An intelligent vehicle drive axle test system

Abstract

The invention relates to the field of drive axle testing, and in particular to an intelligent vehicle drive axle testing system. The invention inputs torque to a main reducer of the drive axle and clamps a drive axle housing through a drive module; a fixed detection module detects the vibration characteristics of sound sources at different detection points; a feature aggregation module analyzes the differences in the vibration characteristics of sound sources at different detection points of the drive axle, calculates the chaotic characterization parameters of the sound source, and classifies the chaotic categories of the sound source when the drive axle is running; a data extraction module adaptively controls the drive module based on the chaotic category of the sound source to obtain data detected by the fixed detection module; an abnormality determination module determines whether the drive axle has an abnormality based on the vibration characteristics of the sound source corresponding to each detection point. Through the above process, the invention improves the accuracy of the drive axle detection result and the detection efficiency while ensuring the reliability of the detection data.

Description

Technical Field

[0001] The invention relates to the field of drive axle testing, and in particular to an intelligent vehicle drive axle testing system. Background Art

[0002] The drive axle is an important part of the automobile transmission system, and its quality directly affects the overall performance and reliability of the automobile. For example, a high-quality drive axle can ensure that power is transmitted from the engine to the wheels smoothly and efficiently; the quality of the drive axle affects the stability and handling of the car during driving; the vibration and noise level of the drive axle will also affect the ride comfort. Therefore, in order to control the quality of the drive axle and adapt to the continuous innovation of automobile technology, the automotive industry has an increasing demand for efficient, accurate and standardized vehicle drive axle testing.

[0003] For example, Chinese patent publication number: CN104535317A discloses a closed drive axle test device that can automatically simulate vehicle steering, wherein a power synthesis box connects a drive motor, a hydraulic motor and an input shaft of a drive axle under test; the left output shaft of the drive axle under test is connected to the input shaft end of a left transmission box; the output shaft end of the left transmission box is connected to the left input shaft of a companion test drive axle; the right output shaft of the drive axle under test is connected to the first input shaft end of a right transmission box, the output shaft of the steering motor is connected to the second input shaft end of the right transmission box, and the output shaft end of the right transmission box is connected to the right input shaft of the companion test drive axle; the output end of the companion test drive axle is connected to a loading hydraulic pump; a hydraulic pipeline is arranged between the output oil port of the loading hydraulic pump and the input oil port of the hydraulic motor.

[0004] However, the prior art still has the following problems: during the drive axle detection process, internal abnormalities may manifest themselves in audio factors and vibration factors. However, the above factors are easily affected by the audio factors and vibration factors associated with the operation of the drive axle itself, and may not be able to guarantee the reliability of the detection data, thereby reducing the accuracy of the detection results. Summary of the invention

[0005] To this end, the present invention provides an intelligent vehicle drive axle test system to overcome the problem in the prior art that internal abnormalities may manifest themselves in audio factors and vibration factors, but the above factors are easily affected by the audio factors and vibration factors associated with the operation of the drive axle itself, and may not be able to guarantee the reliability of the test data, thereby reducing the accuracy of the test results.

[0006] To achieve the above object, the present invention provides an intelligent vehicle drive axle test system, which includes:

[0007] A drive module, comprising a torque motor for inputting torque to a final reducer of the drive axle and a clamping member for clamping a housing of the drive axle;

[0008] A fixed detection module, comprising a plurality of detection probes arranged on one side of the drive axle for detecting vibration characteristics of sound sources at different detection points of the drive axle, wherein the vibration characteristics of the sound sources include sound source power and vibration frequency;

[0009] A feature aggregation module, which is connected to the fixed detection module, is used to analyze the differences in the vibration characteristics of the sound sources at different detection points of the drive axle, calculate the chaotic characterization parameters of the sound source, and classify the chaotic categories of the sound source when the drive axle is running;

[0010] The data extraction module is connected to the driving module, the fixed detection module and the feature aggregation module respectively, and is used to control the driving module based on the chaotic category of the sound source and obtain the data detected by the fixed detection module, including:

[0011] It is used to control the torque motor to increase the power to a predetermined power peak value, maintain the power at the gradient power node, and obtain the vibration characteristics of the sound source corresponding to each detection point within the power maintenance time;

[0012] Or, a measured power is selected, and the torque motor is controlled to maintain the power corresponding to the measured power, and the vibration characteristics of the sound source corresponding to each of the detection points within the power maintenance time are obtained;

[0013] An abnormality determination module, connected to the data extraction module, for determining whether the drive axle has an abnormality based on the vibration characteristics of the sound source corresponding to each of the detection points;

[0014] The gradient increase amount corresponding to the gradient increase is determined based on the chaotic characterization parameters of the sound source.

