Hybrid transmission shell bearing capacity detection method and system

Abstract

The application discloses a kind of hybrid transmission shell bearing capacity detection method and system, it is related to performance detection field.The method is applied to performance detection system, the method includes: in the state of no load of shell, along preset path, transmit ultrasonic test signal, and receive first response signal;The starting point of preset path of shell is applied with preset micro-prestress;In the state that shell is in preset micro-stress application, along preset path, transmit ultrasonic test signal, and receive second response signal;The signal correlation coefficient of first response signal and second response signal is calculated;If signal correlation coefficient is greater than or equal to preset first threshold value, then determine the bearing capacity of shell is qualified.The technical scheme provided in the application is implemented, solve the problem that current hybrid transmission shell bearing capacity nondestructive testing reliability is low.

Description

Technical Field

[0001] This application relates to the technical field of performance testing, specifically to a method and system for testing the load-bearing capacity of a hybrid transmission housing. Background Technology

[0002] As a core component of new energy vehicles, the performance and reliability of hybrid transmissions directly affect the vehicle's power, economy, and safety. The transmission housing, as its fundamental load-bearing component, not only supports the weight of all internal components such as gears, shafts, and clutches, but also must withstand the complex alternating loads, impact torques, and severe vibrations generated by the dual power sources of the engine and electric motor. Therefore, the load-bearing capacity qualification test of the housing before it leaves the factory is particularly important.

[0003] Currently, there are two types of load-bearing capacity tests for hybrid transmissions. One is the static crush test, which uses a large hydraulic testing machine to apply an increasing static load to the housing until it yields or fails, and records the maximum load-bearing capacity. The other is the ultrasonic non-destructive testing method, which uses the principle that ultrasonic waves will be reflected, refracted, or attenuated when they encounter defects in the material to detect defects. Based on the severity of the defects, it is indirectly determined whether the housing's load-bearing capacity is up to standard.

[0004] While static crush testing is intuitive, it is a destructive test and can only be used for sampling inspection. It cannot be performed on every shell that leaves the factory, and there is a risk of missed detection. Although ultrasonic non-destructive testing overcomes the drawbacks of destructive testing, it cannot detect hidden defects such as uneven distribution of residual stress, which seriously affects the long-term load-bearing fatigue performance of the shell. This can lead to premature failure of the shell under alternating loads after installation, causing faults such as abnormal noises and shifting jerks.

[0005] Therefore, there is an urgent need for a highly reliable method for testing the load-bearing capacity of hybrid transmission housings. Summary of the Invention

[0006] To address the issue of low reliability in non-destructive testing of the load-bearing capacity of hybrid transmission housings, this application provides a method and system for testing the load-bearing capacity of hybrid transmission housings.

[0007] In a first aspect, this application provides a method for testing the load-bearing capacity of a hybrid transmission housing, applied in a performance testing system, the method comprising:

[0008] When the housing is unloaded, an ultrasonic test signal is emitted along a preset path, and a first response signal is received.

[0009] A preset micro-prestress is applied to the preset path starting point of the shell;

[0010] When the housing is under the preset micro-stress applied state, the ultrasonic test signal is emitted along the preset path, and a second response signal is received;

[0011] Calculate the signal correlation coefficient between the first response signal and the second response signal;

[0012] If the signal correlation coefficient is greater than or equal to a preset first threshold, then the load-bearing capacity of the shell is determined to be qualified.

[0013] Optionally, before emitting the ultrasonic test signal along a preset path in a no-load state of the housing, the process specifically includes:

[0014] The shell was scanned in three dimensions to obtain a three-dimensional model of the shell;

[0015] Curvature analysis was performed on the three-dimensional model of the shell to obtain a curvature gradient model;

[0016] Identify the maximum curvature gradient feature line of the curvature gradient model;

[0017] The model point with the largest curvature gradient in the maximum curvature gradient feature line is taken as the starting point of the preset path, and the endpoint of the maximum curvature gradient feature line that is farthest from the model point with the largest curvature gradient is taken as the ending point of the preset path.

