Fault diagnosis methods, devices, equipment, media, and products for rotary transformers

Abstract

This application discloses a fault diagnosis method, apparatus, device, medium, and product for a rotary transformer. The method includes: receiving a voltage signal output from the rotary transformer; inputting the voltage signal into an angular velocity observer and calculating the corresponding rotational angular velocity of the rotary transformer using the angular velocity observer; determining a fault diagnosis time for the rotary transformer based on the rotational angular velocity; and performing fault diagnosis on the rotary transformer based on the fault diagnosis time and the voltage signal. According to the embodiments of this application, the fault diagnosis time can be automatically adjusted, thereby ensuring the reliability of the rotary transformer fault diagnosis.

Description

Technical Field

[0001] This application belongs to the field of power electronics technology, and in particular relates to a fault diagnosis method, device, equipment, medium and product for a rotary transformer. Background Technology

[0002] High-precision torque control of drive motors can improve vehicle safety, efficiency, and driving experience. This is typically achieved by measuring the rotor position of the drive motor using a resolver, thus ensuring precise torque control. Therefore, fault detection of resolvers is essential.

[0003] In related technologies, the diagnostic strategy for rotary transformers involves diagnosing faults by analyzing the voltage signal output by the rotary transformer within a fixed detection period. However, this diagnostic strategy has poor reliability and is prone to causing equipment failures.

[0004] Therefore, how to improve the reliability of fault diagnosis of rotary transformers is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, medium, and product for fault diagnosis of a rotary transformer, which can automatically adjust the fault diagnosis time to ensure the reliability of fault diagnosis of the rotary transformer.

[0006] In a first aspect, embodiments of this application provide a fault diagnosis method for a rotary transformer, comprising: receiving a voltage signal output by the rotary transformer; inputting the voltage signal into an angular velocity observer and calculating the corresponding rotational angular velocity of the rotary transformer using the angular velocity observer; determining the corresponding fault diagnosis time of the rotary transformer based on the rotational angular velocity; and performing fault diagnosis on the rotary transformer based on the fault diagnosis time and the voltage signal.

[0007] In one embodiment, fault diagnosis of a rotary transformer is performed based on fault diagnosis time and voltage signal, including: constructing a sliding time window based on fault diagnosis time and preset data processing time; and performing fault diagnosis of the rotary transformer based on the sliding time window and voltage signal.

[0008] In one embodiment, after constructing a sliding time window based on the fault diagnosis time and a preset data processing time, the method further includes: determining the larger of the window length corresponding to the sliding time window and a preset window length threshold, and updating the larger value to the window length corresponding to the sliding time window; and performing fault diagnosis on the rotary transformer based on the sliding time window and the voltage signal, including: performing fault diagnosis on the rotary transformer based on the updated sliding time window and the voltage signal.

[0009] In one embodiment, fault diagnosis of a rotary transformer based on a sliding time window and a voltage signal includes: truncating the voltage signal according to the sliding time window to obtain a truncated target voltage signal; determining the maximum value in the target voltage signal based on the sliding time window and the target voltage signal; and diagnosing the fault of the rotary transformer based on the maximum value and a preset voltage threshold.

[0010] In one embodiment, the target voltage signal includes multiple voltage values. Determining the maximum value in the target voltage signal based on a sliding time window and the target voltage signal includes: taking the i-th target voltage value in the target voltage signal as the maximum voltage value and starting to accumulate a counter, where i is a positive integer; determining the larger voltage value between the (i+1)-th target voltage value and the i-th target voltage value, and updating the maximum voltage value using the larger voltage value; when it is determined that the value accumulated by the counter is not the same as the window length corresponding to the sliding time window, updating the i-th target voltage value using the (i+1)-th target voltage value, and returning to the step of taking the i-th target voltage value in the target voltage signal as the maximum voltage value and starting to accumulate the counter, until the value accumulated by the counter is the same as the window length corresponding to the sliding time window, and then taking the maximum voltage value as the maximum value in the target voltage signal.

[0011] In one implementation, determining the larger voltage value between the (i+1)th target voltage value and the ith target voltage value, and updating the maximum voltage value using the larger voltage value, includes: determining a first larger voltage value between the (i+1)th target voltage value and the ith target voltage value; obtaining the historical maximum voltage value of the previous sliding time window; determining a second larger voltage value between the first larger voltage value and the historical maximum voltage value, and updating the maximum voltage value using the second larger voltage value.

