Method, device and processor for fault location of electric drive bearing in vehicle

Abstract

The application discloses a kind of fault positioning method, device and processor of electric drive bearing in vehicle, the method comprises: obtaining the first initial rotary variable angle signal of motor rotor in vehicle at different time, wherein, first initial rotary variable angle signal is used to indicate the real-time electrical angle of the position where motor rotor is located;First initial rotary variable angle signal is converted, and target rotary variable angle acceleration signal is obtained, wherein, target rotary variable angle acceleration signal is used to indicate the rotary variable angle acceleration of electric drive bearing;Based on target rotary variable angle acceleration signal, fault prediction is carried out to electric drive bearing, and the fault prediction result of electric drive bearing is obtained;In response to fault prediction result for electric drive bearing failure, fault positioning is carried out to electric drive bearing, and the fault positioning result is obtained, wherein, fault positioning result is used to indicate the position of electric drive bearing where failure occurs.The application solves the technical problem of low fault detection efficiency of electric drive bearing.

Description

Technical Field

[0001] This invention relates to the field of vehicles, and more specifically, to a method, apparatus, and processor for protecting an electric motor in a vehicle. Background Technology

[0002] Currently, in vehicles, electric drive bearings are core components of the electric drive system. Their operating environment is extremely harsh, often requiring them to withstand the impact and vibration caused by high speed, high load, frequent start-stop, and complex road conditions. This makes electric drive bearings prone to the following failures: wear, cracks, overheating, and lubrication failure.

[0003] However, if any of the aforementioned faults occur in the electric drive bearing, fault detection often relies on manual labor or additional integrated equipment. These fault detection methods require a considerable amount of time to complete, resulting in low efficiency in electric drive bearing fault detection.

[0004] There is currently no effective solution to the technical problem of low fault detection efficiency of electric drive bearings. Summary of the Invention

[0005] This invention provides a method, apparatus, and processor for locating faults in electric drive bearings in vehicles, thereby at least addressing the technical problem of low fault detection efficiency in electric drive bearings.

[0006] According to one aspect of the present invention, a method for fault location of an electric drive bearing in a vehicle is provided. The method includes: acquiring a first initial resolver angle signal of a motor rotor in the vehicle at different times, wherein the first initial resolver angle signal is used to represent the real-time electrical angle of the motor rotor's position; converting the first initial resolver angle signal to obtain a target resolver angular acceleration signal, wherein the target resolver angular acceleration signal is used to represent the resolver angular acceleration of the electric drive bearing, and the electric drive bearing and the motor rotor are deployed at the same connecting shaft; performing fault prediction on the electric drive bearing based on the target resolver angular acceleration signal to obtain a fault prediction result for the electric drive bearing; and, in response to the fault prediction result indicating that the electric drive bearing has failed, performing fault location on the electric drive bearing to obtain a fault location result, wherein the fault location result indicates the location of the fault on the electric drive bearing.

[0007] Optionally, converting the first initial resolver angle signal to obtain the target resolver angular acceleration signal includes: performing angle conversion on the first initial resolver angle signal to obtain a second initial resolver angle signal, wherein the second initial resolver angle signal is used to represent the resolver angle of the electric drive bearing; and performing differential processing on the second initial resolver angle signal to obtain the target resolver angular acceleration signal.

[0008] Optionally, based on the target resolver angular acceleration signal, fault prediction is performed on the electric drive bearing to obtain the fault prediction result of the electric drive bearing, including: in response to the total number of target resolver angular acceleration signals being the same as the preset number, after verifying the target resolver angular acceleration signal and the sample resolver angular acceleration signal, the target resolver angular acceleration signal is standardized by using the first average value and the first variance of the resolver angular acceleration corresponding to the sample resolver angular acceleration signal; based on the transformed target resolver angular acceleration signal, fault prediction is performed on the electric drive bearing to obtain the fault prediction result.

[0009] Optionally, the method further includes: after verifying the target angular acceleration signal and the sample angular acceleration signal, obtaining the difference result between the target angular acceleration signal and the sample angular acceleration signal; based on the converted target angular acceleration signal, performing fault prediction on the electric drive bearing to obtain the fault prediction result of the electric drive bearing, including: performing offset detection on the converted target angular acceleration signal to obtain an offset detection result, wherein the offset detection result is used to represent the offset of the second average value of the angular acceleration corresponding to the target angular acceleration signal; determining the first score and the first weight of the difference result, and the second score and the second weight of the offset detection result; and using the first weight and the second weight respectively, performing a weighted summation of the first score and the second score to complete the fault prediction of the electric drive bearing and obtain the fault prediction result.

[0010] Optionally, the method further includes: adjusting the first weight and the second weight in response to the next fault prediction result being that the electric drive bearing has failed; and using the adjusted first weight and the adjusted second weight to perform a weighted summation of the first score and the second score to complete the fault prediction of the electric drive bearing and obtain the fault prediction result.

[0011] Optionally, in response to the fault prediction result indicating that the electric drive bearing has failed, the electric drive bearing is located to obtain a fault location result, including: in response to the fault prediction result indicating that the electric drive bearing has failed, determining the initial resonance component signal of the sub-component of the electric drive bearing; enhancing the initial resonance component signal to obtain a target resonance component signal; determining the energy proportion of the target resonance component signal in the neighborhood of the preset fault frequency of the sub-component; and locating the electric drive bearing based on the energy proportion to obtain a fault location result.

[0012] Optionally, based on the energy ratio, fault location is performed on the electric drive bearing to obtain fault location results, including: in response to the energy ratio being greater than the limit ratio, determining the target energy ratio from the energy ratio, wherein the target energy ratio is greater than the remaining energy ratio in the energy ratio excluding the target energy ratio; and performing fault location on the sub-component where the target resonance component signal corresponding to the target energy ratio appears to obtain fault location results.

[0013] Optionally, the method further includes: acquiring initial operating state signals of the motor rotor at different times; determining valid operating state signals from the initial operating state signals, wherein the number of samples of the valid operating state signals is greater than the remaining number of samples in the initial operating state signals excluding the number of samples of the valid operating state signals; and extracting a first initial resolver angle signal from the valid operating state signals.

[0014] According to one aspect of the present invention, a fault location test device for an electric drive bearing in a vehicle is provided. The device may include: a first acquisition unit, configured to acquire a first initial resolver angle signal of a motor rotor in the vehicle at different times, wherein the first initial resolver angle signal is used to represent the real-time electrical angle of the motor rotor's position; a conversion unit, configured to convert the first initial resolver angle signal to obtain a target resolver angular acceleration signal, wherein the target resolver angular acceleration signal is used to represent the resolver angular acceleration of the electric drive bearing, and the electric drive bearing and the motor rotor are deployed at the same connecting shaft; a prediction unit, configured to perform fault prediction on the electric drive bearing based on the target resolver angular acceleration signal, and obtain a fault prediction result for the electric drive bearing; and a location unit, configured to locate the electric drive bearing in response to the fault prediction result indicating that the electric drive bearing has failed, and obtain a fault location result, wherein the fault location result indicates the location of the fault on the electric drive bearing.

[0015] According to another aspect of the present invention, a processor is also provided. The processor is used to run a program, wherein the program, when run by the processor, executes the fault location method for an electric drive bearing in a vehicle according to the embodiments of the present invention.

[0016] According to another aspect of the embodiments of the present invention, a vehicle is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the fault location method for an electric drive bearing in a vehicle according to various embodiments of the present invention during runtime.

[0017] According to another aspect of the present invention, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the fault location method for an electric drive bearing in a vehicle according to the embodiments of the present invention.

[0018] According to another aspect of the present invention, a computer program product is also provided, the computer program product including a computer program, wherein the computer program, when executed by a processor, implements the fault location method for electric drive bearings in vehicles according to the present invention.

[0019] According to another aspect of the present invention, a computer program product is also provided, including a non-volatile computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the fault location method for an electric drive bearing in a vehicle according to the present invention.

[0020] According to another aspect of the embodiments of the present invention, the embodiments of the present application also provide a computer program, which, when executed by a processor, implements the fault location method for electric drive bearings in vehicles described in the above embodiments of the present invention.

