Drive axle sound power level detection method, device, computer equipment and storage medium

Abstract

The present application relates to a method, device, computer equipment, storage medium and computer program product for detecting the sound power level of a drive axle. The method includes: obtaining historical operation data of a measured drive axle of the same model as the drive axle to be detected, where the historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle; obtaining the correlation coefficient between the vibration acceleration of each vibration test point and the sound power level, and determining the target vibration test point according to the correlation coefficient; determining a fitting function according to the vibration acceleration and sound power level of the target vibration test point; and detecting the sound power level of the drive axle to be detected according to the fitting function. By accumulating historical data, the calculation formula and the best test position of the sound power level are determined, so that the sound power level can be directly calculated during the off-line detection of the drive axle, reducing the number of sensors used, shortening the test detection time, and improving the efficiency of the off-line detection of the drive axle.

Description

Technical Field

[0001] The present application relates to the technical field of NVH detection, and particularly to a method, device, computer device, storage medium and computer program product for detecting the sound power level of a drive axle. Background Art

[0002] NVH is the English abbreviation of Noise, Vibration, and Harshness. It is a comprehensive issue for measuring the manufacturing quality of automobiles, and it gives the most direct and obvious feeling to automobile users. The NVH problems of vehicles are one of the concerns of major vehicle manufacturing enterprises and parts enterprises in the international automotive industry. Statistical data shows that about 1 / 3 of the vehicle failure problems are related to the NVH problems of vehicles, and nearly 20% of the R & D expenses of major companies are consumed in solving the NVH problems of vehicles.

[0003] The noise of the drive axle is one of the evaluation indicators of the NVH (noise, vibration, harshness) performance of the drive axle, and it is necessary to detect the sound power level when the drive axle product comes off the production line. The methods for measuring the sound power level usually include the sound pressure method, the sound intensity method, the standard sound source method, and the vibration velocity method. Due to the high background noise in the factory and the general lack of anechoic chamber test resources, only the vibration velocity method is applicable. When using the vibration velocity method to measure the sound power level of the drive axle noise source, it is necessary to arrange multiple vibration acceleration sensors on the surface of the drive axle, and the test preparation time is long. If the vibration velocity method is applied to the drive axle off-line detection, it will affect the production rhythm. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, computer device, computer-readable storage medium and computer program product for detecting the sound power level of a drive axle that can be convenient and fast.

[0005] In a first aspect, the present application provides a method for detecting the sound power level of a drive axle. The method includes:

[0006] Obtain the historical operation data of the measured drive axle of the same model as the drive axle to be detected, where the historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle;

[0007] Obtain the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determine the target vibration test point among all vibration test points according to the correlation coefficient;

[0008] Determine the fitting function according to the vibration acceleration and the sound power level of the target vibration test point;

[0009] Detect the sound power level of the drive axle to be detected according to the fitting function.

[0010] In one embodiment, the process of obtaining the historical operation data of the measured drive axle includes:

[0011] Select m vibration test points on the measured drive axle and obtain n different preset rotational speeds of the measured drive axle;

[0012] When the measured drive axle operates at any one of the preset rotational speeds, obtain the vibration acceleration and radiation index of the m vibration test points. The radiation index is used to indicate the sound radiation situation of the drive axle structure vibration;

[0013] Determine the sound power level corresponding to any one of the preset rotational speeds of the measured drive axle according to the vibration acceleration and radiation index of the m vibration test points;

[0014] Take the n sound power levels of the measured drive axle and the vibration accelerations of the m*n vibration test points obtained as the historical operation data of the measured drive axle.

[0015] In one embodiment, obtaining the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determining the target vibration test point among all vibration test points according to the correlation coefficient includes:

[0016] Take all the vibration accelerations of each vibration test point in the historical operation data and all the sound power levels of the measured drive axle as a sample set, and calculate the correlation coefficient between the vibration acceleration and the sound power level in each sample set;

[0017] Take the vibration test point corresponding to the maximum correlation coefficient as the target vibration test point.

[0018] In one embodiment, determining the fitting function according to the vibration acceleration and the sound power level of the target vibration test point includes:

[0019] Determine the fitting parameters of the fitting function according to the vibration acceleration, the sound power level of the target vibration test point and the preset fitting algorithm; construct the fitting function according to the fitting parameters.

[0020] In one embodiment, the preset fitting algorithm includes at least one of the following two algorithms, and the following two algorithms are the interpolation fitting algorithm and the least squares curve fitting algorithm respectively.

[0021] In one embodiment, detecting the sound power level of the drive axle to be detected according to the fitting function includes:

[0022] When the drive axle to be detected operates at a constant rotational speed and a constant torque within a preset duration, obtain the detected vibration acceleration of the target vibration test point;

[0023] According to the detected vibration acceleration and the fitting function, the sound power level of the drive axle to be detected is calculated. If the sound power level of the drive axle to be detected is less than the preset threshold, the sound power level detection of the drive axle to be detected is qualified.

