Method and System for Extracting Feature Frequency of Fault Diagnosis in Automotive Transmission Systems

Abstract

This invention discloses a method and system for extracting characteristic frequencies for fault diagnosis in automotive transmission systems. The method includes: establishing a dynamic mechanism model of a planetary gearbox; determining characteristic frequencies used for fault diagnosis and the relationships between these characteristic frequencies, where the first characteristic frequency is the motor rotation frequency, the second characteristic frequency is the gear meshing frequency of the planetary gearbox, and the third characteristic frequency is the planetary carrier characteristic frequency; calculating the theoretical characteristic frequency; determining the actual characteristic frequency based on correction coefficients and the theoretical characteristic frequency; and diagnosing and identifying fault characteristics based on the actual characteristic frequency. This invention proposes to accurately obtain the fault characteristic frequencies of the drive assembly without relying on a drive speed sensor, in most applications where drive assembly characteristics cannot be conveniently or accurately obtained. This method reduces the difficulty of vehicle fault diagnosis and analysis for operators and improves the convenience of diagnosing mechanical transmission faults in automotive drive systems.

Description

Technical Field

[0001] This invention relates to the field of automotive transmission system technology, and in particular to a method and system for extracting characteristic frequencies for fault diagnosis in automotive transmission systems. Background Technology

[0002] Automotive mechanical transmission components typically include gears, motors, and bearings. The reliable operation of these components is a prerequisite for the normal functioning of the mechanical powertrain, and unexpected component failures are often the main cause of malfunctions in mechanical transmission components. Currently, a common method is to install vibration and acceleration sensors on the housing of the mechanical transmission components to sense their operating status and determine whether they are functioning properly. This method relies on accurately calculating the real-time fault characteristic frequencies of the mechanical transmission assembly under operating conditions. However, this method faces certain difficulties in application. While the component parameters of mechanical transmission components are generally known after leaving the factory and do not change, the actual rotational frequency input to the transmission assembly by the automotive drive system often deviates from the set or displayed value due to load fluctuations or external interference. This deviation directly affects the accuracy of the actual fault characteristic frequency calculation, leading to missed or incorrect diagnoses of mechanical transmission fault states. These problems urgently need to be addressed. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for extracting characteristic frequencies for fault diagnosis of automotive transmission systems, so as to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a method for extracting feature frequencies for fault diagnosis of automotive transmission systems, comprising:

[0005] Establish a dynamic mechanism model for planetary gearboxes;

[0006] The characteristic frequencies used for fault diagnosis and the relationship between the characteristic frequencies are determined. The characteristic frequencies include a first characteristic frequency, a second characteristic frequency, and a third characteristic frequency. The second characteristic frequency is the gear meshing frequency of the planetary gearbox, the first characteristic frequency is the motor rotation frequency, and the third characteristic frequency is the planet carrier characteristic frequency.

[0007] Calculate the theoretical characteristic frequencies;

[0008] Set a correction factor, and determine the actual characteristic frequency based on the correction factor and the theoretical characteristic frequency;

[0009] Fault characteristics are diagnosed and identified based on actual characteristic frequencies.

[0010] Furthermore, establishing a dynamic mechanism model for planetary gearboxes also includes:

[0011] The vibration signal spectrum of the planetary gearbox is detected. The vibration signal includes a characteristic frequency signal, a first modulation signal that is a multiple of the second characteristic frequency and the first characteristic frequency, and a second modulation signal that is a multiple of the second characteristic frequency and the third characteristic frequency. Without loss of generality, the vibration signal mechanism model is established as follows:

[0012] ——Formula (1);

[0013] in, The second characteristic frequency, The first characteristic frequency, This is the third characteristic frequency.

[0014] Furthermore, including:

[0015] After simplifying the modulation term of the vibration signal mechanism model, a Fourier transform is performed to obtain the formula for the frequency components of the time-domain signal: ——Formula (2);

[0016] Furthermore, setting correction coefficients and determining the actual characteristic frequency based on the correction coefficients and the theoretical characteristic frequency also includes:

[0017] The vibration signal also includes equally spaced sidebands distributed on both sides of the second characteristic frequency. The sidebands include input sidebands and output sidebands. The input sideband is generated by the modulation between the second characteristic frequency and the first characteristic frequency, and the output sideband is generated by the modulation between the second characteristic frequency and the third characteristic frequency.