[0018] Optionally, the step of emitting ultrasonic test signals along a preset path when the housing is unloaded further includes:

[0019] Finite element analysis is performed on the maximum curvature gradient feature line to obtain the principal stress vector field of the maximum curvature gradient feature line. The maximum curvature gradient feature line contains the curvature gradient of multiple continuous model points. Each model point corresponds to a principal stress vector. The principal stress vectors of multiple model points constitute the principal stress vector field.

[0020] The weights of the multiple model points are determined based on the curvature gradients of the multiple model points.

[0021] Based on the weights of the multiple model points, the principal stress vectors of the multiple model points are weighted and averaged to obtain the characterization vector of the principal stress vector field;

[0022] The direction of the characterization vector is taken as the emission direction of the ultrasonic test signal.

[0023] Optionally, the step of using the vector direction of the characterization vector as the emission direction of the ultrasonic test signal further includes:

[0024] Calculate the principal stress consistency coefficient of the principal stress vector field;

[0025] If the principal stress consistency coefficient of the principal stress vector field is greater than or equal to a preset consistency coefficient threshold, then the direction in which the vector direction of the characterizing vector deviates from the preset angle is taken as the transmission direction of the ultrasonic test signal.

[0026] Optionally, before applying a preset micro-stress to the preset path starting point of the housing, the process specifically includes:

[0027] Time-frequency analysis was performed on the first response signal to obtain the dispersion curve;

[0028] Obtain the dispersion curve of a standard qualified shell;

[0029] Calculate the similarity between the dispersion curve of the first response signal and the dispersion curve of the standard qualified shell;

[0030] Based on the curve similarity, the preset micro-stress is adjusted to serve as the micro-stress applied subsequently.

[0031] Optionally, calculating the signal correlation coefficient between the first response signal and the second response signal specifically includes:

[0032] Extract the amplitude of the second harmonic component of the first response signal and the amplitude of the second harmonic component of the second response signal;

[0033] Obtain the amplitude of the fundamental frequency component of the first response signal and the amplitude of the fundamental frequency component of the second response signal;

[0034] The nonlinear response coefficient of the housing is calculated based on the amplitude of the second harmonic component and the amplitude of the fundamental frequency component of the first response signal and the amplitude of the second harmonic component and the amplitude of the fundamental frequency component of the second response signal.

[0035] Determine whether the nonlinear response coefficient is less than or equal to a preset second threshold;

[0036] If so, then the phase spectrum of the first response signal and the second response signal is extracted in a first frequency range, where the first frequency range is the low-frequency band near the center frequency of the ultrasonic test signal;

[0037] Calculate the first cross-correlation coefficient between the phase spectrum of the first response signal in the first frequency range and the phase spectrum of the second response signal in the first frequency range;

[0038] The first cross-correlation coefficient is used as the signal correlation coefficient between the first response signal and the second response signal.

[0039] Optionally, determining whether the nonlinear response coefficient is greater than or equal to a preset second threshold further includes:

[0040] If not, then extract the phase spectrum of the first response signal and the second response signal in a second frequency range, where the second frequency range is the high-frequency band that is significantly equal to the center frequency of the ultrasonic test signal;

[0041] Calculate the second cross-correlation coefficient between the phase spectrum of the first response signal in the second frequency range and the phase spectrum of the second response signal in the second frequency range;

[0042] The second cross-correlation coefficient is used as the signal correlation coefficient between the first response signal and the second response signal.

[0043] Secondly, this application provides a hybrid transmission housing load-bearing capacity testing system, which is a performance testing system. The performance testing system includes an acquisition and testing module and a processing module, wherein:

[0044] The testing module is used to transmit an ultrasonic test signal along a preset path and receive a first response signal when the housing is unloaded; apply a preset micro-stress to the starting point of the preset path of the housing; and transmit the ultrasonic test signal along the preset path and receive a second response signal when the housing is under the preset micro-stress applied state.

[0045] The processing module is used to calculate the signal correlation coefficient between the first response signal and the second response signal; if the signal correlation coefficient is greater than or equal to a preset first threshold, then the load-bearing capacity of the shell is determined to be qualified.

[0046] Thirdly, this application provides an electronic device including a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any one of the first aspects.

[0047] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed, perform the method described in any one of the first aspects.