[0024] In a second aspect, the present application also provides a device for detecting the sound power level of a drive axle. The device includes:

[0025] An acquisition module, configured to acquire historical operation data of a measured drive axle of the same model as the drive axle to be detected, where the historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle;

[0026] A first determination module, which acquires the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determines the target vibration test point among all vibration test points according to the correlation coefficient;

[0027] A second determination module, which determines a fitting function according to the vibration acceleration and the sound power level of the target vibration test point;

[0028] A detection module, configured to detect the sound power level of the drive axle to be detected according to the fitting function.

[0029] In a third aspect, the present application also provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0030] Acquire historical operation data of a measured drive axle of the same model as the drive axle to be detected, where the historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle;

[0031] Acquire the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determine the target vibration test point among all vibration test points according to the correlation coefficient;

[0032] Determine a fitting function according to the vibration acceleration and the sound power level of the target vibration test point;

[0033] Detect the sound power level of the drive axle to be detected according to the fitting function.

[0034] In a fourth aspect, the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0035] Acquire historical operation data of a measured drive axle of the same model as the drive axle to be detected, where the historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle;

[0036] Obtain the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determine the target vibration test point among all vibration test points according to the correlation coefficient;

[0037] Determine the fitting function according to the vibration acceleration and the sound power level of the target vibration test point;

[0038] Detect the sound power level of the drive axle to be detected according to the fitting function.

[0039] In a fifth aspect, the present application also provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0040] Obtain the historical operation data of the measured drive axle of the same model as the drive axle to be detected. The historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle;

[0041] Obtain the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determine the target vibration test point among all vibration test points according to the correlation coefficient;

[0042] Determine the fitting function according to the vibration acceleration and the sound power level of the target vibration test point;

[0043] Detect the sound power level of the drive axle to be detected according to the fitting function.

[0044] The above drive axle sound power level detection method, device, computer device, storage medium and computer program product obtain the historical operation data of the measured drive axle of the same model as the drive axle to be detected. The historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle; obtain the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determine the target vibration test point among all vibration test points according to the correlation coefficient; determine the fitting function according to the vibration acceleration and the sound power level of the target vibration test point; detect the sound power level of the drive axle to be detected according to the fitting function. By accumulating historical data, determine the calculation formula of the sound power level and the best test position, and when detecting the lower limit of the sound power level of the drive axle, the sound power level can be directly calculated, reducing the number of sensors used, shortening the test detection time, and improving the efficiency of the drive axle offline detection. Description of the Drawings

[0045] Figure 1 It is an application environment diagram of the drive axle sound power level detection method in an embodiment;

[0046] Figure 2Schematic flow chart of the method for detecting the sound power level of a drive axle in an embodiment;

[0047] Figure 3 Schematic flow chart of the method for detecting the sound power level of a drive axle in another embodiment;

[0048] Figure 4 Schematic flow chart of the method for detecting the sound power level of a drive axle in yet another embodiment;

[0049] Figure 5 Block diagram of the structure of the device for detecting the sound power level of a drive axle in an embodiment;

[0050] Figure 6 Internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0051] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0052] NVH is the English abbreviation of Noise, Vibration, Harshness. It is a comprehensive issue for measuring the manufacturing quality of automobiles, and the feelings it gives to automobile users are the most direct and obvious. The NVH problems of vehicles are one of the concerns of major vehicle manufacturing enterprises and parts enterprises in the international automotive industry. Statistical data shows that about 1 / 3 of the vehicle faults are related to the NVH problems of the vehicles, and nearly 20% of the R & D expenses of major companies are consumed in solving the NVH problems of the vehicles.

[0053] The drive axle is a mechanism located at the end of the transmission system that can change the speed and torque from the transmission and transmit them to the driving wheels. The drive axle generally consists of a main reducer, a differential, a wheel drive device, a drive axle housing, etc. The steering drive axle also has constant velocity universal joints. In addition, the drive axle also has to bear the vertical force, longitudinal force and lateral force acting between the road surface and the frame or body, as well as the braking torque and reaction force.

[0054] The noise of the drive axle is one of the evaluation indexes of the NVH (noise, vibration, harshness) performance of the drive axle, and it is necessary to detect the sound power level when the drive axle product comes off the production line. The methods for measuring the sound power level usually include the sound pressure method, the sound intensity method, the standard sound source method and the vibration velocity method. Due to the high background noise in the factory and the general lack of anechoic chamber test resources, only the vibration velocity method is applicable. When using the vibration velocity method to measure the sound power level of the drive axle noise source, it is necessary to arrange multiple vibration acceleration sensors on the surface of the drive axle, and the test preparation time is long. If the vibration velocity method is applied to the drive axle off-line detection, it will affect the production rhythm.

[0055] The sound power level is 10 times the base-10 logarithm of the ratio of the sound power to the reference sound power, expressed in decibels. The reference sound power must be specified. Its numerical expression is L W = 10lg(W / W0), where the commonly used reference sound power W0 is 10-12 W. The sound power refers to the total energy of sound radiated by a sound source into space per unit time, with the unit of W.

