Dual-sensor system road load spectrum acquisition and calibration method and system
By attaching strain gauges to a dual-sensor system and configuring a hydraulic servo system, the problems of synchronous acquisition and calibration accuracy of sensor signals were solved, enabling efficient load spectrum acquisition and component design verification.
Patent Information
- Application Number
- CN202511051442.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-29
- Publication Date
- 2025-11-14
AI Technical Summary
In existing load spectrum acquisition systems, the synchronous acquisition and calibration accuracy of sensor signals are insufficient, the accuracy of stress sensor modification is poor, and there is a lack of standardized strain gauge bonding position selection and bridging methods, which affects the reliability and efficiency of load spectrum acquisition.
A dual-sensor system is adopted. By determining the strain gauge type and bonding position of the components, a hydraulic servo system is configured and a standard load sensor is connected in series. Linear fitting of stress signal and external load signal is performed to obtain calibration coefficients and bias values, construct stress-load conversion relationship, and collect and analyze road load spectrum.
It enables synchronous acquisition and high-precision calibration of sensor signals, improves the reliability and efficiency of load spectrum acquisition, and provides a basis for component design and verification.
Smart Images
Figure CN120947864A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of road load spectrum acquisition and calibration technology, and in particular to a method and system for road load spectrum acquisition and calibration using a dual-sensor system. Background Technology
[0002] In passenger vehicle development, load is a key indicator affecting vehicle design progress and reliability. Statistics show that over 80% of damage to automotive mechanical components stems from fatigue failure. Therefore, it is crucial to acquire load data for critical components early in development through road load spectrum acquisition to support fatigue strength design. Currently, stress testing sensors (such as strain gauges) need to be calibrated in series with standard load sensors to convert stress signals into load signals. However, the sensor signals of hydraulic servo calibration systems are typically only used for closed-loop control. Without a dedicated output board, they cannot be directly output to the data acquisition unit, making it difficult to synchronously acquire sensor signals and component stress signals, thus affecting calibration accuracy. Furthermore, the lack of standardized methods for selecting strain gauge placement and bridging methods for complex components further reduces the accuracy of stress sensor modification. These issues collectively constrain the reliability and efficiency of load spectrum acquisition, necessitating a solution that enables high-precision synchronous calibration and is compatible with different component forms. Summary of the Invention
[0003] This invention provides a method and system for road load spectrum acquisition and calibration using a dual-sensor system, which addresses the problems of synchronous acquisition of sensor signals, calibration accuracy, and accuracy of stress sensor modification in existing load spectrum acquisition systems.
[0004] The objective of this invention can be achieved through the following technical solutions: The first aspect of this invention is to provide a method for calibrating road load spectrum acquisition in a dual-sensor system, comprising: Based on the type of load on each component, the corresponding strain gauges for each component are determined and attached to obtain the stress signal of each component. By configuring a hydraulic servo system and connecting a standard load sensor in series, the timing of the external load signal can be obtained. By performing linear fitting on the stress signal and external load signal of each component, a stress-load conversion line is obtained; the calibration coefficient and offset value of each component are obtained from the stress-load conversion line; each component is calibrated based on the calibration coefficient and offset value, and a stress-load conversion relationship is constructed. The vehicle is driven on different road surfaces, and road load spectra are collected through stress-load conversion relationships to obtain road load spectra. The road load spectra are then used to analyze the loads, identify resonance risks and main excitation sources, and provide a basis for the design and verification of components.
[0005] Furthermore, the process of determining the strain gauge corresponding to each component based on the type of load it receives, and then attaching it to obtain the stress value of each component, includes: Based on the type of load on each component, the corresponding strain gauge is determined and attached; by assembling the strain gauges into a bridge circuit, each component is transformed into a stress sensor to obtain the stress value of each component.
[0006] Furthermore, the types of loads applied include tension, compression, bending, shear, and torsion; the types of loads applied are obtained by performing stress analysis on each component of the vehicle.
[0007] Furthermore, the step of obtaining a stress-load conversion straight line by performing linear fitting on the stress signal and external load signal of each component includes: By performing linear fitting on the stress signal and external load signal of each component using the least squares method, a stress-load conversion straight line is obtained.
[0008] Furthermore, the calibration coefficient and offset value of each component are obtained through the stress-load conversion line, and the formula corresponding to the stress-load conversion line is specifically expressed as follows:
[0009] In the formula, Indicates external load, Indicates the calibration coefficient. Indicates the stress value. This represents the bias value.