[0048] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0049] This application employs ultrasonic testing signals to measure the first and second response signals of the hybrid transmission housing before and after the application of micro-stress. When internal stress defects exist within the housing, the applied micro-stress alters the morphology of the defects, thereby changing the propagation path and phase characteristics of the ultrasonic test signal within the housing, resulting in a significant distortion of the second response signal relative to the first response signal. Conversely, a structurally intact housing with adequate load-bearing capacity undergoes only uniform deformation within its elastic range, exhibiting a linear change in its structural characteristics, thus resulting in highly similar response signals. Based on this principle, the signal correlation coefficient between the first and second response signals is calculated to determine whether the load-bearing capacity of the hybrid transmission housing is up to standard. During this process, the latent defects of uneven residual stress distribution within the housing are revealed under the influence of micro-stress, thereby improving the reliability of load-bearing capacity testing of the hybrid transmission housing without disassembly or damage. Attached Figure Description

[0050] Figure 1 This is a schematic flowchart of a method for detecting the load-bearing capacity of a hybrid transmission housing provided in an embodiment of this application.

[0051] Figure 2 This is a schematic diagram of the structure of a hybrid transmission housing load-bearing capacity detection system provided in an embodiment of this application.

[0052] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0053] Explanation of reference numerals in the attached diagram: 1. Test module; 2. Processing module; 300. Electronic device; 301. Processor; 302. Communication bus; 303. User interface; 304. Network interface; 305. Memory. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0055] During the production of hybrid transmission housings, process defects such as insufficient casting cooling time or excessive heat treatment time can lead to uneven distribution of residual stress inside the housing. This phenomenon does not cause significant changes in the internal structure of the housing, so direct structural inspection of the housing cannot detect this defect. If the housing is then assembled on a vehicle, it will be subjected to various torque impacts during vehicle operation, causing the residual stress to be released and the internal structure of the housing to deform. This reduces the fatigue life of the housing and can lead to abnormal noises, shift jerking, and other malfunctions.

[0056] To address the aforementioned issues, this application provides a method for testing the load-bearing capacity of the hybrid transmission housing before it leaves the factory. This method is applied to a performance testing system, such as... Figure 1 As shown, the method includes steps S101 to S105, which are as follows:

[0057] S101. Under no-load conditions on the housing, an ultrasonic test signal is emitted along a preset path, and a first response signal is received.

[0058] In the above steps, the chaotic gearbox housing to be tested is fixed to the testing fixture using a special clamp. After its posture stabilizes, the ultrasonic transmitting probe is moved to the starting point of a preset path, and the ultrasonic receiving probe is moved to the ending point of the preset path. Then, the ultrasonic transmitter and receiver are activated, and the transmitting probe emits an ultrasonic test signal from the starting point of the preset path. After penetrating the housing material, the signal is received by the receiving probe located at the ending point of the preset path. Finally, the received raw signal is amplified, filtered, and converted from digital to analog before preprocessing to obtain the first response signal.

[0059] In one implementation, the hybrid transmission housing has a complex structure, and the mechanical properties of complex structures often exhibit strong anisotropy, greatly increasing the probability of uneven residual stress distribution. Therefore, when setting the preset path, it is necessary to ensure that the preset path can directly guide the ultrasonic test signal to the complex structure prone to uneven residual stress distribution, thereby improving the reliability of the housing load-bearing capacity test results. Specifically:

[0060] First, a 3D line laser scanner is used to perform a full-range scan of the hybrid transmission housing to be inspected. Then, a 3D model of the housing is generated through point cloud stitching, denoising, and surface reconstruction algorithms. This model contains the geometric shape information of the housing surface. Next, based on the 3D point cloud data of the housing model, the Gaussian curvature value of each point on the housing surface is calculated to generate a curvature field distribution cloud map of the entire housing. Then, the rate of change of each model point in the curvature field distribution cloud map in space is calculated to generate a corresponding curvature gradient model. In this model, regions with higher curvature gradient values ​​indicate more complex geometry and a greater likelihood of uneven residual stress distribution. Therefore, this application further identifies the set of points with high and continuously distributed curvature gradient values ​​in the curvature gradient model, thereby obtaining the maximum curvature gradient feature line. The maximum curvature gradient feature line passes through various complex structures on the hybrid transmission housing, improving the comprehensiveness of the inspection results. Furthermore, when applying a preset micro-stress detection second response signal, the superposition effect of ultrasonic test signals in the defect can be utilized to amplify the defect, thereby improving the accuracy of the inspection results.