[0056] The drive axle sound power level detection method provided by the embodiments of the present application can be applied to, for example, Figure 1 the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network, and is used to obtain the vibration velocity obtained by the vibration acceleration sensor installed on the drive axle, and transmit the obtained data to the server 104. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or placed in the cloud or other network servers. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0057] In one embodiment, as Figure 2 shown, a drive axle sound power level detection method is provided. Taking the method applied to the Figure 1 server as an example for illustration, the method includes the following steps:

[0058] Step 202, obtain the historical operation data of the measured drive axle of the same model as the drive axle to be detected. The historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle;

[0059] Among them, the measured drive axle refers to a drive axle of the same model as the drive axle to be detected and has been detected in the laboratory. It can be understood that the sound power levels of drive axles of the same model should be the same. Before mass production of a certain type of drive axle, a small number of sample products will definitely be produced first according to the design plan, and the sample products will be tested in the laboratory to obtain test data, and a large amount of test data of the sample products will be used as historical operation data.

[0060] It should be noted that in mechanical vibration, the original data measured for vibration is the vibration acceleration. Based on the vibration acceleration, the vibration velocity and vibration displacement of the vibration point can be determined. Among them, the vibration velocity is the first derivative of the vibration displacement with respect to time, and the vibration acceleration is the second derivative of the vibration displacement with respect to time. In the embodiments of the present application, both the vibration velocity and the vibration acceleration are effective values.

[0061] Specifically, the sound power level of the noise source of the selected same model of drive axle is detected using the vibration velocity method, and the data obtained from the detection is used as the historical operation data of the measured drive axle. For example, randomly select 7 drive axles of the same model, apply the vibration velocity method to test the sound power level of the drive axle in the laboratory, arrange 14 vibration measurement points on the surface of the drive axle to ensure that the measurement point arrangement positions of each drive axle are the same, and test 10 different drive axle rotation speeds. In this way, 70 sound power level data and 980 vibration acceleration (root mean square value) data of 14 measurement points can be accumulated.

[0062] Step 204: Obtain the correlation coefficient between the vibration acceleration and the sound power level of each vibration measurement point, and determine the target vibration measurement point among all the vibration measurement points according to the correlation coefficient;

[0063] Among them, the correlation coefficient is a non-deterministic relationship and is a quantity that studies the degree of linear correlation between variables. The target vibration measurement point refers to the measurement point selected on the drive axle that can better reflect the sound power level of the noise brought by the vibration of the drive axle. It can be understood that on the surface of the drive axle, there will always be a position where there is a strong connection between the vibration acceleration at this point and the sound power level of the drive axle. Therefore, among all the vibration measurement points used for sound power level detection in the drive axle laboratory, the best detection point can be selected to detect the drive axle to be detected with higher efficiency using the data of one point.

[0064] Specifically, using mathematical methods, perform a correlation analysis on the sound power level data and the vibration acceleration data of each vibration measurement point. For example, based on the SPSS software, perform a Spearman correlation analysis on the aforementioned 70 sound power level data and 980 vibration acceleration data of 14 measurement points, and select the vibration measurement point with the largest correlation coefficient with the sound power level, usually the Spearman correlation coefficient is above 0.95, as the best detection position, that is, the arrangement point of the vibration acceleration sensor for offline detection of the drive to be detected. The Pearson correlation coefficient can also be used to analyze the sound power level data and the vibration acceleration data.

[0065] Step 206: Determine the fitting function according to the vibration acceleration and the sound power level of the target vibration measurement point;

[0066] It can be understood that after a large amount of data is determined, the relationship between the sound power level and the vibration acceleration can be determined based on the selected data. Specifically, a relationship expression is determined to reflect the change of the sound power level with the change of the vibration acceleration. Since there is a large amount of vibration acceleration and sound power level data of the target vibration test points, for the accuracy of the relationship expression, generally all the data is used for fitting to obtain a fitting function to express the relationship between the two.

[0067] Specifically, the data can be input into Matlab software and fitted based on a preset algorithm. For example, the functional relationship between the aforementioned 70 sound power level data and the 70 vibration acceleration data at the best detection position is fitted to solve the fitting coefficients, fitting exponents, and fitting constants, which usually conform to the following functional relationship:

[0068]

[0069] where L WA is the sound power level, ε is the fitting coefficient, λ is the fitting exponent, b is the fitting constant, and a RMS is the vibration acceleration.

[0070] Step 208: Detect the sound power level of the drive axle to be detected according to the fitting function.

[0071] After obtaining the fitting function, the fitting parameters of the fitting function are solidified, that is, the fitting parameters are input into the test system of the offline detection device. The test system of the offline detection device determines the sound power level of the drive axle to be detected according to the fitting function determined by the fitting parameters, and then conducts sound power level detection and analysis.