[0021] In this embodiment of the invention, when locating a fault in an electric drive bearing in a vehicle, the first initial resolver angle signal of the motor rotor at different times can be acquired. The acquired first initial resolver angle signal is converted to obtain a target resolver angle acceleration signal. Based on the target resolver angle acceleration signal, the electric drive bearing is fault-predicted to obtain a fault prediction result. In response to the fault prediction result indicating that the electric drive bearing has failed, the electric drive bearing is located to obtain a fault location result. This achieves the goal of detecting whether the electric drive bearing has failed without relying on additional equipment, thereby solving the technical problem of low fault detection efficiency of electric drive bearings and thus achieving the technical effect of improving the fault detection efficiency of electric drive bearings. Attached Figure Description

[0022] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0023] Figure 1 This is a flowchart of a method for locating faults in an electric drive bearing in a vehicle according to an embodiment of the present invention;

[0024] Figure 2(a) is a flowchart of an abnormality warning and fault location method for an electric drive bearing according to an embodiment of the present invention;

[0025] Figure 2(b) is a schematic diagram of a data transmission process according to an embodiment of the present invention;

[0026] Figure 2(c) is a flowchart of a weight adjustment method according to an embodiment of the present invention;

[0027] Figure 3This is a schematic diagram of a fault location device for an electric drive bearing in a vehicle according to an embodiment of the present invention;

[0028] Figure 4 This is a schematic diagram of a vehicle according to an embodiment of the present invention. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0031] According to an embodiment of the present invention, a method for fault location of an electric drive bearing in a vehicle is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0032] Figure 1 This is a flowchart of a method for locating faults in an electric drive bearing in a vehicle according to an embodiment of the present invention, as shown below. Figure 1 As shown, the method may include the following steps:

[0033] Step S101: Obtain the first initial resolver angle signal of the motor rotor in the vehicle at different times, wherein the first initial resolver angle signal is used to represent the real-time electrical angle of the motor rotor position.

[0034] In the technical solution provided by step S101 of the present invention, the first initial resolver angle signal can be used to represent the real-time electrical angle of the motor rotor position, and the first initial resolver angle signal can be an electrical angle. The first initial resolver angle signal can be a resolver angle signal at a sampling frequency, which can be set according to the type of electric drive bearing. For example, the sampling frequency can be 10 kHz, and the resolver angle signal at a 10 kHz sampling frequency can be represented by A(t). This is only an example and not a specific limitation.

[0035] In this embodiment, the first initial resolver angle signal of the motor rotor in the vehicle at different times is acquired. Optionally, this embodiment can acquire the initial operating state signal of the motor rotor at different times, and divide the acquired initial operating state signal to obtain the first initial resolver angle signal, speed signal, and torque signal of the motor rotor at different times. For example, the speed signal can be represented by n(t), and the torque signal can be represented by T(t).

[0036] Optionally, the collected initial operating state signals can be filtered to obtain valid operating state signals. By dividing the obtained valid operating state signals, the first initial resolver angle signal, speed signal, and torque signal of the motor rotor at different times can be obtained; or, the first initial resolver angle signal, speed signal, and torque signal of the motor rotor at different times can be extracted from the obtained valid operating state signals. This is merely an example and not a specific limitation.

[0037] Step S102: The first initial resolver angle signal is converted to obtain the target resolver angle acceleration signal, wherein the target resolver angle acceleration signal is used to represent the resolver angle acceleration of the electric drive bearing, and the electric drive bearing and the motor rotor are deployed at the same connecting shaft.

[0038] In the technical solution provided by step S102 of the present invention, the target rotational angular acceleration signal can be used to represent the rotational angular acceleration of the electric drive bearing. For example, the rotational angular acceleration of the electric drive bearing can be obtained from the dataset of rotational angular acceleration to be detected {α... rms1_t ,α rms2_t ,…,α rmsi_t ,…,α rms50_t From the above, the rotational angular acceleration of the electric drive bearing can be represented by α(t), where the unit of α(t) is degrees per second. 2 (° / s 2 (This is just an example and is not a specific limitation.)

[0039] In this embodiment, the electric drive bearing and the motor rotor are deployed at the same connecting shaft.

[0040] In this embodiment, after acquiring the first initial resolver angle signal of the motor rotor in the vehicle at different times, the first initial resolver angle signal is converted to obtain the target resolver angular acceleration signal. Optionally, based on the acquired first initial resolver angle signal, this embodiment performs angle conversion on the acquired first initial resolver angle signal, and determines the target resolver angular acceleration signal based on the converted first initial resolver angle signal, thereby achieving the purpose of determining the resolver angular acceleration of the electric drive bearing.

[0041] Optionally, the target rotation angle acceleration signal can be determined based on the converted first initial rotation angle signal. For example, by performing acceleration calculations on the converted first initial rotation angle signal, the target rotation angle acceleration signal can be obtained.

[0042] Step S103: Based on the target resolver angular acceleration signal, perform fault prediction on the electric drive bearing to obtain the fault prediction result of the electric drive bearing.

[0043] In the technical solution provided by step S103 of the present invention, the fault prediction result can be used to indicate whether the electric drive bearing has failed. For example, the fault prediction result can indicate that the electric drive bearing has failed or that the electric drive bearing has not failed; this is only an example and is not specifically limited.

[0044] In this embodiment, after converting the first initial resolver angle signal to obtain the target resolver angle acceleration signal, fault prediction of the electric drive bearing is performed based on the target resolver angle acceleration signal to obtain the fault prediction result of the electric drive bearing. Optionally, this embodiment can determine the number of target resolver angle acceleration signals based on the obtained target resolver angle acceleration signals. Based on the determined number, fault prediction of the electric drive bearing is performed to obtain the fault prediction result of the electric drive bearing, thereby achieving the purpose of determining whether the electric drive bearing has failed.

[0045] Optionally, based on the determined quantities, fault prediction is performed on the electric drive bearing to obtain fault prediction results. For example, the relationship between the quantities and preset quantities is compared. If the quantities are greater than or equal to the preset quantities, the target rotation angle acceleration signal is standardized, and drift detection is performed on the standardized target rotation angle acceleration signal to obtain drift detection results. Alternatively, if the quantities are greater than or equal to the preset quantities, drift detection is performed directly on the target rotation angle acceleration signal to obtain drift detection results. Based on the drift detection results, fault prediction is performed on the electric drive bearing to obtain fault prediction results, thereby achieving the goal of determining whether the electric drive bearing has failed.

[0046] Step S104: In response to the fault prediction result that the electric drive bearing has failed, the electric drive bearing is located to obtain the fault location result, wherein the fault location result is used to indicate the location of the fault on the electric drive bearing.

[0047] In the technical solution provided by step S104 of the present invention, the fault location result is used to indicate the location of the fault on the electric drive bearing. For example, the location of the fault on the electric drive bearing can be the location of the faulty sub-component. The location of the sub-component can include at least one of the following: the location of the inner ring, the location of the outer ring, the location of the rolling element, and the location of the cage, etc. This is only an example and is not specifically limited.

[0048] In this embodiment, after predicting the fault of the electric drive bearing based on the target rotational angular acceleration signal and obtaining the fault prediction result, in response to the fault prediction result indicating that the electric drive bearing has failed, the fault location of the electric drive bearing is performed to obtain the fault location result. Optionally, based on the fault prediction result obtained in this embodiment, the content represented by the fault prediction result is analyzed. If the analyzed fault prediction result indicates that the electric drive bearing has failed, the fault location of the electric drive bearing is performed based on the initial resonance component signal of the sub-component of the electric drive bearing, thereby obtaining the fault location result. This achieves the purpose of determining the location of the fault on the electric drive bearing.

[0049] Optionally, fault location can be obtained by locating the electric drive bearing based on the initial resonant component signal of its sub-components. For example, by determining the energy percentage of the initial resonant component signal within a preset fault frequency neighborhood of the sub-component, and then locating the electric drive bearing based on the determined energy percentage, fault location results can be obtained. Alternatively, the initial resonant component signal of the electric drive bearing's sub-components can be enhanced to obtain a target resonant component signal. Then, the energy percentage of the target resonant component signal within a preset fault frequency neighborhood of the sub-component can be determined. Based on the determined energy percentage, fault location can be obtained for the electric drive bearing, and fault location results can be obtained.

[0050] It should be noted that the fault location method for electric drive bearings in vehicles in this application is not only applicable to specific types of vehicles (e.g., school buses and fire trucks), but also to other types of vehicles, including but not limited to trucks, buses, and cars. In other words, as long as fault location of electric drive bearings in vehicles is involved, regardless of the type of vehicle, the fault location method for electric drive bearings in vehicles in this application can be used to locate the fault in the electric drive bearing.