[0010] Furthermore, the stress-load conversion relationship is specifically expressed as follows:
[0011] In the formula, Indicates the transformed load. Indicates the calibration coefficient. Indicates the stress value. This represents the bias value.
[0012] Furthermore, the analysis and identification of resonance risks and main excitation sources through road load spectrum, and the provision of a basis for component design and verification, include: By observing the load variation over time using the road load spectrum, peak loads, alternating characteristics, and transient impacts can be identified. The power spectral density of the road load spectrum is obtained through fast Fourier transform, which displays the energy distribution of each frequency component. This is used to analyze the frequency components of the load signal, identify resonance risks, and identify the main excitation sources. Then, fatigue characteristics are obtained from the load time-domain signal and the material SN curve. This provides a basis for the design and verification of components.
[0013] A second aspect of the present invention is to provide a road load spectrum acquisition and calibration system for a dual-sensor system, comprising: Component modification module: used to determine the strain gauge corresponding to each component based on the type of load it is subjected to, and then attach it to obtain the stress signal of each component; Configuration module: Used to obtain timing-based external load signals by configuring the hydraulic servo system and connecting a standard load sensor in series; Calibration coefficient fitting module: used to perform linear fitting between the stress signal and external load signal of each component to obtain the stress-load conversion line; obtain the calibration coefficient and offset value of each component through the stress-load conversion line; calibrate each component based on the calibration coefficient and offset value of each component, and construct the stress-load conversion relationship; Vehicle Load Spectrum Acquisition and Application Module: This module allows the vehicle to travel on different road surfaces and acquires road load spectra through stress-load conversion relationships. It then analyzes the loads based on the road load spectra, identifies resonance risks and major excitation sources, and provides a basis for the design and verification of components.
[0014] A third aspect of the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aforementioned method for acquiring and calibrating a road load spectrum of a dual-sensor system.
[0015] A fourth aspect of the present invention is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method for acquiring and calibrating a road load spectrum in a dual-sensor system.
[0016] Compared with existing technologies, the beneficial effects of this invention are as follows: Strain gauges are determined for each component based on the type of load they experience, and then attached to obtain the stress signal for each component; the accuracy problem of stress sensor modification is solved; a time-series external load signal is obtained by configuring a hydraulic servo system and connecting a standard load sensor in series; the problem of synchronous acquisition of sensor signals in existing load spectrum acquisition systems is solved; a stress-load conversion line is obtained by linearly fitting the stress signal and external load signal of each component; the calibration coefficient and offset value of each component are obtained through the stress-load conversion line; each component is calibrated based on its calibration coefficient and offset value, and a stress-load conversion relationship is constructed; the calibration accuracy problem is solved; the vehicle is driven on different road surfaces, and road load spectra are acquired through the stress-load conversion relationship to obtain the road load spectrum; the road load spectrum is used to analyze the load and identify resonance risks and main excitation sources, providing a basis for component design and verification, improving development efficiency and product reliability. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This invention provides a schematic flowchart of the steps for acquiring and calibrating a road load spectrum using a dual-sensor system. Figure 2 This invention provides a schematic diagram of the module flow of a dual-sensor system road load spectrum acquisition and calibration system; Figure 3 Schematic diagram of a modified stress sensor for a component; Figure 4 A schematic diagram of a linear hydraulic cylinder with a series load sensor; Figure 5 A schematic diagram of the time-domain signal acquired by the data acquisition system; Figure 6 This is a schematic diagram of the stress load conversion line and calibration coefficients of the stress sensor. Detailed Implementation
[0019] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.
[0020] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0021] To address the problems existing in the background technology, a method and system for road load spectrum acquisition and calibration using a dual-sensor system were designed, which has significant practical implications.
[0022] like Figure 1 As shown, the first aspect of the present invention is to provide a method for road load spectrum acquisition and calibration of a dual-sensor system, comprising the following steps: Step S001: Determine the strain gauge corresponding to each component based on the type of load it is subjected to, and attach it to obtain the stress signal of each component.
[0023] It should be noted that directly measuring the actual load on key components (such as suspension arms, axles, and steering knuckles) during the whole vehicle road load spectrum acquisition process is extremely difficult. This is because these components are usually integrated into the vehicle system, making it difficult to directly install standard load sensors. These standard load sensors (such as force sensors and torque sensors) are typically large and cannot be directly installed on key vehicle components, especially in space-constrained locations. Furthermore, directly installing external sensors may alter the structural stiffness or stress characteristics of the components, affecting the accuracy of the test results. Therefore, it is necessary to modify stress sensors to transform the components themselves into "sensors" to indirectly measure the loads they bear.
