Device and method for detecting mechanical strength of automobile parts

Abstract

The invention relates to the technical field of automobile part detection, in particular to an automobile part mechanical strength detection device and a detection method thereof. According to the technical scheme, the mechanical strength detection device for the automobile parts comprises a strength detection device body, a functional assembly, a supporting assembly, a clamping assembly, an adjusting assembly, a detection mechanism, a reinforcing assembly, a control assembly, an energy supply assembly and an environment detection assembly, and the functional assembly is arranged on the bottom face of the strength detection device body; a supporting assembly is arranged on the bottom surface of the functional assembly; a clamping assembly is arranged on the surface of the strength detection device main body; according to the invention, all-around and three-dimensional evaluation of the automobile parts under complex working conditions can be realized, the accuracy and reliability of a detection result are remarkably improved, and the actual service working conditions of the automobile parts can be simulated more truly by synchronously collecting and analyzing multi-physical field information, so that the test efficiency is improved. And a more comprehensive and reliable basis is provided for performance evaluation and optimization design of parts.

Description

Technical Field

[0001] This invention relates to the field of automotive parts testing technology, and in particular to an automotive parts mechanical strength testing device and testing method. Background Technology

[0002] Automotive component mechanical strength testing equipment is a device specifically designed to assess the ability of automotive components to resist deformation and damage when subjected to external forces. It is an indispensable part of the automotive manufacturing and quality control process and is of great significance for ensuring the safety and reliability of automobiles.

[0003] Existing mechanical strength testing devices and methods for automotive parts typically rely on a single mechanical testing method, such as tensile, compression, or bending tests. These methods are insufficient to fully reflect the complex multi-physics coupling effects of automotive parts during actual service, leading to discrepancies between test results and actual operating conditions. Consequently, they cannot accurately assess the durability and reliability of the parts.

[0004] Existing mechanical strength testing devices and methods for automotive parts typically rely on single mechanical testing methods, such as tensile, compression, or bending tests. These methods fail to comprehensively reflect the complex multi-physics coupling effects of automotive parts during actual service, leading to discrepancies between test results and actual operating conditions. This results in inaccurate assessments of part durability and reliability. This solution integrates multiple testing technologies, including strain field scanning, acoustic emission localization, infrared thermal imaging, eddy current testing, and X-ray diffraction. It can simultaneously acquire information from multiple physical fields such as force, heat, sound, electricity, and magnetism, constructing a multi-parameter coupled testing model. This enables comprehensive and three-dimensional evaluation of automotive parts under complex operating conditions, significantly improving the accuracy and reliability of test results. By simultaneously acquiring and analyzing multi-physics information, it can more realistically simulate the actual service conditions of automotive parts, revealing potential failure modes that are difficult to detect with single testing methods. This provides a more comprehensive and reliable basis for part performance evaluation and optimized design. Summary of the Invention

[0005] To overcome the limitations of existing mechanical strength testing devices and methods for automotive parts, which typically rely on a single mechanical testing method, such as tensile, compression, or bending tests, it is difficult to fully reflect the complex multi-physics coupling effects of automotive parts during actual service. This leads to discrepancies between the test results and actual working conditions, making it impossible to accurately assess the durability and reliability of the parts.

[0006] The technical solution of the present invention is as follows: a mechanical strength testing device for automotive parts, comprising a strength testing device body, functional components, a support component, a clamping component, an adjustment component, a testing mechanism, a reinforcement component, a control component, a power supply component, and an environmental testing component. The functional components are arranged on the bottom surface of the strength testing device body, the support component is arranged on the bottom surface of the functional components, the clamping component is arranged on the surface of the strength testing device body, the adjustment component is arranged on the top surface of the strength testing device body, the testing mechanism is arranged on one side of the adjustment component, the reinforcement components are arranged at both ends of the testing mechanism, the control component is arranged on one side of the adjustment component, the power supply component is arranged on one side of the support component, and the environmental testing component is arranged on one side of the strength testing device body.

[0007] Preferably, the functional components are used to place the equipment required for mechanical strength testing of automotive parts, the support components are used to support the main body of the strength testing device, the clamping structure is used to clamp and fix the automotive parts to be tested, the adjustment mechanism is used to dynamically adjust the position of the testing mechanism, the testing mechanism is used to test the mechanical strength of the automotive parts, the reinforcement components are used to provide auxiliary support for the testing mechanism, the control components are used to control the overall equipment, the power supply components are used to power and drive the equipment, and the environmental detection components are used to detect the working environment of the equipment.

[0008] A method for testing the mechanical strength of automotive parts includes the following steps:

[0009] S101: Completes calibration operations such as multi-dimensional sensor self-test, hydraulic system pre-loading, and mechanical structure no-load running-in to ensure that the equipment is in the best testing condition;

[0010] S102: Through three-dimensional scanning positioning, multi-point hydraulic clamping and contact surface condition detection, the measured parts are accurately installed and securely fixed.

[0011] S103: Generates a composite load spectrum based on the service conditions of the test component, and achieves accurate planning of dynamic loading paths through multi-axis coupling control and temperature field simulation;

[0012] S104: Integrates multiple detection technologies such as strain field scanning, acoustic emission positioning and infrared thermal imaging to perform coupled detection of multiple physical fields;

[0013] S105: Real-time processing of detection data, feature extraction and damage modeling, and real-time diagnosis and intelligent decision-making through machine learning algorithms;

[0014] S106: Construct multiple safety mechanisms including overload protection, crack containment, and fire suppression to ensure the safety and controllability of the testing process;

[0015] S107: Completes unloading of the tested component, self-cleaning of the equipment, and data archiving, generating a customized test report containing a 3D damage model and life curve;

[0016] S108: Implement preventative maintenance plans, predict the lifespan of critical components, and conduct energy efficiency optimization analysis.

[0017] Preferably, the equipment calibration and parameter initialization before testing include the following steps:

[0018] S201: After the equipment is started, the control component triggers the temperature sensor, pressure sensor, strain gauge and laser displacement sensor to perform self-test, and verifies whether the zero drift value of the sensor is ≤±0.05%FS through the built-in algorithm.

[0019] S202: The power supply component drives the hydraulic pump to gradually increase the pressure to 20MPa at a rate of 5MPa / min, while simultaneously monitoring the rate of hydraulic oil temperature rise. If it exceeds 0.5℃ / min, the cooling circulation subsystem is activated.

[0020] S203: The adjustment component drives the detection mechanism to perform full-stroke reciprocating motion 3 times, records the servo motor current fluctuation curve, and calculates the motion stability coefficient after eliminating abnormal fluctuation points.

[0021] S204: The environmental monitoring component collects current temperature and humidity data, corrects the material's elastic modulus parameters by looking up a table, and simultaneously activates the vibration compensation module to counteract ground vibration interference.

