A dynamic ground pressure measurement system and method for tracked vehicles

Abstract

This invention relates to the field of ground pressure measurement technology, specifically providing a dynamic ground pressure measurement system and method for tracked vehicles. The system includes a test bed, a multi-source information acquisition module, a data fusion and intelligent processing platform, and a comprehensive evaluation and visualization module. The test bed and multi-source information acquisition module acquire dynamic data of the tracked vehicle in real time. The data fusion and intelligent processing platform then interpolates and reconstructs the acquired dynamic data to obtain a dynamic pressure field sequence, which is fed into the comprehensive evaluation and visualization module. This module calculates the key performance indicators of the tracked vehicle, including ground pressure. This invention effectively solves the problems of large blind spots, poor continuity, and limited accuracy in traditional measurement methods under complex dynamic conditions, providing detailed data support and scientific basis for the study of the ground mechanical behavior of tracked vehicles and performance optimization.

Description

Technical Field

[0001] This invention relates to the field of grounding specific pressure measurement technology, specifically providing a dynamic grounding specific pressure measurement system and method for tracked vehicles. Background Technology

[0002] Ground contact pressure is a key performance parameter for tracked vehicles, directly affecting their passability, obstacle-crossing ability, and soil compaction. Ground contact pressure is typically obtained through static calculations or single-point pressure sensor measurements, but these methods often have the following drawbacks: Traditional measurement methods, such as static calculations (vehicle weight / ground contact area), ignore the uneven distribution of dynamic loads, resulting in significant errors; single-point pressure sensor methods can only acquire discrete point data, failing to comprehensively and accurately reflect the pressure distribution across the entire track contact area, and are particularly inadequate to capture dynamic pressure fluctuations and redistributions caused by factors such as track plate connections, road wheel undulations, and acceleration changes during vehicle movement. Therefore, there is an urgent need for an advanced measurement system capable of comprehensively and faithfully capturing the entire interaction between the track and the ground. Summary of the Invention

[0003] To address the aforementioned problems, this invention provides a dynamic ground pressure measurement system and method for tracked vehicles. Through a multi-level pressure sensing structure, synchronous acquisition of multi-source information, and data interpolation reconstruction, it achieves high-precision, high-spatiotemporal resolution dynamic measurement and comprehensive evaluation of the ground pressure distribution during the movement of tracked vehicles.

[0004] The present invention provides a dynamic ground pressure measurement system for tracked vehicles, comprising:

[0005] Test bed, multi-source information acquisition module, data fusion and intelligent processing platform, and comprehensive evaluation and visualization module;

[0006] The test bed includes a pressure sensor array, which is used to obtain the track ground pressure in real time.

[0007] The multi-source information acquisition module includes an array acquisition submodule, a vehicle attitude perception submodule, a kinematics perception submodule, and a spatial positioning submodule. The array acquisition submodule acquires pressure signals based on track ground pressure, the vehicle attitude perception submodule measures the three-dimensional attitude angles of the tracked vehicle in real time, the kinematics perception submodule acquires the motion parameters of the tracked vehicle in real time, and the spatial positioning submodule acquires the absolute position information of the tracked vehicle in real time.

[0008] The data fusion and intelligent processing platform includes a spatiotemporal synchronization unit and a data reconstruction and interpolation unit. The spatiotemporal synchronization unit synchronously correlates the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information to the absolute time and world coordinate system. The data reconstruction and interpolation unit performs interpolation processing on the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information, and then generates pressure signal-absolute time curves, three-dimensional attitude angle-absolute time curves, motion parameter-absolute time curves, and absolute position information-absolute time curves, respectively.

[0009] Based on the pressure signal-absolute time curve, three-dimensional attitude angle-absolute time curve, motion parameter-absolute time curve, and absolute position information-absolute time curve, the key performance indicators of the tracked vehicle are calculated using the comprehensive evaluation and visualization module. The key performance indicators include dynamic ground contact area, average ground contact specific pressure, maximum ground contact specific pressure, ground contact specific pressure non-uniformity coefficient, pressure center coordinates, and pressure center motion trajectory.

[0010] Preferably, the pressure sensing array includes a rigid substrate sensing array and a flexible interpolation sensing array; the rigid substrate sensing array includes a pressure cell unit, which includes a miniature high-frequency dynamic pressure sensor; the flexible interpolation sensing array is composed of distributed thin-film pressure sensors.

[0011] Preferably, the test bed also includes a standard medium, which includes a load-bearing sand layer and a simulated topsoil layer; the total thickness of the standard medium is greater than or equal to 5 times the maximum feature size of the pressure sensor in the pressure sensor array.

