Method, apparatus, device, and storage medium for obtaining correlation coefficient of powertrain

Abstract

The present application provides a method, equipment, device and storage medium for obtaining the correlation coefficient of a powertrain. The method includes: obtaining a rubber correlation coefficient curve corresponding to a rubber hammerhead according to multiple rubber excitation forces received by the powertrain, multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, a frequency range and a frequency resolution; obtaining a steel correlation coefficient curve corresponding to a steel hammerhead according to multiple steel excitation forces received by the powertrain, multiple steel acceleration data generated by the powertrain corresponding to the multiple steel excitation forces, the frequency range and the frequency resolution; and performing splitting and splicing processing on the rubber correlation coefficient curve and the steel correlation coefficient curve according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve, the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, and the frequency range, so as to obtain a target correlation coefficient curve with good signals.

Description

Technical Field

[0001] This application relates to the technical field of vibration dynamics, and in particular, to a method, equipment, device, and storage medium for obtaining the correlation coefficient of a powertrain. Background Art

[0002] With the growth of the economy and the rapid development of the automotive industry, people's requirements for automobiles are also increasing. While demanding good performance and reliability of automobiles, people also hope that the ride is more comfortable, and the powertrain of an automobile has an important impact on the comfort of the automobile. Conducting modal tests on the powertrain can timely detect performance problems in the powertrain based on the test results and further rectify them, providing an effective guarantee for ensuring the comfort of the automobile.

[0003] Currently, the powertrain modal test includes an excitation part, a vibration pickup part, a data acquisition part, and a spectrum analysis part. Specifically, a pulse hammer is used to excite the powertrain to obtain the pulse force generated by the pulse hammer and the acceleration data response of the powertrain, and the obtained pulse force and acceleration data are processed to obtain the correlation coefficient of the powertrain. After the obtained correlation coefficient is greater than the preset correlation coefficient, the frequency response function of the modal test is obtained based on the pulse force and acceleration data, and then the frequency response function is analyzed to fit and identify the modal parameters of each order of the powertrain, including the natural frequency, vibration mode, damping, etc. of the structure.

[0004] However, under the condition that other conditions are the same, due to the large difference in the correlation coefficients of the powertrain obtained by pulse hammers with different material properties in different frequency bands, it is impossible to obtain a correlation coefficient with good signal in the corresponding frequency band of the powertrain. Summary of the Invention

[0005] This application provides a method, equipment, device, and storage medium for obtaining the correlation coefficient of a powertrain to solve the problem that due to the large difference in the correlation coefficients of the powertrain obtained by pulse hammers with different material properties in different frequency bands, it is impossible to obtain a correlation coefficient with good signal in the corresponding frequency band of the powertrain.

[0006] In a first aspect, an embodiment of this application provides a method for obtaining the correlation coefficient of a powertrain, including:

[0007] When a rubber hammer head strikes the powertrain multiple times, according to multiple rubber excitation forces received by the powertrain, multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, a pre-acquired frequency range, and a frequency resolution, obtain a rubber correlation coefficient curve corresponding to the rubber hammer head;

[0008] When the steel hammer strikes the power assembly multiple times, according to the multiple steel excitation forces received by the power assembly, the multiple steel acceleration data generated by the power assembly corresponding to the multiple steel excitation forces, the pre-acquired frequency range, and the frequency resolution, obtain the steel correlation coefficient curve corresponding to the steel hammer;

[0009] According to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve, the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, and the frequency range, perform splitting and splicing processing on the rubber correlation coefficient curve and the steel correlation coefficient curve to obtain the target correlation coefficient curve.

[0010] In a possible design of the first aspect, the frequency range includes a minimum frequency and a maximum frequency. The step of performing splitting and splicing processing on the rubber correlation coefficient curve and the steel correlation coefficient curve according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve, the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, and the frequency range to obtain the target correlation coefficient curve includes:

[0011] According to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, obtain the target point. The rubber correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the rubber excitation force and the rubber acceleration data corresponding to the rubber excitation force and the frequency. The steel correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the steel excitation force and the steel acceleration data corresponding to the steel excitation force and the frequency;

[0012] According to the minimum frequency and the target point, perform splitting processing on the rubber correlation coefficient curve to obtain a first correlation coefficient curve within a first frequency range, where the first frequency range includes the minimum frequency and the frequency corresponding to the target point;

[0013] According to the maximum frequency and the target point, perform splitting processing on the steel correlation coefficient curve to obtain a second correlation coefficient curve within a second frequency range, where the second frequency range includes the maximum frequency and the frequency corresponding to the target point;

[0014] Perform splicing processing on the first correlation coefficient curve and the second correlation coefficient curve to obtain the target correlation coefficient curve.

[0015] Optionally, the step of obtaining the target point according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve includes:

[0016] Based on the correlation coefficients corresponding to the respective data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the respective data points in the steel correlation coefficient curve, through the formula: Formula: Obtain the cut-off frequency, where r 橡胶 (f) is the correlation coefficient corresponding to the frequency f in the rubber correlation coefficient curve, Δ is the frequency resolution, and r 钢制 (f) is the correlation coefficient corresponding to the frequency f in the steel correlation coefficient curve;

[0017] Determine the data point in the rubber correlation coefficient curve corresponding to the cut-off frequency and the cut-off point with the largest correlation coefficient among the data points in the steel correlation coefficient curve corresponding to the cut-off frequency as the target point.