[0061] Finally, all model points on the maximum curvature gradient feature line are traversed, and the model point with the largest curvature gradient value is found. This point is set as the starting point of the preset path. Then, the endpoint on the maximum curvature gradient feature line that is farthest from the starting point of the preset path is set as the ending point of the preset path. This improves the initial sensitivity of the ultrasonic test signal to the defect and further amplifies the influence of the defect on the ultrasonic test signal.

[0062] In one implementation, although a preset path can guide the propagation path of the ultrasonic test signal, the complex structure along the maximum curvature gradient characteristic line results in a complex and variable stress state. Therefore, when setting the emission direction of the ultrasonic test signal, it is necessary to match the emission direction with the complex stress state of the preset path to comprehensively capture the nonlinear response of the material. Specifically:

[0063] The three-dimensional model of the hybrid transmission housing is input into the finite element analysis model. The finite element analysis model simulates the stress state of the hybrid transmission housing under typical working conditions and performs static solutions to obtain three mutually perpendicular stress components at each model point on the three-dimensional housing model. Then, the stress component with the largest absolute value among the three mutually perpendicular stress components at each model point is taken as the principal stress vector of that model point. Then, the principal stress vectors of multiple model points corresponding to the maximum curvature gradient feature line are extracted and jointly constructed to form the principal stress vector field.

[0064] Then, the curvature gradient of each model point on the maximum curvature gradient characteristic line is analyzed. It can be understood that the larger the curvature gradient of a model point, the more significant its stress concentration effect and the more prominent its nonlinear response of the material. Therefore, the principal stress vector of this model point should be the focus. To this end, this application normalizes the curvature gradient of each model point on the maximum curvature gradient characteristic line to obtain the weight of each model point on the maximum curvature gradient characteristic line. Then, the weight of each model point on the maximum curvature gradient characteristic line is multiplied by its corresponding principal stress vector and averaged to obtain the characterization vector that can characterize the entire principal stress vector field. Finally, the vector direction of the characterization vector of the principal stress vector field is used as the transmission direction of the ultrasonic test signal, thereby ensuring that the ultrasonic wave propagation direction is consistent with the average force flow direction with a large mechanical weight on the maximum curvature gradient characteristic line. This comprehensively captures the nonlinear response of key model points and improves the accuracy and reliability of load-bearing capacity assessment.

[0065] In one implementation, when setting the transmission direction of the ultrasonic test signal, if the vector directions of the principal stress vectors at various model points on the maximum curvature gradient feature line are mostly similar, then the obtained characterization vector is also basically consistent with the principal stress vectors at each model point. In this case, if the transmission direction of the ultrasonic test signal follows the current characterization vector direction, the propagation path of the ultrasonic test signal will highly coincide with the principal stress vector directions at each model point, thus failing to effectively capture the nonlinear response of the material on the maximum curvature gradient feature line. Therefore, this application, after obtaining the characterization vector, also calculates the principal stress consistency coefficient of the principal stress vector field. Specifically, it first sets the transmission direction of the ultrasonic test signal according to the current characterization vector direction, which will lead to the propagation path of the ultrasonic test signal being highly coincident with the principal stress vector directions at each model point, thus failing to effectively capture the nonlinear response of the material on the maximum curvature gradient feature line. The principal stress vector at each model point is converted into a unit vector. Then, multiple unit vectors are summed to obtain a sum vector. Finally, the magnitude of the sum vector is divided by the number of unit vectors to obtain the average vector magnitude. This average vector magnitude is the principal stress consistency coefficient. It should be noted that if all unit vectors point in the same direction, the sum of the vectors will result in a sum vector with a very large magnitude. In the ideal case, the magnitude of the sum vector is equal to the sum of the magnitudes of all unit vectors, that is, the principal stress consistency coefficient is 1. If the vector directions of all unit vectors are completely random, the vectors will cancel each other out. In the extreme case, the magnitude of the sum vector will be equal to 0, that is, the principal stress consistency coefficient is 0. Finally, if the principal stress consistency coefficient of the principal stress vector field is greater than or equal to the preset consistency coefficient threshold, it means that the vector directions of the principal stress vectors at each model point on the maximum curvature gradient feature line are mostly similar. At this time, the direction of the ultrasonic test signal is taken as the direction of the ultrasonic test signal that deviates from the vector direction of the characterization vector by a preset angle. The preset angle is a random value within a preset angle range (preferably 30 degrees to 50 degrees), so that the ultrasonic test signal can effectively interact with the microstructure and thus effectively capture the nonlinear response characteristics of the material.