[0012] Preferably, the array acquisition submodule acquires all the pressure signals corresponding to the track grounding pressure at the same frequency, with an acquisition frequency of not less than 1kHz.

[0013] Preferably, the three-dimensional attitude angles include the roll angle, pitch angle, and yaw angle of the tracked vehicle.

[0014] Preferably, the data fusion and intelligent processing platform also includes an intelligent data correction unit. Before interpolation, the intelligent data correction unit is used to identify and correct abnormal values ​​in pressure signals, three-dimensional attitude angles, motion parameters, and absolute position information.

[0015] Preferably, the intelligent data correction unit is a pre-trained deep learning model, and the type of deep learning model is a convolutional neural network (CNN) or a long short-term memory network (LSTM).

[0016] A method for measuring the dynamic ground pressure of tracked vehicles, based on a dynamic ground pressure measurement system for tracked vehicles, includes the following measurement methods:

[0017] S1: Establish a test bed and drive the tracked vehicle through the test bed under different predetermined working conditions; synchronously collect pressure signals, three-dimensional attitude angles, motion parameters, and absolute position information until the tracked vehicle leaves the test bed;

[0018] S2: Unify the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information to the same absolute time and world coordinate system;

[0019] S3: Identify and repair outliers in pressure signals, 3D attitude angles, motion parameters, and absolute position information, including bus denoising and dynamic error compensation;

[0020] S4: Generate pressure signal-absolute time curves, three-dimensional attitude angle-absolute time curves, motion parameter-absolute time curves, and absolute position information-absolute time curves using the pressure signal, three-dimensional attitude angle, motion parameter-absolute time curves, and absolute position information-absolute time curves processed by S3;

[0021] S5: Calculate the key performance indicators of tracked vehicles using pressure signal-absolute time curve, three-dimensional attitude angle-absolute time curve, motion parameter-absolute time curve, and absolute position information-absolute time curve.

[0022] Preferably, in S1, after establishing the test bed, the method further includes using a standard pressure generator to perform static and dynamic calibration on each pressure sensor in the pressure sensor array to obtain the corresponding pressure-output transfer function.

[0023] Preferably, the key performance indicators include grounding specific pressure, dynamic grounding area, average grounding specific pressure, maximum grounding specific pressure, grounding specific pressure non-uniformity coefficient, pressure center coordinates, and pressure center movement trajectory;

[0024] The calculation method for key performance indicators is as follows:

[0025] The ground pressure ratio is the average pressure value measured by all pressure sensors in the pressure sensor array;

[0026] Dynamic grounding area The calculation formula is ;

[0027] Average grounding specific voltage The calculation formula is ;

[0028] Maximum grounding specific voltage The calculation formula is ;

[0029] Grounding specific voltage non-uniformity coefficient The calculation formula is ;

[0030] Coordinates of the center of pressure The calculation formula is , ;

[0031] The trajectory of the pressure center is the coordinate of the pressure center. The trajectory formed over time;

[0032] in, This indicates the serial number of the pressure sensor. Indicates the first The pressure value measured by a pressure sensor. Indicates the preset threshold. , Indicates pressure sensor The corresponding area of ​​action, This indicates the total number of active pressure sensors in the pressure sensor array. Indicates the first The position coordinates of the pressure sensor.

[0033] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0034] This invention relates to a distributed measurement system for dynamic ground pressure of tracked vehicles based on multi-source information fusion. Through an innovative multi-level sensing structure and advanced information processing technology, it achieves high-precision, all-around measurement of the ground pressure distribution of tracked vehicles. This system not only overcomes the limitations of traditional measurement methods under dynamic conditions but also significantly improves data reliability and accuracy through intelligent data fusion and correction. Its comprehensive evaluation and visualization module can generate detailed performance evaluation reports, providing users with in-depth insights into the vehicle's ground passability, mobility, and stability. Furthermore, the system possesses high flexibility and scalability, adapting to changes in different test scenarios and requirements, providing strong data support for the design optimization and performance improvement of tracked vehicles. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of the test bed of the dynamic ground pressure measurement system for tracked vehicles provided in an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of the position of the pressure sensing array according to an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the dynamic ground pressure measurement system for tracked vehicles provided in an embodiment of the present invention.