[0018] Optionally, the obtaining the target point according to the correlation coefficients corresponding to the respective data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the respective data points in the steel correlation coefficient curve includes:

[0019] Obtain the intersection point of the rubber correlation coefficient curve and the steel correlation coefficient curve according to the correlation coefficients corresponding to the respective data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the respective data points in the steel correlation coefficient curve, and determine this intersection point as the target point.

[0020] In another possible design of the first aspect, before the rubber hammer strikes the powertrain multiple times, the method further includes:

[0021] Conduct a pre-test on the powertrain to obtain the frequency range and the frequency resolution.

[0022] In still another possible design of the first aspect, when the rubber hammer strikes the powertrain multiple times, according to the multiple rubber excitation forces received by the powertrain, the multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the previously obtained frequency range and frequency resolution, the obtaining of the rubber correlation coefficient curve corresponding to the rubber hammer includes:

[0023] When the rubber hammer strikes the powertrain multiple times, obtain the initial rubber correlation coefficient curve according to the multiple rubber excitation forces received by the powertrain, the multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the previously obtained frequency range and frequency resolution;

[0024] When the correlation coefficients corresponding to the data points in the initial rubber correlation coefficient curve are all greater than the preset rubber correlation coefficient, the initial rubber correlation coefficient curve is determined as the rubber correlation coefficient curve.

[0025] In a second aspect, an embodiment of the present application provides an acquisition device for the correlation coefficient of a powertrain, including:

[0026] A processing module, configured to obtain the rubber correlation coefficient curve corresponding to the rubber hammer head according to the multiple rubber excitation forces received by the powertrain, the multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the pre-acquired frequency range, and the frequency resolution when the rubber hammer head strikes the powertrain multiple times;

[0027] The processing module is further configured to obtain the steel correlation coefficient curve corresponding to the steel hammer head according to the multiple steel excitation forces received by the powertrain, the multiple steel acceleration data generated by the powertrain corresponding to the multiple steel excitation forces, the pre-acquired frequency range, and the frequency resolution when the steel hammer head strikes the powertrain multiple times;

[0028] The processing module is further configured to perform splitting and splicing processing on the rubber correlation coefficient curve and the steel correlation coefficient curve according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve, the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, and the frequency range to obtain a target correlation coefficient curve.

[0029] In a possible design of the second aspect, the processing module is specifically configured to:

[0030] Obtain a target point according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve. The rubber correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the rubber excitation force and the rubber acceleration data corresponding to the rubber excitation force and the frequency. The steel correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the steel excitation force and the steel acceleration data corresponding to the steel excitation force and the frequency;

[0031] Perform splitting processing on the rubber correlation coefficient curve according to the minimum frequency and the target point to obtain a first correlation coefficient curve within a first frequency range, where the first frequency range includes the minimum frequency and the frequency corresponding to the target point;

[0032] Split the steel correlation coefficient curve according to the maximum frequency and the target point to obtain a second correlation coefficient curve within a second frequency range, where the second frequency range includes the maximum frequency and the frequency corresponding to the target point;

[0033] Perform splicing processing on the first correlation coefficient curve and the second correlation coefficient curve to obtain the target correlation coefficient curve.

[0034] Optionally, the processing module is specifically configured to:

[0035] According to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, through the formula: Formula: Obtain the cut-off frequency, where r 橡胶 (f) is the correlation coefficient corresponding to the frequency f in the rubber correlation coefficient curve, Δf is the frequency resolution, and r 钢制 (f) is the correlation coefficient corresponding to the frequency f in the steel correlation coefficient curve;

[0036] Determine the data point in the rubber correlation coefficient curve corresponding to the cut-off frequency and the cut-off point with the maximum correlation coefficient among the data points in the steel correlation coefficient curve corresponding to the cut-off frequency as the target point.

[0037] Optionally, the processing module is specifically configured to: obtain the intersection point of the rubber correlation coefficient curve and the steel correlation coefficient curve according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, and determine the intersection point as the target point.

[0038] In another possible design of the second aspect, before the rubber hammer strikes the powertrain multiple times, the processing module is further configured to:

[0039] Conduct a pre-test on the powertrain to obtain the frequency range and the frequency resolution.

[0040] In yet another possible design of the second aspect, when the rubber hammer strikes the powertrain multiple times, according to the multiple rubber excitation forces received by the powertrain, the multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the previously obtained frequency range and frequency resolution, obtain the initial rubber correlation coefficient curve;

[0041] When the correlation coefficients corresponding to the data points in the initial rubber correlation coefficient curve are all greater than the preset rubber correlation coefficient, the initial rubber correlation coefficient curve is determined as the rubber correlation coefficient curve.

[0042] In a third aspect, an embodiment of the present application provides an electronic device, including: a processor, a memory, and computer program instructions stored on the memory and executable on the processor. When the processor executes the computer program instructions, it is used to implement the methods provided by the first aspect and various possible designs.

[0043] In a fourth aspect, an embodiment of the present application may provide a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the first aspect and various possible designs.

[0044] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, it is used to implement the methods provided by the first aspect and various possible designs.