[0072] Specifically, the target vibration detection point is used as the best detection position, and a vibration acceleration sensor is installed at the best detection position of the drive axle to be detected. Then the drive axle is started to run, and the sound power level is calculated according to the vibration acceleration obtained by the vibration acceleration sensor and the fitting function.

[0073] In the method provided by the above embodiments, historical operation data of a measured drive axle of the same model as the drive axle to be detected is obtained. The historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle; the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point is obtained, and the target vibration test point among all vibration test points is determined according to the correlation coefficient; a fitting function is determined according to the vibration acceleration and the sound power level of the target vibration test point; the sound power level of the drive axle to be detected is detected according to the fitting function. By accumulating historical data, the calculation formula of the sound power level and the optimal test position are determined, and the sound power level can be directly calculated during the off-line detection of the drive axle sound power level, reducing the number of sensors used, shortening the test detection time, and improving the efficiency of the drive axle off-line detection.

[0074] In one embodiment, referring to Figure 3 , the process of obtaining the historical operation data of the measured drive axle includes:

[0075] Step 302, select m vibration test points on the measured drive axle, and obtain n different preset rotational speeds of the measured drive axle;

[0076] Step 304, when the measured drive axle is operating at any one of the preset rotational speeds, obtain the vibration acceleration and the radiation index of the m vibration test points. The radiation index is used to indicate the sound radiation situation of the drive axle structure vibration;

[0077] Step 306, determine the sound power level corresponding to any one of the preset rotational speeds of the measured drive axle according to the vibration acceleration and the radiation index of the m vibration test points;

[0078] Step 308, take the n sound power levels of the measured drive axle and the vibration accelerations of the m*n vibration test points obtained as the historical operation data of the measured drive axle.

[0079] Among them, the preset rotational speed refers to the speed of the drive axle during operation. Different rotational speeds generate different noise levels, and the corresponding sound power levels will also be different. Generally speaking, the greater the rotational speed, the greater the noise and the greater the sound power level. To avoid the contingency of single data, multiple different rotational speeds are set for the drive axle, corresponding to multiple different sound power levels, so as to combine the vibration accelerations of multiple vibration test points to form historical operation data.

[0080] In addition, when detecting the sound power level of the drive axle in the laboratory, the vibration acceleration data and radiation index directly obtained in the laboratory can be used to calculate the sound power level of the drive axle operating at any preset speed according to a preset algorithm. It should be noted that there is a corresponding relationship between the sound power level data and the vibration acceleration data. There is a sound power level corresponding to a preset speed, and this sound power level calculation corresponds to obtaining m vibration accelerations at m vibration test points. That is, if the data is recorded in the form of a table, it is a table of m * n. The rows represent m vibration test points, and the columns represent n sound power levels. The corresponding vibration acceleration values are in the table.

[0081] It should be noted that when obtaining historical operation data, in order to obtain enough data to ensure the accuracy of the subsequent correlation coefficient and fitting function, multiple drive axles of the same model can be randomly selected and tested in the laboratory to obtain more data. For example, l drive axles are selected, and m vibration test points and n different preset speeds are selected for each drive axle. According to the above description, a total of m * n * l vibration acceleration data can be obtained.

[0082] In the method provided in the above embodiment, m vibration test points are selected on the measured drive axle, and n different preset speeds are set for the measured drive axle; when the measured drive axle is operating at any preset speed, the vibration acceleration and radiation index of the m vibration test points are obtained. The radiation index is used to indicate the sound radiation situation of the drive axle structure vibration; according to the vibration acceleration and radiation index of the m vibration test points, the sound power level corresponding to any preset speed of the measured drive axle is determined; the n sound power levels of the measured drive axle and the vibration accelerations of the m * n vibration test points obtained are used as the historical operation data of the measured drive axle. Based on a large amount of accumulated historical data, the relationship between the sound power level and the vibration acceleration is determined, and the best detection position is determined, so as to shorten the detection time, reduce the number of required sensors, and improve the efficiency and reliability of the drive axle offline detection when the drive axle is offline detected.

[0083] In one of the embodiments, the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point is obtained, and the target vibration test point among all vibration test points is determined according to the correlation coefficient, including:

[0084] All the vibration accelerations of each vibration test point in the historical operation data and all the sound power levels of the measured drive axle are used as a sample set, and the correlation coefficient between the vibration acceleration and the sound power level in each sample set is calculated;

[0085] The vibration test point corresponding to the maximum correlation coefficient is used as the target vibration test point.

[0086] The correlation coefficient represents the degree of linear correlation between two variables. The larger the correlation coefficient, the closer the relationship between the two. In this embodiment, the two variables are the vibration acceleration of the vibration test point and the sound power level of the drive axle. Therefore, the vibration acceleration data of other vibration test points are all interference items. In order to obtain the relationship between the vibration acceleration data of each vibration test point and the sound power level of the drive axle, the vibration acceleration data of each vibration test point and the sound power level data are formed into a set, and the relationship between the vibration acceleration and the sound power level is studied in this set.