[0051] In steps S101 to S104 of this application, when fault location is performed on the electric drive bearing in a vehicle, the first initial resolver angle signal of the motor rotor at different times can be obtained. The obtained first initial resolver angle signal is converted to obtain the target resolver angle acceleration signal. Based on the target resolver angle acceleration signal, fault prediction is performed on the electric drive bearing to obtain the fault prediction result of the electric drive bearing. In response to the fault prediction result indicating that the electric drive bearing has failed, fault location is performed on the electric drive bearing to obtain the fault location result. Thus, the purpose of detecting whether the electric drive bearing has failed is achieved without relying on additional equipment, thereby solving the technical problem of low fault detection efficiency of electric drive bearings and achieving the technical effect of improving the fault detection efficiency of electric drive bearings.

[0052] The method described in this embodiment will be further described below.

[0053] As an optional embodiment, step S102, converting the first initial resolver angle signal to obtain the target resolver angular acceleration signal, includes: performing angle conversion on the first initial resolver angle signal to obtain a second initial resolver angle signal, wherein the second initial resolver angle signal is used to represent the resolver angle of the electric drive bearing; and performing differential processing on the second initial resolver angle signal to obtain the target resolver angular acceleration signal.

[0054] In this embodiment, the aforementioned second initial resolver angle signal can be used to represent the resolver angle of the electric drive bearing, which can be a mechanical angle. For example, the resolver angle of the electric drive bearing can be represented by θ(t), where the unit of θ(t) is degrees (°). This is only an example and is not specifically limited.

[0055] In this embodiment, after acquiring the first initial resolver angle signal of the motor rotor in the vehicle at different times, the first initial resolver angle signal is converted to obtain a second initial resolver angle signal. Optionally, this embodiment can obtain the second initial resolver angle signal by converting the acquired first initial resolver angle signal. For example, mechanical angle conversion can be performed on the acquired first initial resolver angle signal to obtain the second initial resolver angle signal, thereby achieving the purpose of determining the resolver angle of the electric drive bearing.

[0056] Optionally, the obtained first initial resolver angle signal can be converted to obtain a second initial resolver angle signal, which can be achieved by formula (1):

[0057]

[0058] In this embodiment, after converting the first initial resolver angle signal to obtain the second initial resolver angle signal, differential processing is performed on the second initial resolver angle signal to obtain the target resolver angular acceleration signal. Optionally, this embodiment performs differential processing on the second initial resolver angle signal based on the converted signal to obtain the target resolver angular acceleration signal, thereby achieving the goal of determining the resolver angular acceleration of the electric drive bearing and thus improving the accuracy of the resolver angular acceleration.

[0059] Optionally, the target rotation angle acceleration signal can be obtained by differential processing of the above-mentioned second initial rotation angle signal, which can be achieved by formula (2):

[0060]

[0061] Δt=1 / f s =0.0001s (3)

[0062] Among them, f s It can be used to represent the sampling frequency of a sampling point (in Hz), and Δt can be used to represent the time interval between adjacent sampling points.

[0063] The following section further describes the steps of the above embodiment for predicting the fault of the electric drive bearing based on the target resolver angular acceleration signal, and obtaining the fault prediction result of the electric drive bearing.

[0064] As an optional embodiment, step S103, based on the target resolver angular acceleration signal, performs fault prediction on the electric drive bearing to obtain the fault prediction result of the electric drive bearing, including: in response to the total number of target resolver angular acceleration signals being the same as the preset number, after verifying the target resolver angular acceleration signal and the sample resolver angular acceleration signal, using the first average value and the first variance of the resolver angular acceleration corresponding to the sample resolver angular acceleration signal to perform a standardized transformation on the target resolver angular acceleration signal; based on the transformed target resolver angular acceleration signal, performs fault prediction on the electric drive bearing to obtain the fault prediction result.

[0065] In this embodiment, the aforementioned sample rotational angular acceleration signal can be obtained from the normal sample rotational angular acceleration dataset {α} rms1_h ,α rms2_h ,…,α rmsi_h ,…,α rms1000_h Obtained from}

[0066] In this embodiment, the preset quantity can be set according to the required accuracy of fault prediction. For example, the preset quantity can be 50 or 60. The values ​​here are only illustrative and are not specifically limited.

[0067] In this embodiment, after converting the first initial revolute angle signal to obtain the target revolute angle acceleration signal, in response to the total number of target revolute angle acceleration signals being the same as a preset number, after verifying the target revolute angle acceleration signal and the sample revolute angle acceleration signal, the first average value and the first variance of the revolute angle acceleration corresponding to the sample revolute angle acceleration signal are used. Optionally, this embodiment can determine the number of target revolute angle acceleration signals based on obtaining the target revolute angle acceleration signal. Based on the determined number, the relationship between the number and the preset number is compared. If the number is the same as the preset number, then after performing a difference test on the target revolute angle acceleration signal and the sample revolute angle acceleration signal, the first average value and the first variance of the revolute angle acceleration corresponding to the sample revolute angle acceleration signal are used to standardize the target revolute angle acceleration signal.

[0068] Optionally, the first average value and first variance of the rotational angular acceleration corresponding to the above sample rotational angular acceleration signal can be achieved by the following equations (4) and (6):

[0069]

[0070] Where μ0 can be used to represent the first average value mentioned above, and X can be used to represent the first average value mentioned above. i It can be used to represent the above sample rotation angle acceleration signal, and n can be used to represent the number of the above sample rotation angle acceleration signals.

[0071]

[0072] Where μ1 can be used to represent the second average value of the rotational angular acceleration corresponding to the above target rotational angular acceleration signal, Y j It can be used to represent the above target rotational angular acceleration signal, and m can be used to represent the number of the above target rotational angular acceleration signals.

[0073]

[0074] Wherein, σ0 can be used to represent the first variance mentioned above.

[0075]

[0076] Wherein, σ1 can be used to represent the second variance of the rotational angular acceleration corresponding to the above target rotational angular acceleration signal.

[0077] Optionally, after performing a difference test on the target rotational angular acceleration signal and the sample rotational angular acceleration signal, the degree of difference between the first average and the second average, as well as the degrees of freedom, are also obtained. The above process can be achieved by the following equations (8) and (9):

[0078]

[0079] Where t can be used to represent the aforementioned degree of difference, and df can be used to represent the aforementioned degree of freedom.

[0080] In this embodiment, after standardizing the target rotational angular acceleration signal using the first average value and first variance of the rotational angular acceleration corresponding to the sample rotational angular acceleration signal, fault prediction of the electric drive bearing is performed based on the transformed target rotational angular acceleration signal to obtain a fault prediction result. Optionally, this embodiment, based on the obtained first average value and first variance, uses the first average value and first variance to standardize the target rotational angular acceleration signal; drift detection is performed on the standardized target rotational angular acceleration signal to obtain a drift detection result. Based on the drift detection result, fault prediction of the electric drive bearing is performed to obtain a fault prediction result, thereby achieving the goal of determining whether the electric drive bearing has failed, and thus realizing the technical effect of improving the accuracy of fault prediction of the electric drive bearing.

[0081] Optionally, the target rotation angular acceleration signal can be standardized using the first average value and the first variance, which can be achieved by the following equation (10):

[0082]

[0083] Among them, Z j It can be used to represent the converted target rotational angular acceleration signal.

[0084] The following section further describes the steps of the above embodiment for predicting the fault of the electric drive bearing based on the converted target rotational angular acceleration signal, and obtaining the fault prediction result of the electric drive bearing.

[0085] As an optional embodiment, the method further includes: after verifying the target angular acceleration signal and the sample angular acceleration signal, obtaining the difference result between the target angular acceleration signal and the sample angular acceleration signal; based on the converted target angular acceleration signal, performing fault prediction on the electric drive bearing to obtain a fault prediction result for the electric drive bearing, including: performing offset detection on the converted target angular acceleration signal to obtain an offset detection result, wherein the offset detection result is used to represent the offset of the second average value of the angular acceleration corresponding to the target angular acceleration signal; determining a first score and a first weight of the difference result, and a second score and a second weight of the offset detection result; and using the first weight and the second weight respectively, performing a weighted summation of the first score and the second score to complete the fault prediction of the electric drive bearing and obtain a fault prediction result.

[0086] In this embodiment, after examining the target rotational angular acceleration signal and the sample rotational angular acceleration signal, a difference result between the target rotational angular acceleration signal and the sample rotational angular acceleration signal is obtained. Optionally, after examining the difference between the target rotational angular acceleration signal and the sample rotational angular acceleration signal, the degree of difference between the first average value and the second average value, as well as the degrees of freedom, are also obtained. Then, a difference result corresponding to the aforementioned degree of difference and degrees of freedom can be obtained. For example, this difference result can be represented by p. This is only an example and is not specifically limited.