[0045] The method, equipment, device, and storage medium for obtaining the correlation coefficient of the powertrain provided by the embodiments of the present application, when the rubber hammer head strikes the powertrain multiple times, according to multiple rubber excitation forces received by the powertrain, multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the pre-acquired frequency range, and the frequency resolution, obtain the rubber correlation coefficient curve corresponding to the rubber hammer head. When the steel hammer head strikes the powertrain multiple times, according to multiple steel excitation forces received by the powertrain, multiple steel acceleration data generated by the powertrain corresponding to the multiple steel excitation forces, the pre-acquired frequency range, and the frequency resolution, obtain the steel correlation coefficient curve corresponding to the steel hammer head. According to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve, the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, the frequency range, perform splitting and splicing processing on the rubber correlation coefficient curve and the steel correlation coefficient curve to obtain the target correlation coefficient curve, where the signal and quality of the correlation coefficient of the target correlation coefficient curve in the frequency band corresponding to the powertrain are good, laying a foundation for subsequent calculation to obtain the frequency response function and modal parameters. Description of the Drawings

[0046] The drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0047] Figure 1 Schematic diagram of the system for obtaining the correlation coefficient of the powertrain provided by the embodiment of the present application;

[0048] Figure 2 It is a schematic flowchart of the first embodiment of the method for obtaining the correlation coefficient of the powertrain provided by the embodiment of the present application;

[0049] Figure 3 It is a schematic flowchart of the second embodiment of the method for obtaining the correlation coefficient of the powertrain provided by the embodiment of the present application;

[0050] Figure 4 It is a schematic flowchart of the third embodiment of the method for obtaining the correlation coefficient of the powertrain provided by the embodiment of the present application;

[0051] Figure 5 It is a schematic structural diagram of the device for obtaining the correlation coefficient of the powertrain provided by the embodiment of the present application;

[0052] Figure 6 It is a schematic structural diagram of the electronic device provided by the embodiment of the present application.

[0053] Through the above-mentioned drawings, the clear embodiments of the present disclosure have been shown, and there will be more detailed descriptions hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of the present disclosure in any way, but to illustrate the concept of the present disclosure to those skilled in the art by referring to specific embodiments. Detailed embodiments

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0055] Before introducing the embodiments of the present application, first, the application background of the embodiments of the present application will be explained:

[0056] With the rapid development of the automotive industry, while cars bring great convenience to people's travel, there are still a large number of vehicle problems, which affect the comfort of people taking cars. As a key component of a car, the powertrain provides continuous power output for the car. During the operation of the powertrain, the dynamic characteristics such as bending and torsional vibrations generated by excitation have an important impact on the noise, vibration, and harshness (NVH) of the car and the ride comfort. Conducting modal tests on the powertrain is the main means to study the powertrain, enabling the timely discovery of performance problems in the powertrain based on the test results and further rectifying them, providing an effective guarantee for the comfort of the car. Good NVH performance and ride comfort performance add luster to the car, making the car more competitive in the market compared to cars of the same level.

[0057] Currently, the modal test of the powertrain includes an excitation part, a vibration pickup part, a data acquisition part, and a spectrum analysis part. Specifically, a pulse hammer is used to excite the powertrain to obtain the pulse force generated by the pulse hammer and the acceleration data response of the powertrain. The obtained pulse force and acceleration data are processed to obtain the correlation coefficient of the powertrain. Among them, the correlation coefficient is the ratio of the maximum energy in the output signal to the total energy in the output signal, which is used to evaluate the measurement quality of the frequency response function. When the obtained correlation coefficient is greater than the preset correlation coefficient, it means that a high-quality frequency response function can be obtained. Then, the frequency response function of the modal test can be obtained based on the pulse force and acceleration data. After that, the frequency response function is analyzed to fit and identify the modal parameters of each order of the powertrain, including the natural frequency, vibration mode, damping, etc. of the structure.

[0058] However, under the condition that other conditions are the same, due to the large difference in the correlation coefficients of the powertrain obtained by pulse hammers with different material properties. For example, the correlation coefficient of the powertrain obtained using a rubber hammer head has good signals in the low-frequency part (30Hz - 100Hz), but poor signals in the mid-frequency part (100Hz - 500Hz) and the high-frequency part (above 500Hz); the correlation coefficient of the powertrain obtained using a steel hammer head has good signals in the mid-frequency and high-frequency parts, but poor signals in the low-frequency part, resulting in the inability to obtain a correlation coefficient with good signals in the corresponding frequency band of the powertrain.

[0059] In view of the above problems, the inventive concept of the present application is as follows: Since the corresponding frequency band of the powertrain usually includes at least two of the low-frequency part, the middle-frequency part, and the high-frequency part, for example, the corresponding frequency band of the powertrain can be the low-frequency part and the middle-frequency part, and the correlation coefficients of the powertrain obtained by impulse hammers with different material properties vary greatly in different frequency bands, resulting in the inability to obtain a good correlation coefficient of the signal within the corresponding frequency band of the powertrain. Based on this, the inventor found that if multiple correlation coefficient curves of impulse hammers with different material properties in the corresponding frequency band of the powertrain can be obtained, and the multiple correlation coefficient curves are split according to the target points (which can also be called cut-off frequency points) determined by each data point in each correlation coefficient curve to obtain multiple sub-correlation coefficient curves, and the sub-correlation coefficient curves with large correlation coefficients in different frequency ranges are spliced to obtain a target correlation coefficient curve with good signal, the problem in the prior art that a good correlation coefficient of the signal cannot be obtained within the corresponding frequency band of the powertrain can be solved.