[0024] It should be further noted that different components (such as tension / compression rods, bending beams, and torsional shafts) experience different stresses, requiring different strain gauge placement schemes (such as uniaxial strain gauges, T-strain gauges, and shear strain gauges). For irregularly shaped components such as those made by casting or welding, CAE simulation analysis is needed to determine the optimal strain gauge placement to ensure measurement accuracy.
[0025] Specifically, by performing stress analysis on each component of the automobile, the type of load on each component is obtained; the types of loads include tension, compression, bending, shear, and torsion.
[0026] Each component is assigned a strain gauge based on the type of load it experiences, and these gauges are then attached. By assembling the strain gauges into a bridge circuit, each component is transformed into a stress sensor to acquire its stress signal (i.e., stress data). The unit of stress data is microstrain. A schematic diagram of the component-to-stress-sensor transformation is shown below. Figure 3 As shown.
[0027] Thus, the stress signal of each component is obtained through the above method.
[0028] Step S002: Obtain the timing-based external load signal by configuring the hydraulic servo system and connecting a standard load sensor in series.
[0029] It should be noted that, in order to provide precise and controllable loading conditions and simulate the stress state of components under real working conditions, the hydraulic servo system ensures the stability and repeatability of the loading process through closed-loop control (such as real-time feedback adjustment of force, displacement, torque, and angle). Since the system's built-in sensor signals are typically only used for internal control loops and cannot be directly output to an external data acquisition unit, additional standard sensors (such as load or torque sensors) need to be connected in series to bypass the system's closed nature and achieve synchronous output of the loading signal, providing reliable input data for subsequent calibration.
[0030] Specifically, firstly, a hydraulic servo system (including linear / torsional hydraulic cylinders) is configured. Closed-loop control is achieved through its built-in load / torque and displacement / angle sensors to ensure precise loading. Since the system's built-in sensor signals are only used for internal control, an additional standard load / torque sensor needs to be connected in series to output its signal to the data acquisition system, providing a synchronous load input signal for subsequent calibration. This yields a time-series external load signal.
[0031] The data acquisition system hardware (multi-channel input, power supply) and software (signal unit conversion, fitting tools) are configured to synchronously acquire and record the sensor signals (standard load / torque) connected in series in the hydraulic servo system and the stress signals output by the strain gauge bridge on the components, ensuring time alignment between the two and providing raw data pairs for calibration. A schematic diagram of a linear hydraulic cylinder with a series load sensor is shown below. Figure 4 As shown; the hydraulic servo system includes a displacement sensor 1, a hydraulic module 2, a first load sensor 3, and a second load sensor 4; wherein the first load sensor 3 and the second load sensor 4 are connected.
[0032] Based on the acquired synchronous data pairs (load signal - strain signal), with strain value on the x-axis and load signal on the y-axis, calibration coefficients are calculated through linear fitting to establish the stress-load conversion relationship. After calibration, the actual load on components can be calculated from the strain signal during actual vehicle testing, generating a load spectrum for fatigue analysis.
[0033] The purpose of the data acquisition system is to synchronously record load signals and component strain signals to establish a quantitative relationship between them. This system requires multi-channel input, supporting strain gauge bridge power supply (e.g., 1 / 4 bridge, half bridge, full bridge), sensor signal reception (e.g., voltage / current input), and calibration coefficient calculation functions. Through the synergy of hardware (e.g., high-precision ADC modules) and software (e.g., time-domain analysis, curve fitting tools), the system ensures the synchronization, low noise, and high resolution of the raw data (strain, load), providing a high-quality data foundation for calibration coefficient fitting. A schematic diagram of the time-domain signals acquired by the data acquisition system is shown below. Figure 5 As shown.
[0034] The purpose of the calibration process is to convert strain signals into engineering-usable load signals, providing input for fatigue analysis. A known load (such as stepped loading) is applied to the modified components using a hydraulic servo system, while simultaneously acquiring strain gauge signals and signals from cascaded sensors. A linear or nonlinear calibration equation is fitted with load as the ordinate and strain as the abscissa. The calibration results (coefficients A and bias C) will be used for real-time load conversion of strain signals during actual vehicle testing, ensuring the accuracy of the physical meaning of the road load spectrum and ultimately supporting the reliability design and verification of the components.
[0035] At this point, the configuration and setup are complete, and the timing of the external load signal is obtained.