[0012] In one embodiment, determining the corresponding fault diagnosis time of the rotary transformer based on the rotational angular velocity includes: calculating the corresponding rotational period of the rotary transformer based on the rotational angular velocity and a preset period calculation formula; and determining the corresponding fault diagnosis time of the rotary transformer based on a preset adjustment coefficient and the rotational period.

[0013] Secondly, embodiments of this application provide a fault diagnosis device for a rotary transformer, the device comprising:

[0014] The receiving module is used to receive the voltage signal output by the rotary transformer;

[0015] The calculation module is used to input the voltage signal into the angular velocity observer and calculate the rotational angular velocity corresponding to the rotary transformer through the angular velocity observer;

[0016] The module is determined, and the corresponding fault diagnosis time for the rotary transformer is determined based on the rotational angular velocity.

[0017] The diagnostic module performs fault diagnosis on the rotary transformer based on the fault diagnosis time and voltage signal.

[0018] Thirdly, embodiments of this application provide a fault diagnosis device for a rotary transformer, the device comprising: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements the fault diagnosis method for the rotary transformer in the first aspect or any embodiment of the first aspect.

[0019] Fourthly, a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the fault diagnosis method for a rotary transformer according to the first aspect or any embodiment of the first aspect.

[0020] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform a fault diagnosis method for a rotary transformer as described in the first aspect or any embodiment of the first aspect.

[0021] The fault diagnosis method, apparatus, equipment, medium, and product of the rotary transformer in this application embodiment can determine the corresponding rotational angular velocity of the rotary transformer based on the voltage signal of the rotary transformer. In this way, the fault diagnosis time required for the rotary transformer is measured by the rotational angle of the rotary transformer, so that the fault diagnosis time most suitable for the current working condition can be adaptively calculated regardless of whether the drive motor is running at extremely low speed, high speed, or variable speed, thereby improving the reliability of the rotary transformer fault diagnosis. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram of the architecture of a rotary transformer demodulation system provided in one embodiment of this application;

[0024] Figure 2 This is a schematic diagram illustrating the recovery of the SIN signal according to an embodiment of this application;

[0025] Figure 3 A flowchart illustrating a fault diagnosis method for a rotary transformer according to an embodiment of this application is shown.

[0026] Figure 4 A flowchart illustrating a fault diagnosis method for a rotary transformer according to an embodiment of this application is shown.

[0027] Figure 5 A flowchart illustrating a fault diagnosis method for a rotary transformer according to an embodiment of this application is shown.

[0028] Figure 6 A schematic diagram of a process for determining the maximum value using a sliding time window is shown in one embodiment of this application;

[0029] Figure 7 This is a schematic diagram of the structure of a fault diagnosis device for a rotary transformer provided in another embodiment of this application;

[0030] Figure 8 This is a schematic diagram of the structure of a fault diagnosis device for a rotary transformer provided in another embodiment of this application. Detailed Implementation

[0031] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0032] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0033] High-precision torque control of drive motors can improve vehicle safety, efficiency, and driving experience. Generally, the rotor position of the drive motor can be measured using a rotary transformer, thus ensuring high-precision torque control. Specifically, accurate measurement and detection of the motor rotor position ensures high-precision torque output. This is achieved by acquiring the voltage output from the rotary transformer and demodulating it, thereby enabling precise detection of the drive motor torque.

[0034] Figure 1 This is a schematic diagram of the architecture of a rotary transformer demodulation system provided in one embodiment of this application, as shown below. Figure 1 As shown, the rotary transformer demodulation system may include a motor controller 110 and a rotary transformer 120. The rotary transformer may be mounted on the rotor of the drive motor. Furthermore, the demodulation system may also include a main control chip 111, a hardware modulation module 112, a first signal conversion module 113, and a second signal conversion module 114.