[0060] Exemplarily, the method for obtaining the correlation coefficient of the powertrain provided in the embodiment of the present application can be applied to Figure 1 the schematic diagram of a system for obtaining the correlation coefficient of the powertrain shown in Figure 1 This is the schematic diagram of the system for obtaining the correlation coefficient of the powertrain provided in the embodiment of the present application, which is used to solve the above technical problems. As Figure 1 shown, the system for obtaining the correlation coefficient of the powertrain may include: a powertrain 11, a vibration sensor 12, a hammer head 13, a force hammer 14, and a terminal device 15.

[0061] Among them, the vibration sensor 12 is connected to the powertrain 11 and is used to obtain the acceleration data generated by the powertrain 11 when the hammer head 13 strikes the powertrain 11.

[0062] In this embodiment, the hammer head 13 is connected to the force hammer 14 and is used to receive the striking instruction sent by the terminal device 15 and strike the powertrain 11.

[0063] Among them, the hammer head 13 may include a rubber hammer head and a steel hammer head.

[0064] Optionally, the terminal device 15 is respectively connected to the force hammer 14 and the vibration sensor 12, and can obtain multiple excitation forces received by the powertrain 11 and the acceleration data generated by the powertrain 11 corresponding to the excitation forces when the hammer head 13 strikes the powertrain 11, and execute the program code of the method for obtaining the correlation coefficient of the powertrain, so as to obtain the target correlation coefficient curve.

[0065] Optionally, the force hammer 14 can be replaced by an exciter.

[0066] Optionally, an excitation force sensor may be provided inside the hammer head 13, or an excitation force sensor may be provided outside the hammer head 13, which can be set according to the actual situation.

[0067] In practical applications, since the server is also a processing device with data processing capabilities, therefore, the Figure 1 terminal device in the above application scenario can also be implemented by the server. In the embodiments of the present application, the server and the terminal device used for data processing can be collectively referred to as electronic devices.

[0068] Next, the technical solution of the present application will be described in detail through specific embodiments.

[0069] It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0070] Figure 2 FIG. 15 is a schematic flowchart of the first embodiment of the method for obtaining the correlation coefficient of the powertrain provided by the embodiment of the present application. As Figure 2 shown, the method for obtaining the correlation coefficient of the powertrain may include the following steps:

[0071] S101: When the rubber hammer head strikes the powertrain multiple times, according to multiple rubber excitation forces received by the powertrain, multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the pre-acquired frequency range, and the frequency resolution, obtain the rubber correlation coefficient curve corresponding to the rubber hammer head.

[0072] In the embodiments of the present application, when the hammer head strikes the powertrain each time, the electronic device may obtain the acceleration data generated by the powertrain through a vibration sensor connected to the powertrain. The electronic device may also obtain the excitation force received by the powertrain through an excitation force sensor provided inside or outside the hammer head.

[0073] Among them, the rubber correlation coefficient can be obtained through the formula: to obtain the rubber correlation coefficient corresponding to the rubber hammer head, where r 2 (f) 橡胶 is the rubber correlation coefficient, G FX (f) is the input-output cross-power spectral density, G FF (f) is the input-output auto-power spectral density, G XX (f) is the auto-spectrum of the response.

[0074] Among them, G FX (f), G FF (f), G XX(f) The specific process can refer to existing methods, and the embodiments of the present application do not specifically limit this.

[0075] Furthermore, according to the calculated rubber correlation coefficient, a rubber correlation coefficient curve can be plotted. Among them, the rubber correlation coefficient curve is used to represent the corresponding relationship between the rubber excitation force and the correlation coefficient between the rubber acceleration data corresponding to the rubber excitation force and the frequency.

[0076] In an implementable implementation manner, when the rubber hammer head strikes the powertrain multiple times, according to multiple rubber excitation forces received by the powertrain, multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the pre-acquired frequency range, and the frequency resolution, an initial rubber correlation coefficient curve is obtained.

[0077] In this implementable manner, further, when the correlation coefficients corresponding to each data point in the initial rubber correlation coefficient curve are all greater than the preset rubber correlation coefficient, the initial rubber correlation coefficient curve is determined as the rubber correlation coefficient curve.

[0078] Exemplarily, the frequency resolution can be 1 Hz, can be 2 Hz, or can also be 3 Hz, the preset rubber correlation coefficient can be 0.7, can be 0.8, or can also be 0.9. The frequency resolution and the rubber correlation coefficient can be determined according to the actual situation, and the embodiments of the present application do not limit this.

[0079] Among them, the maximum value of the correlation coefficient is 1. The higher the correlation coefficient, the better the quality of the frequency response function of the modal test obtained according to the pulse force and the acceleration data subsequently. Generally, it is considered that the quality of the frequency response function of the modal test obtained according to the pulse force and the acceleration data with a correlation coefficient less than 0.7 is poor.

[0080] S102: When the steel hammer head strikes the powertrain multiple times, according to multiple steel excitation forces received by the powertrain, multiple steel acceleration data generated by the powertrain corresponding to the multiple steel excitation forces, the pre-acquired frequency range, and the frequency resolution, a steel correlation coefficient curve corresponding to the steel hammer head is obtained.

[0081] Among them, the formula can be used: To obtain the steel correlation coefficient corresponding to the steel hammer head, where r 2 (f) 钢制 is the rubber correlation coefficient.

[0082] Among them, G FX (f), G FF (f), G XX(f) The specific process can refer to existing methods, and the embodiments of the present application do not specifically limit this.