[0036] Step S003: Obtain the stress-load conversion line by performing linear fitting on the stress signal and external load signal of each component; obtain the calibration coefficient and offset value of each component through the stress-load conversion line; calibrate each component according to the calibration coefficient and offset value of each component, and construct the stress-load conversion relationship.
[0037] It should be noted that since the series sensors measure the external load applied by the hydraulic system (such as the thrust of the actuator cylinder), but what is actually needed is the local stress / load of the key parts of the components (such as the fatigue stress at a certain point of the suspension arm), the load data obtained by the series sensors above cannot be directly used as the final load data to judge the fatigue degree. That is, it needs to be analyzed in conjunction with the stress value. Therefore, the calibration of the components is carried out by analyzing the relationship between the stress value and the load value.
[0038] Specifically, with stress values on the horizontal axis and load signal data from load sensors on the vertical axis, a straight line is fitted using the least squares method based on the stress signal and external load signal of each component to obtain the stress-load conversion straight line; the least squares method is a well-known technique and will not be elaborated on here.
[0039] The formula corresponding to the stress-load transformation line is specifically expressed as follows:
[0040] In the formula, Indicates external load, Indicates the calibration coefficient. Indicates the stress value. This represents the bias value.
[0041] Each component is calibrated based on its calibration coefficient and offset value, and a stress-load conversion relationship is constructed; specifically, the stress-load conversion relationship is expressed as follows:
[0042] In the formula, Indicates the transformed load. Indicates the calibration coefficient. Indicates the stress value. This represents the bias value.
[0043] The stress load conversion line and calibration coefficient diagram of the stress sensor are shown below. Figure 6 As shown.
[0044] Thus, the stress-load conversion relationship is obtained through the above method.
[0045] Step S004: Drive the vehicle on different road surfaces and collect road load spectra through stress-load conversion relationship to obtain road load spectra; analyze the load and identify resonance risks and main excitation sources through road load spectra, and provide a basis for the design and verification of components.
[0046] It's important to note that by recording the dynamic load time history of key vehicle components under actual road conditions, multi-dimensional, random load data (such as composite conditions like bumps, turns, and braking) in a real environment is obtained. This provides high-fidelity input for fatigue life prediction, structural optimization, and reliability verification. This operation is necessary because laboratory bench tests cannot fully reproduce the random load characteristics of complex road conditions, and fatigue damage to components stems precisely from the accumulation of long-term dynamic loads. Simultaneously, the strain-load relationship established during the calibration phase needs to be validated through real-vehicle testing and adapted to localized design standards for different regional road conditions (such as highways and unpaved roads), ultimately ensuring a closed-loop implementation from laboratory data to product reliability. In short, without real-vehicle load spectra, all calibration and simulation will lose their practical engineering significance.
[0047] Specifically, the vehicle is driven on different road surfaces, and the road load spectrum is acquired by collecting data through the stress-load conversion relationship. The road load spectrum is a time-domain signal.
[0048] By observing the load variation over time using the road load spectrum, peak loads, alternating characteristics, and transient impacts can be identified. The power spectral density of the road load spectrum is obtained through Fast Fourier Transform (FFT), displaying the energy distribution of each frequency component. This is used to analyze the frequency components of the load signal, identify resonance risks, and pinpoint the main excitation sources. Then, fatigue characteristics are obtained from the load time-domain signal and the material's Stress-Number of Cycles to Failure (SN) curves. This provides a basis for component design and verification, improving development efficiency and product reliability. The FFT is a well-known technique and will not be elaborated upon here.
[0049] This concludes the embodiment.
[0050] like Figure 2 As shown, a second aspect of the present invention is to provide a road load spectrum acquisition and calibration system for a dual-sensor system, comprising: Component modification module 101: used to determine the strain gauge corresponding to each component according to the type of load it is subjected to, and to attach it to obtain the stress signal of each component; Configuration module 102: used to obtain timing external load signals by configuring the hydraulic servo system and connecting a standard load sensor in series; Calibration coefficient fitting module 103: used to perform linear fitting between the stress signal and the external load signal of each component to obtain the stress-load conversion line; obtain the calibration coefficient and offset value of each component through the stress-load conversion line; calibrate each component based on the calibration coefficient and offset value of each component, and construct the stress-load conversion relationship; Vehicle Load Spectrum Acquisition and Application Module 104: This module allows the vehicle to travel on different road surfaces and acquires the road load spectrum through stress-load conversion relationships. It then analyzes the load and identifies resonance risks and main excitation sources based on the road load spectrum, providing a basis for the design and verification of components.