[0035] For example, the main control chip 111 of the motor controller generates an excitation PWM signal, which is then processed by the hardware modulation module 112 of the controller to generate the input excitation positive (EXC+) and excitation negative (EXC-) of the resolver. Under excitation and rotor rotation, the resolver outputs four signals: sine positive (sin+), sine negative (sin-), cosine positive (cos+), and cosine negative (cos-). These signals are processed by the first signal conversion module 113 and the second signal conversion module 114, respectively, to generate a recovered SIN signal and a recovered COS signal. These two signals are then sent to the main control chip for demodulating the resolver angle. The first signal conversion module 113 and the second signal conversion module 114 can each include differential circuits, filter circuits, and amplitude conversion circuits. The recovered SIN signal generated by the main control chip 111 is as follows: Figure 2 As shown, Figure 2 This is a schematic diagram of the recovery of the SIN signal provided in one embodiment of this application.

[0036] Furthermore, obtaining the correct rotation angle in real time is essential for ensuring torque control accuracy during motor operation. Therefore, diagnostics of the PWM excitation, SIN signal recovery, and COS signal recovery are necessary. When the resolver angle cannot be obtained, the motor controller needs to enter a safety shutdown state to avoid outputting unexpected torque and current.

[0037] Specifically, when the sin+ and sin- signals are normal, the main control chip 111 performs peak sampling on the recovered SIN signal to obtain the rotation frequency of the rotary transformer. For example, the rotation frequency of different rotary transformers can be 5Hz, 0.2Hz, and their corresponding recovered SIN signals are as follows: Figure 2As shown, when both sin+ and sin- are disconnected, the recovered SIN signal obtained from sin+ and sin- fluctuates around the midpoint voltage (i.e., 1.65V). Similarly, for the COS recovered signal, when both cos+ and cos- are disconnected, the recovered COS signal also fluctuates around the midpoint voltage. The fault phenomena are consistent for both, therefore, the same fault diagnosis strategy can be used for faults involving disconnected recovered signals (including recovered SIN or recovered COS signals).

[0038] In related technologies, after a fault occurs, the midpoint voltage, sampling error, and ADC resolution of the recovered signal are acquired. Furthermore, if the voltage of the recovered signal remains within the fault diagnosis voltage range for a certain time Ts, a fault is reported. The fault diagnosis voltage range can be represented as [VL, VH], where VL is the lower limit of the fault diagnosis voltage range and VH is the upper limit of the fault diagnosis voltage range.

[0039] However, the lower the rotation frequency of the rotary transformer, the longer the normal recovery SIN signal persists within the fault diagnosis voltage range. Specifically, such as... Figure 2 As shown, when the rotary transformer rotates at a frequency of 0.2Hz, and sin+ and sin- are normal, the recovered SIN voltage is in [VL, VH] (corresponding to...). Figure 2 The duration of [1.5V, 1.8V] is approximately 0.24s (corresponding to...). Figure 2 Between points A and B, Ts needs to be greater than 0.24s, so Ts = 0.3s can be chosen. However, for a rotary transformer with a rotation frequency of 5Hz, the rotary transformer angle has already rotated 540 degrees within Ts. Therefore, using a fault diagnosis strategy with a fixed diagnosis time, as the rotary transformer rotation frequency increases, the time for closed-loop adjustment of the incorrect rotary transformer angle is used, and the relative rotational electrical cycle of the motor is longer, increasing the probability of controller overcurrent.

[0040] In view of this, embodiments of this application provide a method, apparatus, device, medium, and product for fault diagnosis of a rotary transformer. The fault diagnosis method for a rotary transformer provided in this application embodiment will be described first below.

[0041] Figure 3 A flowchart illustrating a fault diagnosis method for a rotary transformer according to an embodiment of this application is shown. Figure 3 As shown, the fault diagnosis method for a rotary transformer includes the following steps:

[0042] S310 receives the voltage signal output from the rotary transformer.

[0043] S320. Input the voltage signal into the angular velocity observer and calculate the rotational angular velocity corresponding to the rotary transformer through the angular velocity observer.

[0044] S330. Determine the fault diagnosis time corresponding to the rotary transformer based on the rotational angular velocity.

[0045] S340. Based on the fault diagnosis time and voltage signal, perform fault diagnosis on the rotary transformer.

[0046] In some embodiments, in S310, a voltage signal output from a resolver is received. The voltage signal output from the resolver may be a recovery signal. The recovery signal may include a recovery SIN signal and a recovery COS signal.

[0047] For example, the main control chip may receive the voltage signal output by the resolver.

[0048] In some embodiments, in S320, a voltage signal is input to an angular velocity observer, and the angular velocity of the rotary transformer is calculated by the angular velocity observer. The angular velocity observer can be used to calculate the angular velocity based on the voltage signal.