[0018] Calculate the output equally spaced frequency values, where the output equally spaced frequency values ​​are the equally spaced frequency values ​​of the output sidebands;

[0019] Let the correction factor be the ratio between the output equally spaced frequency values ​​and the theoretical third characteristic frequency;

[0020] The actual characteristic frequency is the product of the correction coefficient and the theoretical characteristic frequency.

[0021] Furthermore, the error range of the output equally spaced frequency values ​​is set to be between ±q.

[0022] Furthermore, the characteristic frequencies used for fault diagnosis are determined, as well as the relationships between these characteristic frequencies, including the following formula:

[0023] ——Formula (3);

[0024] in, Indicates the number of teeth on the sun gear. This indicates a gear ring.

[0025] Furthermore, calculating the theoretical characteristic frequencies also includes:

[0026] Set the input motor speed, and determine the theoretical first characteristic frequency based on the motor speed;

[0027] Based on the relationship between the module, number of teeth, pressure angle, top height, clearance coefficient, and characteristic frequency of the planetary gearbox, the second and third characteristic frequencies of the planetary gearbox are calculated.

[0028] Furthermore, including:

[0029] Verify the corrected characteristic frequencies;

[0030] After the characteristic frequency is corrected, it is determined whether the corresponding frequency value can be found in the spectrum.

[0031] If the corresponding frequency value is found in the spectrogram, the accuracy of the corrected characteristic frequency is verified.

[0032] Furthermore, including:

[0033] By calculating the corrected actual characteristic frequency, the calculated equally spaced frequency values ​​of the sideband between the second and third characteristic frequencies, as well as the calculated equally spaced frequency values ​​of the sideband between the second and first characteristic frequencies, are obtained.

[0034] The vibration signal is detected, a spectrum is generated based on the vibration signal, and the equally spaced frequency values ​​of the sideband between the second and third characteristic frequencies, as well as the equally spaced frequency values ​​of the sideband between the second and first characteristic frequencies, are obtained from the spectrum.

[0035] Compare the calculated equal-interval frequency values ​​with the graphical equal-interval frequency values ​​to determine if they are consistent. If they are consistent, the corrected characteristic frequency is accurate.

[0036] On the other hand, a fault diagnosis feature frequency extraction system for automotive transmission systems is provided, applied to any of the aforementioned fault diagnosis feature frequency extraction methods for automotive transmission systems, including:

[0037] The detection module is used to detect vibration signals from the planetary gearbox.

[0038] The modeling module is used to establish a dynamic mechanism model of the planetary gearbox based on vibration signals;

[0039] The first calculation module is used to calculate the theoretical characteristic frequencies;

[0040] The second calculation module is used to calculate and output equally spaced frequency values;

[0041] In the configuration module, the correction coefficient is set as the ratio between the output equally spaced frequency values ​​and the theoretical third characteristic frequency.

[0042] The third calculation module is used to calculate the actual characteristic frequency, where the actual characteristic frequency is the product of the correction coefficient and the theoretical characteristic frequency.

[0043] The verification module is used to verify the corrected characteristic frequency and determine whether the corrected characteristic frequency can be found in the spectrum. If the corresponding frequency value is found in the spectrum, the accuracy of the corrected characteristic frequency is verified.

[0044] The analysis module diagnoses and identifies fault characteristics based on actual characteristic frequencies.

[0045] Compared with existing technologies, the beneficial effects of this invention are: it proposes a method for extracting characteristic frequencies for fault diagnosis in automotive transmission systems. This method accurately determines the fault characteristic frequencies of the drive assembly in most applications where drive assembly characteristics cannot be conveniently or accurately obtained, without relying on a drive speed sensor. This method reduces the difficulty for operators in diagnosing and analyzing vehicle faults and improves the convenience of diagnosing mechanical transmission faults in automotive drive systems. Attached Figure Description

[0046] Figure 1 Flowchart of a method for extracting feature frequencies for fault diagnosis in automotive transmission systems;

[0047] Figure 2 This is a table of theoretical characteristic frequencies for an input rotational speed of 2400 rpm in this embodiment of the invention;

[0048] Figure 3 This is the actual corrected characteristic frequency table for an input rotational speed of 2400 rpm in this embodiment of the invention;

[0049] Figure 4 This is a connection block diagram of the automotive transmission system fault diagnosis feature frequency extraction system in an embodiment of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] In the description of this invention, unless otherwise stated, "a plurality of" means two or more; the terms "upper," "lower," "left," "right," "inner," "outer," "front end," "rear end," "head," "tail," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0052] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0053] Please refer to the accompanying drawings. This invention provides a technical solution: a method for extracting characteristic frequencies for fault diagnosis of automotive transmission systems, comprising the following steps:

[0054] S102. Establish a dynamic mechanism model for the planetary gearbox;

[0055] Specifically, the vibration signal spectrum of the planetary gearbox is detected. The vibration signal includes a characteristic frequency signal, a first modulation signal that is a multiple of the second and first characteristic frequencies, and a second modulation signal that is a multiple of the second and third characteristic frequencies. The characteristic frequencies include the first, second, and third characteristic frequencies. The second characteristic frequency is the gear meshing frequency of the planetary gearbox, the first characteristic frequency is the motor rotation frequency, and the third characteristic frequency is the planetary carrier characteristic frequency. Without loss of generality, the vibration signal mechanism model is established as follows:

[0056] ——Formula (1);

[0057] in, The second characteristic frequency, The first characteristic frequency, This is the third characteristic frequency.

[0058] Understandably, since the gear meshing frequency is higher than the other two frequencies, it manifests as the carrier frequency. The input and output rotation frequencies are the motor rotation frequency and the planetary carrier characteristic frequency, respectively. The input and output rotation frequencies are lower, manifesting as the modulation frequencies. Therefore, in addition to the three frequency values ​​mentioned above, the actual vibration sensor will also receive the modulation signal of the meshing frequency and the input rotation frequency and its harmonics (amplitude modulation), as well as the modulation signal of the meshing frequency and the output rotation frequency and its harmonics (amplitude modulation). Without loss of generality, we only consider the first-order component of the meshing frequency signal (carrier frequency) and ignore the influence of phase to establish a signal mechanism model for the vibration sensor.

[0059] Furthermore, after simplifying the modulation term of the vibration signal mechanism model, a Fourier transform is performed to obtain the formula for the frequency components of the time-domain signal: ——Formula (2).

[0060] In this process, the time-domain signal of formula (1) is transformed into the frequency-domain signal of formula (2), which takes into account the phenomenological mechanism model of the signal received by the vibration signal sensor. In addition to the meshing frequency, input frequency and its harmonics, and output frequency and its harmonics, there will also be sidebands symmetrically distributed on both sides of the meshing frequency, with the input frequency and output frequency as equal intervals, respectively.

[0061] S104. Determine the characteristic frequencies used for fault diagnosis and the relationship between the characteristic frequencies. The characteristic frequencies include a first characteristic frequency, a second characteristic frequency, and a third characteristic frequency. The second characteristic frequency is the gear meshing frequency of the planetary gearbox, the first characteristic frequency is the motor rotation frequency, and the third characteristic frequency is the planet carrier characteristic frequency.

[0062] S106. Calculate the theoretical characteristic frequency;

[0063] Furthermore, the relationship between the characteristic frequencies is as follows:

[0064] ——Formula (3);

[0065] in, Indicates the number of teeth on the sun gear. This indicates a gear ring.

[0066] Furthermore, calculating the theoretical characteristic frequencies also includes:

[0067] Set the input motor speed, and determine the theoretical first characteristic frequency based on the motor speed;

[0068] Based on the relationship between the module, number of teeth, pressure angle, top height, clearance coefficient, and characteristic frequency of the planetary gearbox, the second and third characteristic frequencies of the planetary gearbox are calculated.

[0069] For example: when the input speed, i.e., the input frequency, is 40Hz, the calculated main characteristic frequency of the planetary gearbox is as follows: Figure 2 As shown, when the input speed Input frequency conversion The output frequency of the planetary carrier side should be found in the spectrum diagram. Input frequency on the sun gear side and meshing frequency However, no corresponding characteristic frequency was actually found in the frequency spectrum. This is because the actual rotational speed was not the originally set value. This causes the characteristic frequencies in the actual spectrum to not strictly correspond to the frequencies in Table 1. Once there is a deviation between the actual switching frequency and the originally set switching frequency, the higher the fault characteristic frequency value, the greater the error in the actual characteristic frequency in the spectrum.

[0070] S108. Set the correction coefficient, and determine the actual characteristic frequency based on the correction coefficient and the theoretical characteristic frequency;

[0071] Specifically, the vibration signal also includes equally spaced sidebands distributed on both sides of the second characteristic frequency. The sidebands include input sidebands and output sidebands. The input sideband is generated by the modulation between the second characteristic frequency and the first characteristic frequency, and the output sideband is generated by the modulation between the second characteristic frequency and the third characteristic frequency.