[0051] A third aspect of the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a method for acquiring and calibrating a road load spectrum of a dual-sensor system.
[0052] A fourth aspect of the present invention is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for acquiring and calibrating a road load spectrum of a dual-sensor system.
[0053] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, etc.) containing computer-usable program code.
[0054] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, systems, and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0055] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0056] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the present invention.
Claims
1. A method for acquiring and calibrating road load spectrum in a dual-sensor system, characterized in that, include: Based on the type of load on each component, the corresponding strain gauges for each component are determined and attached to obtain the stress signal of each component. By configuring a hydraulic servo system and connecting a standard load sensor in series, the timing of the external load signal can be obtained. By performing linear fitting on the stress signal and external load signal of each component, a stress-load conversion straight line is obtained; The calibration coefficient and offset value of each component are obtained through the stress-load conversion line; each component is calibrated based on its calibration coefficient and offset value, and the stress-load conversion relationship is constructed. The vehicle is driven on different road surfaces, and road load spectra are collected through stress-load conversion relationships to obtain road load spectra. The road load spectra are then used to analyze the loads, identify resonance risks and main excitation sources, and provide a basis for the design and verification of components.
2. The method for road load spectrum acquisition and calibration of a dual-sensor system according to claim 1, characterized in that, The process of determining the strain gauge corresponding to each component based on the type of load it experiences, attaching it, and obtaining the stress value of each component includes: Based on the type of load on each component, the corresponding strain gauge is determined and attached; by assembling the strain gauges into a bridge circuit, each component is transformed into a stress sensor to obtain the stress value of each component.
3. The method for road load spectrum acquisition and calibration of a dual-sensor system according to claim 2, characterized in that, The types of loads applied include tension, compression, bending, shear, and torsion; these load types are obtained through stress analysis of each component of the vehicle.
4. The method for road load spectrum acquisition and calibration of a dual-sensor system according to claim 1, characterized in that, The process of obtaining a stress-load conversion straight line by performing linear fitting on the stress signal and external load signal of each component includes: By performing linear fitting on the stress signal and external load signal of each component using the least squares method, a stress-load conversion straight line is obtained.
5. The method for road load spectrum acquisition and calibration of a dual-sensor system according to claim 1, characterized in that, The calibration coefficient and offset value of each component are obtained through the stress-load conversion straight line. The formula corresponding to the stress-load conversion straight line is specifically expressed as follows: In the formula, Indicates external load, Indicates the calibration coefficient. Indicates the stress value. This represents the bias value.
6. The method for road load spectrum acquisition and calibration of a dual-sensor system according to claim 1, characterized in that, The stress-load conversion relationship is specifically expressed as follows: In the formula, Indicates the transformed load. Indicates the calibration coefficient. Indicates the stress value. This represents the bias value.
7. The method for road load spectrum acquisition and calibration of a dual-sensor system according to claim 1, characterized in that, The analysis and identification of resonance risks and main excitation sources through road load spectrum, and the provision of a basis for component design and verification, include: By observing the load variation over time using the road load spectrum, peak loads, alternating characteristics, and transient impacts can be identified. The power spectral density of the road load spectrum is obtained through fast Fourier transform, displaying the energy distribution of each frequency component. This is used to analyze the frequency components of the load signal, identify resonance risks, and identify the main excitation sources. Then, fatigue characteristics are obtained from the load time-domain signal and the material SN curve. This provides a basis for the design and verification of components.
8. A road load spectrum acquisition and calibration system with dual sensors, characterized in that, include: Component modification module: used to determine the strain gauge corresponding to each component based on the type of load it is subjected to, and then attach it to obtain the stress signal of each component; Configuration module: Used to obtain timing-based external load signals by configuring the hydraulic servo system and connecting a standard load sensor in series; Calibration coefficient fitting module: used to perform linear fitting between the stress signal and the external load signal of each component to obtain the stress-load conversion line; The calibration coefficient and offset value of each component are obtained through the stress-load conversion line; each component is calibrated based on its calibration coefficient and offset value, and the stress-load conversion relationship is constructed. Vehicle Load Spectrum Acquisition and Application Module: This module allows the vehicle to travel on different road surfaces and acquires road load spectra through stress-load conversion relationships. It then analyzes the loads based on the road load spectra, identifies resonance risks and major excitation sources, and provides a basis for the design and verification of components.
9. An electronic device, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the road load spectrum acquisition and calibration method of any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the road load spectrum acquisition and calibration method of any one of claims 1-7.