[0049] In one example, the angular velocity observer may include a preset angular velocity algorithm, and use the preset angular velocity algorithm to calculate the rotational angular velocity corresponding to the resolver. In another example, the angular velocity observer may be a phase-locked loop (PLL), and use the PLL to calculate the rotational angular velocity corresponding to the resolver.

[0050] In some embodiments, in S330, the fault diagnosis time corresponding to the rotary transformer can be determined based on the rotational angular velocity.

[0051] Among them, the fault diagnosis time can be used to characterize and determine whether there is a fault of disconnection of the recovery signal in the rotary transformer.

[0052] In some optional embodiments, the rotation period of the rotary transformer can be calculated based on the rotational angular velocity and a preset period calculation formula, and the corresponding fault diagnosis time of the rotary transformer can be determined based on a preset adjustment coefficient and the rotation period.

[0053] For example, the preset period calculation formula can be a formula that characterizes the relationship between angular velocity and period. The rotation period of the rotary transformer can be calculated based on the rotational angular velocity and the preset period calculation formula.

[0054] For example, a preset adjustment coefficient can be used to adjust the fault diagnosis time, and the preset adjustment coefficient can be determined in advance by technicians according to different needs.

[0055] In one example, the preset adjustment factor can be set to 2, meaning the corresponding fault diagnosis time for the rotary transformer can be two rotation cycles of the rotary transformer. Alternatively, the preset adjustment factor can be set to 1, meaning the corresponding fault diagnosis time for the rotary transformer can be one rotation cycle of the rotary transformer.

[0056] For example, the preset adjustment coefficient can be determined based on the magnitude of the rotational angular velocity. For instance, a larger preset adjustment coefficient can be set when the rotational angular velocity is large, while a smaller preset adjustment coefficient can be set when the rotational angular velocity is small.

[0057] In this embodiment, the rotation period of the rotary transformer is calculated based on the rotational angular velocity and the preset period calculation formula. The corresponding fault diagnosis time of the rotary transformer is determined based on the preset adjustment coefficient and the rotation period, thereby ensuring the reliability of the calculated fault diagnosis time.

[0058] In some embodiments, in S340, fault diagnosis of the rotary transformer can be performed based on the fault diagnosis time and voltage signal.

[0059] For example, the relationship between the voltage signal during the fault diagnosis time and a preset voltage threshold can be determined to diagnose faults in a rotary transformer. The preset voltage threshold can be pre-set by technicians according to different needs.

[0060] For example, the preset voltage threshold can be a preset voltage threshold range. For instance, the preset voltage threshold range can be [VL, VH].

[0061] In one example, if the voltage signal during the fault diagnosis time is found to be outside the preset voltage threshold range, it can be determined that the rotary transformer is not abnormal; conversely, if the voltage signal during the fault diagnosis time is found to be within the preset voltage threshold range, it can be determined that the rotary transformer is faulty.

[0062] For example, the received voltage signal is input to an angular velocity observer, which calculates the corresponding rotational angular velocity of the rotary transformer. Based on the rotational angular velocity, the corresponding fault diagnosis time for the rotary transformer is determined. Then, based on the determined fault diagnosis time and the voltage signal, fault diagnosis is performed on the rotary transformer. That is, Figure 3 In the embodiment shown, the rotational angular velocity of the rotary transformer is determined based on the voltage signal of the rotary transformer. In this way, the fault diagnosis time required for the rotary transformer is measured by the rotational angle of the rotary transformer. This allows for the adaptive calculation of the most suitable fault diagnosis time for the current operating condition, regardless of whether the drive motor is running at extremely low speed, high speed, or variable speed, thereby improving the reliability of rotary transformer fault diagnosis.

[0063] In order to enable fault detection through fault diagnosis time, as another implementation of this application, this application also provides another implementation of fault diagnosis for a rotary transformer, as detailed in the following embodiments.

[0064] Figure 4 A flowchart illustrating a fault diagnosis method for a rotary transformer according to an embodiment of this application is shown. Figure 4 As shown, the sampling time determination method includes the following steps S410-S450:

[0065] S410 receives the voltage signal output from the rotary transformer.

[0066] S420. Input the voltage signal into the angular velocity observer and calculate the rotational angular velocity corresponding to the rotary transformer through the angular velocity observer.