[0072] Calculate the output equally spaced frequency values, where the output equally spaced frequency values ​​are the equally spaced frequency values ​​of the output sidebands;

[0073] Let the correction factor be the ratio between the output equally spaced frequency values ​​and the theoretical third characteristic frequency;

[0074] The actual characteristic frequency is the product of the correction coefficient and the theoretical characteristic frequency.

[0075] Optionally, the error range of the output equally spaced frequency values ​​can be set to ±q.

[0076] For example, by observing the sidebands in the spectrum, frequencies with equal intervals of 10.7 Hz can be found. Since these frequencies are closest to the output switching frequency of 10.32 Hz, it can be preliminarily determined that they are the output switching frequency. With meshing frequency The sidebands generated by mutual modulation can be used to obtain correction coefficients:

[0077] The error range of the output equally spaced frequency values ​​is q, which is ±0.05.

[0078] Based on this correction coefficient method, the characteristic frequencies in Table 1 are corrected, as shown in Table 3.

[0079] S110. Diagnose and identify fault characteristics based on actual characteristic frequencies.

[0080] Specifically, the corrected characteristic frequencies are verified;

[0081] After the characteristic frequency is corrected, it is determined whether the corresponding frequency value can be found in the spectrum.

[0082] If the corresponding frequency value is found in the spectrogram, the accuracy of the corrected characteristic frequency is verified.

[0083] For example: Based on the corrected characteristic frequencies in Table 2, determine whether the corresponding frequency value can be found in the spectrum. Meshing frequency. With output frequency Phase modulation generates sidebands spaced 10.7 Hz apart, proving that the corresponding sidebands can be found in the spectrum; meshing frequency. With input frequency Phase modulation generates sidebands spaced at 41.5 Hz, proving that the corresponding sidebands can be found in the spectrogram.

[0084] Furthermore, by calculating the corrected actual characteristic frequency, the calculated equally spaced frequency values ​​of the sideband between the second and third characteristic frequencies, as well as the calculated equally spaced frequency values ​​of the sideband between the second and first characteristic frequencies, are obtained.

[0085] The vibration signal is detected, a spectrum is generated based on the vibration signal, and the equally spaced frequency values ​​of the sideband between the second and third characteristic frequencies, as well as the equally spaced frequency values ​​of the sideband between the second and first characteristic frequencies, are obtained from the spectrum.

[0086] Compare the calculated equal-interval frequency values ​​with the graphical equal-interval frequency values ​​to determine if they are consistent. If they are consistent, the corrected characteristic frequency is accurate.

[0087] On the other hand, such as Figure 4 As shown, a fault diagnosis feature frequency extraction system for automotive transmission systems is provided, applied to any of the aforementioned fault diagnosis feature frequency extraction methods for automotive transmission systems, comprising:

[0088] The detection module is used to detect vibration signals from the planetary gearbox.

[0089] The modeling module is used to establish a dynamic mechanism model of the planetary gearbox based on vibration signals;

[0090] The first calculation module is used to calculate the theoretical characteristic frequencies;

[0091] The second calculation module is used to calculate and output equally spaced frequency values;

[0092] In the configuration module, the correction coefficient is set as the ratio between the output equally spaced frequency values ​​and the theoretical third characteristic frequency.

[0093] The third calculation module is used to calculate the actual characteristic frequency, where the actual characteristic frequency is the product of the correction coefficient and the theoretical characteristic frequency.

[0094] The verification module is used to verify the corrected characteristic frequency and determine whether the corrected characteristic frequency can be found in the spectrum. If the corresponding frequency value is found in the spectrum, the accuracy of the corrected characteristic frequency is verified.

[0095] The diagnostic module diagnoses and identifies fault characteristics based on actual characteristic frequencies.