[0083] Furthermore, according to the calculated steel correlation coefficient, a steel correlation coefficient curve can be plotted. Among them, the steel correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the steel excitation force and the steel acceleration data corresponding to the steel excitation force, and the frequency.

[0084] In an achievable implementation manner, when the steel hammer head strikes the powertrain multiple times, according to the multiple steel excitation forces received by the powertrain, the multiple steel acceleration data generated by the powertrain corresponding to the multiple steel excitation forces, the pre-acquired frequency range, and the frequency resolution, a steel initial correlation coefficient curve is obtained.

[0085] In this achievable manner, further, when the correlation coefficients corresponding to the data points in the steel initial correlation coefficient curve are all greater than the preset steel correlation coefficient, the steel initial correlation coefficient curve is determined as the steel correlation coefficient curve.

[0086] S103: According to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve, the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, and the frequency range, the rubber correlation coefficient curve and the steel correlation coefficient curve are split and spliced to obtain a target correlation coefficient curve.

[0087] Among them, since the correlation coefficient is used to evaluate the measurement quality of the frequency response function, the pulse force and acceleration data with small correlation coefficients cannot be used to obtain a good-quality frequency response function. Therefore, it is necessary to split and splice the rubber correlation coefficient curve and the steel correlation coefficient curve to facilitate obtaining the target correlation coefficient curve. After that, a good-quality frequency response function can be obtained according to the hammer head material, excitation force, and acceleration data corresponding to the target correlation coefficient curve.

[0088] For the specific implementation of this step, reference can be made to the description in the following Figure 3 embodiment shown, which will not be elaborated here.

[0089] The method for obtaining the correlation coefficient of the powertrain provided by the embodiment of the present application obtains the rubber correlation coefficient curve corresponding to the rubber hammer head by, when the rubber hammer head strikes the powertrain multiple times, according to multiple rubber excitation forces received by the powertrain, multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the pre-acquired frequency range, and the frequency resolution. When the steel hammer head strikes the powertrain multiple times, according to multiple steel excitation forces received by the powertrain, multiple steel acceleration data generated by the powertrain corresponding to the multiple steel excitation forces, the pre-acquired frequency range, and the frequency resolution, obtain the steel correlation coefficient curve corresponding to the steel hammer head. According to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve, the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, and the frequency range, perform splitting and splicing processing on the rubber correlation coefficient curve and the steel correlation coefficient curve to obtain the target correlation coefficient curve, where the signal and quality of the correlation coefficient of the target correlation coefficient curve within the frequency band corresponding to the powertrain are good, laying a foundation for subsequent calculation to obtain the frequency response function and modal parameters.

[0090] Based on any of the above embodiments, the frequency range includes the minimum frequency and the maximum frequency. Figure 3 It is a schematic flowchart of the second embodiment of the method for obtaining the correlation coefficient of the powertrain provided by the embodiment of the present application. As Figure 3 shown, S103 can be implemented through the following steps:

[0091] S201: Obtain the target point according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve.

[0092] In a specific implementation manner, according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, through the formula: Formula: Obtain the cut-off frequency, r 橡胶 (f) is the correlation coefficient corresponding to the frequency f in the rubber correlation coefficient curve, Δf is the frequency resolution, r 钢制 (f) is the correlation coefficient corresponding to the frequency f in the steel correlation coefficient curve.

[0093] In this implementation manner, further, the data point in the rubber correlation coefficient curve corresponding to the cut-off frequency and the cut-off point with the largest correlation coefficient among the data points in the steel correlation coefficient curve corresponding to the cut-off frequency are determined as the target point.

[0094] In another specific implementation manner, the intersection point of the rubber correlation coefficient curve and the steel correlation coefficient curve can also be obtained according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, and this intersection point is determined as the target point.

[0095] S202: Split the rubber correlation coefficient curve according to the minimum frequency and the target point to obtain the first correlation coefficient curve within the first frequency range.

[0096] Wherein, the first frequency range includes the minimum frequency and the frequency corresponding to the target point.

[0097] In a possible implementation manner, the rubber correlation coefficient curve is split according to the target point to obtain two sub-rubber correlation coefficient curves. Then, the sub-rubber correlation coefficient curve with the frequency range from the minimum frequency to the target point is determined as the first correlation coefficient curve.

[0098] S203: Split the steel correlation coefficient curve according to the maximum frequency and the target point to obtain the second correlation coefficient curve within the second frequency range.

[0099] Wherein, the second frequency range includes the maximum frequency and the frequency corresponding to the target point.

[0100] In a possible implementation manner, the steel correlation coefficient curve is split according to the target point to obtain two sub-steel correlation coefficient curves. Then, the sub-steel correlation coefficient curve with the frequency range from the target point to the maximum frequency is determined as the second correlation coefficient curve.

[0101] S204: Splice the first correlation coefficient curve and the second correlation coefficient curve to obtain the target correlation coefficient curve.

[0102] In a possible implementation manner, the electronic device can perform linear fitting on the first correlation coefficient curve and the second correlation coefficient curve, and splice the first correlation coefficient curve and the second correlation coefficient curve to obtain the target correlation coefficient curve.