[0038] The reference numerals in the figures include:

[0039] Tracked vehicle S101, enclosure structure S102, standard medium S103, optical observation window S104, high-speed camera S105, pressure sensor array S106, data acquisition box S107, data fusion and intelligent processing platform S108, ultra-wideband positioning technology S109, global satellite positioning system S110. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and do not constitute a limitation thereof. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of the invention. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, some operations related to the invention are not shown or described in the specification. This is to avoid obscuring the core parts of the invention with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0041] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined to form various implementations. Furthermore, the order of the steps or actions in the method description can be changed or adjusted in a manner readily apparent to those skilled in the art. Therefore, the various orders in the specification and drawings are merely for the clear description of a particular embodiment and do not imply a mandatory order, unless otherwise stated that a particular order must be followed.

[0042] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0043] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0044] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0045] like Figure 1 , Figure 2 and Figure 3 As shown, this embodiment of the invention provides a dynamic grounding specific pressure measurement system for tracked vehicles, including a test bed, a multi-source information acquisition module, a data fusion and intelligent processing platform S108, and a comprehensive evaluation and visualization module. The test bed is used to support the tracked vehicle S101 being measured so that the multi-source information acquisition module can collect relevant data. The data fusion and intelligent processing platform S108 processes and analyzes the collected data, and the comprehensive evaluation and visualization module calculates the corresponding grounding specific pressure and other parameters.

[0046] The test bed is the basic structure for pressure sensing, including an enclosure structure S102, a rigid load-bearing base, a pressure sensor array S106, a standard medium S103, an optical observation window S104, and a high-speed camera S105. The enclosure structure S102 is used to accommodate the pressure sensor array S106, the standard medium S103, the optical observation window S104, and the high-speed camera S105 to form the test bed, and the rigid load-bearing base serves as mechanical support. The test bed is divided into a guide zone, a trigger zone, a measurement zone, and a buffer zone along the direction of travel of the tracked vehicle S101. The guide zone guides the tracked vehicle into the measurement zone in a stable posture; this area is paved with a standard medium layer S103. The trigger zone detects the tracked vehicle's entry into the measurement zone and triggers the multi-source information acquisition module; the triggering function is implemented by pressure sensors at the edge of the pressure sensor array S106. The measurement zone is the core test area, under which the pressure sensor array S106 is deployed to acquire real-time ground pressure distribution data generated during the tracked vehicle's movement. The buffer zone ensures the tracked vehicle smoothly leaves the measurement zone, completing data acquisition, while preventing impact on the measurement system when the vehicle leaves the measurement zone. The pressure sensor array S106 is arranged on a rigid load-bearing base and includes a rigid substrate sensor array and a flexible interpolation sensor array. The rigid substrate sensor array uses M... N are arranged in a matrix form on a rigid load-bearing base. The rigid base sensing array includes pressure cell units, each containing a miniature high-frequency dynamic pressure sensor. In this embodiment, the miniature high-frequency dynamic pressure sensor is a sensing element based on strain or capacitance principles, with a sampling frequency of not less than 1 kHz and a natural frequency higher than 5 kHz to ensure accurate capture of dynamic loads; the sensing surface material is high-hardness ceramic or special stainless steel to resist the impact of track patterns and media wear. A flexible interpolation sensing array is laid on the rigid base sensing array. The flexible interpolation sensing array is made of nanomaterials or conductive polymers and adopts a distributed thin-film pressure sensor form to improve spatial resolution, used to sense subtle pressure changes between the rigid base sensing arrays, and to achieve "gapless" coverage of the measurement. In this embodiment, all pressure sensors are connected through a central data acquisition unit. The central data acquisition unit includes a multi-channel synchronous data acquisition card, a hardware trigger control module, and a high-precision clock module. The hardware trigger control module is used to send a unified trigger signal to each acquisition channel, so that each pressure sensor starts sampling at the same time. The high-precision clock module provides a unified time reference for all acquisition channels and timestamps the acquired data, thereby achieving time synchronization of data from each sensor in the pressure sensor array, with a synchronization error of less than 1ms.

[0047] The standard medium S103 is placed on the top layer of the test bed. The filling and stratification of the standard medium S103 are controllable, consisting of a lower load-bearing sand layer and an upper simulated topsoil layer. The physical parameters of the standard medium S103, such as density and moisture content, can be monitored in real time. The moisture content is monitored by a moisture content monitoring device (such as a soil moisture sensor) installed in the standard medium S103, and the density is determined by a density monitoring device or a preset filling mass-volume relationship. According to the test requirements, the moisture content can be adjusted by a water addition device or a ventilation and drying device, and the density can be adjusted by re-leveling or adding medium material.