[0087] In this embodiment, the offset detection may include positive offset detection and negative offset detection.

[0088] In this embodiment, the aforementioned offset detection result can be used to represent the offset of the second average value of the rotational angular acceleration corresponding to the target rotational angular acceleration signal. For example, the aforementioned offset detection result may include positive offset detection result and negative offset detection result, and the positive offset detection result can be used... To represent, the negative offset detection result can be used To express.

[0089] In this embodiment, after obtaining the difference between the target rotational angular acceleration signal and the sample rotational angular acceleration signal, offset detection is performed on the converted target rotational angular acceleration signal to obtain an offset detection result. Optionally, based on the above difference result, this embodiment performs positive offset detection on the converted target rotational angular acceleration signal to obtain a positive offset detection result, and performs negative offset detection on the converted target rotational angular acceleration signal to obtain a negative offset detection result, thereby achieving the purpose of offset detection on the converted target rotational angular acceleration signal.

[0090] Optionally, the converted target rotation angular acceleration signal is subjected to positive offset detection to obtain the positive offset detection result, which can be achieved by the following equation (11):

[0091]

[0092] Where r can be used to represent the allowable offset magnitude. For example, r = 0.2σ0.

[0093] Optionally, negative offset detection is performed on the converted target rotation angle acceleration signal to obtain the negative offset detection result, which can be achieved by the following equation (12):

[0094]

[0095] For example,

[0096] In this embodiment, the aforementioned first score can be represented by S. p The first weight mentioned above can be represented by W. p The second score mentioned above can be represented as... To represent this, the aforementioned second weight can be expressed as... To express.

[0097] In this embodiment, after offset detection is performed on the converted target rotation angular acceleration signal to obtain the offset detection result, a first score and a first weight of the difference result, as well as a second score and a second weight of the offset detection result are determined. The first score and the second score are then weighted and summed using the first weight and the second weight respectively to complete the fault prediction of the electric drive bearing, thus obtaining the fault prediction result. Optionally, based on the offset detection result, this embodiment can determine the first score and the first weight of the difference result, as well as the second score and the second weight of the offset detection result. The first score is adjusted using the first weight to obtain an adjusted first score, and the second score is adjusted using the second weight to obtain an adjusted second score. The adjusted first score and the adjusted second score are summed to obtain a sum value, which is used as the fault prediction result of the electric drive bearing. This achieves the goal of determining whether the electric drive bearing has failed, thereby improving the accuracy of fault prediction for electric drive bearings.

[0098] Optionally, the first score and the second score are weighted and summed using the first weight and the second weight respectively to complete the fault prediction of the electric drive bearing and obtain the fault prediction result, which can be achieved by the following formula (13):

[0099]

[0100] Among them, Score can be used to represent the fault prediction result (also known as the comprehensive anomaly score), W p , It can be used to represent the importance of statistically significant differences and actual engineering deviations in the determination of anomaly warnings, and to constrain... S p , They can be used to represent p-value and S, respectively. j The score is based on the value.

[0101] The fault detection steps described above in this embodiment will be further explained below.

[0102] As an optional embodiment, in response to the next fault prediction result being that the electric drive bearing has failed, the first weight and the second weight are adjusted; the first score and the second score are weighted and summed using the adjusted first weight and the adjusted second weight respectively, so as to complete the fault prediction of the electric drive bearing and obtain the fault prediction result.

[0103] In this embodiment, in response to the next fault prediction result indicating a fault in the electric drive bearing, the first weight and the second weight are adjusted. The first score and the second score are then weighted and summed using the adjusted first weight and the adjusted second weight to complete the fault prediction for the electric drive bearing, thus obtaining the fault prediction result. Optionally, this embodiment analyzes the next fault prediction result. If the analyzed result indicates a fault in the electric drive bearing, it means an abnormal warning has been accumulated, and the first weight and the second weight are adjusted. The first score is adjusted using the adjusted first weight to obtain an adjusted first score, and the second score is adjusted using the adjusted second weight to obtain an adjusted second score. The adjusted first score and the adjusted second score are then summed to obtain a sum value, which is used as the fault prediction result for the electric drive bearing. This achieves the goal of determining whether the electric drive bearing has failed, thereby improving the accuracy of fault prediction for the electric drive bearing.

[0104] For example, set: p > 0.05, S p =0 (healthy); 0.01≤p<0.05, S p =1 (warning); p≤0.01, S p =2 (dangerous); Set S j <2σ0 Finally, if the score is less than 0.5, the current state of the electric drive bearing is determined to be healthy; if the score is less than 1, the current state of the electric drive bearing is determined to be a warning state; if the score is greater than or equal to 1, the current state of the electric drive bearing is determined to be dangerous.

[0105] For example, the above method of adjusting the first and second weights can be as follows: the initial weight is set to W. p =0.5, and The system automatically adjusts W for each accumulated abnormal warning. p and The ratio is adjusted with a single step size ΔW = 0.05. The core of the adaptive early warning strategy based on dynamic weight optimization is to dynamically adjust the statistical significance (p-value) and engineering offset (S). j The weight allocation of values ​​is used to improve the sensitivity of fault detection. Among them, the adaptive early warning strategy based on dynamic weight optimization aims to minimize the false alarm rate and constructs the objective function shown in equation (14):

[0106]

[0107] In order to dynamically adjust the weights, it is necessary to quantize the p-value and S. j The correlation between the values ​​and the actual fault state, where p-value and S... j The correlation coefficients between the values ​​and the actual fault states are shown in equations (15) and (16) below:

[0108]

[0109] Where T can be used to represent the total number of historical cumulative abnormal warnings, y t It can be used to represent binary labels (0 = healthy, 1 = abnormal (including: warning + danger)). p-value and S, respectively j The higher the correlation coefficient between the value and the mean of y, the stronger the correlation between the indicator and the fault state. If... Then increase like Then increase Continuously monitor and update the weights in formula (13) until the system is stable.

[0110] The following section further describes the steps of responding to the fault prediction result that the electric drive bearing has failed, locating the fault in the electric drive bearing, and obtaining the fault location result.

[0111] As an optional embodiment, step S104, in response to the fault prediction result indicating a fault in the electric drive bearing, involves fault location of the electric drive bearing to obtain a fault location result, including: in response to the fault prediction result indicating a fault in the electric drive bearing, determining the initial resonant component signal of the sub-component of the electric drive bearing; enhancing the initial resonant component signal to obtain a target resonant component signal; determining the energy proportion of the target resonant component signal in the neighborhood of a preset fault frequency of the sub-component; and based on the energy proportion, performing fault location of the electric drive bearing to obtain a fault location result.

[0112] In this embodiment, the aforementioned sub-components may include: an inner ring, an outer ring, rolling elements, and a cage.

[0113] In this embodiment, the initial resonant component signal of the aforementioned sub-component can be represented by H. k ={H i H o H r H c} is used to represent this.

[0114] In this embodiment, the aforementioned target resonance component signal can be represented by H. k’ ={H i’ H o’ H r’ H c’} is used to represent this.

[0115] In this embodiment, after performing fault prediction on the electric drive bearing based on the target rotational angular acceleration signal and obtaining the fault prediction result, in response to the fault prediction result indicating a fault in the electric drive bearing, the initial resonance component signal of the sub-component of the electric drive bearing is determined; the initial resonance component signal is then enhanced to obtain the target resonance component signal. Optionally, based on the fault prediction result of the electric drive bearing obtained in this embodiment, the content represented by the fault prediction result is parsed. If the parsed fault prediction result indicates a fault in the electric drive bearing, the initial resonance component signal of the sub-component of the electric drive bearing is determined, and the target resonance component signal is obtained by enhancing the initial resonance component signal.

[0116] Optionally, the initial resonant component signal of the sub-component of the electric drive bearing can be determined by the following equations (17) to (29):

[0117]

[0118] Where m represents the number of rolling elements, d represents the diameter of the rolling elements, D represents the bearing pitch circle diameter, and α represents the bearing contact angle. For example, if the bearing model is a 6008 deep groove ball bearing, then m is 12, d is 7.938 mm, D is 54 mm, and α is 0°. The calculated O...i =6.882, O o =5.118, O r =3.328, O c =0.427.