[0103] The method for obtaining the correlation coefficient of the powertrain provided by the embodiment of the present application obtains a target point according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, splits the rubber correlation coefficient curve according to the minimum frequency and the target point to obtain a first correlation coefficient curve within a first frequency range, splits the steel correlation coefficient curve according to the maximum frequency and the target point to obtain a second correlation coefficient curve within a second frequency range, splices the first correlation coefficient curve and the second correlation coefficient curve to obtain a target correlation coefficient curve, and provides a basis for calculating the frequency response function and identifying the modal parameters by obtaining a signal and a target correlation coefficient curve with good quality, thereby providing an analysis basis for the comprehensive identification of the powertrain structure frequency.

[0104] Optionally, in some embodiments, before S101, the method for obtaining the correlation coefficient of the powertrain further includes: performing a pre-test on the powertrain to obtain a frequency range and a frequency resolution. In other words, the frequency-domain signal starts from the minimum frequency of the frequency range and reaches the maximum frequency of the frequency range at intervals of the frequency difference of the frequency resolution.

[0105] Based on any of the above embodiments, Figure 4 is a schematic flowchart of the third embodiment of the method for obtaining the correlation coefficient of the powertrain provided by the embodiment of the present application. As Figure 4 shown, the method for obtaining the correlation coefficient of the powertrain may include the following steps:

[0106] Step 1: Perform a pre-test on the powertrain to obtain a frequency range and a frequency resolution;

[0107] Step 2: When the rubber hammer strikes the powertrain multiple times, obtain a rubber initial correlation coefficient curve according to multiple rubber excitation forces received by the powertrain, multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the frequency range obtained by the pre-test, and the frequency resolution;

[0108] Step 3: Whether the correlation coefficients corresponding to all data points in the rubber initial correlation coefficient curve are greater than a preset rubber correlation coefficient. If the correlation coefficients corresponding to all data points in the rubber initial correlation coefficient curve are greater than the preset rubber correlation coefficient, determine the rubber initial correlation coefficient curve as the rubber correlation coefficient curve and execute Step 4; if there is any data point in the rubber initial correlation coefficient curve whose corresponding correlation coefficient is less than or equal to the preset rubber correlation coefficient, control the rubber hammer to strike the powertrain multiple times again and execute Step 2;

[0109] Step 4: When the steel hammer head strikes the powertrain multiple times, according to multiple steel excitation forces received by the powertrain, multiple steel acceleration data generated by the powertrain corresponding to the multiple steel excitation forces, the pre-tested frequency range, and the frequency resolution, obtain the initial steel correlation coefficient curve;

[0110] Step 5: Whether the correlation coefficients corresponding to the data points in the initial steel correlation coefficient curve are all greater than the preset steel correlation coefficient. If the correlation coefficients corresponding to the data points in the initial steel correlation coefficient curve are all greater than the preset steel correlation coefficient, then determine the initial steel correlation coefficient curve as the steel correlation coefficient curve and execute Step 6; if there is any data point in the initial steel correlation coefficient curve whose corresponding correlation coefficient is less than or equal to the preset steel correlation coefficient, then control the steel hammer head to strike the powertrain multiple times again and execute Step 4;

[0111] Step 6: Perform splitting and splicing processing on the rubber correlation coefficient curve and the steel correlation coefficient curve to obtain the target correlation coefficient curve.

[0112] The following is an apparatus embodiment of the present application, which can be used to execute the method embodiment of the present application. For details not disclosed in the apparatus embodiment of the present application, please refer to the method embodiment of the present application.

[0113] Figure 5 It is a structural schematic diagram of an apparatus for obtaining the correlation coefficient of a powertrain provided in an embodiment of the present application. As Figure 5 shown, the apparatus for obtaining the correlation coefficient of the powertrain includes:

[0114] A processing module 51, configured to, when a rubber hammer head strikes the powertrain multiple times, according to multiple rubber excitation forces received by the powertrain, multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the pre-obtained frequency range, and the frequency resolution, obtain the rubber correlation coefficient curve corresponding to the rubber hammer head;

[0115] The processing module 51 is further configured to, when a steel hammer head strikes the powertrain multiple times, according to multiple steel excitation forces received by the powertrain, multiple steel acceleration data generated by the powertrain corresponding to the multiple steel excitation forces, the pre-obtained frequency range, and the frequency resolution, obtain the steel correlation coefficient curve corresponding to the steel hammer head;

[0116] The processing module 51 is further configured to, according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve, the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, and the frequency range, perform splitting and splicing processing on the rubber correlation coefficient curve and the steel correlation coefficient curve to obtain the target correlation coefficient curve.

[0117] In a possible design of the embodiment of the present application, the processing module 51 is specifically configured to:

[0118] Obtain a target point according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve. The rubber correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the rubber excitation force and the rubber acceleration data corresponding to the rubber excitation force and the frequency. The steel correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the steel excitation force and the steel acceleration data corresponding to the steel excitation force and the frequency;

[0119] Split the rubber correlation coefficient curve according to the minimum frequency and the target point to obtain a first correlation coefficient curve within a first frequency range, where the first frequency range includes the minimum frequency and the frequency corresponding to the target point;

[0120] Split the steel correlation coefficient curve according to the maximum frequency and the target point to obtain a second correlation coefficient curve within a second frequency range, where the second frequency range includes the maximum frequency and the frequency corresponding to the target point;

[0121] Stitch the first correlation coefficient curve and the second correlation coefficient curve to obtain a target correlation coefficient curve.