[0048] The total thickness of the standard medium S103 is at least five times the maximum feature size of a single pressure sensor in the pressure sensor array S106. For example, if the pressure sensor in the pressure sensor array S106 is circular, the maximum feature size is the diameter; if it is rectangular, the maximum feature size is the maximum side length. This is to fully simulate the mechanical properties of the real ground and ensure that the track ground pressure can be transmitted to the bottom pressure sensor array S106 with the least possible distortion.

[0049] Both the optical observation window S104 and the high-speed camera S105 are installed on the side wall of the enclosure structure S102 to visually observe the state changes of the tracked vehicle S101 as it travels on the test bed. The high-speed camera S105 can acquire process images of this process and can add the acquired process images to the final report to enrich the report content.

[0050] This embodiment of the invention also includes a data acquisition box S107, which is equipped with a multi-source information acquisition module. The multi-source information acquisition module is responsible for synchronously and rapidly acquiring various physical quantities during the test. The multi-source information acquisition module includes several functional sub-modules, specifically: an array acquisition sub-module, a vehicle attitude perception sub-module, a kinematics perception sub-module, and a spatial positioning sub-module. The array acquisition sub-module directly connects to all pressure sensors of the pressure sensor array S106 via a dedicated interface and acquires all pressure signals from all pressure sensors at an acquisition frequency of not less than 1 kHz. The vehicle attitude perception sub-module is typically installed near the center of mass of the tracked vehicle S101 under test and uses a high-precision inertial measurement unit (IMU) to measure the three-dimensional attitude angles of the tracked vehicle S101 in real time. The three-dimensional attitude angles include the roll angle, pitch angle, and yaw angle of the tracked vehicle S101. The kinematics perception sub-module acquires the motion parameters of the tracked vehicle S101 in real time, including velocity and acceleration. These motion parameters can be acquired in real time through encoders, radar, or vision methods. The number of spatial positioning submodules is not unique, but at least S109 is installed on both the test bed and the tracked vehicle S101, using Global Positioning System S110 (GNSS) or Ultra Wideband (UWB) positioning technology, which can obtain the absolute position information of the tracked vehicle S101 relative to the test bed at the centimeter level in real time.

[0051] All functional sub-modules of the multi-source information acquisition module ensure high consistency of data in time through a unified hardware triggering and clock synchronization mechanism, laying the foundation for subsequent multi-source data fusion.

[0052] The data fusion and intelligent processing platform S108 is the core unit of the measurement system, responsible for integrating, correcting, and deeply analyzing the large amount of multi-source data collected. The data fusion and intelligent processing platform S108 includes a spatiotemporal synchronization unit, a data reconstruction and interpolation unit, and an intelligent data correction unit. The spatiotemporal synchronization unit synchronously correlates the collected pressure signals, three-dimensional attitude angles, motion parameters, and absolute position information to absolute time and world coordinate systems. The collected pressure signals, three-dimensional attitude angles, motion parameters, and absolute position information are all discrete points and may contain outliers or noise. This embodiment of the invention includes an intelligent data correction unit to identify and correct outliers in the pressure signals, three-dimensional attitude angles, motion parameters, and absolute position information. Specifically, this embodiment of the invention uses a pre-trained deep learning model for outlier correction. The deep learning model employs a Convolutional Neural Network (CNN), a Long Short-Term Memory (LSTM) network, or a combination of both. The deep learning model takes the original pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information as input, and uses the pressure signal obtained from the pressure sensor calibration experiment as a supervised label. It is trained through supervised learning to learn the dynamic response characteristics and hysteresis effect of the pressure signal of the tracked vehicle S101 under dynamic working conditions. After the system is built, static and dynamic calibrations are performed on the pressure sensors on the test bed. The multi-source data collected during the calibration process is used to construct a training dataset. A stable deep learning model is obtained through iterative training and parameter optimization. The trained model is then deployed in the intelligent data correction unit to perform online denoising, dynamic error compensation, and other outlier correction on the original measurement data (pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information), improving the reliability and accuracy of the data.

[0053] The pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information, processed by the intelligent data correction unit, are sent to the data reconstruction and interpolation unit. To improve resolution, the data reconstruction and interpolation unit in this embodiment of the invention employs an improved Kriging space interpolation algorithm that considers terrain anisotropy and signal spatial correlation. This algorithm interpolates the original pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information separately, thereby improving resolution. The data reconstruction and interpolation unit then generates pressure signal-absolute time curves, three-dimensional attitude angle-absolute time curves, motion parameter-absolute time curves, and absolute position information-absolute time curves from the interpolated data. Data interpolation enables a leap from "point measurement" to "field perception." Through the interpolated pressure signal-absolute time curves, three-dimensional attitude angle-absolute time curves, motion parameter-absolute time curves, and absolute position information-absolute time curves, parameters such as pressure, three-dimensional attitude angle, absolute position, velocity, and acceleration at different times can be obtained. These parameters change over time; in this embodiment of the invention, these parameters obtained based on the aforementioned curves are referred to as a dynamic pressure field sequence.