[0015] Furthermore, the feature aggregation module calculates the chaotic characterization parameter of the sound source according to formula (1):

[0016]

[0017] In formula (1), H represents the chaotic characterization parameter of the sound source, Wi represents the sound source frequency of the i-th detection point within the predetermined time period, ΔW represents the mean value of the sound source frequency of each detection point within the predetermined time period, Fi represents the vibration frequency of the i-th detection point within the predetermined time period, ΔF represents the mean value of the vibration frequency of each detection point within the predetermined time period, and n represents the number of detection points.

[0018] Furthermore, the feature aggregation module divides the chaotic sound source categories of the driving bridge during operation into the following categories:

[0019] If the sound source chaos characterization parameter is greater than or equal to the preset sound source chaos characterization parameter standard threshold, the sound source chaos category when the drive axle is running is a high chaos category;

[0020] If the sound source chaos characterization parameter is less than the preset sound source chaos characterization parameter standard threshold value, the sound source chaos category when the drive axle is running is a low chaos category.

[0021] Furthermore, the data extraction module is used to control the driving module based on the chaotic category of the sound source to obtain the data detected by the fixed detection module, including:

[0022] If the chaotic category of the sound source during the operation of the drive axle is a high chaotic category, it is used to control the torque motor to increase the power to a predetermined power peak value, maintain the power at the gradient power node, and obtain the vibration characteristics of the sound source corresponding to each detection point during the power maintenance time;

[0023] If the chaos category of the sound source during the operation of the drive axle is a low chaos category, it is used to select the measured power, control the torque motor to maintain the power corresponding to the measured power, and obtain the vibration characteristics of the sound source corresponding to each of the detection points within the power maintenance time.

[0024] Furthermore, the data extraction module controls the torque motor to increase power by gradient, wherein:

[0025] The gradient increase amount corresponding to the gradient increase is negatively correlated with the chaotic characterization parameter of the sound source.

[0026] Furthermore, the data extraction module is used to control the torque motor to increase the power to a predetermined power peak value, and to maintain the power at the gradient power node, including:

[0027] Used to control the torque motor to gradually increase power;

[0028] Used to control the torque motor to maintain the corresponding power for a predetermined period of time after completing the power increase;

[0029] The single power increase is the power increase gradient, and the gradient power node is the power reached by the speed motor after the power increase gradient is increased.

[0030] Furthermore, the data extraction module is used to select the measurement power, wherein:

[0031] The measured power is a predetermined power peak value and 0.5 times the predetermined power peak value.

[0032] Furthermore, the abnormality determination module is used to determine whether the drive axle has an abnormality based on the sound source vibration characteristics corresponding to each of the detection points, including:

[0033] If the sound source power discrete value corresponding to the detection point is greater than the preset sound source power discrete value standard threshold, or / and the vibration frequency discrete value corresponding to the detection point is greater than the preset vibration frequency discrete value standard threshold, it is determined that there is an abnormality in the drive axle.

[0034] Furthermore, it also includes an abnormal warning module, which is connected to the abnormal determination module and makes a warning prompt according to the determination result of the abnormal determination module.

[0035] Furthermore, the detection probe includes an audio detection unit for obtaining a sound source power corresponding to a detection point and a vibration detection unit for obtaining a vibration frequency corresponding to a detection point.

[0036] Compared with the prior art, the present invention inputs torque to the main reducer of the drive axle and clamps the drive axle housing through the drive module; the fixed detection module detects the vibration characteristics of the sound source at different detection points; the feature aggregation module analyzes the differences in the vibration characteristics of the sound source at different detection points of the drive axle, calculates the chaotic characterization parameters of the sound source, and divides the chaotic categories of the sound source when the drive axle is running; the data extraction module adaptively controls the drive module based on the chaotic category of the sound source to obtain the data detected by the fixed detection module; the abnormality judgment module judges whether there is an abnormality in the drive axle based on the vibration characteristics of the sound source corresponding to each detection point. Through the above process, the present invention improves the accuracy of the detection results of the drive axle and improves the detection efficiency while ensuring the reliability of the detection data.