[0122] Optionally, the processing module 51 is specifically configured to:

[0123] According to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, through the formula: Formula: Obtain the cut-off frequency, r 橡胶 (f) is the correlation coefficient corresponding to the frequency f in the rubber correlation coefficient curve, Δf is the frequency resolution, r 钢制 (f) is the correlation coefficient corresponding to the frequency f in the steel correlation coefficient curve;

[0124] Determine the data point in the rubber correlation coefficient curve corresponding to the cut-off frequency and the cut-off point with the largest correlation coefficient among the data points in the steel correlation coefficient curve corresponding to the cut-off frequency as the target point.

[0125] Optionally, the processing module 51 is specifically configured to: Obtain the intersection point of the rubber correlation coefficient curve and the steel correlation coefficient curve according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, and determine the intersection point as the target point.

[0126] In another possible design of the embodiment of the present application, before the rubber hammer head strikes the powertrain multiple times, the processing module 51 is further configured to:

[0127] Conduct a pre-test on the powertrain to obtain the frequency range and frequency resolution.

[0128] In still another possible design of the embodiment of the present application, when the rubber hammer head strikes the powertrain multiple times, according to the multiple rubber excitation forces received by the powertrain, the multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the previously obtained frequency range and frequency resolution, obtain the initial rubber correlation coefficient curve;

[0129] When the correlation coefficients corresponding to the data points in the initial rubber correlation coefficient curve are all greater than the preset rubber correlation coefficient, then determine the initial rubber correlation coefficient curve as the rubber correlation coefficient curve.

[0130] The device for obtaining the powertrain correlation coefficient provided by the embodiment of the present application can be used to execute the method for obtaining the powertrain correlation coefficient in any of the above embodiments, and its implementation principle and technical effects are similar, which will not be elaborated here.

[0131] It should be noted that it should be understood that the division of each module of the above device is only a logical function division. In actual implementation, it can be fully or partially integrated into a physical entity, or physically separated. And these modules can all be implemented in the form of software called by a processing element; they can also all be implemented in the form of hardware; or some modules can be implemented in the form of software called by a processing element, and some modules can be implemented in the form of hardware. In addition, all or part of these modules can be integrated together or independently implemented. The processing element mentioned here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed by the integrated logic circuit in the processor element or the instruction in the form of software.

[0132] Figure 6 It is a schematic structural diagram of the electronic device provided by the embodiment of the present application. As Figure 6 shown, the electronic device may include: a processor 61, a memory 62, and computer program instructions stored in the memory 62 and executable on the processor 61. When the processor 61 executes the computer program instructions, it implements the method for obtaining the powertrain correlation coefficient provided in any of the foregoing embodiments.

[0133] Optionally, the electronic device may further include an interface for interacting with other devices.

[0134] Optionally, the above-mentioned various components of the electronic device may be connected through a system bus.

[0135] The memory 62 can be a separate storage unit or a storage unit integrated in the processor. The number of processors is one or more.

[0136] It should be understood that the processor 61 can be a Central Processing Unit (CPU), or other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The steps of the method disclosed in this application can be directly implemented by a hardware processor or completed by a combination of hardware and software modules in the processor.

[0137] The system bus can be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The system bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of simplicity, only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus. The memory may include a Random Access Memory (RAM), and may also include a Non-Volatile Memory (NVM), such as at least one disk memory.

[0138] All or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a readable memory. When the program is executed, it performs the steps of the above method embodiments; and the foregoing memory (storage medium) includes: Read-Only Memory (ROM), RAM, flash memory, hard disk, solid state drive, magnetic tape, floppy disk, optical disc, and any combination thereof.

[0139] The electronic device provided in the embodiments of this application can be used to execute the method for obtaining the correlation coefficient of the powertrain provided in any of the above method embodiments. The implementation principle and technical effects are similar and will not be elaborated here.

[0140] An embodiment of the present application provides a computer-readable storage medium storing computer instructions, which, when running on a computer, cause the computer to execute the above-mentioned method for obtaining the correlation coefficient of the powertrain.

[0141] The above-mentioned computer-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory, electrically erasable programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, read-only memory, magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium may be any available medium accessible by a general-purpose or special-purpose computer.

[0142] Optionally, the readable storage medium is coupled to the processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium may also be a component of the processor. The processor and the readable storage medium may be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium may also exist as discrete components in the device.

[0143] An embodiment of the present application further provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium, and when the at least one processor executes the computer program, the above-mentioned method for obtaining the correlation coefficient of the powertrain can be implemented.