[0119] f i =O i ×f n (twenty one)

[0120] f o =O o ×f n (twenty two)

[0121] f r =O r ×f n (twenty three)

[0122] f c =O c ×f n (twenty four)

[0123] Among them, f n = n / 60, where n is the rotational speed. k ={O i O o O r O c} can be used to represent the theoretical fault order of four fault types, f k ={f i f o f r f c} can be used to represent the theoretical fault frequency of four fault types. After acquiring the abnormal signal, the primary feature enhancement of the signal is achieved based on the resonance coefficient decomposition. Assuming the original signal is x, the original signal can be decomposed into a high resonance component H and a low resonance component L. At this time, the improved Q-factor resonance coefficient decomposition is performed. The Q-factor can be defined as follows (25):

[0124]

[0125] Where ζ can be used to represent the damping ratio, for example, ζ = 0.03. Then, a multi-Q factor atomic dictionary is constructed, and a set of wavelet basis functions is generated for each fault type k, as shown in equation (26):

[0126]

[0127] Here, A can be used to represent the normalization coefficient, and β can be used to represent the attenuation coefficient. For each Q kThe signal is decomposed into high and low resonance components through L1-TV joint optimization, and the objective function is set as shown in equation (27):

[0128]

[0129] in, It can be used to ensure that the error between the decomposed signal and the original signal is minimized, λ1‖H k ||1 can be used to ensure high resonance component H for the L1 norm. k Exhibiting sparsity, λ2‖L k || TV It can be used to piecewise smooth the low-resonance components of the TV norm to suppress random noise, and λ1=0.1·median(|x|) can be used to control the sparsity of fault features. This can be used to control the smoothness of the background component. Finally, according to equations (28) and (29), the high and low resonance components are iteratively updated using the Alternating Direction Multiplier Method (ADMM) until convergence:

[0130]

[0131] Alternatively, the target resonant component signal can be obtained by enhancing the initial resonant component signal using the transfer function shown in equation (30):

[0132]

[0133] Here, N can be used to represent the order, for example, N = 6. Through G... k (f) For each H k Perform filtering, where, when f = f k When f deviates from f, the signal does not attenuate; when f deviates from f, the signal does not atten k At that time, the degree of attenuation is determined by Q. k The output H is determined by both the order N and the order N. k’ .

[0134] In this embodiment, the preset fault frequency can be the theoretical fault frequency f. k .

[0135] In this embodiment, the aforementioned energy percentage can be represented by E. k To express.

[0136] In this embodiment, after enhancing the initial resonant component signal to obtain the target resonant component signal, the energy proportion of the target resonant component signal within the preset fault frequency neighborhood of the sub-component is determined. Based on the energy proportion, the electric drive bearing is located to obtain the fault location result. Optionally, this embodiment, based on obtaining the target resonant component signal, can determine the energy proportion of the target resonant component signal within the preset fault frequency neighborhood of the sub-component. Based on the relationship between the energy proportion and the limiting proportion, the electric drive bearing is located to obtain the fault location result. This achieves the goal of determining the location of the fault on the electric drive bearing, thereby improving the technical effect of fault detection efficiency for electric drive bearings.

[0137] Optionally, the energy proportion of the target resonant component signal in the neighborhood of the preset fault frequency of the sub-component can be determined by the following equation (31):

[0138]

[0139] Where, Δf = 0.05 * f k .

[0140] The following section further describes the steps of the above embodiment for fault location of electric drive bearings based on energy ratio to obtain fault location results.

[0141] As an optional embodiment, fault location of the electric drive bearing is performed based on the energy ratio to obtain the fault location result, including: in response to the energy ratio being greater than the limit ratio, determining the target energy ratio from the energy ratio, wherein the target energy ratio is greater than the remaining energy ratio in the energy ratio other than the target energy ratio; and performing fault location on the sub-component where the target resonance component signal corresponding to the target energy ratio appears to obtain the fault location result.

[0142] In this embodiment, the target energy percentage is greater than the remaining energy percentage other than the target energy percentage.

[0143] In this embodiment, after determining the energy percentage of the target resonant component signal in the neighborhood of the preset fault frequency of the sub-component, in response to the energy percentage being greater than the limit percentage, the target energy percentage is determined from the energy percentage; the sub-component in which the target resonant component signal corresponding to the target energy percentage appears is located for fault location, and the fault location result is obtained.

[0144] Optionally, this embodiment compares the energy percentage with a limit percentage based on the determined energy percentage. If the energy percentage is greater than the limit percentage, the energy percentages are sorted. From the sorted energy percentages, the target energy percentage is determined, and the sub-components corresponding to the target energy percentage are located for fault location. The fault location result can be obtained, thereby achieving the purpose of determining the location of the fault on the electric drive bearing, thus realizing the technical effect of improving the fault detection efficiency of the electric drive bearing.

[0145] The extraction steps of the first initial refractive angle signal in this embodiment will be further described below.

[0146] As an optional embodiment, the method further includes: acquiring initial operating state signals of the motor rotor at different times; determining valid operating state signals from the initial operating state signals, wherein the number of samples of the valid operating state signals is greater than the remaining number of samples in the initial operating state signals excluding the number of samples of the valid operating state signals; and extracting a first initial resolver angle signal from the valid operating state signals.

[0147] In this embodiment, the number of samples of the aforementioned valid operating status signals can be set according to different types of electric drive bearings. For example, the number of samples of the aforementioned valid operating status signals can be 1500. This value is only for illustrative purposes and is not a specific limitation.

[0148] In this embodiment, the initial operating state signals of the motor rotor at different times are collected. Then, the validity of the collected initial operating state signals is detected to obtain valid operating state signals. Finally, the first initial resolver angle signal can be extracted from the valid operating state signals, thereby achieving the purpose of determining the phase change of the current flowing through the electric drive bearing, and thus realizing the technical effect of improving the accuracy of the first initial resolver angle signal.

[0149] For example, vehicles transmit high-frequency samples (f) to the cloud at fixed intervals (T = 100ms). s Using 10kHz data, a "collection-buffering-transmission" strategy is implemented. During data transmission, high-frequency signals are returned in real-time every 100ms; during data collection and buffering, null values ​​are returned. For example, after continuously collecting and buffering N sets of high-frequency data, the accumulated N sets of data are packaged and uploaded to the cloud with a transmission cycle of 100ms, for a total transmission time of N*100ms. The N sets of high-frequency data may include: a resolver angle signal A(t), a rotational speed signal n(t), and a torque signal T(t) at a 10kHz sampling frequency.

[0150] It should be noted that although the cloud receives data in 100ms period, the actual time interval between adjacent sampling points of each data packet is as shown in (3) above, because the original signal is a high-frequency signal collected based on the Pulse Width Modulation (PWM) carrier frequency.

[0151] Furthermore, based on the two-dimensional operating condition diagram of speed-torque (nT), the typical characteristic operating condition range selected is (4000±500rpm, 30±20Nm). When acquiring data from the cloud, data that continuously maintains two complete bearing rotation cycles within the characteristic operating condition range is called a valid operating condition segment. For example, if the number of pole pairs of the motor is 4, the number of sampling points required for one bearing rotation cycle is shown in the following formula (32):

[0152]

[0153] Where n can represent the rotational speed, in rpm. Since the input characteristic operating condition data is variable, the minimum boundary of the characteristic operating condition rotational speed is taken to obtain the maximum number of points k. Then, n = 3500 rpm, f... s Substituting 10kHz into equation (32) above, we can see that the minimum number of sampling points required for one cycle of bearing rotation is 686, and the minimum number for two cycles is 1372. Therefore, we can set 1500 data points that continuously meet the characteristic working conditions as one effective working condition segment to leave a margin and improve the reliability of the data.

[0154] In this embodiment of the invention, when locating a fault in an electric drive bearing in a vehicle, the first initial resolver angle signal of the motor rotor at different times can be acquired. The acquired first initial resolver angle signal is converted to obtain a target resolver angle acceleration signal. Based on the target resolver angle acceleration signal, the electric drive bearing is fault-predicted to obtain a fault prediction result. In response to the fault prediction result indicating that the electric drive bearing has failed, the electric drive bearing is located to obtain a fault location result. This achieves the goal of detecting whether the electric drive bearing has failed without relying on additional equipment, thereby solving the technical problem of low fault detection efficiency of electric drive bearings and thus achieving the technical effect of improving the fault detection efficiency of electric drive bearings.

[0155] The technical solutions of the embodiments of the present invention will be illustrated below with reference to preferred embodiments.

[0156] Currently, in vehicles, electric drive bearings are core components of the electric drive system. Their operating environment is extremely harsh, often requiring them to withstand the impact and vibration caused by high speed, high load, frequent start-stop, and complex road conditions. This makes electric drive bearings prone to the following failures: wear, cracks, overheating, and lubrication failure.