[0087] For example, when testing the drive axle, a total of n different preset speeds are selected, and n sound power levels {L W1 、L W2 、…、L Wn} can be obtained. When obtaining each sound power level, the vibration acceleration at each vibration test point can be obtained at this time. For m vibration test points, data {a 11 、a 12 、…、a 1n}, {a 21 、a 22 、…、a 2n}, …, {a m1 、a m2 、…、a mn} are obtained. When performing correlation analysis, {L W1 、L W2 、…、L Wn} and {a 11 、a 12 、…、a 1n} are used to obtain the first correlation coefficient, which represents the relationship between the vibration acceleration of the first vibration test point and the sound power level; {L W1 、L W2 、…、L Wn} and {a 21 、a 22 、…、a 2n} are used to obtain the second correlation coefficient, which represents the relationship between the vibration acceleration of the second vibration test point and the sound power level; and so on, multiple correlation coefficients are obtained.

[0088] Specifically, in one embodiment, the Spearman (correlation analysis) method can be used to input the data in each formed sample set into the software SPSS to obtain m Spearman correlation coefficients, and the vibration point corresponding to the maximum value is used as the best detection position, and a vibration acceleration sensor is installed during offline detection. It should be noted that generally, when using Spearman correlation analysis to determine the relationship between two variables, the Spearman correlation coefficient needs to reach above 0.95 to better illustrate the mutual relationship between the two variables. Therefore, when using Spearman correlation analysis to analyze the relationship between the sound power level and the vibration acceleration at the vibration test point, a threshold can be set to test the obtained correlation coefficient to ensure the correct best detection position.

[0089] In the method provided in the above embodiment, all the vibration accelerations of each vibration test point in the historical operation data and all the sound power levels of the measured drive axles are used as a sample set, and the correlation coefficient between the vibration acceleration and the sound power level in each sample set is calculated; the vibration test point corresponding to the maximum correlation coefficient is used as the target vibration test point. Based on a large amount of accumulated historical data, the relationship between the sound power level and the vibration acceleration is determined, and the best detection position is determined, so as to shorten the detection duration during the offline detection of the drive axle, reduce the number of required sensors, and improve the efficiency and reliability of the offline detection of the drive axle.

[0090] In one embodiment, according to the vibration acceleration and the sound power level of the target vibration test point, determining a fitting function includes:

[0091] Determining the fitting parameters of the fitting function according to the vibration acceleration, the sound power level of the target vibration test point, and a preset fitting algorithm; constructing a fitting function according to the fitting parameters.

[0092] For example, based on the Matlab software, the foregoing n sound power level data {L W1 、L W2 、…、L Wn} and the n vibration acceleration data {a i1 、a i2 、…、a in} of the best observation point are used for function relationship fitting, and the fitting coefficients, fitting exponents, and fitting constants in the relational expression are obtained. For example, after inputting the sound power level data and the vibration acceleration data, ε = 93.5, λ = 0.104, and b = -0.06 are obtained, and the fitting function is:

[0093]

[0094] Express the functional relationship between the sound power level and the vibration acceleration using the above formula, and then input the obtained ε = 93.5, λ = 0.104, and b = -0.06 into the test system of the offline detection device.

[0095] In the method provided by the above embodiment, according to the vibration acceleration, sound power level of the target vibration test point, and the preset fitting algorithm, determine the fitting parameters of the fitting function; according to the fitting parameters, construct the fitting function. According to the historical cumulative data of the optimal detection position, determine the relationship between the sound power level and the vibration acceleration, so that the offline detection device can directly use the obtained functional relationship to detect the sound power level, shorten the detection duration, reduce the number of required sensors, and improve the efficiency and reliability of the drive axle offline detection.

[0096] In one embodiment, the preset fitting algorithm includes at least one of the following two algorithms, and the following two algorithms are the interpolation fitting algorithm and the least squares curve fitting algorithm respectively.

[0097] In one embodiment, refer to Figure 4 , detecting the sound power level of the drive axle to be detected according to the fitting function includes:

[0098] Step 402, when the drive axle to be detected operates at a constant speed and constant torque within a preset duration, obtain the detected vibration acceleration of the target vibration test point;

[0099] Step 404, according to the detected vibration acceleration and the fitting function, calculate the sound power level of the drive axle to be detected. If the sound power level of the drive axle to be detected is less than the preset threshold, the sound power level detection of the drive axle to be detected is qualified.

[0100] According to the explanation of the fitting function, when performing the lower limit detection of the drive axle, only the vibration acceleration of the target vibration test point as the best detection guidance needs to be obtained and substituted into the fitting function to obtain the sound power level. When obtaining the detected vibration acceleration of the target vibration test point, first, a vibration acceleration sensor needs to be installed at the best detection position, and then the drive axle is allowed to operate at a constant speed and constant torque to obtain the data of the vibration acceleration sensor within a preset duration. It can be known that since the drive axle operates at a constant speed and constant torque, the vibration of the drive axle is uniform, and the generated noise is also uniform. Therefore, the vibration acceleration sensor obtains not a specific value, but the vibration amplitude within a period of time, similar to a sine or cosine function, and then the vibration acceleration is obtained according to data such as amplitude, peak value, and frequency.