[0022] S205: Use a torque wrench to check the torque of the four locating pins of the clamping assembly to ensure that the actual clamping force deviates from the design value by ≤±2Nm, and record the torque decay curve;

[0023] S206: Verify the phase synchronization of the 16-channel data acquisition card by injecting a standard signal through a pulse signal generator, requiring the time difference between channels to be ≤1μs;

[0024] S207: Simulates an emergency stop signal and detects the linkage response time of safety light curtains, access control switches, and overload protection devices to ensure that the total downtime is ≤80ms;

[0025] S208: Adjust the brightness of the industrial camera's fill light to maintain the illuminance of the detection area at 800±50Lux, and verify the signal-to-noise ratio of the image acquisition system to be ≥40dB using a grayscale card;

[0026] S209: Run the dynamic loading control algorithm, load the preset stepped wave signal for 10 minutes of preheating, and monitor whether the stabilization time of the control loop is ≤3 sampling cycles.

[0027] Preferably, the installation and fixation of the test piece includes the following steps:

[0028] S301: Use a structured light scanner to acquire full-size data of parts, compare it with the CAD model to verify the installation direction, and generate a spatial coordinate offset compensation matrix.

[0029] S302: By projecting crosshairs through a laser alignment instrument and cooperating with the XYZ three-axis platform driven by a servo motor, sub-millimeter-level alignment of the positioning pin and the hole position of the measured part can be achieved;

[0030] S303: It adopts a four-jaw hydraulic clamp, with each jaw equipped with an independent pressure sensor, and applies clamping force in three stages according to a preset torque curve;

[0031] S304: Fiber optic strain gauges are attached to critical stress areas to monitor the initial strain caused by clamping in real time. When the local strain exceeds 0.05%, the clamping sequence is automatically adjusted.

[0032] S305: The contact rate of the clamping surface is detected by an ultrasonic probe, and the effective contact area is required to be ≥85%. Areas with poor contact are marked and pressure is applied again.

[0033] S306: Calculate the expansion amount at the current temperature based on the CTE coefficient of the material under test, and compensate for the stress concentration caused by thermal deformation by adjusting the fine-tuning clamping position of the component.

[0034] S307: Apply molybdenum disulfide lubricant to the surface of the moving pair, use an infrared thermal imager to detect frictional heat generation, and ensure that the temperature rise during the start-up phase is ≤2℃ / min;

[0035] S308: Use a multimeter to verify the continuity between the device under test and the equipment grounding system. The grounding resistance should be ≤0.1Ω to prevent electrostatic discharge from interfering with the test data.

[0036] S309: Install a removable protective cover, and configure a safety light curtain and audible and visual alarm. When a foreign object enters the detection area, the three-level alarm system will be triggered immediately.

[0037] Preferably, dynamic loading path planning includes:

[0038] S401: Based on the service conditions of the test component, a dynamic load spectrum is compiled using the rainflow counting method, which includes composite signals of sine waves, square waves and random vibrations, with a total duration of ≥10^6 cycles;

[0039] S402: The loading rate is dynamically adjusted using a fuzzy control algorithm. The loading rate is kept at a constant speed of 5MPa / s before the yield point, and then reduced to 1MPa / s when the ultimate strength is approached.

[0040] S403: Achieves combined tension-compression-bending-torsion loading through a six-degree-of-freedom motion platform, with the phase difference of each axis controlled within ±2°, and synchronously acquires data from six-component force sensors;

[0041] S404: The detection mechanism integrates an infrared heating array and a liquid nitrogen cooling channel to achieve a temperature gradient loading from -40℃ to 150℃, with the heating / cooling rate adjustable to 10℃ / min;

[0042] S405: A spray system driven by a power supply component generates a 5% NaCl salt spray environment according to ASTM B117 standard, and achieves closed-loop control with the help of a humidity sensor;

[0043] S406: An electromagnetic vibration table is installed on the hydraulic actuator to achieve 0-2000Hz wideband vibration superposition, and the vibration energy distribution is controlled by the power spectral density function;

[0044] S407: Arrange an acoustic emission sensor array in the predicted crack initiation region, set a threshold value of -65dB, and capture microcrack propagation signals in real time.

[0045] S408: Establish a finite element model of the test piece, synchronize real-time detection data to the virtual prototype, and realize dynamic mapping and comparison between stress cloud diagram and physical entity;

[0046] S409: When material hardening is detected, automatically switch to displacement control mode; when softening trend is detected, immediately switch to load control mode.

[0047] Preferably, the multiphysics coupling detection includes the following steps:

[0048] S501: Uses DIC digital image correlation technology to acquire full-size strain fields at a frame rate of 10Hz, with a spatial resolution of 0.1mm, and generates strain gradient thermograms;

[0049] S502: The coordinates of the crack source are determined by a triangulation algorithm using a 16-channel acoustic emission sensor array, with a positioning accuracy of ≤5mm.

[0050] S503: Acquires temperature field data at a rate of 200Hz, establishes a temperature-stress coupling model, and identifies abnormal temperature rise regions;

[0051] S504: Integrating an eddy current sensor into the inspection mechanism, analyzing changes in the material's microstructure through impedance changes, and plotting a defect depth-phase angle curve;

[0052] S505: Acquires dynamic response signals through an accelerometer array and uses frequency domain decomposition to identify natural frequencies and damping ratios at each order.

[0053] S506: Deploy a portable X-ray diffractometer at the critical section to measure the residual stress distribution according to ASTM E915 standard, with a scanning step of 0.5 mm;

[0054] S507: Employs a water immersion focusing probe to perform tomographic scanning at a frequency of 5MHz to generate a three-dimensional reconstruction model of internal defects.

[0055] S508: Synchronously acquire EIS data in a corrosive environment, and analyze corrosion rate and film integrity through equivalent circuit model;

[0056] S509: Input the nine types of detection data into the support vector machine classifier, establish an intensity degradation grading model, and output a probabilistic damage assessment report.

[0057] Preferably, when conducting real-time data analysis and decision-making, the following steps are included:

[0058] S601: Employs wavelet threshold denoising algorithm to filter out high-frequency noise, corrects sensor drift through Kalman filter, and has a data update period of ≤50ms.

[0059] S602: Extract 32 feature indicators from the time domain / frequency domain / time-frequency domain, including peak factor, waveform factor and spectral kurtosis, to construct a high-dimensional feature space;

[0060] S603: A crack propagation rate model was established based on the Paris formula, and the remaining fatigue life was predicted by combining the real-time load spectrum, with a confidence interval of ≤±15%.

[0061] S604: Train an LSTM neural network to identify 5 typical failure modes with a classification accuracy of ≥98%;

[0062] S605: Generates a dynamic dashboard in the control component interface to display equivalent stress, safety factor and life consumption rate parameters in real time;

[0063] S606: The alarm threshold is dynamically adjusted according to the real-time performance degradation of the material. When the remaining lifespan is <20%, the three-level alarm procedure is activated.

[0064] S607: Uses a distributed file system to store raw data, establishes a time-series database to support millisecond-level data playback, and has a storage period of ≥10 years;

[0065] S608: Transmits encrypted data packets to the cloud via 5G network, supports more than 3 experts to annotate diagnoses online at the same time, and has a consultation response time of ≤5 minutes;

[0066] S609: Generates a detection strategy tree based on the Q-learning algorithm, and automatically selects the optimal detection path according to the real-time status, reducing invalid detection time by more than 30%.