[0157] However, if any of the aforementioned faults occur in the electric drive bearing, fault detection often relies on manual labor or additional integrated equipment. These fault detection methods require a considerable amount of time to complete, resulting in low efficiency in electric drive bearing fault detection.

[0158] To address the aforementioned technical problems, this invention proposes a fault location method for electric drive bearings in vehicles. When locating faults in electric drive bearings, the method acquires the first initial resolvent angle signal of the motor rotor at different times. The acquired first initial resolvent angle signal is then converted to obtain a target resolvent angle acceleration signal. Based on the target resolvent angle acceleration signal, fault prediction is performed on the electric drive bearing to obtain a fault prediction result. In response to the fault prediction result indicating a fault in the electric drive bearing, fault location is performed on the electric drive bearing to obtain a fault location result. This achieves the goal of detecting faults in electric drive bearings without relying on additional equipment, thus solving the technical problem of low fault detection efficiency for electric drive bearings and ultimately improving the technical effect of fault detection efficiency.

[0159] In this embodiment, by executing the abnormal warning and fault location method for electric drive bearings, the fault location of the electric drive bearing can be determined, thus obtaining the fault location result, i.e., the location of the fault on the electric drive bearing. Figure 2(a) is a flowchart of an abnormal warning and fault location method for electric drive bearings according to an embodiment of the present invention. As shown in Figure 2(a), the method may include the following steps:

[0160] Step S201: Collect high-frequency data that is highly dynamic and multi-dimensional.

[0161] After acquiring the high-frequency data of the vehicle, proceed to step S202, where the high-frequency data is packaged and uploaded to the cloud using the "collection-caching-transmission" data upload method with a fixed low-frequency cycle.

[0162] After uploading the high-frequency data to the cloud in a fixed low-frequency cycle using the "acquisition-caching-transmission" data upload method, step S203 is entered. The cloud reads the typical characteristic working condition interval data, identifies the effective working condition segment, and uses the second-order difference method to calculate the rotational angular acceleration corresponding to the target rotational angular acceleration signal.

[0163] After calculating the rotational angular acceleration corresponding to the target rotational angular acceleration signal using the second-order difference method, the process proceeds to step S204. When the number of effective working condition segments reaches the preset number, online statistical analysis is initiated.

[0164] When the number of valid working condition segments reaches the preset number, after starting online statistical analysis, proceed to step S205, perform t-test and cumulative drift detection between the dataset to be detected and the healthy dataset, construct an adaptive early warning strategy with dynamic weight optimization, and calculate the comprehensive anomaly score of the data to be detected.

[0165] After calculating the comprehensive anomaly score of the data to be tested, proceed to step S206, where a three-level early warning mechanism is set for the comprehensive anomaly score. When the comprehensive anomaly score indicates health, the bearing is predicted to be in a healthy state. When the comprehensive anomaly score indicates warning or danger, the process of fault location for the electric drive bearing is initiated.

[0166] After initiating the fault location process for the electric drive bearing, proceed to step S207 to perform dual-domain collaborative extraction of weak fault features.

[0167] In the technical solution provided by step S207 of the present invention, by using the above formulas (17) to (30), the dual-domain collaborative extraction of weak fault features can be realized.

[0168] After performing dual-domain collaborative extraction of weak fault features, proceed to step S208 to calculate the energy proportion of the neighborhood of the theoretical fault frequency.

[0169] In the technical solution provided by step S208 of the present invention, the energy proportion of each enhanced signal in the neighborhood of the corresponding theoretical fault frequency can be calculated using the above formula (31). It is then determined whether the energy proportion exceeds the limit, and finally E is set. k The part corresponding to the type with the highest over-limit ratio is the final failure point of the electric drive bearing, thereby achieving precise location of the failure point.

[0170] For example, the above data transmission process can be illustrated in Figure 2(b). For instance, Figure 2(b) is a schematic diagram of a data transmission process according to an embodiment of the present invention. During the data transmission process, the vehicle terminal 210 transmits high-frequency samples (f) to the cloud terminal 211 at a fixed period (T = 100ms). s The system uses 10kHz data to implement a "collection-buffering-transmission" strategy. During data transmission, high-frequency signals are returned in real-time every 100ms. During data collection and buffering, null values ​​(NULL) are returned. For example, after continuously collecting and buffering N sets of high-frequency data, the accumulated N sets are packaged and uploaded to the cloud at a transmission cycle of 100ms, with a total transmission time of N*100ms. The N sets of high-frequency data can include: a resolver angle signal A(t), a rotational speed signal n(t), and a torque signal T(t) at a sampling frequency of 10kHz.

[0171] In this embodiment, the overall anomaly score of the data to be detected can be adjusted by performing a weight adjustment method. Figure 2(c) is a flowchart of a weight adjustment method according to an embodiment of the present invention. As shown in Figure 2(c), the method may include the following steps:

[0172] Step S221: Invoke the "acquisition-caching-transmission" strategy to obtain high-frequency sampling data.

[0173] After invoking the "acquisition-caching-transmission" strategy to obtain high-frequency sampling data, proceed to step S222 to determine whether the high-frequency sampling data is a valid operating condition segment.

[0174] If the high-frequency sampled data is determined to be a valid operating condition segment, then proceed to step S223, where the rotational angular acceleration signal is calculated using the second-order difference method.

[0175] In the technical solution provided by step S223 of the present invention, by using the above formulas (1) and (2), after obtaining the effective working condition segment, the electrical angle can be converted to obtain the mechanical angle, and the mechanical angle can be differentially processed according to the second-order difference method to obtain the rotational angular acceleration signal.

[0176] If it is determined that the high-frequency sampling data is not a valid operating condition segment, proceed to step S224 and wait for a valid operating condition segment to be uploaded.

[0177] After calculating the rotational angular acceleration signal according to the second-order difference method, proceed to step S225 to determine whether the number of valid working condition segments exceeds the preset number.

[0178] If it is determined that the number of valid working condition segments exceeds the preset number, proceed to step S226 to calculate the comprehensive anomaly score.

[0179] In the technical solution provided by step S226 of the present invention, the comprehensive anomaly score is calculated using the above formulas (11) to (13).

[0180] If it is determined that the number of valid operating condition segments does not exceed the preset number, proceed to step S227 and wait for the accumulation of valid operating condition segments.

[0181] After calculating the comprehensive anomaly score, proceed to step S228, where a three-level early warning mechanism is used to determine the current state of the electric drive bearing.

[0182] If the current state of the electric drive bearing is determined to be a warning / dangerous state, proceed to step S229 and record the p value and S. t The statistical correlation between the value and the actual fault state is used to adjust the first and second weights with a single adjustment step size.

[0183] In the technical solution provided by step S229 of the present invention, by using the above formulas (14) to (16), the first weight and the second weight can be adjusted by adjusting the step size in a single step.

[0184] If the current state of the electric drive bearing is determined to be healthy, proceed to step S221.

[0185] In this embodiment, when locating a fault in an electric drive bearing in a vehicle, the first initial resolver angle signal of the motor rotor at different times can be acquired. The acquired first initial resolver angle signal is converted to obtain a target resolver angle acceleration signal. Based on the target resolver angle acceleration signal, the electric drive bearing is fault-predicted to obtain a fault prediction result. In response to the fault prediction result indicating that the electric drive bearing has failed, the electric drive bearing is located to obtain a fault location result. This achieves the goal of detecting whether the electric drive bearing has failed without relying on additional equipment, thereby solving the technical problem of low fault detection efficiency of electric drive bearings and thus achieving the technical effect of improving the fault detection efficiency of electric drive bearings.

[0186] According to embodiments of the present invention, a fault location device for an electric drive bearing in a vehicle is also provided. It should be noted that this fault location device for an electric drive bearing in a vehicle can be used to perform a fault location method for an electric drive bearing in a vehicle according to one of the embodiments.

[0187] Figure 3 This is a schematic diagram of a fault location device for an electric drive bearing in a vehicle according to an embodiment of the present invention. Figure 3 As shown, the fault location device 300 for the electric drive bearing in the vehicle may include: a first acquisition unit 301, a conversion unit 302, a prediction unit 303, and a location unit 304.

[0188] The first acquisition unit 301 is used to acquire the first initial resolver angle signal of the motor rotor in the vehicle at different times, wherein the first initial resolver angle signal is used to represent the real-time electrical angle of the motor rotor position.