[0066] S102. Apply a preset micro-stress to the preset path starting point of the shell.

[0067] In the above steps, after the measurement of the first response signal is completed, a micro-stress release command is sent to the force-controlled loading stage. The micro-stress release command includes information such as the release position and the magnitude of the force release. At this time, the force-controlled loading stage applies a preset micro-stress at the preset path starting point of the shell according to the micro-stress release command. Under the influence of the preset micro-stress, the shape of the internal defect structure of the shell is changed. Especially for structures with internal stress defects, the structural changes are more obvious because the internal stress is released.

[0068] In one embodiment, when setting the micro-stress, it is necessary to both reduce the degree of damage to the workpiece and improve the reliability of the detection results. Therefore, this application obtains a dispersion curve by performing time-frequency analysis on the first response signal. The dispersion curve is a curve showing the change in the propagation speed of ultrasound at different frequencies. Under unloaded conditions, the dispersion curve can reflect the severity of micro-defects in the shell. If the severity of micro-defects in the shell is high, it indicates that there are already a large number of micro-cracks or holes inside. In this case, the applied micro-stress is smaller to prevent serious damage to the workpiece. If the severity of micro-defects in the shell is low, it indicates that its internal structure is intact. In this case, the applied micro-stress is larger, thereby amplifying extremely small structural defects. Specifically:

[0069] Obtain the dispersion curve of a standard qualified shell, and then calculate the curve similarity between the dispersion curve of the first response signal and the dispersion curve of the standard qualified shell. Specifically, cosine similarity can be used for calculation. If the curve similarity is high, it indicates that the defect degree of the current internal structure of the shell is relatively minor, and vice versa. At this time, based on the defect degree of the current internal structure of the shell, the curve similarity is multiplied by a preset micro-stress, which is used as the micro-stress for the current shell test, thereby reducing the degree of damage to the workpiece and improving the reliability of the test results.

[0070] S103. When the shell is under a preset micro-stress applied state, an ultrasonic test signal is emitted along a preset path, and a second response signal is received.

[0071] S104. Calculate the signal correlation coefficient between the first response signal and the second response signal.

[0072] In steps S103 to S104 above, when the housing is under a preset micro-stress applied state, the ultrasonic receiver receives the original signal at the end of the preset path. At this time, the received original signal is also subjected to preprocessing operations such as amplification, filtering, and digital-to-analog conversion to obtain the second response signal.

[0073] Then, the amplitude of the second harmonic component of the first response signal and the amplitude of the second harmonic component of the second response signal are extracted. It should be noted that when ultrasound propagates in a nonlinear material, the propagation of the wave will be distorted due to the defects in the microstructure of the material. This distortion can be decomposed into the sum of waves of different frequencies. The second harmonic component is a component that is twice the fundamental frequency. Compared with the fundamental frequency component and higher frequency components, it can reflect the nonlinear response of micro-defects and is significantly different from environmental noise. Therefore, the second harmonic component can be used to characterize the severity of micro-defects in the shell in this application, i.e., the amplitude of the second harmonic component.