[0144] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

Claims

1. A method for obtaining the correlation coefficient of a powertrain, characterized in that, Including: When the rubber hammer head strikes the powertrain multiple times, according to multiple rubber excitation forces received by the powertrain, multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, a pre-acquired frequency range, and a frequency resolution, obtain a rubber correlation coefficient curve corresponding to the rubber hammer head; When the steel hammer head strikes the powertrain multiple times, according to multiple steel excitation forces received by the powertrain, multiple steel acceleration data generated by the powertrain corresponding to the multiple steel excitation forces, the pre-acquired frequency range, and the frequency resolution, obtain a steel correlation coefficient curve corresponding to the steel hammer head, where the frequency range includes a minimum frequency and a maximum frequency; According to the correlation coefficients corresponding to each data point in the rubber correlation coefficient curve and the correlation coefficients corresponding to each data point in the steel correlation coefficient curve, obtain a target point. The rubber correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the rubber excitation force and the rubber acceleration data corresponding to the rubber excitation force and the frequency. The steel correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the steel excitation force and the steel acceleration data corresponding to the steel excitation force and the frequency; According to the minimum frequency and the target point, perform a splitting process on the rubber correlation coefficient curve to obtain a first correlation coefficient curve within a first frequency range, where the first frequency range includes the minimum frequency and the frequency corresponding to the target point; According to the maximum frequency and the target point, perform a splitting process on the steel correlation coefficient curve to obtain a second correlation coefficient curve within a second frequency range, where the second frequency range includes the maximum frequency and the frequency corresponding to the target point; Perform a splicing process on the first correlation coefficient curve and the second correlation coefficient curve to obtain the target correlation coefficient curve; The obtaining the target point according to the correlation coefficients corresponding to each data point in the rubber correlation coefficient curve and the correlation coefficients corresponding to each data point in the steel correlation coefficient curve includes: According to the correlation coefficients corresponding to each data point in the rubber correlation coefficient curve and the steel Determine the truncation point with the largest correlation coefficient among the data points in the rubber correlation coefficient curve corresponding to the truncation frequency and the data points in the steel correlation coefficient curve corresponding to the truncation frequency as the target point.

2. The method according to claim 1, wherein The obtaining the target point according to the correlation coefficients corresponding to each data point in the rubber correlation coefficient curve and the correlation coefficients corresponding to each data point in the steel correlation coefficient curve includes: Obtain the intersection point of the rubber correlation coefficient curve and the steel correlation coefficient curve according to the correlation coefficients corresponding to each data point in the rubber correlation coefficient curve and the correlation coefficients corresponding to each data point in the steel correlation coefficient curve, and determine this intersection point as the target point.

3. The method according to claim 1, characterized in that, Before the rubber hammer head strikes the powertrain multiple times, the method further includes: Perform a pre-test on the powertrain to obtain the frequency range and the frequency resolution.

4. The method according to claim 1, characterized in that, When the rubber hammer head strikes the powertrain multiple times, based on the multiple rubber excitation forces received by the powertrain, the multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the pre-obtained frequency range, and the frequency resolution, obtaining the rubber correlation coefficient curve corresponding to the rubber hammer head includes: When the rubber hammer head strikes the powertrain multiple times, based on the multiple rubber excitation forces received by the powertrain, the multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the pre-obtained frequency range, and the frequency resolution, obtain the initial rubber correlation coefficient curve; When the correlation coefficients corresponding to the data points in the initial rubber correlation coefficient curve are all greater than the preset rubber correlation coefficient, then determine the initial rubber correlation coefficient curve as the rubber correlation coefficient curve.

5. An apparatus for obtaining a correlation coefficient of a powertrain, characterized in that, Includes: A processing module, configured to, when the rubber hammer head strikes the powertrain multiple times, based on the multiple rubber excitation forces received by the powertrain, the multiple rubber acceleration data generated by the powertrain corresponding to the multiple rubber excitation forces, the pre-obtained frequency range, and the frequency resolution, obtain the rubber correlation coefficient curve corresponding to the rubber hammer head; The processing module is further configured to, when the steel hammer head strikes the powertrain multiple times, based on the multiple steel excitation forces received by the powertrain, the multiple steel acceleration data generated by the powertrain corresponding to the multiple steel excitation forces, the pre-obtained frequency range, and the frequency resolution, obtain the steel correlation coefficient curve corresponding to the steel hammer head, where the frequency range includes a minimum frequency and a maximum frequency; The processing module is further configured to obtain a target point according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve. The rubber correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the rubber excitation force and the rubber acceleration data corresponding to the rubber excitation force and the frequency. The steel correlation coefficient curve is used to represent the corresponding relationship between the correlation coefficient between the steel excitation force and the steel acceleration data corresponding to the steel excitation force and the frequency; According to the minimum frequency and the target point, perform a splitting process on the rubber correlation coefficient curve to obtain a first correlation coefficient curve within a first frequency range, where the first frequency range includes the minimum frequency and the frequency corresponding to the target point; According to the maximum frequency and the target point, perform a splitting process on the steel correlation coefficient curve to obtain a second correlation coefficient curve within a second frequency range, where the second frequency range includes the maximum frequency and the frequency corresponding to the target point; Perform a splicing process on the first correlation coefficient curve and the second correlation coefficient curve to obtain the target correlation coefficient curve; The processing module is specifically configured to, according to the correlation coefficients corresponding to the data points in the rubber correlation coefficient curve and the correlation coefficients corresponding to the data points in the steel correlation coefficient curve, pass The correlation coefficient corresponding to the medium frequency of ; Determine the cut-off point with the largest correlation coefficient among the data points in the rubber correlation coefficient curve corresponding to the cut-off frequency and the data points in the steel correlation coefficient curve corresponding to the cut-off frequency as the target point.

6. An electronic device, comprising: A processor, a memory, and computer program instructions stored on the memory and executable on the processor, wherein the processor is configured to implement the method for obtaining the powertrain correlation coefficient according to any one of claims 1 to 4 when executing the computer program instructions.

7. A computer-readable storage medium, characterized in that, Computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by the processor, they are configured to implement the method for obtaining the powertrain correlation coefficient according to any one of claims 1 to 4.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it is configured to implement the method for obtaining the powertrain correlation coefficient according to any one of claims 1 to 4.

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