[0067] Preferably, the following steps are included when carrying out safety protection and emergency response:

[0068] S701: When the detected load exceeds 110% of the rated value, the hydraulic valve group is completely unloaded within 8ms, and the mechanical limit device is triggered simultaneously for dual protection.

[0069] S702: Before the predicted crack length reaches the critical value, a polymer crack-inhibiting agent is automatically injected and filled at the crack front through a microporous system.

[0070] S703: Deploy perfluorohexanone fire suppression systems in the hydraulic station area to complete area flooding fire suppression within 3 seconds when high temperature or smoke is detected;

[0071] S704: When the safety light curtain is triggered, immediately cut off the main power supply and start the compressed air purging device to remove harmful substances from the detection area;

[0072] S705: Uses RAID6 disk array to achieve redundant data storage and is equipped with UPS power supply to support 30 minutes of emergency power supply;

[0073] S706: Monitors oil cleanliness via an online particulate counter, and automatically starts bypass filtration circulation when the ISO code exceeds 18 / 15;

[0074] S707: Add filters and shielding layers inside the control cabinet to ensure that the equipment can still work normally under an electromagnetic field strength of 10V / m;

[0075] S708: An electrochemical gas sensor is installed in the corrosion detection area, and the forced ventilation system is activated when the Cl2 concentration exceeds 1 ppm.

[0076] S709: Run virtual fault scenarios automatically every month to verify the response logic of the security system and the action sequence of the actuators.

[0077] Preferably, the post-detection processing and report generation include the following steps:

[0078] S801: A graded pressure reduction strategy is adopted, the load is unloaded at a rate of 2MPa / s, and the residual deformation is monitored simultaneously. The deformation rebound rate is ≤5% within 24 hours after unloading.

[0079] S802: Automatically removes metal debris and corrosion products using a six-axis robot, and achieves a dust removal efficiency of 99.97% using an industrial vacuum cleaner with a HEPA filter;

[0080] S803: The clamping assembly returns to the origin according to the preset program, and the repeatability is verified to be ≤0.01mm by a laser interferometer;

[0081] S804: Start the high-pressure water gun and steam cleaning system to deeply clean the hydraulic lines and sensor surfaces, and apply anti-rust oil after drying.

[0082] S805: Automatically calculates the filter replacement cycle based on the hydraulic oil contamination level, manages consumable inventory through RFID tags, and triggers a purchase request when the inventory falls below a safety threshold.

[0083] S806: Generates a digital twin archive according to the VDI 2630 standard, including raw data, analysis reports and video recordings, and stores it on a blockchain anti-tampering platform;

[0084] S807: Select a report template according to customer requirements, and automatically insert 3D damage model, life curve, and test conclusions. Supports Chinese, English, Japanese, and German languages.

[0085] S808: Generates a unique digital fingerprint for each tested component, enabling full lifecycle quality traceability via QR code, with data retention period ≥ 15 years.

[0086] Preferably, equipment maintenance and performance optimization include the following steps:

[0087] S901: Automatically generates maintenance work orders based on equipment runtime, including 32 standard operations;

[0088] S902: By using vibration monitoring and oil analysis, a model of the remaining service life of servo motors, hydraulic pumps, and ball screws is established, with a prediction error of ≤10%.

[0089] S903: Collects power consumption data of power supply components, uses genetic algorithms to optimize hydraulic system parameters, and achieves a 15% reduction in unit detection energy consumption;

[0090] S904: Automatically checks the software update package of the control components every month, and achieves seamless upgrades through dual-machine hot standby, with an upgrade failure rate of <0.01%;

[0091] S905: Establish an IoT-based spare parts management system to monitor inventory in real time through RFID and gravity sensors and automatically generate replenishment lists;

[0092] S906: Uses biometric technology to verify operating permissions, combined with VR training system to assess operating skills, and the validity period of the qualification certificate is synchronized with the equipment upgrade cycle;

[0093] S907: Regularly test the noise, vibration, and waste liquid generated during equipment operation to ensure compliance with the ISO 14000 environmental management system requirements;

[0094] S908: Analyze historical fault data through FTA fault tree analysis to identify the top 3 improvement items and incorporate them into the next year's technical improvement plan.

[0095] The beneficial effects of this invention are:

[0096] 1. Compared to existing mechanical strength testing devices and methods for automotive parts, which typically rely on single mechanical testing methods such as tensile, compression, or bending tests, this approach struggles to comprehensively reflect the complex multi-physics coupling effects of automotive parts during actual service. This leads to discrepancies between test results and actual operating conditions, hindering accurate assessment of part durability and reliability. This solution integrates multiple testing technologies, including strain field scanning, acoustic emission localization, infrared thermal imaging, eddy current testing, and X-ray diffraction. It can simultaneously collect information from multiple physical fields such as force, heat, sound, electricity, and magnetism, constructing a multi-parameter coupled testing model. This enables comprehensive and three-dimensional evaluation of automotive parts under complex operating conditions, significantly improving the accuracy and reliability of test results. By simultaneously collecting and analyzing multi-physics information, it can more realistically simulate the actual service conditions of automotive parts, revealing potential failure modes that are difficult to detect with single testing methods. This provides a more comprehensive and reliable basis for part performance evaluation and optimized design.

[0097] 2. Compared to existing mechanical strength testing devices and methods for automotive parts, which often focus on data acquisition but lack the ability to process, extract features, and analyze data in real time, this solution addresses the issue of low efficiency and missed opportunities for optimal intervention. This is because the system, through real-time data analysis and intelligent decision-making, performs real-time noise reduction, feature extraction, damage modeling, and machine learning diagnosis on the test data. This enables real-time status monitoring, fault warnings, and intelligent decision-making. The system dynamically adjusts testing strategies based on real-time data, optimizes testing paths, reduces ineffective testing time, and significantly improves testing efficiency and intelligence. It automates the entire process from data acquisition to intelligent decision-making, significantly reducing manual intervention and increasing testing efficiency. Furthermore, the machine learning-based intelligent diagnostic function enables real-time fault warnings and predictive maintenance, helping to reduce quality risks and improve production efficiency.

[0098] 3. Compared to existing mechanical strength testing devices and methods for automotive parts, safety protection measures are usually quite basic, limited to overload protection and emergency stop functions. They lack proactive protection and emergency response mechanisms for complex conditions such as crack propagation, fire, and human error, posing certain safety hazards. This solution constructs a multi-layered, comprehensive safety protection and emergency response mechanism, including overload protection, crack containment, fire suppression, personnel protection, and data security. It can monitor abnormal states in real time during the testing process and automatically trigger corresponding safety protection and emergency response procedures, effectively reducing accident risks and ensuring the safety and controllability of the testing process. By constructing a multi-layered safety protection system, the safety risks during the testing process are effectively reduced, ensuring the safety of personnel, equipment, and the tested parts. At the same time, the comprehensive data security mechanism ensures the integrity and traceability of the test data, providing strong support for quality control and accountability. Attached Figure Description

[0099] Figure 1 The diagram shown is a first three-dimensional structural schematic of a mechanical strength testing device for automotive parts according to the present invention.