[0067] S430. Determine the fault diagnosis time corresponding to the rotary transformer based on the rotational angular velocity.

[0068] S440. Construct a sliding time window based on the fault diagnosis time and the preset data processing time.

[0069] S450. Based on the sliding time window and voltage signal, perform fault diagnosis on the rotary transformer.

[0070] Steps S410-S430 are the same as steps S310-S330, and will not be repeated here.

[0071] In some embodiments, in S440, a sliding time window can be constructed based on the fault diagnosis time and the preset data processing time.

[0072] For example, a sliding time window can be used to capture voltage signals, thereby enabling fault diagnosis based on the captured voltage signals.

[0073] For example, the preset data processing time can be used to characterize the time the main control chip spends processing data.

[0074] In one example, the sliding time window can be obtained by dividing the fault diagnosis time by the preset data processing time.

[0075] In some optional embodiments, the larger of the window length corresponding to the sliding time window and the preset window length threshold can be determined, and the larger value can be updated to the window length corresponding to the sliding time window.

[0076] For example, a preset window length threshold can be used to characterize the minimum time window to avoid the calculated sliding time window being too small, which would render the sliding time window meaningless.

[0077] The preset window length threshold can be pre-set by technicians according to different needs. In one example, the preset window length threshold can be calculated based on the minimum time threshold and the preset data processing time. For example, the preset window length threshold can be obtained by dividing the minimum time threshold by the preset data processing time.

[0078] In this embodiment, by setting a preset data processing time and selecting the window with the larger window length from the preset data processing time and the calculated sliding time window, the reliability of the diagnostic tool for judging the fault of the rotary transformer is ensured.

[0079] In some embodiments, in S450, fault diagnosis is performed on the rotary transformer based on the sliding time window and the voltage signal.

[0080] For example, voltage signals can be captured by a sliding time window, and fault diagnosis of the rotary transformer can be performed using the voltage signals within the time window.

[0081] In some optional embodiments, the voltage signal is truncated according to a sliding time window to obtain a truncated target voltage signal, and the maximum value of the target voltage signal is determined based on the sliding time window and the target voltage signal. Fault diagnosis of the rotary transformer is then performed based on the maximum value and a preset voltage threshold.

[0082] For example, the target voltage signal can represent the voltage signal within a sliding time window.

[0083] Furthermore, the target voltage signal includes multiple voltage values. The i-th target voltage value in the target voltage signal is taken as the maximum voltage value, and the counter is started to accumulate, where i is a positive integer. The larger voltage value between the (i+1)-th target voltage value and the i-th target voltage value is determined, and the maximum voltage value is updated using the larger voltage value. When it is determined that the value accumulated by the counter is not the same as the window length corresponding to the sliding time window, the i-th target voltage value is updated using the (i+1)-th target voltage value, and the process returns to the step of taking the i-th target voltage value in the target voltage signal as the maximum voltage value and starting to accumulate the counter, until the value accumulated by the counter is the same as the window length corresponding to the sliding time window, and the maximum voltage value is taken as the maximum value in the target voltage signal.

[0084] For example, the counter can first be initialized. The first target voltage signal is taken as the maximum voltage value, and the counter begins to accumulate. The larger of the second and first target voltage values ​​is determined, and the maximum voltage value is updated using the larger voltage. If the accumulated counter value is not the same as the window length corresponding to the sliding time window, the first target voltage value is updated using the second target voltage value, and the process returns to the step of taking the first target voltage value as the maximum voltage value and starting the counter accumulation. That is, the second target voltage value is compared with the maximum voltage value, and the larger one is updated as the maximum voltage value, until the accumulated counter value is the same as the window length corresponding to the sliding time window. In other words, all voltage values ​​within the sliding time window have been compared, and the maximum voltage value is taken as the maximum value in the target voltage signal. It can be understood that by updating the comparator value and comparing it with the window length of the sliding time window, the maximum value within the sliding event window can be quickly determined.

[0085] In some alternative embodiments, a first larger voltage value is determined between the (i+1)th target voltage value and the ith target voltage value. The historical maximum voltage value of the previous sliding time window is obtained. A second larger voltage value is determined between the first larger voltage value and the historical maximum voltage value, and the maximum voltage value is updated using the second larger voltage value.