[0037] In particular, the present invention calculates the sound source chaos characterization parameters by analyzing the differences in the vibration characteristics of the sound sources at different detection points of the drive axle. The operating sound source power and vibration frequency of the drive axle itself during operation may hide potential abnormal risks, but there may be certain differences between the corresponding sound source vibration characteristics at different detection points. Therefore, the present application characterizes the potential abnormal tendency caused by the abnormal characteristics of the drive axle by calculating the sound source chaos characterization parameters, highlights the hidden potential abnormal risks, and provides data support for the subsequent classification of the sound source chaos categories during the operation of the drive axle, and then, adaptively controls the drive module to obtain the data detected by the fixed detection module, and then, on the premise of ensuring the reliability of the detection data, improves the accuracy of the drive axle detection results and improves the detection efficiency.

[0038] In particular, the present invention divides the sound source chaos categories during the operation of the drive axle to adaptively control the drive module to obtain the data detected by the fixed detection module, and judges the potential abnormal tendency according to the sound source chaos characterization parameters corresponding to each detection point. For the detection points under the high chaos category, different detection methods are used for detection in a targeted manner, and more detailed detection of the detection points under the high chaos category can be performed. For example, the power is increased in a gradient increasing manner to stimulate the sound source vibration characteristics reflected by the potential abnormality, and the power can be increased and maintained in a more detailed manner with different gradient increases to determine the detection points that have potential abnormal risks. The detection method of the detection points under the low chaos category is simplified, and only the relevant sound source vibration characteristics under the characteristic measurement power node are analyzed. On the premise of ensuring reliability, the amount of analysis data is reduced to ensure the accuracy of the drive axle detection results and improve the detection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a functional module diagram of an intelligent vehicle drive axle test system according to an embodiment of the invention;

[0040] Figure 2 A logical decision diagram for classifying the chaotic categories of sound sources when the drive axle is running for the embodiment of the invention;

[0041] Figure 3 A logic decision diagram for controlling a driving module to obtain detection data according to an embodiment of the invention;

[0042] Figure 4 This is a logic determination diagram for determining whether a drive axle has an abnormality according to an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0045] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the term "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0046] See also Figures 1 to 4 As shown, Figure 1 is a functional module diagram of an intelligent vehicle drive axle test system according to an embodiment of the present invention, Figure 2 A logical decision diagram for classifying the chaotic sound source categories when the drive axle is running for the embodiment of the invention, Figure 3 A logic decision diagram for controlling the driving module to obtain detection data according to an embodiment of the invention. Figure 4 The intelligent vehicle drive axle test system of the embodiment of the present invention comprises:

[0047] A drive module, comprising a torque motor for inputting torque to a final reducer of the drive axle and a clamping member for clamping a housing of the drive axle;

[0048] A fixed detection module, comprising a plurality of detection probes arranged on one side of the drive axle for detecting vibration characteristics of sound sources at different detection points of the drive axle, wherein the vibration characteristics of the sound sources include sound source power and vibration frequency;

[0049] A feature aggregation module, which is connected to the fixed detection module, is used to analyze the differences in the vibration characteristics of the sound sources at different detection points of the drive axle, calculate the chaotic characterization parameters of the sound source, and classify the chaotic categories of the sound source when the drive axle is running;

[0050] The data extraction module is connected to the driving module, the fixed detection module and the feature aggregation module respectively, and is used to control the driving module based on the chaotic category of the sound source and obtain the data detected by the fixed detection module, including:

[0051] It is used to control the torque motor to increase the power to a predetermined power peak value, maintain the power at the gradient power node, and obtain the vibration characteristics of the sound source corresponding to each detection point within the power maintenance time;

[0052] Or, a measured power is selected, and the torque motor is controlled to maintain the power corresponding to the measured power, and the vibration characteristics of the sound source corresponding to each of the detection points within the power maintenance time are obtained;

[0053] An abnormality determination module, connected to the data extraction module, for determining whether the drive axle has an abnormality based on the vibration characteristics of the sound source corresponding to each of the detection points;

[0054] The gradient increase amount corresponding to the gradient increase is determined based on the chaotic characterization parameters of the sound source.

[0055] Specifically, there is no limitation on the specific structure of the torque motor, and it only needs to have the function of providing a relatively constant torque to the main reducer of the drive axle. The torque input to the main reducer is adjusted by adjusting the power of the torque motor. This is a prior art and will not be elaborated on.