[0100] Figure 2 The diagram shown is a second three-dimensional structural schematic of a mechanical strength testing device for automotive parts according to the present invention.

[0101] Figure 3 The diagram shown is a three-dimensional structural diagram of the bottom surface of an automotive parts mechanical strength testing device according to the present invention.

[0102] Figure 4 The diagram shows the workflow of a mechanical strength testing method for automotive parts according to the present invention.

[0103] Explanation of reference numerals in the attached drawings: 1. Main body of the strength testing device; 2. Functional component; 3. Support component; 4. Clamping structure; 5. Adjustment mechanism; 6. Testing mechanism; 7. Reinforcing component; 8. Control component; 9. Power supply component; 10. Environmental monitoring component. Detailed Implementation

[0104] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0105] Please see Figure 1-3This invention provides an embodiment of a mechanical strength testing device for automotive parts, comprising a strength testing device body 1, a functional component 2, a support component 3, a clamping component 4, an adjustment component 5, a testing mechanism 6, a reinforcement component 7, a control component 8, a power supply component 9, and an environmental detection component 10. The functional component 2 is disposed on the bottom surface of the strength testing device body 1, the support component 3 is disposed on the bottom surface of the functional component 2, the clamping component 4 is disposed on the surface of the strength testing device body 1, the adjustment component 5 is disposed on the top surface of the strength testing device body 1, the testing mechanism 6 is disposed on one side of the adjustment component 5, the reinforcement component 7 is disposed at both ends of the testing mechanism 6, the control component 8 is disposed on one side of the adjustment component 5, the power supply component 9 is disposed on one side of the support component 3, and the environmental detection component 10 is disposed on one side of the strength testing device body 1.

[0106] The equipment required for mechanical strength testing of automotive parts is placed using functional component 2. The main body 1 of the strength testing device is supported by the support component. The automotive parts to be tested are clamped and fixed by the clamping structure. The position of the testing mechanism 6 is dynamically adjusted by the adjustment mechanism 5. The mechanical strength of the automotive parts is tested by the testing mechanism 6. The testing mechanism 6 is further supported by the reinforcement component 7. The overall equipment is controlled by the control component 8. The equipment is powered by the power supply component 9. The working environment of the equipment is monitored by the environmental monitoring component 10.

[0107] Please see Figure 4 In this embodiment, a method for testing the mechanical strength of automotive parts includes the following steps:

[0108] S101: Completes calibration operations such as multi-dimensional sensor self-test, hydraulic system pre-loading, and mechanical structure no-load running-in to ensure that the equipment is in the best testing condition;

[0109] S102: Through three-dimensional scanning positioning, multi-point hydraulic clamping and contact surface condition detection, the measured parts are accurately installed and securely fixed.

[0110] S103: Generates a composite load spectrum based on the service conditions of the test component, and achieves accurate planning of dynamic loading paths through multi-axis coupling control and temperature field simulation;

[0111] S104: Integrates multiple detection technologies such as strain field scanning, acoustic emission positioning and infrared thermal imaging to perform coupled detection of multiple physical fields;

[0112] S105: Real-time processing of detection data, feature extraction and damage modeling, and real-time diagnosis and intelligent decision-making through machine learning algorithms;

[0113] S106: Construct multiple safety mechanisms including overload protection, crack containment, and fire suppression to ensure the safety and controllability of the testing process;

[0114] S107: Completes unloading of the tested component, self-cleaning of the equipment, and data archiving, generating a customized test report containing a 3D damage model and life curve;

[0115] S108: Implement preventative maintenance plans, predict the lifespan of critical components, and conduct energy efficiency optimization analysis.

[0116] Preferably, the equipment calibration and parameter initialization before testing include the following steps:

[0117] S201: After the equipment is started, the control component 8 triggers the temperature sensor, pressure sensor, strain gauge and laser displacement sensor to perform self-test, and verifies whether the zero drift value of the sensor is ≤ ±0.05%FS through the built-in algorithm.

[0118] S202: Power supply component 9 drives the hydraulic pump to gradually increase the pressure to 20MPa at a rate of 5MPa / min, while simultaneously monitoring the rate of hydraulic oil temperature rise. If it exceeds 0.5℃ / min, the cooling circulation subsystem is started.

[0119] S203: Adjustment component 5 drives detection mechanism 6 to perform full-stroke reciprocating motion 3 times, records the servo motor current fluctuation curve, and calculates the motion stability coefficient after eliminating abnormal fluctuation points.

[0120] S204: Environmental monitoring component 10 collects current temperature and humidity data, corrects the material elastic modulus parameters by looking up a table, and simultaneously starts the vibration compensation module to counteract ground vibration interference.

[0121] S205: Use a torque wrench to check the torque of the four locating pins of the clamping assembly 4 to ensure that the actual clamping force deviates from the design value by ≤±2Nm, and record the torque decay curve;

[0122] S206: Verify the phase synchronization of the 16-channel data acquisition card by injecting a standard signal through a pulse signal generator, requiring the time difference between channels to be ≤1μs;

[0123] S207: Simulates an emergency stop signal and detects the linkage response time of safety light curtains, access control switches, and overload protection devices to ensure that the total downtime is ≤80ms;

[0124] S208: Adjust the brightness of the industrial camera's fill light to maintain the illuminance of the detection area at 800±50Lux, and verify the signal-to-noise ratio of the image acquisition system to be ≥40dB using a grayscale card;

[0125] S209: Run the dynamic loading control algorithm, load the preset stepped wave signal for 10 minutes of preheating, and monitor whether the stabilization time of the control loop is ≤3 sampling cycles.

[0126] Preferably, the installation and fixation of the test piece includes the following steps:

[0127] S301: Use a structured light scanner to acquire full-size data of parts, compare it with the CAD model to verify the installation direction, and generate a spatial coordinate offset compensation matrix.

[0128] S302: By projecting crosshairs through a laser alignment instrument and cooperating with the XYZ three-axis platform driven by a servo motor, sub-millimeter-level alignment of the positioning pin and the hole position of the measured part can be achieved;

[0129] S303: It adopts a four-jaw hydraulic clamp, with each jaw equipped with an independent pressure sensor, and applies clamping force in three stages according to a preset torque curve;

[0130] S304: Fiber optic strain gauges are attached to critical stress areas to monitor the initial strain caused by clamping in real time. When the local strain exceeds 0.05%, the clamping sequence is automatically adjusted.

[0131] S305: The contact rate of the clamping surface is detected by an ultrasonic probe, and the effective contact area is required to be ≥85%. Areas with poor contact are marked and pressure is applied again.

[0132] S306: Calculate the expansion amount at the current temperature based on the CTE coefficient of the material under test, and compensate for the stress concentration caused by thermal deformation by adjusting the clamping position of component 5.