[0101] For example, let the drive axle to be detected operate at a constant speed and constant torque to obtain a RMS = 0.4399, and substitute it into the fitting function Calculate to obtain LWA If it is 85.8, the sound power level of the drive axle at this rotational speed and torque is 85.8 dB(A). Compare the calculated sound power level with the preset threshold to determine whether the sound power level of the drive axle to be detected meets the production standard.

[0102] It should be emphasized here that the drive axle to be detected and the drive axle from which historical data is obtained must be of the same model in order to ensure the accuracy of the obtained fitting function.

[0103] In the method provided in the above embodiment, when the drive axle to be detected operates at a constant rotational speed and a constant torque within a preset time period, the detected vibration acceleration of the target vibration test point is obtained; according to the detected vibration acceleration and the fitting function, the sound power level of the drive axle to be detected is calculated. If the sound power level of the drive axle to be detected is less than the preset threshold, the sound power level detection of the drive axle to be detected is qualified. According to the historical cumulative data of the optimal detection position, the relationship between the sound power level and the vibration acceleration is determined, so that the offline detection equipment can directly use the obtained functional relationship to detect the sound power level, shorten the detection time, reduce the number of required sensors, and improve the efficiency and reliability of the drive axle offline detection.

[0104] It should be understood that although each step in the flowcharts involved in the above embodiments is displayed in sequence according to the indication of the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages do not necessarily have to be executed at the same moment, but can be executed at different moments. The execution order of these steps or stages does not necessarily have to be sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0105] Based on the same inventive concept, the embodiments of the present application also provide a drive axle sound power level detection device for implementing the drive axle sound power level detection method involved above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the drive axle sound power level detection device provided below can refer to the limitations on the drive axle sound power level detection method in the above text, and will not be repeated here.

[0106] In one embodiment, as Figure 5 shown, a drive axle sound power level detection device is provided, including: an acquisition module 501, a first determination module 502, a second determination module 503, and a detection module 504, where:

[0107] An acquisition module 501, configured to acquire historical operation data of a measured drive axle of the same model as the drive axle to be detected, where the historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle;

[0108] A first determination module 502, configured to obtain a correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determine a target vibration test point among all vibration test points according to the correlation coefficient;

[0109] A second determination module 503, configured to determine a fitting function according to the vibration acceleration and the sound power level of the target vibration test point;

[0110] A detection module 504, configured to detect the sound power level of the drive axle to be detected according to the fitting function.

[0111] In one embodiment, the acquisition module 501 is further configured to:

[0112] Select m vibration test points on the measured drive axle, and acquire n different preset rotational speeds of the measured drive axle;

[0113] When the measured drive axle operates at any one of the preset rotational speeds, acquire the vibration acceleration and the radiation index of the m vibration test points, where the radiation index is used to indicate the sound radiation condition of the drive axle structure vibration;

[0114] Determine the sound power level corresponding to any one of the preset rotational speeds of the measured drive axle according to the vibration acceleration and the radiation index of the m vibration test points;

[0115] Use the n sound power levels of the measured drive axle and the vibration accelerations of the m×n vibration test points obtained as the historical operation data of the measured drive axle.

[0116] In one embodiment, the first determination module 502 is further configured to:

[0117] Use all the vibration accelerations of each vibration test point in the historical operation data and all the sound power levels of the measured drive axle as a sample set, and calculate the correlation coefficient between the vibration acceleration and the sound power level in each sample set;

[0118] Use the vibration test point corresponding to the maximum correlation coefficient as the target vibration test point.

[0119] In one embodiment, the second determination module 503 is further configured to:

[0120] Determine the fitting parameters of the fitting function according to the vibration acceleration, the sound power level of the target vibration test point, and a preset fitting algorithm; and construct the fitting function according to the fitting parameters.

[0121] In one embodiment, the second determination module 503 is further configured to: The preset fitting algorithm includes at least one of the following two algorithms, which are the interpolation fitting algorithm and the least squares curve fitting algorithm respectively.

[0122] In one embodiment, the detection module 504 is further configured to:

[0123] When the drive axle to be detected operates at a constant rotational speed and a constant torque within a preset duration, obtain the detected vibration acceleration of the target vibration test point;

[0124] According to the detected vibration acceleration and the fitting function, calculate the sound power level of the drive axle to be detected. If the sound power level of the drive axle to be detected is less than the preset threshold, the sound power level detection of the drive axle to be detected is qualified.

[0125] Each module in the above drive axle sound power level detection device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above respective modules.

[0126] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 6 shown. The computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the historical operation data of the drive axle. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a drive axle sound power level detection method.

[0127] Those skilled in the art can understand that Figure 6 the structure shown in

[0128] is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0129] Obtain the historical operation data of a measured drive axle of the same model as the drive axle to be detected. The historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle.