[0056] Specifically, there is no limitation on the specific structure of the clamping component, which only needs to clamp the drive axle to keep the drive axle stable, and details will not be given here.

[0057] Specifically, there is no limitation on the specific structure of the drive axle being tested. The components of the drive axle mainly include a main reducer, a differential, and a half-axle. The engine torque can be input into the main reducer and transmitted to the drive wheels through the differential, a half-axle, etc. This is the existing technology and will not be elaborated on.

[0058] Specifically, there is no limitation on the feature aggregation module, data extraction module, anomaly determination module and anomaly warning module, and they can be composed of logic components or a combination of logic components, and the logic components include a field programmable processor, a computer or a microprocessor in a computer.

[0059] Specifically, the layout positions of the detection points are not limited, and are evenly distributed on the surface of the drive axle with corresponding spacings. Technical personnel in this field can set them by themselves. Preferably, the spacing between the detection points should be selected within the range of [30cm, 50cm].

[0060] Specifically, the feature aggregation module calculates the chaotic characterization parameter of the sound source according to formula (1):

[0061]

[0062] In formula (1), H represents the chaotic characterization parameter of the sound source, Wi represents the sound source frequency of the i-th detection point within the predetermined time period, ΔW represents the mean value of the sound source frequency of each detection point within the predetermined time period, Fi represents the vibration frequency of the i-th detection point within the predetermined time period, ΔF represents the mean value of the vibration frequency of each detection point within the predetermined time period, and n represents the number of detection points.

[0063] Specifically, the predetermined time period is selected within the interval [30s, 60s].

[0064] Specifically, in this example, the sound source frequency within the predetermined time period is the average value of the sound source frequency obtained at the corresponding detection point within the predetermined time period;

[0065] The vibration frequency within the predetermined time period is the average value of the vibration frequencies obtained at the corresponding detection points within the predetermined time period.

[0066] The present invention calculates the sound source chaos characterization parameters by analyzing the differences in the vibration characteristics of the sound sources at different detection points of the drive axle. The operating sound source power and vibration frequency of the drive axle itself during operation may hide potential abnormal risks, but there may be certain differences between the corresponding sound source vibration characteristics at different detection points. Therefore, the present application characterizes the potential abnormal tendency caused by the abnormal characteristics of the drive axle by calculating the sound source chaos characterization parameters, highlights the hidden potential abnormal risks, and provides data support for the subsequent classification of the sound source chaos categories during the operation of the drive axle, and then, adaptively controls the drive module to obtain the data detected by the fixed detection module, and then, on the premise of ensuring the reliability of the detection data, improves the accuracy of the drive axle detection results and improves the detection efficiency.

[0067] Specifically, the feature aggregation module divides the chaotic sound source categories when the drive axle is running, including:

[0068] If the sound source chaos characterization parameter is greater than or equal to the preset sound source chaos characterization parameter standard threshold, the sound source chaos category when the drive axle is running is a high chaos category;

[0069] If the sound source chaos characterization parameter is less than the preset sound source chaos characterization parameter standard threshold value, the sound source chaos category when the drive axle is running is a low chaos category.

[0070] Specifically, the data extraction module is used to control the driving module based on the chaotic category of the sound source to obtain the data detected by the fixed detection module, including:

[0071] If the chaotic category of the sound source during the operation of the drive axle is a high chaotic category, it is used to control the torque motor to increase the power to a predetermined power peak value, maintain the power at the gradient power node, and obtain the vibration characteristics of the sound source corresponding to each detection point during the power maintenance time;

[0072] If the chaos category of the sound source during the operation of the drive axle is a low chaos category, it is used to select the measured power, control the torque motor to maintain the power corresponding to the measured power, and obtain the vibration characteristics of the sound source corresponding to each of the detection points within the power maintenance time.

[0073] The present invention divides the sound source chaos categories when the drive bridge is running, so as to adaptively control the drive module to obtain the data detected by the fixed detection module, judge the potential abnormal tendency according to the sound source chaos characterization parameters corresponding to each detection point, and adopt different detection methods to detect the detection points under the high chaos category in a targeted manner, so as to perform more precise detection on the detection points under the high chaos category. For example, the power is increased in a gradient increasing manner to stimulate the sound source vibration characteristics reflected by the potential abnormality, and the power can be increased and maintained in a more detailed manner with different gradient increases to determine the detection points with potential abnormal risks, simplify the detection method of the detection points under the low chaos category, and only analyze the relevant sound source vibration characteristics under the characteristic measurement power node. Under the premise of ensuring reliability, the amount of analysis data is reduced, the accuracy of the drive bridge detection results is guaranteed, and the detection efficiency is improved.