[0074] Next, the fundamental frequency component amplitudes of the first and second response signals are obtained. It should be noted that the fundamental frequency component can be understood as the center frequency component of the ultrasonic wave. Normally, the fundamental frequency components of the first and second response signals are the same. However, when the shell is subjected to a preset micro-stress, its internal structure changes. This alters the material's ability to reflect and scatter ultrasonic waves, resulting in a slight shift in the measured fundamental frequency component. Since the internal stress defects within the shell are micro-defects, this application calculates a first ratio of the fundamental frequency component amplitude of the first response signal to that of the second response signal, and a second ratio of the fundamental frequency component amplitude of the first response signal. The first ratio represents the relative change of the fundamental frequency component due to applied stress, reflecting the linear response of the material. The second ratio represents the relative change of the second harmonic component due to applied stress, reflecting the nonlinear response of the material. The second ratio is then compared with the first ratio again to obtain the nonlinear response coefficient of the shell. It should be noted that for a qualified shell, after applying micro-stress, the nonlinear response and linear response of its internal structure change proportionally. For a shell with defects, applying micro-stress will greatly excite the nonlinear effect of the internal structure, causing the second ratio to change faster than the first ratio. The more severe the defect, the greater the difference in the rate of change between the first and second ratios. Therefore, this application uses the nonlinear response coefficient of the shell as a measure of the degree of microscopic damage within the material.

[0075] In one implementation, the actual hybrid transmission housing inspection environment often contains a large amount of vibration noise, which causes the amplitude of the detected ultrasonic signal to deviate, leading to misjudgment or missed detection. Therefore, this application utilizes the characteristic that phase information is insensitive to amplitude changes, and uses the cross-correlation coefficient of the phase spectrum as the final evaluation index, thereby effectively eliminating the interference caused by amplitude fluctuations and significantly improving the stability and reliability of the detection results. Specifically:

[0076] The nonlinear response coefficient of the shell is then compared with a preset second threshold. If the nonlinear response coefficient of the shell is less than or equal to the preset second threshold, it indicates that there are few microscopic defects in the shell. In this case, the focus is mainly on detecting the macroscopic elastic deformation of the shell. Macroscopic elastic deformation mainly causes a linear change in wave velocity, which is mainly manifested in the low-frequency phase spectrum. Therefore, this application first extracts the phase spectrum of the first response signal in the first frequency range and the phase spectrum of the second response signal in the first frequency range. The first frequency range is the frequency band near the center frequency of the ultrasonic wave, i.e., the low-frequency band, which is preferably [-0.5f, 1.5f], where f is the center frequency of the ultrasonic wave. Then, the first cross-correlation coefficient between the phase spectrum of the first response signal in the first frequency range and the phase spectrum of the second response signal in the first frequency range is calculated. Specifically, the following formula can be used:

[0077]

[0078] Where R is the cross-correlation coefficient. Let i be the phase value at the i-th frequency point of the phase spectrum of the first response signal within the first frequency range. Let i be the phase value at the i-th frequency point of the phase spectrum of the second response signal within the first frequency range. The first response signal is the average phase value of all frequency points in the phase spectrum of the first frequency range. The average value of the phase values ​​at all frequency points in the phase spectrum of the second response signal within the first frequency range.

[0079] The above formula uses the Pearson correlation coefficient calculation principle to calculate the first cross-correlation coefficient between the phase spectrum of the first response signal and the phase spectrum of the second response signal within the first frequency range. This coefficient is then used as the signal correlation coefficient between the first and second response signals. The higher the signal correlation coefficient, the more prominent the linear response of the shell, thus indicating that the shell is healthier.

[0080] If the nonlinear response coefficient of the shell is greater than the preset second threshold, it indicates that there are many microscopic defects in the shell. In this case, the focus should be on detecting the microscopic damage structure of the shell. The microscopic damage structure mainly causes nonlinear distortion of the waveform, which is mainly manifested in the high-frequency phase spectrum. Therefore, this application first extracts the phase spectrum of the first response signal in the second frequency range and the phase spectrum of the second response signal in the second frequency range. The second frequency range is a frequency band that is significantly higher than the center frequency of the ultrasonic wave, i.e., the high-frequency band. This application preferably selects the frequency band where the second harmonic component is located, i.e., [1.5f, 2.5f], where f is the center frequency of the ultrasonic wave. Then, the second cross-correlation coefficient of the phase spectrum of the first response signal in the second frequency range and the phase spectrum of the second response signal in the second frequency range are calculated. This is used as the signal correlation coefficient between the first response signal and the second response signal. The specific calculation method still adopts the calculation principle of Pearson correlation coefficient. The second cross-correlation coefficient of the phase spectrum of the first response signal and the phase spectrum of the second response signal in the first frequency range is calculated. It will not be elaborated further here. It should be noted that the effect of microscopic defects on ultrasound is non-linear. It generates new frequency components and distorts the original waveform. If the second cross-correlation coefficient is very small, it indicates that the microscopic damage to the shell is relatively severe.