[0130] Obtain the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determine the target vibration test point among all vibration test points according to the correlation coefficient.

[0131] Determine the fitting function according to the vibration acceleration and the sound power level of the target vibration test point.

[0132] Detect the sound power level of the drive axle to be detected according to the fitting function.

[0133] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0134] Select m vibration test points on the measured drive axle, and obtain n different preset rotational speeds of the measured drive axle.

[0135] When the measured drive axle operates at any one of the preset rotational speeds, obtain the vibration acceleration and the radiation index of the m vibration test points. The radiation index is used to indicate the sound radiation situation of the drive axle structure vibration.

[0136] Determine the sound power level corresponding to any one of the preset rotational speeds of the measured drive axle according to the vibration acceleration and the radiation index of the m vibration test points.

[0137] Take the n sound power levels of the measured drive axle and the vibration accelerations of the m*n vibration test points obtained as the historical operation data of the measured drive axle.

[0138] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0139] Take all the vibration accelerations of each vibration test point in the historical operation data and all the sound power levels of the measured drive axle as a sample set, and calculate the correlation coefficient between the vibration acceleration and the sound power level in each sample set.

[0140] Take the vibration test point corresponding to the maximum correlation coefficient as the target vibration test point.

[0141] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0142] Determine the fitting parameters of the fitting function according to the vibration acceleration, the sound power level of the target vibration test point and the preset fitting algorithm; construct the fitting function according to the fitting parameters.

[0143] In one embodiment, when the processor executes the computer program, the following steps are further implemented: The preset fitting algorithm includes at least one of the following two algorithms, which are the interpolation fitting algorithm and the least squares curve fitting algorithm respectively.

[0144] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0145] When the drive axle to be detected operates at a constant rotational speed and a constant torque within a preset time period, obtain the detected vibration acceleration of the target vibration test point;

[0146] According to the detected vibration acceleration and the fitting function, calculate the sound power level of the drive axle to be detected. If the sound power level of the drive axle to be detected is less than the preset threshold, the sound power level detection of the drive axle to be detected is qualified.

[0147] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, the following steps are implemented:

[0148] Obtain the historical operation data of the measured drive axle of the same model as the drive axle to be detected. The historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle;

[0149] Obtain the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determine the target vibration test point among all vibration test points according to the correlation coefficient;

[0150] Determine the fitting function according to the vibration acceleration and the sound power level of the target vibration test point;

[0151] Detect the sound power level of the drive axle to be detected according to the fitting function.

[0152] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0153] Select m vibration test points on the measured drive axle, and obtain n different preset rotational speeds of the measured drive axle;

[0154] When the measured drive axle operates at any one of the preset rotational speeds, obtain the vibration acceleration and the radiation index of the m vibration test points. The radiation index is used to indicate the sound radiation situation of the drive axle structure vibration;

[0155] According to the vibration acceleration and the radiation index of the m vibration test points, determine the sound power level corresponding to any one of the preset rotational speeds of the measured drive axle;

[0156] Take the obtained n sound power levels of the measured drive axle and the vibration accelerations of the m*n vibration test points as the historical operation data of the measured drive axle.

[0157] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0158] Take all the vibration accelerations of each vibration test point in the historical operation data and all the sound power levels of the measured drive axle as a sample set, and calculate the correlation coefficient between the vibration acceleration and the sound power level in each sample set;

[0159] Take the vibration test point corresponding to the maximum correlation coefficient as the target vibration test point.

[0160] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0161] Determine the fitting parameters of the fitting function according to the vibration acceleration, sound power level of the target vibration test point and the preset fitting algorithm; construct the fitting function according to the fitting parameters.

[0162] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: The preset fitting algorithm includes at least one of the following two algorithms, and the following two algorithms are the interpolation fitting algorithm and the least squares curve fitting algorithm respectively.

[0163] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0164] Under the condition that the drive axle to be detected operates at a constant speed and constant torque within a preset time period, obtain the detected vibration acceleration of the target vibration test point;

[0165] Calculate the sound power level of the drive axle to be detected according to the detected vibration acceleration and the fitting function. If the sound power level of the drive axle to be detected is less than the preset threshold, the sound power level detection of the drive axle to be detected is qualified.

[0166] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0167] Obtain the historical operation data of the measured drive axle of the same model as the drive axle to be detected. The historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle;

[0168] Obtain the correlation coefficient between the vibration acceleration and the sound power level of each vibration test point, and determine the target vibration test point among all the vibration test points according to the correlation coefficient;

[0169] Determine the fitting function according to the vibration acceleration and sound power level of the target vibration test point;

[0170] Detect the sound power level of the drive axle to be detected according to the fitting function.