[0133] S307: Apply molybdenum disulfide lubricant to the surface of the moving pair, use an infrared thermal imager to detect frictional heat generation, and ensure that the temperature rise during the start-up phase is ≤2℃ / min;

[0134] S308: Use a multimeter to verify the continuity between the device under test and the equipment grounding system. The grounding resistance should be ≤0.1Ω to prevent electrostatic discharge from interfering with the test data.

[0135] S309: Install a removable protective cover, and configure a safety light curtain and audible and visual alarm. When a foreign object enters the detection area, the three-level alarm system will be triggered immediately.

[0136] Preferably, dynamic loading path planning includes:

[0137] S401: Based on the service conditions of the test component, a dynamic load spectrum is compiled using the rainflow counting method, which includes composite signals of sine waves, square waves and random vibrations, with a total duration of ≥10^6 cycles;

[0138] S402: The loading rate is dynamically adjusted using a fuzzy control algorithm. The loading rate is kept at a constant speed of 5MPa / s before the yield point, and then reduced to 1MPa / s when the ultimate strength is approached.

[0139] S403: Achieves combined tension-compression-bending-torsion loading through a six-degree-of-freedom motion platform, with the phase difference of each axis controlled within ±2°, and synchronously acquires data from six-component force sensors;

[0140] S404: The detection mechanism 6 integrates an infrared heating array and a liquid nitrogen cooling channel to achieve a temperature gradient loading from -40℃ to 150℃, and the heating / cooling rate is adjustable to 10℃ / min;

[0141] S405: A spray system driven by power supply component 9 generates a 5% NaCl salt spray environment according to ASTM B117 standard, and achieves closed-loop control with the help of a humidity sensor;

[0142] S406: An electromagnetic vibration table is installed on the hydraulic actuator to achieve 0-2000Hz wideband vibration superposition, and the vibration energy distribution is controlled by the power spectral density function;

[0143] S407: Arrange an acoustic emission sensor array in the predicted crack initiation region, set a threshold value of -65dB, and capture microcrack propagation signals in real time.

[0144] S408: Establish a finite element model of the test piece, synchronize real-time detection data to the virtual prototype, and realize dynamic mapping and comparison between stress cloud diagram and physical entity;

[0145] S409: When material hardening is detected, automatically switch to displacement control mode; when softening trend is detected, immediately switch to load control mode.

[0146] Preferably, the multiphysics coupling detection includes the following steps:

[0147] S501: Uses DIC digital image correlation technology to acquire full-size strain fields at a frame rate of 10Hz, with a spatial resolution of 0.1mm, and generates strain gradient thermograms;

[0148] S502: The coordinates of the crack source are determined by a triangulation algorithm using a 16-channel acoustic emission sensor array, with a positioning accuracy of ≤5mm.

[0149] S503: Acquires temperature field data at a rate of 200Hz, establishes a temperature-stress coupling model, and identifies abnormal temperature rise regions;

[0150] S504: An eddy current sensor is integrated into the detection mechanism 6 to analyze the changes in the microstructure of the material through impedance changes and to plot the defect depth-phase angle curve.

[0151] S505: Acquires dynamic response signals through an accelerometer array and uses frequency domain decomposition to identify natural frequencies and damping ratios at each order.

[0152] S506: Deploy a portable X-ray diffractometer at the critical section to measure the residual stress distribution according to ASTM E915 standard, with a scanning step of 0.5 mm;

[0153] S507: Employs a water immersion focusing probe to perform tomographic scanning at a frequency of 5MHz to generate a three-dimensional reconstruction model of internal defects.

[0154] S508: Synchronously acquire EIS data in a corrosive environment, and analyze corrosion rate and film integrity through equivalent circuit model;

[0155] S509: Input the nine types of detection data into the support vector machine classifier, establish an intensity degradation grading model, and output a probabilistic damage assessment report.

[0156] Preferably, when conducting real-time data analysis and decision-making, the following steps are included:

[0157] S601: Employs wavelet threshold denoising algorithm to filter out high-frequency noise, corrects sensor drift through Kalman filter, and has a data update period of ≤50ms.

[0158] S602: Extract 32 feature indicators from the time domain / frequency domain / time-frequency domain, including peak factor, waveform factor and spectral kurtosis, to construct a high-dimensional feature space;

[0159] S603: A crack propagation rate model was established based on the Paris formula, and the remaining fatigue life was predicted by combining the real-time load spectrum, with a confidence interval of ≤±15%.

[0160] S604: Train an LSTM neural network to identify 5 typical failure modes with a classification accuracy of ≥98%;

[0161] S605: Generates a dynamic dashboard on the control component 8 interface to display equivalent stress, safety factor and life consumption rate parameters in real time;

[0162] S606: The alarm threshold is dynamically adjusted according to the real-time performance degradation of the material. When the remaining lifespan is <20%, the three-level alarm procedure is activated.

[0163] S607: Uses a distributed file system to store raw data, establishes a time-series database to support millisecond-level data playback, and has a storage period of ≥10 years;

[0164] S608: Transmits encrypted data packets to the cloud via 5G network, supports more than 3 experts to annotate diagnoses online at the same time, and has a consultation response time of ≤5 minutes;

[0165] S609: Generates a detection strategy tree based on the Q-learning algorithm, and automatically selects the optimal detection path according to the real-time status, reducing invalid detection time by more than 30%.

[0166] Preferably, the following steps are included when carrying out safety protection and emergency response:

[0167] S701: When the detected load exceeds 110% of the rated value, the hydraulic valve group is completely unloaded within 8ms, and the mechanical limit device is triggered simultaneously for dual protection.

[0168] S702: Before the predicted crack length reaches the critical value, a polymer crack-inhibiting agent is automatically injected and filled at the crack front through a microporous system.

[0169] S703: Deploy perfluorohexanone fire suppression systems in the hydraulic station area to complete area flooding fire suppression within 3 seconds when high temperature or smoke is detected;

[0170] S704: When the safety light curtain is triggered, immediately cut off the main power supply and start the compressed air purging device to remove harmful substances from the detection area;

[0171] S705: Uses RAID6 disk array to achieve redundant data storage and is equipped with UPS power supply to support 30 minutes of emergency power supply;

[0172] S706: Monitors oil cleanliness via an online particulate counter, and automatically starts bypass filtration circulation when the ISO code exceeds 18 / 15;

[0173] S707: Add filters and shielding layers inside the control cabinet to ensure that the equipment can still work normally under an electromagnetic field strength of 10V / m;

[0174] S708: An electrochemical gas sensor is installed in the corrosion detection area, and the forced ventilation system is activated when the Cl2 concentration exceeds 1 ppm.

[0175] S709: Run virtual fault scenarios automatically every month to verify the response logic of the security system and the action sequence of the actuators.

[0176] Preferably, the post-detection processing and report generation include the following steps:

[0177] S801: A graded pressure reduction strategy is adopted, the load is unloaded at a rate of 2MPa / s, and the residual deformation is monitored simultaneously. The deformation rebound rate is ≤5% within 24 hours after unloading.