[0189] The conversion unit 302 is used to convert the first initial resolver angle signal to obtain the target resolver angle acceleration signal, wherein the target resolver angle acceleration signal is used to represent the resolver angle acceleration of the electric drive bearing, and the electric drive bearing and the motor rotor are deployed at the same connecting shaft.

[0190] The prediction unit 303 is used to predict the fault of the electric drive bearing based on the target rotation angular acceleration signal, and obtain the fault prediction result of the electric drive bearing.

[0191] The positioning unit 304 is used to locate the electric drive bearing in response to the fault prediction result that the electric drive bearing has failed, and to obtain the fault location result, wherein the fault location result is used to indicate the location of the fault on the electric drive bearing.

[0192] Optionally, the conversion unit 302 may include: a first conversion module, used to perform angle conversion on the first initial resolver angle signal to obtain a second initial resolver angle signal, wherein the second initial resolver angle signal is used to represent the resolver angle of the non-electrically driven bearing; and a processing module, used to perform differential processing on the second initial resolver angle signal to obtain a target resolver angle acceleration signal.

[0193] Optionally, the prediction unit 303 may include: a second conversion module, configured to, in response to the total number of target rotation angle acceleration signals being the same as the preset number, after verifying the target rotation angle acceleration signals and sample rotation angle acceleration signals, standardize the target rotation angle acceleration signals using the first average value and first variance of the rotation angle accelerations corresponding to the sample rotation angle acceleration signals; and a prediction module, configured to perform fault prediction on the electric drive bearing based on the converted target rotation angle acceleration signals, and obtain fault prediction results.

[0194] Optionally, the fault location device 300 for the electric drive bearing in the vehicle may include: a second acquisition unit, used to obtain the difference result between the target rotation angle acceleration signal and the sample rotation angle acceleration signal after verifying the target rotation angle acceleration signal and the sample rotation angle acceleration signal; the prediction module may include: a detection submodule, used to perform offset detection on the converted target rotation angle acceleration signal to obtain an offset detection result, wherein the offset detection result is used to represent the offset of the second average value of the rotation angle acceleration corresponding to the target rotation angle acceleration signal; a first determination submodule, used to determine the first score and the first weight of the difference result, and the second score and the second weight of the offset detection result; and a weighting submodule, used to perform weighted summation of the first score and the second score using the first weight and the second weight respectively, to complete the fault prediction of the electric drive bearing and obtain the fault prediction result.

[0195] Optionally, the fault location device 300 for the electric drive bearing in the vehicle may include: an adjustment unit, used to adjust the first weight and the second weight in response to the next fault prediction result that the electric drive bearing has failed; and a weighting unit, used to perform a weighted summation of the first score and the second score using the adjusted first weight and the adjusted second weight, respectively, to complete the fault prediction of the electric drive bearing and obtain the fault prediction result.

[0196] Optionally, the positioning unit 304 may include: a first determining module, configured to determine the initial resonant component signal of the sub-component of the electric drive bearing in response to the fault prediction result indicating a fault in the electric drive bearing; an enhancement module, configured to enhance the initial resonant component signal to obtain a target resonant component signal; a second determining module, configured to determine the energy proportion of the target resonant component signal in the neighborhood of a preset fault frequency of the sub-component; and a positioning module, configured to locate the electric drive bearing based on the energy proportion to obtain a fault positioning result.

[0197] Optionally, the positioning module may include: a second determining submodule, configured to determine a target energy percentage from the energy percentage in response to an energy percentage greater than a limit percentage, wherein the target energy percentage is greater than the remaining energy percentage in the energy percentage excluding the target energy percentage; and a positioning submodule, configured to perform fault positioning on the sub-components in which the target resonant component signal corresponding to the target energy percentage appears, and obtain a fault positioning result.

[0198] Optionally, the fault location device 300 for the electric drive bearing in the vehicle may include: a third acquisition unit for acquiring initial operating state signals of the motor rotor at different times; a determination unit for determining valid operating state signals from the initial operating state signals, wherein the number of samples of the valid operating state signals is greater than the remaining number of samples in the initial operating state signals excluding the number of samples of the valid operating state signals; and an extraction unit for extracting a first initial resolver angle signal from the valid operating state signals.

[0199] In this embodiment, a fault location device for an electric drive bearing in a vehicle is provided. The device may include: a first acquisition unit for acquiring a first initial resolver angle signal of the motor rotor at different times, wherein the first initial resolver angle signal represents the real-time electrical angle of the motor rotor's position; a conversion unit for converting the first initial resolver angle signal to obtain a target resolver angular acceleration signal, wherein the target resolver angular acceleration signal represents the resolver angular acceleration of the electric drive bearing, and the electric drive bearing and the motor rotor are deployed on the same connecting shaft; a prediction unit for predicting a fault in the electric drive bearing based on the target resolver angular acceleration signal, and obtaining a fault prediction result for the electric drive bearing; and a location unit for locating the electric drive bearing in response to the fault prediction result indicating a fault in the electric drive bearing, and obtaining a fault location result, wherein the fault location result represents the location of the fault on the electric drive bearing. This achieves the goal of detecting whether an electric drive bearing is faulty without relying on additional equipment, thereby solving the technical problem of low fault detection efficiency for electric drive bearings and ultimately improving the technical effect of improving the fault detection efficiency of electric drive bearings.

[0200] According to an embodiment of the present invention, a processor is also provided for running a program, wherein the program is executed by the processor to perform the fault location method for the electric drive bearing in the vehicle in the embodiment.

[0201] According to an embodiment of the present invention, a vehicle is also provided. Figure 4 This is a schematic diagram of a vehicle according to an embodiment of the present invention, such as... Figure 4 As shown, the vehicle 400 may include a memory 410 and a processor 420, wherein the memory 410 is used to store computer programs; and the processor 420 is used to run the programs stored in the memory 410 to implement the fault location method for electric drive bearings in the vehicle of this application.

[0202] In this application, "multiple" refers to two or more.

[0203] In this application, unless otherwise expressly defined, the terms "installation," "connection," and "linking" 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; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0204] The terms “first,” “second,” “third,” “fourth,” etc., in this application (if present) are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0205] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0206] Unless otherwise specified, all steps in this application may be performed sequentially or randomly. For example, the fault location method for an electric drive bearing in a vehicle may include steps S101 and S102, indicating that the fault location method for an electric drive bearing in a vehicle may include steps S101 and S102 performed sequentially, or it may include steps S102 and S101 performed sequentially.

[0207] For example, the fault location method for electric drive bearings in vehicles in this application may also include step S103, which means that step S103 can be added to the method in any order. For example, the fault location method for electric drive bearings in vehicles in this application may include steps S101, S102 and S103, or it may include steps S101, S103 and S102, or it may include steps S103, S101 and S102, etc. This is only an example and is not specifically limited.

[0208] For example, the fault location method for electric drive bearings in vehicles according to this application may also include step S104, meaning that step S104 can be added to the method in any order. For example, the fault location method for electric drive bearings in vehicles according to this application may include steps S101, S102, S103 and S104, or it may include steps S101, S103, S102 and S104, or it may include steps S104, S103, S101 and S102, etc. This is only an example and is not specifically limited.

[0209] According to another aspect of the present invention, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the fault location method for an electric drive bearing in a vehicle as described in the embodiment.

[0210] Computer-readable storage media, also known as computer storage media, may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. These propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable storage media can transmit, propagate, or transfer programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0211] The program code contained in a computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, radio frequency, or any suitable combination thereof.

[0212] According to an embodiment of the present invention, a computer program product is also provided, the computer program product including a computer program, wherein when the computer program is executed by a processor, it implements the fault location method for the electric drive bearing in the vehicle in the embodiment.

[0213] According to an embodiment of the present invention, a computer program product is also provided, including a non-volatile computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the fault location method for an electric drive bearing in a vehicle as described in the embodiment.

[0214] According to an embodiment of the present invention, a computer program is also provided, which, when executed by a processor, implements the fault location method for the electric drive bearing in the vehicle described in the embodiment.

[0215] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: acquiring a first initial resolver angle signal of the motor rotor in the vehicle at different times, wherein the first initial resolver angle signal is used to represent the real-time electrical angle of the motor rotor's position; converting the first initial resolver angle signal to obtain a target resolver angular acceleration signal, wherein the target resolver angular acceleration signal is used to represent the resolver angular acceleration of the electric drive bearing, and the electric drive bearing and the motor rotor are deployed at the same connecting shaft; based on the target resolver angular acceleration signal, performing fault prediction on the electric drive bearing to obtain a fault prediction result for the electric drive bearing; in response to the fault prediction result indicating that the electric drive bearing has failed, performing fault location on the electric drive bearing to obtain a fault location result, wherein the fault location result is used to indicate the location of the fault on the electric drive bearing.