[0086] For example, the first larger voltage value can represent the larger value between the (i+1)th target voltage value and the ith target voltage value; the second larger voltage value can represent the larger value between the historical maximum voltage value corresponding to the previous sliding time window and the first larger voltage value. It is understood that when determining the maximum value within the sliding event window, the maximum value from the previous time window can be introduced, thereby increasing the robustness of fault detection.

[0087] For example, a fault in a rotary transformer can be determined by identifying the maximum value among target voltage values ​​and comparing it with the maximum voltage value within a sliding time window and a preset voltage threshold. This avoids comparing all voltage values ​​within the sliding time window with the preset voltage threshold, thus improving fault diagnosis efficiency.

[0088] Understandable Figure 2 In the embodiment shown, a sliding time window is constructed based on the fault diagnosis time and the preset data processing time. The rotating transformer is then diagnosed using the sliding time window and the voltage signal. In other words, the system can continuously collect and analyze voltage signal data through the sliding time window mechanism, thereby significantly improving the real-time performance of fault detection and the system's rapid response capability.

[0089] The following is combined Figure 5 , Figure 6 The following examples illustrate fault diagnosis for rotary transformers.

[0090] Figure 5 A flowchart illustrating a fault diagnosis method for a rotary transformer according to an embodiment of this application is shown. Figure 6 A schematic diagram of a process for determining the maximum value using a sliding time window is shown in one embodiment of this application.

[0091] like Figure 5 As shown, in S510, the recovered SIN signal and recovered COS signal sampled by the main control chip are shaped to obtain the target sine function value (SIN_Real) and the target cosine function value (COS_Real). In S520, the target sine function value and the target cosine function value are used as inputs to the angular velocity observer to obtain the rotational angular velocity of the rotary transformer. In S530, the length of the sliding time window is calculated based on the rotational angular velocity.

[0092] In one example, the sliding time window SlidingWinLen can be calculated using the following formula (1):

[0093]

[0094] in, This refers to the sliding window filtering execution time, i.e., the preset data processing time. Furthermore, the preset adjustment coefficient can be 2, meaning the entire sliding window length corresponds to the time of two rotary transformer rotation cycles. For example... rad / s, The rotation period of the rotary transformer is then... The sliding time window length is =80. The preset window length threshold can be set to 0.01 / The minimum time threshold is set to 0.01.

[0095] In S540, the absolute values ​​of the target sine and cosine functions are obtained by taking their absolute values, i.e., SIN_Abs and COS_Abs.

[0096] In the S550, the target sine and cosine function values, after taking their absolute values, are filtered using a sliding time window to obtain the maximum voltage values, namely SIN_Max and COS_Max.

[0097] Furthermore, such as Figure 6As shown, in S551, the counter, current maximum value, previous window maximum value, and output value (i.e., maximum voltage value) can be initialized, i.e., reset to zero. In S552, the sliding time window length is calculated. In S553, the counter is incremented. In S554, the current voltage value and the current maximum value are compared, and the larger of the two is updated as the current maximum value. In S555, the counter increment value is compared with the window length corresponding to the sliding time window. If the counter increment value is determined to be less than the window length corresponding to the sliding time window, S556 is executed, comparing the current maximum value and the previous window maximum value, and updating the larger of the two as the current maximum value. This process of S553-S556 is repeated until the counter increment value is greater than or equal to the window length corresponding to the sliding time window. In S557, the counter is reset to zero, the previous window maximum value is updated using the maximum voltage value, and the current maximum value is output as the maximum voltage value.

[0098] In S560, fault diagnosis is performed based on the current maximum value.

[0099] In this embodiment, fault diagnosis is performed by simultaneously disconnecting sin+ and sin-, and simultaneously disconnecting cos+ and cos-. The maximum value of the recovered signal is obtained by sliding window time filtering, and the sliding window length is calculated in real time based on the rotation frequency of the rotary transformer. This allows for faster and more reliable fault diagnosis, avoiding overcurrent and long unexpected torque time in the controller.

[0100] Based on the fault diagnosis method for rotary transformers provided in the above embodiments, this application also provides specific implementation methods for a fault diagnosis device for rotary transformers. Please refer to the following embodiments.