[0178] S802: Automatically removes metal debris and corrosion products using a six-axis robot, and achieves a dust removal efficiency of 99.97% using an industrial vacuum cleaner with a HEPA filter;

[0179] S803: Clamping component 4 returns to the origin according to the preset program, and the repeatability accuracy is verified to be ≤0.01mm by a laser interferometer;

[0180] S804: Start the high-pressure water gun and steam cleaning system to deeply clean the hydraulic lines and sensor surfaces, and apply anti-rust oil after drying.

[0181] S805: Automatically calculates the filter replacement cycle based on the hydraulic oil contamination level, manages consumable inventory through RFID tags, and triggers a purchase request when the inventory falls below a safety threshold.

[0182] S806: Generates a digital twin archive according to the VDI 2630 standard, including raw data, analysis reports and video recordings, and stores it on a blockchain anti-tampering platform;

[0183] S807: Select a report template according to customer requirements, and automatically insert 3D damage model, life curve, and test conclusions. Supports Chinese, English, Japanese, and German languages.

[0184] S808: Generates a unique digital fingerprint for each tested component, enabling full lifecycle quality traceability via QR code, with data retention period ≥ 15 years.

[0185] Preferably, equipment maintenance and performance optimization include the following steps:

[0186] S901: Automatically generates maintenance work orders based on equipment runtime, including 32 standard operations;

[0187] S902: By using vibration monitoring and oil analysis, a model of the remaining service life of servo motors, hydraulic pumps, and ball screws is established, with a prediction error of ≤10%.

[0188] S903: Collects power consumption data of power supply component 9, uses genetic algorithm to optimize hydraulic system parameters, and achieves a 15% reduction in unit detection energy consumption;

[0189] S904: Automatically checks the software update package of control component 8 every month, and achieves seamless upgrade through dual-machine hot standby, with an upgrade failure rate of <0.01%;

[0190] S905: Establish an IoT-based spare parts management system to monitor inventory in real time through RFID and gravity sensors and automatically generate replenishment lists;

[0191] S906: Uses biometric technology to verify operating permissions, combined with VR training system to assess operating skills, and the validity period of the qualification certificate is synchronized with the equipment upgrade cycle;

[0192] S907: Regularly test the noise, vibration, and waste liquid generated during equipment operation to ensure compliance with the ISO 14000 environmental management system requirements;

[0193] S908: Analyze historical fault data through FTA fault tree analysis to identify the top 3 improvement items and incorporate them into the next year's technical improvement plan.

[0194] Example 1

[0195] Background: With the increasing demand for lightweight and performance-enhancing automobiles, the requirements for the accuracy and efficiency of mechanical strength testing of automotive parts are becoming increasingly stringent. Traditional testing methods have shortcomings such as limited testing means, low level of intelligence, and insufficient safety protection, making it difficult to meet the comprehensive testing needs under complex working conditions. This embodiment takes the automotive suspension arm as the testing object and adopts the testing device and method of this invention to achieve high-precision and high-efficiency testing under multi-physical field coupling conditions.

[0196] Implementation steps:

[0197] S1001: Start the device. Control component 8 triggers a self-test of the multi-dimensional sensor to verify the sensor accuracy.

[0198] S1002: Power supply component 9 drives the hydraulic system to preload, and adjustment component 5 performs no-load running-in to ensure the stability of the mechanical structure;

[0199] S1003: Environmental monitoring component 10 collects environmental parameters and corrects the monitoring model;

[0200] S1004: Use a structured light scanner to obtain full-size data of the suspension arm, compare it with the CAD model, and generate an installation compensation matrix;

[0201] S1005: Achieves sub-millimeter alignment of the swing arm hole position through a laser alignment instrument and a three-axis platform;

[0202] S1006: Employs a four-jaw hydraulic clamp that applies clamping force in stages, monitors and adjusts the clamping sequence in real time to ensure secure fixation;

[0203] S1007: Based on the service conditions of the suspension arm, a composite load spectrum including sine waves and random vibrations is compiled.

[0204] S1008: Employs a fuzzy control algorithm to dynamically adjust the loading rate and achieves multi-axis coupled loading through a six-degree-of-freedom motion platform;

[0205] S1009: Integrates temperature field simulation and salt spray environment control to simulate the multi-physics field coupling effect under actual working conditions;

[0206] S1010: Uses DIC technology to collect full-size strain fields and combines acoustic emission sensor arrays to locate crack sources;

[0207] S1011: Analyze the temperature-stress coupling effect and changes in material microstructure through infrared thermal imaging and eddy current detection;

[0208] S1012: Integrates X-ray diffraction and ultrasonic testing to assess residual stress and internal defects;

[0209] S1013: Perform real-time denoising, feature extraction, and damage modeling on the detection data;

[0210] S1014: Train an LSTM neural network to identify failure modes and generate a dynamic dashboard to display key parameters;

[0211] S1015: Dynamically adjust the alarm threshold based on the material performance degradation to trigger a three-level alarm procedure;

[0212] S1016: Construct a multi-layered safety mechanism including overload protection, crack containment, and fire suppression;

[0213] S1017: When an abnormal state is detected, the safety protection and emergency handling procedures are automatically triggered to ensure that the detection process is safe and controllable;

[0214] S1018: The load is unloaded using a graded pressure reduction strategy, and debris in the detection area is automatically removed by a six-axis robot;

[0215] S1019: Generates customized inspection reports containing 3D damage models and life curves, supporting multi-language output;

[0216] S1020: Generates a unique digital fingerprint for the tested component, enabling full lifecycle quality traceability;

[0217] S1021: Automatically generate maintenance work orders based on equipment runtime and implement preventive maintenance plans;

[0218] S1022: Predict the remaining service life of key components through vibration monitoring and oil analysis;

[0219] S1023: Collects power consumption data, optimizes hydraulic system parameters, and reduces detection energy consumption.

[0220] Data comparison table:

[0221]

[0222] In summary, this embodiment achieves high-precision and high-efficiency testing of automotive suspension arms by applying the mechanical strength testing device and method of this patented invention. Compared with existing technologies, this solution demonstrates significant advantages in testing accuracy, fault diagnosis accuracy, multi-physics field coupling testing capability, real-time data analysis and decision-making capability, safety protection and emergency handling mechanisms, testing efficiency, equipment failure rate, and maintenance costs. This solution not only improves the accuracy and reliability of testing results but also significantly improves testing efficiency and reduces quality risks and maintenance costs through intelligent and automated testing processes, providing strong support for the quality control and optimized design of automotive components.