[0074] Specifically, the data extraction module controls the torque motor to increase power gradiently, wherein:

[0075] The gradient increase amount corresponding to the gradient increase is negatively correlated with the chaotic characterization parameter of the sound source.

[0076] In this embodiment, optionally,

[0077] Compare the sound source chaos characterization parameter H with the first chaos characterization parameter H1 and the second sound source chaos characterization parameter H2.

[0078] If H>H2, the first gradient increase amount s1 is determined, and s1=0.1s0 is set;

[0079] If H1≤H≤H2, the second gradient increase amount s2 is determined, and s2=0.25s0 is set;

[0080] If H ​

[0081] Among them, s0 represents the increase in the base gradient, 10kw<s0<50kw, H1=1.1H0, H2=1.3H0.

[0082] H0 represents the standard threshold value of the chaotic characterization parameter of the sound source, and H0 is selected in the interval [0.2, 0.6].

[0083] Specifically, the data extraction module is used to control the torque motor to increase the power gradient to a predetermined power peak value, and the power needs to be maintained at the gradient power node, including:

[0084] Used to control the torque motor to gradually increase power;

[0085] Used to control the torque motor to maintain the corresponding power for a predetermined period of time after completing the power increase;

[0086] The single power increase is the power increase gradient, and the gradient power node is the power reached by the speed motor after the power increase gradient is increased.

[0087] Specifically, the data extraction module is used to select the measurement power, wherein:

[0088] The measured power is a predetermined power peak value and 0.5 times the predetermined power peak value.

[0089] It can be understood that the predetermined power peak is 0.9 times the power of the corresponding torque motor under the maximum torque that the drive axle main reducer can withstand.

[0090] Specifically, the abnormality determination module is used to determine whether the drive axle has an abnormality based on the sound source vibration characteristics corresponding to each of the detection points, including:

[0091] If the sound source power discrete value corresponding to the detection point is greater than the preset sound source power discrete value standard threshold, or / and the vibration frequency discrete value corresponding to the detection point is greater than the preset vibration frequency discrete value standard threshold, it is determined that there is an abnormality in the drive axle.

[0092] Specifically, the discrete value of the sound source power is calculated according to the following formula:

[0093]

[0094] Wherein, G represents the discrete value of the sound source power, Yi represents the sound source power at the detection point at the i-th moment during the power maintenance time, ΔY represents the mean value of the sound source power at the detection point during the power maintenance time, and T represents the power maintenance time.

[0095] The standard threshold value G0 of the discrete value of the sound source power is selected in the interval [0.12, 0.32].

[0096] Specifically, the discrete value of the vibration frequency is calculated according to the following formula:

[0097]

[0098] Wherein, P represents the discrete value of the vibration frequency, Fi represents the vibration frequency of the detection point at the i-th moment during the power maintenance time, ΔF represents the mean value of the vibration frequency of the detection point during the power maintenance time, and T represents the power maintenance time.

[0099] Specifically, the vibration frequency discrete value standard threshold value P0 is selected within the interval [0.15, 0.35].

[0100] The power maintenance time is selected in the interval [30s, 60s].

[0101] Specifically, it also includes an abnormal warning module, which is connected to the abnormal determination module and makes a warning prompt according to the determination result of the abnormal determination module.

[0102] Among them, if the abnormality determination module determines that there is an abnormality in the drive axle, a warning prompt is issued.

[0103] Specifically, the detection probe includes an audio detection unit for obtaining the sound source power corresponding to the detection point and a vibration detection unit for obtaining the vibration frequency corresponding to the detection point.