[0171] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0172] Select m vibration test points on the measured drive axle and obtain n different preset rotational speeds of the measured drive axle;

[0173] When the measured drive axle operates at any one of the preset rotational speeds, obtain the vibration acceleration and radiation index of the m vibration test points. The radiation index is used to indicate the sound radiation situation of the drive axle structure vibration;

[0174] Determine the sound power level corresponding to any one of the preset rotational speeds of the measured drive axle according to the vibration acceleration and radiation index of the m vibration test points;

[0175] Take the n sound power levels of the measured drive axle obtained and the vibration accelerations of the m*n vibration test points as the historical operation data of the measured drive axle.

[0176] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0177] Take all the vibration accelerations of each vibration test point in the historical operation data and all the sound power levels of the measured drive axle as a sample set, and calculate the correlation coefficient between the vibration acceleration and the sound power level in each sample set;

[0178] Take the vibration test point corresponding to the maximum correlation coefficient as the target vibration test point.

[0179] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0180] Determine the fitting parameters of the fitting function according to the vibration acceleration, sound power level of the target vibration test point and the preset fitting algorithm; construct the fitting function according to the fitting parameters.

[0181] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: The preset fitting algorithm includes at least one of the following two algorithms, and the following two algorithms are the interpolation fitting algorithm and the least squares curve fitting algorithm respectively.

[0182] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0183] When the drive axle to be detected operates at a constant rotational speed and a constant torque within a preset duration, obtain the detected vibration acceleration of the target vibration test point;

[0184] According to the detected vibration acceleration and the fitting function, the sound power level of the drive axle to be detected is calculated. If the sound power level of the drive axle to be detected is less than the preset threshold, the sound power level detection of the drive axle to be detected is qualified.

[0185] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0186] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., and are not limited thereto. The processors involved in the embodiments provided in this application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., and are not limited thereto.

[0187] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0188] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for detecting the sound power level of a drive axle, characterized in that, The method includes: Obtaining historical operation data of a measured drive axle of the same model as the drive axle to be detected, where the historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle; Obtaining the correlation coefficient between the vibration acceleration of each vibration test point and the sound power level, and determining the target vibration test point among all the vibration test points according to the correlation coefficient; Determining a fitting function according to the vibration acceleration of the target vibration test point and the sound power level; Detecting the sound power level of the drive axle to be detected according to the fitting function.

2. The method according to claim 1, wherein The process of obtaining the historical operation data of the measured drive axle includes: Selecting m vibration test points on the measured drive axle and obtaining n different preset rotational speeds of the measured drive axle; When the measured drive axle operates at any one of the preset rotational speeds, obtaining the vibration acceleration and the radiation index of the m vibration test points, where the radiation index is used to indicate the sound radiation situation of the drive axle structure vibration; Determining the sound power level corresponding to any one of the preset rotational speeds of the measured drive axle according to the vibration acceleration and the radiation index of the m vibration test points; Taking the n sound power levels of the measured drive axle and the vibration accelerations of the m*n vibration test points obtained as the historical operation data of the measured drive axle.

3. The method according to claim 2, characterized in that, The obtaining the correlation coefficient between the vibration acceleration of each vibration test point and the sound power level, and determining the target vibration test point among all the vibration test points according to the correlation coefficient includes: Taking all the vibration accelerations of each vibration test point in the historical operation data and all the sound power levels of the measured drive axle as a sample set, and calculating the correlation coefficient between the vibration acceleration and the sound power level in each sample set; Taking the vibration test point corresponding to the maximum correlation coefficient as the target vibration test point.

4. The method according to claim 1, characterized in that The determining a fitting function according to the vibration acceleration of the target vibration test point and the sound power level includes: Determining the fitting parameters of the fitting function according to the vibration acceleration of the target vibration test point, the sound power level and a preset fitting algorithm; constructing a fitting function according to the fitting parameters.

5. The method according to claim 4, wherein The preset fitting algorithm includes at least one of the following two algorithms, and the following two algorithms are respectively an interpolation fitting algorithm and a least squares curve fitting algorithm.

6. The method according to claim 1, characterized in that The detecting the sound power level of the drive axle to be detected according to the fitting function includes: When the drive axle to be detected operates at a constant rotational speed and a constant torque within a preset time period, obtaining the detected vibration acceleration of the target vibration test point; Calculating the sound power level of the drive axle to be detected according to the detected vibration acceleration and the fitting function, and if the sound power level of the drive axle to be detected is less than a preset threshold, the sound power level detection of the drive axle to be detected is qualified.

7. A drive axle sound power level detection device, characterized in that, The device includes: An obtaining module, configured to obtain historical operation data of a measured drive axle of the same model as the drive axle to be detected, where the historical operation data includes the sound power level of the measured drive axle and the vibration acceleration of each vibration test point on the measured drive axle; The first determination module obtains the correlation coefficient between the vibration acceleration of each vibration test point and the sound power level, and determines the target vibration test point among all the vibration test points according to the correlation coefficient; The second determination module determines a fitting function according to the vibration acceleration of the target vibration test point and the sound power level; The detection module is configured to detect the sound power level of the drive axle to be detected according to the fitting function.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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