[0081] S105. If the signal correlation coefficient is greater than or equal to the preset first threshold, then the load-bearing capacity of the shell is determined to be qualified.

[0082] In the above steps, if the signal correlation coefficient is greater than or equal to the preset first threshold, it indicates that the shell has neither macroscopic elastic deformation defects nor microscopic structural damage defects. Therefore, it can be determined that the shell's load-bearing capacity is qualified and can withstand alternating loads, thereby reducing the occurrence of faults such as abnormal noises and shifting jerks. Conversely, if the correlation coefficient is not greater than or equal to the preset first threshold, it is determined that the shell's load-bearing capacity is unqualified and remanufacturing is required to ensure that the load-bearing capacity of the shell is qualified before leaving the factory.

[0083] Reference Figure 2 This application also provides a hybrid transmission housing load-bearing capacity testing system. The system is a performance testing system, comprising a test acquisition module 1 and a processing module 2, wherein:

[0084] Test module 1 is used to transmit ultrasonic test signals along a preset path and receive a first response signal when the shell is unloaded; apply a preset micro-stress to the starting point of the preset path of the shell; and transmit ultrasonic test signals along the preset path and receive a second response signal when the shell is under the preset micro-stress applied state.

[0085] Processing module 2 is used to calculate the signal correlation coefficient between the first response signal and the second response signal; if the signal correlation coefficient is greater than or equal to a preset first threshold, the bearing capacity of the shell is determined to be qualified.

[0086] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0087] This application also discloses an electronic device. (See reference...) Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0088] The communication bus 302 is used to enable communication between these components.

[0089] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0090] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0091] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 305, and by calling data stored in memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0092] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. (Refer to...) Figure 3 The memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a method of detecting the load-bearing capacity of a hybrid transmission housing.

[0093] exist Figure 3In the illustrated electronic device 300, the user interface 303 is mainly used to provide an input interface for the user and acquire user input data; while the processor 301 can be used to call an application program stored in the memory 305 for detecting the load-bearing capacity of a hybrid transmission housing. When executed by one or more processors 301, the electronic device 300 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0094] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0095] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0096] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0097] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0098] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0099] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0100] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for testing the load-bearing capacity of a hybrid transmission housing, characterized in that, The method, applied in a performance testing system, includes: When the housing is unloaded, an ultrasonic test signal is emitted along a preset path, and a first response signal is received. A preset micro-stress is applied to the preset path starting point of the housing; When the housing is under the preset micro-stress applied state, the ultrasonic test signal is emitted along the preset path, and a second response signal is received; Calculate the signal correlation coefficient between the first response signal and the second response signal; If the signal correlation coefficient is greater than or equal to a preset first threshold, then the load-bearing capacity of the shell is determined to be qualified. Before emitting the ultrasonic test signal along a preset path under unloaded conditions of the housing, the process specifically includes: The shell was scanned in three dimensions to obtain a three-dimensional model of the shell; Curvature analysis was performed on the three-dimensional model of the shell to obtain a curvature gradient model; Identify the maximum curvature gradient feature line of the curvature gradient model; The model point with the largest curvature gradient in the maximum curvature gradient feature line is taken as the starting point of the preset path, and the endpoint of the maximum curvature gradient feature line that is farthest from the model point with the largest curvature gradient is taken as the ending point of the preset path.