[0054] The interpolated high-resolution dynamic pressure field sequence is then input into the comprehensive evaluation and visualization module, which calculates several key performance indicators, including grounding specific pressure. In addition to grounding specific pressure, this embodiment of the invention also calculates other key performance indicators such as dynamic grounding area, average grounding specific pressure, maximum grounding specific pressure, grounding specific pressure non-uniformity coefficient, pressure center coordinates, and pressure center trajectory.

[0055] Furthermore, by performing a two-dimensional integration on the pressure distribution in the contact area between the tracked vehicle S101 and the test bed, the pitching and rolling moments of the tracked vehicle S101 can be further calculated. Specifically, with the track ground contact center as the origin of the reference coordinate system, let the nth... The pressure measured by each pressure sensor is Its effective area is The vertical coordinate relative to the origin of the reference coordinate system is The horizontal coordinate is Then the grounding reaction force generated by each pressure sensor is By summing the ground reaction forces of all pressure sensors, the pitching moment and rolling moment of the tracked vehicle S101 can be calculated separately. The pitching moment can be expressed as the sum of the moments of each ground reaction force relative to the lateral axis.

[0056] .

[0057] An increase in pitch moment indicates an uneven distribution of load between the front and rear of the vehicle, which may lead to a tendency to pitch forward or backward. Roll moment can be expressed as the sum of the moments of each ground reaction force relative to the longitudinal axis:

[0058] .

[0059] An increase in rolling moment indicates a greater difference in force distribution between the left and right tracks of tracked vehicle S101, increasing the risk of lateral tilting or instability. Therefore, real-time calculation of pitch and rolling moments can reflect the stability of tracked vehicle S101 during operation.

[0060] In this embodiment of the invention, after calculating multiple key performance indicators using the comprehensive evaluation and visualization module, a comprehensive performance evaluation report is output. The comprehensive performance evaluation report includes ground pressure cloud maps, time-series curves of various key performance indicators, etc., which can intuitively reflect the ground passability, mobility, and stability of the tracked vehicle S101, and provide a comprehensive and detailed evaluation of the performance of the tracked vehicle S101.

[0061] This invention also provides a method for measuring the dynamic grounding specific voltage of a tracked vehicle S101 using the aforementioned dynamic grounding specific voltage measurement system, specifically including:

[0062] S1: Establish a test bed, drive the tracked vehicle S101 through the test bed under different predetermined working conditions, and simultaneously collect pressure signals, three-dimensional attitude angles, motion parameters, and absolute position information until the tracked vehicle S101 leaves the test bed.

[0063] The test bed was constructed according to the aforementioned test bed structure. First, a standard pressure generator was used to perform static and dynamic calibration on each pressure sensor in the pressure sensor array S106, obtaining the corresponding pressure-output transfer function and frequency response characteristics. The pressure-output transfer function refers to the ratio of the Laplace transform of the system output to the Laplace transform of the input, and is one of the fundamental mathematical tools for describing the dynamic characteristics of a system. Simultaneously, all pressure sensors were initialized and a synchronous trigger threshold was set. When the pressure signal detected by any one or more sensing units in the pressure sensor array exceeds this trigger threshold, the central data acquisition unit sends a unified trigger signal to all acquisition channels, thereby initiating synchronous data acquisition to ensure that each pressure sensor can synchronously record pressure data when the tracked vehicle S101 enters the test area. The trigger threshold can be set based on the no-load noise level of the pressure sensors or the minimum ground pressure of the tracked vehicle to avoid false triggering caused by environmental disturbances or noise signals. A large amount of calibration data was collected during the calibration process for subsequent deep learning model training.

[0064] The tracked vehicle S101 is driven into the test bed and travels through it under different predetermined working conditions until it leaves the test bed. In this embodiment of the invention, the different predetermined working conditions include different speeds, different loads, and different steering. Multiple working conditions can obtain more comprehensive and richer data.