[0096] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for extracting characteristic frequencies for fault diagnosis in automotive transmission systems, characterized in that, include: Establish a dynamic mechanism model for planetary gearboxes; The characteristic frequencies used for fault diagnosis and the relationship between the characteristic frequencies are determined. The characteristic frequencies include a first characteristic frequency, a second characteristic frequency, and a third characteristic frequency. The second characteristic frequency is the gear meshing frequency of the planetary gearbox, the first characteristic frequency is the motor rotation frequency, and the third characteristic frequency is the planet carrier characteristic frequency. Calculate the theoretical characteristic frequencies; Set a correction factor, and determine the actual characteristic frequency based on the correction factor and the theoretical characteristic frequency; Diagnose and identify fault characteristics based on actual characteristic frequencies; The vibration signal spectrum of the planetary gearbox is detected. The vibration signal includes a characteristic frequency signal, a first modulation signal modulated by a second characteristic frequency and a harmonic of the first characteristic frequency, and a second modulation signal modulated by a harmonic of the third characteristic frequency and the second characteristic frequency. Without loss of generality, the vibration signal mechanism model is established as follows: -- Official (1); in, The second characteristic frequency, The first characteristic frequency, The third characteristic frequency, The vibration amplitude is the second characteristic frequency. The amplitude of the i-th harmonic of the first characteristic frequency. The amplitude of the j-th harmonic of the third characteristic frequency; After simplifying the modulation term of the vibration signal mechanism model, a Fourier transform is performed to obtain the formula for the frequency components of the time-domain signal: --Official (2); The vibration signal also includes equally spaced sidebands distributed on both sides of the second characteristic frequency. The sidebands include input sidebands and output sidebands. The input sideband is generated by the modulation between the second characteristic frequency and the first characteristic frequency, and the output sideband is generated by the modulation between the second characteristic frequency and the third characteristic frequency. Calculate the output equally spaced frequency values, where the output equally spaced frequency values ​​are the equally spaced frequency values ​​of the output sidebands; Let the correction factor be the ratio between the output equally spaced frequency values ​​and the theoretical third characteristic frequency; The actual characteristic frequency is the product of the correction coefficient and the theoretical characteristic frequency.

2. The method for extracting feature frequencies for fault diagnosis of automotive transmission systems according to claim 1, characterized in that, The error range for the output equally spaced frequency values ​​is set to ±q, where +q is the upper limit of the error for the output equally spaced frequency values ​​and -q is the lower limit of the error for the output equally spaced frequency values.

3. The method for extracting feature frequencies for fault diagnosis of automotive transmission systems according to claim 1, characterized in that, The characteristic frequencies used for fault diagnosis are determined, as well as the relationships between these characteristic frequencies, including the following formulas: -- Official (3); in, Indicates the number of teeth on the sun gear. Indicates a gear ring, Input the motor speed.

4. The method for extracting feature frequencies for fault diagnosis of automotive transmission systems according to claim 3, characterized in that, Calculating the theoretical characteristic frequencies also includes: Set the input motor speed, and determine the theoretical first characteristic frequency based on the motor speed; Based on the relationship between the module, number of teeth, pressure angle, top height, clearance coefficient, and characteristic frequency of the planetary gearbox, the second and third characteristic frequencies of the planetary gearbox are calculated.

5. The method for extracting feature frequencies for fault diagnosis of automotive transmission systems according to claim 1, characterized in that, include: Verify the corrected characteristic frequencies; After the characteristic frequency is corrected, it is determined whether the corresponding frequency value can be found in the spectrum. If the corresponding frequency value is found in the spectrogram, the accuracy of the corrected characteristic frequency is verified.

6. The method for extracting feature frequencies for fault diagnosis of an automotive transmission system according to claim 5, characterized in that, include: By calculating the corrected actual characteristic frequency, the calculated equally spaced frequency values ​​of the sideband between the second and third characteristic frequencies, as well as the calculated equally spaced frequency values ​​of the sideband between the second and first characteristic frequencies, are obtained. The vibration signal is detected, a spectrum is generated based on the vibration signal, and the equally spaced frequency values ​​of the sideband between the second and third characteristic frequencies, as well as the equally spaced frequency values ​​of the sideband between the second and first characteristic frequencies, are obtained from the spectrum. Compare the calculated equal-interval frequency values ​​with the graphical equal-interval frequency values ​​to determine if they are consistent. If they are consistent, the corrected characteristic frequency is accurate.

7. A fault diagnosis feature frequency extraction system for an automotive transmission system, applied to the fault diagnosis feature frequency extraction method for an automotive transmission system as described in any one of claims 1 to 6, characterized in that, include: The detection module is used to detect vibration signals from the planetary gearbox. The modeling module is used to establish a dynamic mechanism model of the planetary gearbox based on vibration signals; The first calculation module is used to calculate the theoretical characteristic frequencies; The second calculation module is used to calculate and output equally spaced frequency values; In the configuration module, the correction coefficient is set as the ratio between the output equally spaced frequency values ​​and the theoretical third characteristic frequency. The third calculation module is used to calculate the actual characteristic frequency, where the actual characteristic frequency is the product of the correction coefficient and the theoretical characteristic frequency. The verification module is used to verify the corrected characteristic frequency and determine whether the corrected characteristic frequency can be found in the spectrum. If the corresponding frequency value is found in the spectrum, the corrected characteristic frequency is verified to be accurate. The analysis module diagnoses and identifies fault characteristics based on actual characteristic frequencies.

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