[0223] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A device for testing the mechanical strength of automotive parts; characterized in that: The device includes a strength testing device body (1), a functional component (2), a support component (3), a clamping component (4), an adjustment component (5), a testing mechanism (6), a reinforcement component (7), a control component (8), a power supply component (9), and an environmental detection component (10). The functional component (2) is provided on the bottom surface of the strength testing device body (1), the support component (3) is provided on the bottom surface of the functional component (2), the clamping component (4) is provided on the surface of the strength testing device body (1), the adjustment component (5) is provided on the top surface of the strength testing device body (1), the testing mechanism (6) is provided on one side of the adjustment component (5), the reinforcement component (7) is provided at both ends of the testing mechanism (6), the control component (8) is provided on one side of the adjustment component (5), the power supply component (9) is provided on one side of the support component (3), and the environmental detection component (10) is provided on one side of the strength testing device body (1).

2. A method for testing the mechanical strength of automotive parts, characterized in that: It includes the following steps: S101: Completes calibration operations such as multi-dimensional sensor self-test, hydraulic system pre-loading, and mechanical structure no-load running-in to ensure that the equipment is in the best testing condition; S102: Through three-dimensional scanning positioning, multi-point hydraulic clamping and contact surface condition detection, the measured parts are accurately installed and securely fixed. S103: Generates a composite load spectrum based on the service conditions of the test component, and achieves accurate planning of dynamic loading paths through multi-axis coupling control and temperature field simulation; S104: Integrates multiple detection technologies such as strain field scanning, acoustic emission positioning and infrared thermal imaging to perform coupled detection of multiple physical fields; S105: Real-time processing of detection data, feature extraction and damage modeling, and real-time diagnosis and intelligent decision-making through machine learning algorithms; S106: Construct multiple safety mechanisms including overload protection, crack containment, and fire suppression to ensure the safety and controllability of the testing process; S107: Completes unloading of the tested component, self-cleaning of the equipment, and data archiving, generating a customized test report containing a 3D damage model and life curve; S108: Implement preventative maintenance plans, predict the lifespan of critical components, and conduct energy efficiency optimization analysis.

3. The method for testing the mechanical strength of automotive parts according to claim 2, characterized in that: The equipment calibration and parameter initialization before testing include the following steps: S201: After the equipment is started, the control component (8) triggers the temperature sensor, pressure sensor, strain gauge and laser displacement sensor to perform self-test, and verifies whether the zero drift value of the sensor is ≤ ±0.05%FS through the built-in algorithm. S202: The power supply component (9) drives the hydraulic pump to gradually increase the pressure to 20MPa at a rate of 5MPa / min, and monitors the hydraulic oil temperature rise rate at the same time. If it exceeds 0.5℃ / min, the cooling circulation subsystem is started. S203: The adjustment component (5) drives the detection mechanism (6) to perform a full-stroke reciprocating motion 3 times, records the servo motor current fluctuation curve, and calculates the motion stability coefficient after eliminating abnormal fluctuation points; S204: The environmental monitoring component (10) collects current temperature and humidity data, corrects the material elastic modulus parameters by looking up a table, and simultaneously starts the vibration compensation module to counteract ground vibration interference. S205: Use a torque wrench to check the torque of the four locating pins of the clamping assembly (4) to ensure that the actual clamping force deviates from the design value by ≤±2Nm, and record the torque decay curve; S206: Verify the phase synchronization of the 16-channel data acquisition card by injecting a standard signal through a pulse signal generator, requiring the time difference between channels to be ≤1μs; S207: Simulates an emergency stop signal and detects the linkage response time of safety light curtains, access control switches, and overload protection devices to ensure that the total downtime is ≤80ms; S208: Adjust the brightness of the industrial camera's fill light to maintain the illuminance of the detection area at 800±50Lux, and verify the signal-to-noise ratio of the image acquisition system to be ≥40dB using a grayscale card; S209: Run the dynamic loading control algorithm, load the preset stepped wave signal for 10 minutes of preheating, and monitor whether the stabilization time of the control loop is ≤3 sampling cycles.

4. The method for testing the mechanical strength of automotive parts according to claim 2, characterized in that: The following steps are included when installing and fixing the test piece: S301: Use a structured light scanner to acquire full-size data of parts, compare it with the CAD model to verify the installation direction, and generate a spatial coordinate offset compensation matrix. S302: By projecting crosshairs through a laser alignment instrument and cooperating with the XYZ three-axis platform driven by a servo motor, sub-millimeter-level alignment of the positioning pin and the hole position of the measured part can be achieved; S303: It adopts a four-jaw hydraulic clamp, with each jaw equipped with an independent pressure sensor, and applies clamping force in three stages according to a preset torque curve; S304: Fiber optic strain gauges are attached to critical stress areas to monitor the initial strain caused by clamping in real time. When the local strain exceeds 0.05%, the clamping sequence is automatically adjusted. S305: The contact rate of the clamping surface is detected by an ultrasonic probe, and the effective contact area is required to be ≥85%. Areas with poor contact are marked and pressure is applied again. S306: Calculate the expansion amount at the current temperature based on the CTE coefficient of the material under test, and compensate for the stress concentration caused by thermal deformation by adjusting the clamping position of component (5); S307: Apply molybdenum disulfide lubricant to the surface of the moving pair, use an infrared thermal imager to detect frictional heat generation, and ensure that the temperature rise during the start-up phase is ≤2℃ / min; S308: Use a multimeter to verify the continuity between the device under test and the equipment grounding system. The grounding resistance should be ≤0.1Ω to prevent electrostatic discharge from interfering with the test data. S309: Install a removable protective cover, and configure a safety light curtain and audible and visual alarm. When a foreign object enters the detection area, the three-level alarm system will be triggered immediately.

5. The method for testing the mechanical strength of automotive parts according to claim 2, characterized in that: When performing dynamic loading path planning, the following are included: S401: Based on the service conditions of the test component, a dynamic load spectrum is compiled using the rainflow counting method, which includes composite signals of sine waves, square waves and random vibrations, with a total duration of ≥10^6 cycles; S402: The loading rate is dynamically adjusted using a fuzzy control algorithm. The loading rate is kept at a constant speed of 5MPa / s before the yield point, and then reduced to 1MPa / s when the ultimate strength is approached. S403: Achieves combined tension-compression-bending-torsion loading through a six-degree-of-freedom motion platform, with the phase difference of each axis controlled within ±2°, and synchronously acquires data from six-component force sensors; S404: The infrared heating array and liquid nitrogen cooling channel are integrated in the detection mechanism (6) to achieve temperature gradient loading from -40℃ to 150℃, and the heating / cooling rate can be adjusted to 10℃ / min; S405: A spray system driven by a power supply component (9) generates a 5% NaCl salt spray environment according to ASTM B117 standard, and achieves closed-loop control with a humidity sensor; S406: An electromagnetic vibration table is installed on the hydraulic actuator to achieve 0-2000Hz wideband vibration superposition, and the vibration energy distribution is controlled by the power spectral density function; S407: Arrange an acoustic emission sensor array in the predicted crack initiation region, set a threshold value of -65dB, and capture microcrack propagation signals in real time. S408: Establish a finite element model of the test piece, synchronize real-time detection data to the virtual prototype, and realize dynamic mapping and comparison between stress cloud diagram and physical entity; S409: When material hardening is detected, automatically switch to displacement control mode; when softening trend is detected, immediately switch to load control mode.