[0065] During the movement of the tracked vehicle S101, a multi-source information acquisition module collects pressure signals, three-dimensional attitude angles, motion parameters, and absolute position information until the tracked vehicle S101 leaves the test bed. Specifically, the multi-source information acquisition module includes an array acquisition submodule, a vehicle attitude perception submodule, a kinematic perception submodule, and a spatial positioning submodule. The pressure sensor array S106 acquires the track ground pressure of the tracked vehicle S101 during its movement, and the array acquisition submodule obtains all pressure signals in real time based on the track ground pressure. The vehicle attitude perception submodule is installed near the center of mass of the tracked vehicle S101 and is used to measure the three-dimensional attitude angles of the tracked vehicle S101 in real time, including the roll angle, pitch angle, and yaw angle. The kinematic perception submodule integrates the tracked vehicle's CAN bus and is equipped with radar. It is used to acquire the motion parameters of the tracked vehicle S101 in real time, including the speed and acceleration of the tracked vehicle S101. The absolute position information of the tracked vehicle S101 is obtained in real time using the spatial positioning submodule.

[0066] S2: Unify the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information to the same absolute time and world coordinate system.

[0067] The acquired pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information are sent to the data fusion and intelligent processing platform S108. The data fusion and intelligent processing platform S108 includes a spatiotemporal synchronization unit, an intelligent data correction unit, and a data reconstruction and interpolation unit. The spatiotemporal synchronization unit, intelligent data correction unit, and data reconstruction and interpolation unit process the acquired pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information data in sequence.

[0068] The spatiotemporal synchronization unit unifies the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information to the same absolute time, and accurately registers the three-dimensional attitude angle and absolute position information to the world coordinate system of the test bed for subsequent calculations.

[0069] S3: Identify and repair outliers in pressure signals, 3D attitude angles, motion parameters, and absolute position information, including bus denoising and dynamic error compensation.

[0070] The intelligent data correction unit is used to identify and repair outliers in pressure signals, three-dimensional attitude angles, motion parameters, and absolute position information, including bus denoising and dynamic error compensation. In this embodiment of the invention, the intelligent data correction unit is a CNN-LSTM hybrid deep learning model, and the deep learning model of the intelligent data correction unit is trained using calibration data collected during the pressure sensor calibration process as training samples. The deep learning model takes the original pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information as input, and the pressure signal obtained from the pressure sensor calibration experiment as a supervision label. It is trained through supervised learning to learn the dynamic response characteristics and hysteresis effect of the pressure signal of the tracked vehicle S101 under dynamic working conditions. After the system is built, the pressure sensor on the test bed is statically and dynamically calibrated. The multi-source data collected during the calibration process is used to construct a training dataset. A stable deep learning model is obtained through iterative training and parameter optimization. The trained model is deployed in the intelligent data correction unit to perform online denoising, dynamic error compensation, and other outlier repair on the original measurement data (pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information), thereby improving the reliability and accuracy of the data.

[0071] The pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information, after being identified and repaired by the intelligent data correction unit, are all discrete point data with low resolution. This embodiment of the invention uses interpolation to improve their resolution.

[0072] The data reconstruction and interpolation unit executes the core field reconstruction algorithm: using the corrected rigid array data as robust data, it integrates the high-resolution details provided by the flexible interpolation layer, and adopts an improved Kriging space interpolation algorithm that considers anisotropy to generate a high-resolution, full-field continuous pressure distribution matrix with a grid density far exceeding the number of physical sensors at each time step.

[0073] S4: Generate pressure signal-absolute time curves, three-dimensional attitude angle-absolute time curves, motion parameter-absolute time curves, and absolute position information-absolute time curves using the pressure signal, three-dimensional attitude angle, motion parameter-absolute time curves, and absolute position information-absolute time curves processed by S3.

[0074] The interpolated pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information have improved resolution and are no longer scattered discrete points. Based on these interpolated data, the data reconstruction and interpolation unit generates the corresponding pressure signal-absolute time curves, three-dimensional attitude angle-absolute time curves, motion parameter-absolute time curves, and absolute position information-absolute time curves relative to absolute time.

[0075] High-resolution data yields more accurate and smoother curves. Each absolute time on the curve corresponds to specific data (pressure signal, three-dimensional attitude angle, motion parameters, or absolute position information). In this embodiment of the invention, these time-varying data (pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information) are referred to as a dynamic pressure field sequence.

[0076] S5: Calculate the key performance indicators of the tracked vehicle S101 using the pressure signal-absolute time curve, three-dimensional attitude angle-absolute time curve, motion parameter-absolute time curve, and absolute position information-absolute time curve.