[0104] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. An intelligent vehicle drive axle test system, characterized in that: include: A drive module, comprising a torque motor for inputting torque to a final reducer of the drive axle and a clamping member for clamping a housing of the drive axle; A fixed detection module, comprising a plurality of detection probes arranged on one side of the drive axle for detecting vibration characteristics of sound sources at different detection points of the drive axle, wherein the vibration characteristics of the sound sources include sound source power and vibration frequency; A feature aggregation module, which is connected to the fixed detection module, is used to analyze the differences in the vibration characteristics of the sound sources at different detection points of the drive axle, calculate the chaotic characterization parameters of the sound source, and classify the chaotic categories of the sound source when the drive axle is running; The data extraction module is connected to the driving module, the fixed detection module and the feature aggregation module respectively, and is used to control the driving module based on the chaotic category of the sound source and obtain the data detected by the fixed detection module, including: It is used to control the torque motor to increase the power to a predetermined power peak value, maintain the power at the gradient power node, and obtain the vibration characteristics of the sound source corresponding to each detection point within the power maintenance time; Or, a measured power is selected, and the torque motor is controlled to maintain the power corresponding to the measured power, and the vibration characteristics of the sound source corresponding to each of the detection points within the power maintenance time are obtained; An abnormality determination module, connected to the data extraction module, for determining whether the drive axle has an abnormality based on the vibration characteristics of the sound source corresponding to each of the detection points; The gradient increase amount corresponding to the gradient increase is determined based on the chaotic characterization parameters of the sound source.

2. The intelligent vehicle drive axle test system according to claim 1, characterized in that: The feature aggregation module calculates the chaotic characterization parameters of the sound source according to formula (1): In formula (1), H represents the chaotic characterization parameter of the sound source, Wi represents the sound source frequency of the i-th detection point within the predetermined time period, ΔW represents the mean value of the sound source frequency of each detection point within the predetermined time period, Fi represents the vibration frequency of the i-th detection point within the predetermined time period, ΔF represents the mean value of the vibration frequency of each detection point within the predetermined time period, and n represents the number of detection points.

3. The intelligent vehicle drive axle test system according to claim 2, characterized in that: The feature aggregation module divides the chaotic sound source categories when the drive axle is running, including: If the sound source chaos characterization parameter is greater than or equal to the preset sound source chaos characterization parameter standard threshold, the sound source chaos category when the drive axle is running is a high chaos category; If the sound source chaos characterization parameter is less than the preset sound source chaos characterization parameter standard threshold value, the sound source chaos category when the drive axle is running is a low chaos category.

4. The intelligent vehicle drive axle test system according to claim 3, characterized in that: The data extraction module is used to control the driving module based on the chaotic category of the sound source to obtain the data detected by the fixed detection module, including: If the chaotic category of the sound source during the operation of the drive axle is a high chaotic category, it is used to control the torque motor to increase the power to a predetermined power peak value, maintain the power at the gradient power node, and obtain the vibration characteristics of the sound source corresponding to each detection point during the power maintenance time; If the chaos category of the sound source during the operation of the drive axle is a low chaos category, it is used to select the measured power, control the torque motor to maintain the power corresponding to the measured power, and obtain the vibration characteristics of the sound source corresponding to each of the detection points within the power maintenance time.

5. The intelligent vehicle drive axle test system according to claim 1, characterized in that: The data extraction module controls the torque motor to increase power gradiently, wherein: The gradient increase amount corresponding to the gradient increase is negatively correlated with the chaotic characterization parameter of the sound source.

6. The intelligent vehicle drive axle test system according to claim 5, characterized in that: The data extraction module is used to control the torque motor to increase the power to a predetermined power peak value, and the power needs to be maintained at the gradient power node. include, Used to control the torque motor to gradually increase power; Used to control the torque motor to maintain the corresponding power for a predetermined period of time after completing the power increase; The single power increase is the power increase gradient, and the gradient power node is the power reached by the speed motor after the power increase gradient is increased.

7. The intelligent vehicle drive axle test system according to claim 1, characterized in that: The data extraction module is used to select the measurement power, wherein: The measured power is a predetermined power peak value and 0.5 times the predetermined power peak value.

8. The intelligent vehicle drive axle test system according to claim 1, characterized in that: The abnormality determination module is used to determine whether the drive axle has an abnormality based on the sound source vibration characteristics corresponding to each of the detection points, including: If the sound source power discrete value corresponding to the detection point is greater than the preset sound source power discrete value standard threshold, or / and the vibration frequency discrete value corresponding to the detection point is greater than the preset vibration frequency discrete value standard threshold, it is determined that there is an abnormality in the drive axle.

9. The intelligent vehicle drive axle test system according to claim 1, characterized in that: It also includes an abnormal warning module, which is connected to the abnormal determination module and makes a warning prompt according to the determination result of the abnormal determination module.

10. The intelligent vehicle drive axle test system according to claim 1, characterized in that: The detection probe comprises an audio detection unit for obtaining the sound source power corresponding to the detection point and a vibration detection unit for obtaining the vibration frequency corresponding to the detection point.

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