6. The method for testing the mechanical strength of automotive parts according to claim 2, characterized in that: The following steps are included in multiphysics coupling detection: S501: Uses DIC digital image correlation technology to acquire full-size strain fields at a frame rate of 10Hz, with a spatial resolution of 0.1mm, and generates strain gradient thermograms; S502: The coordinates of the crack source are determined by a triangulation algorithm using a 16-channel acoustic emission sensor array, with a positioning accuracy of ≤5mm. S503: Acquires temperature field data at a rate of 200Hz, establishes a temperature-stress coupling model, and identifies abnormal temperature rise regions; S504: Integrate an eddy current sensor into the detection mechanism (6) to analyze the changes in the microstructure of the material through impedance changes and plot the defect depth-phase angle curve; S505: Acquires dynamic response signals through an accelerometer array and uses frequency domain decomposition to identify natural frequencies and damping ratios at each order. S506: Deploy a portable X-ray diffractometer at the critical section to measure the residual stress distribution according to ASTM E915 standard, with a scanning step of 0.5 mm; S507: Employs a water immersion focusing probe to perform tomographic scanning at a frequency of 5MHz to generate a three-dimensional reconstruction model of internal defects. S508: Synchronously acquire EIS data in a corrosive environment, and analyze corrosion rate and film integrity through equivalent circuit model; S509: Input the nine types of detection data into the support vector machine classifier, establish an intensity degradation grading model, and output a probabilistic damage assessment report.

7. The method for testing the mechanical strength of automotive parts according to claim 2, characterized in that: When conducting real-time data analysis and decision-making, the following steps are included: S601: Employs wavelet threshold denoising algorithm to filter out high-frequency noise, corrects sensor drift through Kalman filter, and has a data update period of ≤50ms. S602: Extract 32 feature indicators from the time domain / frequency domain / time-frequency domain, including peak factor, waveform factor and spectral kurtosis, to construct a high-dimensional feature space; S603: A crack propagation rate model was established based on the Paris formula, and the remaining fatigue life was predicted by combining the real-time load spectrum, with a confidence interval of ≤±15%. S604: Train an LSTM neural network to identify 5 typical failure modes with a classification accuracy of ≥98%; S605: Generate a dynamic instrument panel on the interface of the control component (8) to display the equivalent stress, safety factor and life consumption rate parameters in real time; S606: The alarm threshold is dynamically adjusted according to the real-time performance degradation of the material. When the remaining lifespan is <20%, the three-level alarm procedure is activated. S607: Uses a distributed file system to store raw data, establishes a time-series database to support millisecond-level data playback, and has a storage period of ≥10 years; S608: Transmits encrypted data packets to the cloud via 5G network, supports more than 3 experts to annotate diagnoses online at the same time, and has a consultation response time of ≤5 minutes; S609: Generates a detection strategy tree based on the Q-learning algorithm, and automatically selects the optimal detection path according to the real-time status, reducing invalid detection time by more than 30%.

8. The method for testing the mechanical strength of automotive parts according to claim 2, characterized in that: When carrying out safety protection and emergency response, the following steps are included: S701: When the detected load exceeds 110% of the rated value, the hydraulic valve group is completely unloaded within 8ms, and the mechanical limit device is triggered simultaneously for dual protection. S702: Before the predicted crack length reaches the critical value, a polymer crack-inhibiting agent is automatically injected and filled at the crack front through a microporous system. S703: Deploy perfluorohexanone fire suppression systems in the hydraulic station area to complete area flooding fire suppression within 3 seconds when high temperature or smoke is detected; S704: When the safety light curtain is triggered, immediately cut off the main power supply and start the compressed air purging device to remove harmful substances from the detection area; S705: Uses RAID6 disk array to achieve redundant data storage and is equipped with UPS power supply to support 30 minutes of emergency power supply; S706: Monitors oil cleanliness via an online particulate counter, and automatically starts bypass filtration circulation when the ISO code exceeds 18 / 15; S707: Add filters and shielding layers inside the control cabinet to ensure that the equipment can still work normally under an electromagnetic field strength of 10V / m; S708: An electrochemical gas sensor is installed in the corrosion detection area, and the forced ventilation system is activated when the Cl2 concentration exceeds 1 ppm. S709: Run virtual fault scenarios automatically every month to verify the response logic of the security system and the action sequence of the actuators.

9. The method for testing the mechanical strength of automotive parts according to claim 2, characterized in that: The post-detection processing and report generation process includes the following steps: S801: A graded pressure reduction strategy is adopted, the load is unloaded at a rate of 2MPa / s, and the residual deformation is monitored simultaneously. The deformation rebound rate is ≤5% within 24 hours after unloading. S802: Automatically removes metal debris and corrosion products using a six-axis robot, and achieves a dust removal efficiency of 99.97% using an industrial vacuum cleaner with a HEPA filter; S803: The clamping assembly (4) returns to the origin according to the preset program, and the repeatability accuracy is verified to be ≤0.01mm by the laser interferometer; S804: Start the high-pressure water gun and steam cleaning system to deeply clean the hydraulic lines and sensor surfaces, and apply anti-rust oil after drying. S805: Automatically calculates the filter replacement cycle based on the hydraulic oil contamination level, manages consumable inventory through RFID tags, and triggers a purchase request when the inventory falls below a safety threshold. S806: Generates a digital twin archive according to the VDI 2630 standard, including raw data, analysis reports and video recordings, and stores it on a blockchain anti-tampering platform; S807: Select a report template according to customer requirements, and automatically insert 3D damage model, life curve, and test conclusions. Supports Chinese, English, Japanese, and German languages. S808: Generates a unique digital fingerprint for each tested component, enabling full lifecycle quality traceability via QR code, with data retention period ≥ 15 years.

10. A method for testing the mechanical strength of automotive parts according to claim 2, characterized in that: When performing equipment maintenance and performance optimization, the following steps are included: S901: Automatically generates maintenance work orders based on equipment runtime, including 32 standard operations; S902: By using vibration monitoring and oil analysis, a model of the remaining service life of servo motors, hydraulic pumps, and ball screws is established, with a prediction error of ≤10%. S903: Collect the power consumption data of the power supply component (9), use the genetic algorithm to optimize the hydraulic system parameters, and achieve a 15% reduction in unit detection energy consumption; S904: The software update package of the control component (8) is automatically checked every month, and the upgrade is achieved seamlessly through dual-machine hot standby, with an upgrade failure rate of <0.01%; S905: Establish an IoT-based spare parts management system to monitor inventory in real time through RFID and gravity sensors and automatically generate replenishment lists; S906: Uses biometric technology to verify operating permissions, combined with VR training system to assess operating skills, and the validity period of the qualification certificate is synchronized with the equipment upgrade cycle; S907: Regularly test the noise, vibration, and waste liquid generated during equipment operation to ensure compliance with the ISO 14000 environmental management system requirements; S908: Analyze historical fault data through FTA fault tree analysis to identify the top 3 improvement items and incorporate them into the next year's technical improvement plan.

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