2. The method according to claim 1, characterized in that, The step of transmitting ultrasonic test signals along a preset path when the casing is unloaded specifically includes: Finite element analysis is performed on the maximum curvature gradient feature line to obtain the principal stress vector field of the maximum curvature gradient feature line. The maximum curvature gradient feature line contains the curvature gradient of multiple continuous model points. Each model point corresponds to a principal stress vector. The principal stress vectors of multiple model points constitute the principal stress vector field. The weights of the multiple model points are determined based on the curvature gradients of the multiple model points. Based on the weights of the multiple model points, the principal stress vectors of the multiple model points are weighted and averaged to obtain the characterization vector of the principal stress vector field; The direction of the characterization vector is taken as the emission direction of the ultrasonic test signal.

3. The method according to claim 2, characterized in that, The step of using the vector direction of the characterization vector as the emission direction of the ultrasonic test signal further includes: Calculate the principal stress consistency coefficient of the principal stress vector field; If the principal stress consistency coefficient of the principal stress vector field is greater than or equal to a preset consistency coefficient threshold, then the direction in which the vector direction of the characterizing vector deviates from the preset angle is taken as the transmission direction of the ultrasonic test signal.

4. The method according to claim 1, characterized in that, Before applying a preset micro-stress to the preset path starting point of the shell, the specific steps include: Time-frequency analysis was performed on the first response signal to obtain the dispersion curve; Obtain the dispersion curve of a standard qualified shell; Calculate the similarity between the dispersion curve of the first response signal and the dispersion curve of the standard qualified shell; Based on the curve similarity, the preset micro-stress is adjusted to serve as the micro-stress applied subsequently.

5. The method according to claim 1, characterized in that, The calculation of the signal correlation coefficient between the first response signal and the second response signal specifically includes: Extract the amplitude of the second harmonic component of the first response signal and the amplitude of the second harmonic component of the second response signal; Obtain the amplitude of the fundamental frequency component of the first response signal and the amplitude of the fundamental frequency component of the second response signal; The nonlinear response coefficient of the housing is calculated based on the amplitude of the second harmonic component and the amplitude of the fundamental frequency component of the first response signal and the amplitude of the second harmonic component and the amplitude of the fundamental frequency component of the second response signal. Determine whether the nonlinear response coefficient is less than or equal to a preset second threshold; If so, then extract the phase spectrum of the first response signal and the second response signal in a first frequency range, where the first frequency range is the low-frequency band near the center frequency of the ultrasonic test signal; Calculate the first cross-correlation coefficient between the phase spectrum of the first response signal in the first frequency range and the phase spectrum of the second response signal in the first frequency range; The first cross-correlation coefficient is used as the signal correlation coefficient between the first response signal and the second response signal.

6. The method according to claim 5, characterized in that, The step of determining whether the nonlinear response coefficient is less than or equal to a preset second threshold further includes: If not, then extract the phase spectrum of the first response signal and the second response signal in a second frequency range, where the second frequency range is a high-frequency band that is significantly higher than the center frequency of the ultrasonic test signal; Calculate the second cross-correlation coefficient between the phase spectrum of the first response signal in the second frequency range and the phase spectrum of the second response signal in the second frequency range; The second cross-correlation coefficient is used as the signal correlation coefficient between the first response signal and the second response signal.

7. A hybrid transmission housing load-bearing capacity testing system, characterized in that, The system is used to execute a method for testing the housing load-bearing capacity of a hybrid transmission as described in any one of claims 1-6. The system is a performance testing system, comprising an acquisition and testing module (1) and a processing module (2), wherein: The test module (1) is used to transmit an ultrasonic test signal along a preset path and receive a first response signal when the housing is unloaded; apply a preset micro-stress to the starting point of the preset path of the housing; and transmit the ultrasonic test signal along the preset path and receive a second response signal when the housing is under the preset micro-stress applied state. The processing module (2) is used to calculate the signal correlation coefficient between the first response signal and the second response signal; if the signal correlation coefficient is greater than or equal to a preset first threshold, then the bearing capacity of the shell is determined to be qualified.

8. An electronic device, characterized in that, The device includes a processor (301), a memory (305), a user interface (303), and a network interface (304). The memory (305) is used to store instructions. The user interface (303) and the network interface (304) are used to communicate with other devices. The processor (301) is used to execute the instructions stored in the memory (305) to cause the electronic device (300) to perform the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the method as described in any one of claims 1 to 6.

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