnetic adsorption structure comprises a permanent magnet chuck array arranged on the upper surface of the bearing flat plate and a magnetic guide base arranged at the lower end of the depth-adjustable force transmission frame, the adsorption force of the permanent magnet chuck array is adjusted by an electric control coil, and the current relationship between the adsorption force and the electric control coil satisfies wherein represents the adsorption force of the permanent magnet chuck array, represents the current of the electric control coil, represents the material characteristic attenuation coefficient of the electric control coil, and the permanent magnet chuck array is arranged in a regular hexagonal distribution with a spacing of 45-50 mm between adjacent chucks, so that the shear strength of the corresponding adsorption interface of the permanent magnet chuck array is greater than 50 MPa under the maximum test load.

3. The spatial quick plate loading test method according to claim 1, characterized in that: The fiber grating strain sensor is arranged along the axis direction of the modular force transmission rod, each modular force transmission rod is provided with at least three measuring points, and the center wavelength drift of the fiber grating strain sensor and the strain relationship satisfy Wherein The wavelength drift of the fiber grating strain sensor is represented by Δλ, The center wavelength of the fiber grating strain sensor is represented by λ0, The fiber photoelastic coefficient of the fiber grating strain sensor is represented by σ, The strain of the modular force transmission rod is represented by ε, and the temperature compensation module corrects the wavelength drift caused by temperature in real time through the thermistor pasted on the surface of the modular force transmission rod.

4. The spatial quick plate loading test method according to claim 3, characterized in that: The modular force transmission rod adopts a variable cross-section hollow tubular structure, the cross-section outer diameter of which linearly decreases from the lower end to 0.8 at the upper end, wherein is the length of the cross-section outer diameter, the wall thickness is uniform , the cross-section moment of inertia of the variable cross-section hollow tubular structure is distributed along the axis and satisfies , wherein denotes the distance from the lower end of the modular force transmission rod, denotes the length of the modular force transmission rod.

5. The spatial quick plate loading test method according to claim 1, wherein, The deep-load-settlement three-dimensional relationship surface is calculated to obtain the Gaussian curvature and average curvature of each point. The Gaussian curvature and average curvature of each point are calculated, and when the curvature change rate of the point is greater than 0.3 times the maximum Gaussian curvature in the depth-load-settlement three-dimensional relationship surface, the point is marked as a curvature mutation candidate point. According to the spatial depth mutation point candidate region, corresponding spatial depth mutation measuring points are identified and calculated. The curvature mutation candidate point is extended in space-time neighborhood, a spherical neighborhood with the curvature mutation candidate point as the center and a radius of 0.5 m is selected, and the density of the candidate points in the spherical neighborhood is counted, and when the density is more than 5 / m 3 , the spherical neighborhood is determined as a spatial depth mutation point candidate region. The partial derivatives of each spatial point in the spatial depth mutation point candidate region along the depth direction and the load direction are calculated to obtain the depth direction gradient and load direction gradient of each spatial point in the candidate region.

6. The spatial quick plate loading test method according to claim 5, wherein, According to the spatial target test, corresponding depth direction gradient threshold and load direction gradient threshold are set, and based on the corresponding depth direction gradient threshold and load direction gradient threshold, the depth direction gradient and load direction gradient of each spatial point in the candidate region are identified as mutation points; if the absolute value of the depth direction gradient of the spatial point is greater than the depth direction gradient threshold and the absolute value of the load direction gradient is greater than the load direction gradient threshold, it is determined as the corresponding spatial depth mutation measuring point. The automatic adjustment of the loading rate of the applied load is calculated by a loading rate adjustment formula, wherein the loading rate adjustment formula is: The specific implementation process of the inversion process is:

7. The spatial quick plate loading test method according to claim 1, wherein The load data, settlement data and strain data corresponding to different spatial depth mutation measuring points are obtained, and the dynamic time warping algorithm is used to synchronize the time stamps of the corresponding load data, settlement data and strain data to eliminate the time offset caused by the difference in sampling frequency and ensure that the time synchronization error is less than 10ms, so as to obtain the load data, settlement data and strain data after time synchronization; ； wherein, represents the loading rate at the time moment, represents the loading rate at the time moment, represents an exponential function, represents the strain change rate corresponding to the spatial depth mutation point, represents an adjustment coefficient, and the value range is 0.2-0.5, represents a preset threshold.

8. The spatial quick plate loading test method according to claim 1, wherein, ​ ​ By adopting the elastic half-space theory combined with the Burgers viscoelastic model to construct a corresponding spatial test mechanics response model, wherein the model parameters include an elastic modulus , a Poisson's ratio , a Kelvin body elastic modulus , a Kelvin body viscous coefficient , and a Maxwell body viscous coefficient ; The time-synchronized load data, settlement data and strain data are input into the spatial test mechanics response model to derive corresponding load-settlement and strain inversion calculation formulas, wherein for the elastic stage, the settlement amount and the relationship between the transmitted load amount is , wherein represents the diameter of the bearing flat plate; for the viscoelastic stage, the integral form of the Burgers viscoelastic model is used to describe the change of the strain data with time ; Based on the load-settlement and strain inversion calculation formula and combined with the space test mechanics response model, the load data, settlement data and strain data after time synchronization are subjected to model prediction inversion analysis, so as to set the relative error between the measured data and the model prediction data as the objective function, and the corresponding space test mechanics response model is optimized based on the objective function optimization, and the mechanical parameters corresponding to the space target test are output by inversion optimization.

9. The spatial quick plate loading test method according to claim 8, wherein, The objective function is specifically: ； wherein, represents the objective function, represents the total number of spatial depth mutation points, represents the predicted settlement value of the th spatial depth mutation point, represents the measured settlement value of the th spatial depth mutation point, represents the predicted strain value of the th spatial depth mutation point, represents the measured strain value of the th spatial depth mutation point.

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