[0077] The pressure signal-absolute time curve, three-dimensional attitude angle-absolute time curve, motion parameter-absolute time curve, and absolute position information-absolute time curve carry the entire dynamic pressure field sequence. The key performance indicators of the tracked vehicle S101 are calculated using the dynamic pressure field sequence.

[0078] The pressure signal-absolute time curve, three-dimensional attitude angle-absolute time curve, motion parameter-absolute time curve, and absolute position information-absolute time curve (i.e., the dynamic pressure field sequence) are input into the comprehensive evaluation and visualization module. The module then calculates the key performance indicators of the tracked vehicle S101. Key performance indicators include ground pressure specificity. In addition to ground pressure specificity, this embodiment of the invention also calculates other key performance indicators, including dynamic ground area, average ground pressure specificity, maximum ground pressure specificity, ground pressure specificity non-uniformity coefficient, pressure center coordinates, and pressure center trajectory.

[0079] Specifically, in the pressure sensing array, the first The pressure measured by each pressure sensor is When the measured pressure is greater than the preset threshold At that time, the pressure sensor is considered to be in an effective grounding state. satisfy Its corresponding effective area is The total number of effective pressure sensors in the pressure sensor array S106 is The specific calculation method for key performance indicators is as follows:

[0080] The method for calculating the ground pressure ratio is as follows: the pressure value measured by the pressure sensor is... This pressure value can be equivalently viewed as the ground pressure specific value within the corresponding area of ​​action, which is the measured ground pressure specific value. In actual use, the pressure value of a single pressure sensor is not used; the average value is usually used to obtain the maximum value. The average pressure value of each pressure sensor.

[0081] The dynamic grounding area is calculated as follows: when the measured pressure of a certain pressure sensor exceeds a preset threshold... If the sensing unit is considered to be in an effective grounding state, then the dynamic grounding area of ​​the tracked vehicle at a certain moment is... for .

[0082] Average grounding specific voltage The calculation method is as follows: the average grounding specific pressure is the area-weighted average of the pressure within the grounding area, expressed as... .

[0083] Maximum grounding specific voltage The calculation method is as follows: the maximum pressure value measured by all pressure sensing units within the grounding area, i.e. .

[0084] Grounding specific voltage non-uniformity coefficient It is used to characterize the uniformity of grounding pressure distribution and can be expressed as the ratio of the maximum grounding specific pressure to the average grounding specific pressure, i.e. .

[0085] Coordinates of the center of pressure The calculation method is as follows: taking the test bed coordinate system as the reference coordinate system, let the first... The position coordinates of the pressure sensors are Then the coordinates of the pressure center can be expressed as , .

[0086] The method for calculating the trajectory of the pressure center is as follows: during the movement of the tracked vehicle S101, the coordinates of the pressure center are calculated continuously at each moment. The trajectory formed over time is the trajectory of the pressure center, which is used to reflect the dynamic changes of the ground load of the tracked vehicle during the driving process.

[0087] In this embodiment of the invention, after calculating multiple key performance indicators using the comprehensive evaluation and visualization module, a comprehensive performance evaluation report is output. The comprehensive performance evaluation report includes ground pressure cloud maps, time-series curves of various key performance indicators, etc., which can intuitively reflect the ground passability, mobility, and stability of the tracked vehicle S101, and provide a comprehensive and detailed evaluation of the performance of the tracked vehicle S101.

[0088] Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

[0089] The specific embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. Any other corresponding changes and modifications made in accordance with the technical concept of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A dynamic ground pressure measurement system for tracked vehicles, characterized in that, include: Test bed, multi-source information acquisition module, data fusion and intelligent processing platform, and comprehensive evaluation and visualization module; The test bed includes a pressure sensor array, which is used to acquire the track ground pressure in real time. The multi-source information acquisition module includes an array acquisition submodule, a vehicle attitude perception submodule, a kinematics perception submodule, and a spatial positioning submodule. The array acquisition submodule acquires pressure signals based on track ground pressure. The vehicle attitude perception submodule measures the three-dimensional attitude angles of the tracked vehicle in real time. The kinematics perception submodule acquires the motion parameters of the tracked vehicle in real time. The spatial positioning submodule acquires the absolute position information of the tracked vehicle in real time. The data fusion and intelligent processing platform includes a spatiotemporal synchronization unit and a data reconstruction and interpolation unit. The spatiotemporal synchronization unit synchronously associates the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information with absolute time and world coordinate system. The data reconstruction and interpolation unit performs interpolation processing on the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information, and then generates pressure signal-absolute time curves, three-dimensional attitude angle-absolute time curves, motion parameter-absolute time curves, and absolute position information-absolute time curves, respectively. Based on the pressure signal-absolute time curve, the three-dimensional attitude angle-absolute time curve, the motion parameter-absolute time curve, and the absolute position information-absolute time curve, the key performance indicators of the tracked vehicle are calculated using the comprehensive evaluation and visualization module. The key performance indicators include dynamic grounding area, average grounding specific pressure, maximum grounding specific pressure, grounding specific pressure non-uniformity coefficient, pressure center coordinates, and pressure center motion trajectory.