[0216] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: performing angle conversion on the first initial resolver angle signal to obtain a second initial resolver angle signal, wherein the second initial resolver angle signal is used to represent the resolver angle of the electric drive bearing; performing differential processing on the second initial resolver angle signal to obtain a target resolver angle acceleration signal.

[0217] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: In response to the total number of target rotation angle acceleration signals being the same as the preset number, after verifying the target rotation angle acceleration signals and the sample rotation angle acceleration signals, the target rotation angle acceleration signals are standardized using the first average value and the first variance of the rotation angle accelerations corresponding to the sample rotation angle acceleration signals; based on the transformed target rotation angle acceleration signals, fault prediction is performed on the electric drive bearing to obtain the fault prediction result.

[0218] Optionally, when the above-mentioned computer program is executed by the processor, the program code implements the following steps: after examining the target rotation angle acceleration signal and the sample rotation angle acceleration signal, the difference result between the target rotation angle acceleration signal and the sample rotation angle acceleration signal is obtained; based on the converted target rotation angle acceleration signal, fault prediction of the electric drive bearing is performed to obtain the fault prediction result of the electric drive bearing, including: performing offset detection on the converted target rotation angle acceleration signal to obtain an offset detection result, wherein the offset detection result is used to represent the offset of the second average value of the angle corresponding to the target rotation angle acceleration signal; determining the first score and the first weight of the difference result, and the second score and the second weight of the offset detection result; using the first weight and the second weight respectively, the first score and the second score are weighted and summed to complete the fault prediction of the electric drive bearing and obtain the fault prediction result.

[0219] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: in response to the next fault prediction result being that the electric drive bearing has failed, the first weight and the second weight are adjusted; the first score and the second score are weighted and summed using the adjusted first weight and the adjusted second weight respectively, so as to complete the fault prediction of the electric drive bearing and obtain the fault prediction result.

[0220] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: in response to the fault prediction result that the electric drive bearing has failed, the initial resonance component signal of the sub-component of the electric drive bearing is determined; the initial resonance component signal is enhanced to obtain the target resonance component signal; the energy ratio of the target resonance component signal in the neighborhood of the preset fault frequency of the sub-component is determined; based on the energy ratio, the electric drive bearing is fault located to obtain the fault location result.

[0221] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: in response to the energy percentage being greater than the limit percentage, determining the target energy percentage from the energy percentage, wherein the target energy percentage is greater than the remaining energy percentage in the energy percentage other than the target energy percentage; performing fault location on the sub-component where the target resonance component signal corresponding to the target energy percentage appears, and obtaining the fault location result.

[0222] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: determining a valid operating state signal from the initial operating state signal, wherein the number of samples of the valid operating state signal is greater than the remaining number of samples in the initial operating state signal excluding the number of samples of the valid operating state signal; and extracting a first initial resolver angle signal from the valid operating state signal.

[0223] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0224] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0225] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0226] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0227] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0228] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0229] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for fault location of an electric drive bearing in a vehicle, characterized in that, include: The first initial resolver angle signal of the motor rotor in the vehicle at different times is obtained, wherein the first initial resolver angle signal is used to represent the real-time electrical angle of the motor rotor position; The first initial resolver angle signal is converted to obtain a target resolver angle acceleration signal, wherein the target resolver angle acceleration signal is used to represent the resolver angle acceleration of the electric drive bearing, and the electric drive bearing and the motor rotor are deployed at the same connecting shaft; Based on the target rotational angular acceleration signal, fault prediction is performed on the electric drive bearing to obtain the fault prediction result of the electric drive bearing; In response to the fault prediction result indicating that the electric drive bearing has the fault, the electric drive bearing is located to obtain a fault location result, wherein the fault location result is used to indicate the location of the fault on the electric drive bearing.

2. The method according to claim 1, characterized in that, The first initial revolute angle signal is converted to obtain the target revolute angular acceleration signal, including: The first initial resolver angle signal is converted to an angle to obtain a second initial resolver angle signal, wherein the second initial resolver angle signal is used to represent the resolver angle of the electric drive bearing; The second initial resolver angle signal is differentially processed to obtain the target resolver angle acceleration signal.

3. The method according to claim 1, characterized in that, Based on the target rotational angular acceleration signal, fault prediction is performed on the electric drive bearing to obtain the fault prediction result of the electric drive bearing, including: In response to the fact that the total number of the target rotation angle acceleration signals is the same as the preset number, after verifying the target rotation angle acceleration signals and the sample rotation angle acceleration signals, the target rotation angle acceleration signals are standardized by using the first average value and the first variance of the rotation angle acceleration corresponding to the sample rotation angle acceleration signals. Based on the converted target rotational angular acceleration signal, fault prediction is performed on the electric drive bearing to obtain the fault prediction result.

4. The method according to claim 3, characterized in that, The method further includes: After examining the target rotation angle acceleration signal and the sample rotation angle acceleration signal, the difference between the target rotation angle acceleration signal and the sample rotation angle acceleration signal is obtained; Based on the converted target helical angle acceleration signal, fault prediction is performed on the electric drive bearing to obtain the fault prediction result, including: offset detection is performed on the converted target helical angle acceleration signal to obtain the offset detection result, wherein the offset detection result is used to represent the offset of the second average value of the helical angle acceleration corresponding to the target helical angle acceleration signal; Determine a first score and a first weight for the difference results, and a second score and a second weight for the offset detection results; The first score and the second score are weighted and summed using the first weight and the second weight respectively to complete the fault prediction of the electric drive bearing and obtain the fault prediction result.

5. The method according to claim 4, characterized in that, The method further includes: In response to the next fault prediction result being that the electric drive bearing has failed, the first weight and the second weight are adjusted. The first score and the second score are weighted and summed using the adjusted first weight and the adjusted second weight respectively, in order to complete the fault prediction of the electric drive bearing and obtain the fault prediction result.

6. The method according to claim 1, characterized in that, In response to the fault prediction result indicating that the electric drive bearing has a fault, fault location is performed on the electric drive bearing to obtain fault location results, including: In response to the fault prediction result indicating that the electric drive bearing has the fault, the initial resonant component signal of the sub-component of the electric drive bearing is determined; The initial resonance component signal is enhanced to obtain the target resonance component signal; Determine the energy percentage of the target resonant component signal within the neighborhood of the preset fault frequency of the sub-component; Based on the energy ratio, the fault location of the electric drive bearing is performed to obtain the fault location result.

7. The method according to claim 6, characterized in that, Based on the energy ratio, the fault location of the electric drive bearing is performed to obtain the fault location result, including: In response to the energy percentage being greater than the limit percentage, a target energy percentage is determined from the energy percentages, wherein the target energy percentage is greater than the remaining energy percentages excluding the target energy percentage; The fault location is performed on the sub-component that appears in the target resonance component signal corresponding to the target energy ratio, and the fault location result is obtained.

8. The method according to any one of claims 1 to 7, characterized in that, The method further includes: Obtain the initial operating state signal of the motor rotor at different times; From the initial operating state signal, a valid operating state signal is determined, wherein the number of samples of the valid operating state signal is greater than the remaining number of samples in the initial operating state signal excluding the number of samples of the valid operating state signal; The first initial resolver angle signal is extracted from the effective operating state signal.

9. A fault location device for an electric drive bearing in a vehicle, characterized in that, include: The first acquisition unit is used to acquire the first initial resolver angle signal of the motor rotor in the vehicle at different times, wherein the first initial resolver angle signal is used to represent the real-time electrical angle of the position of the motor rotor. A conversion unit is used to convert the first initial resolver angle signal to obtain a target resolver angle acceleration signal, wherein the target resolver angle acceleration signal is used to represent the resolver angle acceleration of the electric drive bearing, and the electric drive bearing and the motor rotor are deployed at the same connecting shaft; The prediction unit is used to predict the fault of the electric drive bearing based on the target rotational angular acceleration signal, and obtain the fault prediction result of the electric drive bearing. A positioning unit is configured to, in response to the fault prediction result indicating that the electric drive bearing has a fault, locate the electric drive bearing to obtain a fault positioning result, wherein the fault positioning result indicates the location of the fault on the electric drive bearing.

10. A processor, characterized in that, The processor is used to run a program, wherein the program, when run by the processor, executes the fault location method for the electric drive bearing in the vehicle according to any one of claims 1 to 8.

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