2. The dynamic ground pressure measurement system for tracked vehicles as described in claim 1, characterized in that, The pressure sensing array includes a rigid substrate sensing array and a flexible interpolation sensing array; the rigid substrate sensing array includes a pressure cell unit, which includes a miniature high-frequency dynamic pressure sensor; the flexible interpolation sensing array is composed of distributed thin-film pressure sensors.

3. The dynamic ground pressure measurement system for tracked vehicles as described in claim 1, characterized in that, The test bed also includes a standard medium, which comprises a load-bearing sand layer and a simulated topsoil layer; the total thickness of the standard medium is greater than or equal to 5 times the maximum feature size of the pressure sensor in the pressure sensing array.

4. The dynamic ground pressure measurement system for tracked vehicles as described in claim 1, characterized in that, The array acquisition submodule acquires all the pressure signals corresponding to the track grounding pressure at the same frequency, with an acquisition frequency of not less than 1kHz.

5. The dynamic ground pressure measurement system for tracked vehicles as described in claim 1, characterized in that, The three-dimensional attitude angles include the roll angle, pitch angle, and yaw angle of the tracked vehicle.

6. The dynamic ground pressure measurement system for tracked vehicles as described in claim 1, characterized in that, The data fusion and intelligent processing platform also includes an intelligent data correction unit. Before interpolation, the intelligent data correction unit is used to identify and correct abnormal values ​​in the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information.

7. The dynamic ground pressure measurement system for tracked vehicles as described in claim 6, characterized in that, The intelligent data correction unit is a pre-trained deep learning model, and the type of deep learning model is either a convolutional neural network (CNN) or a long short-term memory network (LSTM).

8. A method for measuring the dynamic ground contact specific voltage of a tracked vehicle, characterized in that, Based on the tracked vehicle dynamic ground pressure measurement system as described in any one of claims 1-7, the measurement method includes: S1: Establish the test bed, drive the tracked vehicle through the test bed under different predetermined working conditions; synchronously collect the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information until the tracked vehicle leaves the test bed; S2: Unify the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information to the same absolute time and world coordinate system; S3: Identify and repair outliers in the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information, including bus denoising and dynamic error compensation; S4: Using the pressure signal, three-dimensional attitude angle, motion parameters, and absolute position information processed in S3, generate pressure signal-absolute time curves, three-dimensional attitude angle-absolute time curves, motion parameter-absolute time curves, and absolute position information-absolute time curves; S5: Calculate the key performance indicators of the tracked vehicle using the pressure signal-absolute time curve, three-dimensional attitude angle-absolute time curve, motion parameter-absolute time curve, and absolute position information-absolute time curve.

9. The method for measuring the dynamic ground pressure of tracked vehicles as described in claim 8, characterized in that, In step S1, after establishing the test bed, the method further includes using a standard pressure generator to perform static and dynamic calibration on each pressure sensor in the pressure sensor array to obtain the corresponding pressure-output transfer function.

10. The method for measuring the dynamic ground pressure of tracked vehicles as described in claim 9, characterized in that, The key performance indicators include grounding specific pressure, dynamic grounding area, average grounding specific pressure, maximum grounding specific pressure, grounding specific pressure non-uniformity coefficient, pressure center coordinates, and pressure center movement trajectory. The calculation method for the key performance indicators is as follows: The ground pressure ratio is the average value of the pressure values ​​measured by all pressure sensors in the pressure sensing array; The dynamic grounding area The calculation formula is ; The average grounding ratio The calculation formula is ; The maximum grounding voltage The calculation formula is ; The grounding specific voltage non-uniformity coefficient The calculation formula is ; The coordinates of the pressure center The calculation formula is , ; The trajectory of the pressure center is the coordinate of the pressure center. The trajectory formed over time; in, This indicates the serial number of the pressure sensor. Indicates the first The pressure value measured by a pressure sensor. Indicates the preset threshold. , Indicates pressure sensor The corresponding area of ​​action, This indicates the total number of valid pressure sensors in the pressure sensor array. Indicates the first The position coordinates of the pressure sensor.

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