[0101] First see Figure 7 The fault diagnosis device for a rotary transformer provided in this application includes the following modules:

[0102] The receiving module 701 is used to receive the voltage signal output by the rotary transformer;

[0103] The calculation module 702 is used to input the voltage signal into the angular velocity observer and calculate the rotational angular velocity corresponding to the rotary transformer through the angular velocity observer;

[0104] The determination module 703 is used to determine the fault diagnosis time corresponding to the rotary transformer based on the rotational angular velocity;

[0105] The diagnostic module 704 is used to perform fault diagnosis on the rotary transformer based on the fault diagnosis time and voltage signal.

[0106] In one embodiment, the diagnostic module 704 performs fault diagnosis on the rotary transformer based on the fault diagnosis time and voltage signal as follows: a sliding time window is constructed based on the fault diagnosis time and a preset data processing time; the rotary transformer is then diagnosed based on the sliding time window and the voltage signal.

[0107] In one embodiment, after constructing a sliding time window based on the fault diagnosis time and the preset data processing time, the diagnosis module 704 is further configured to: determine the larger of the window length corresponding to the sliding time window and the preset window length threshold, and update the larger value to the window length corresponding to the sliding time window; the diagnosis module 704 performs fault diagnosis on the rotary transformer based on the sliding time window and the voltage signal in the following manner: perform fault diagnosis on the rotary transformer based on the updated sliding time window and the voltage signal.

[0108] In one embodiment, the diagnostic module 704 performs fault diagnosis on the rotary transformer based on a sliding time window and a voltage signal in the following manner: the voltage signal is truncated according to the sliding time window to obtain a truncated target voltage signal; the maximum value in the target voltage signal is determined according to the sliding time window and the target voltage signal; and the rotary transformer is diagnosed based on the maximum value and a preset voltage threshold.

[0109] In one embodiment, the target voltage signal includes multiple voltage values; the diagnostic module 704 determines the maximum value in the target voltage signal based on the sliding time window and the target voltage signal in the following manner: taking the i-th target voltage value in the target voltage signal as the maximum voltage value and starting to accumulate the counter, where i is a positive integer; determining the larger voltage value between the (i+1)-th target voltage value and the i-th target voltage value, and updating the maximum voltage value using the larger voltage value; when it is determined that the value accumulated by the counter is not the same as the window length corresponding to the sliding time window, updating the i-th target voltage value using the (i+1)-th target voltage value, and returning to the step of taking the i-th target voltage value in the target voltage signal as the maximum voltage value and starting to accumulate the counter, until the value accumulated by the counter is the same as the window length corresponding to the sliding time window, and taking the maximum voltage value as the maximum value in the target voltage signal.

[0110] In one embodiment, the diagnostic module 704 determines the larger voltage value between the (i+1)th target voltage value and the ith target voltage value in the following manner, and updates the maximum voltage value using the larger voltage value: determining the first larger voltage value between the (i+1)th target voltage value and the ith target voltage value; obtaining the historical maximum voltage value of the previous sliding time window; determining the second larger voltage value between the first larger voltage value and the historical maximum voltage value, and updating the maximum voltage value using the second larger voltage value.

[0111] In one embodiment, the determining module 703 determines the corresponding fault diagnosis time of the rotary transformer based on the rotational angular velocity in the following manner: calculating the rotational period of the rotary transformer based on the rotational angular velocity and a preset period calculation formula; and determining the corresponding fault diagnosis time of the rotary transformer based on a preset adjustment coefficient and the rotational period.

[0112] Figure 8 A schematic diagram of the hardware structure of the fault diagnosis device for a rotary transformer provided in the embodiments of this application is shown.

[0113] The fault diagnosis device for the rotary transformer may include a processor 801 and a memory 802 storing computer program instructions.

[0114] Specifically, the processor 801 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0115] Memory 802 may include mass storage for data or instructions. For example, and not limitingly, memory 802 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 802 may include removable or non-removable (or fixed) media. Where appropriate, memory 802 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 802 is non-volatile solid-state memory.

[0116] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to one aspect of this disclosure.

[0117] The processor 801 reads and executes computer program instructions stored in the memory 802 to implement any of the fault diagnosis methods for the rotary transformer in the above embodiments.

[0118] In one example, the fault diagnosis device for the rotary transformer may also include a communication interface 803 and a bus 810. Wherein, as... Figure 8 As shown, the processor 801, memory 802, and communication interface 803 are connected through bus 810 and complete communication with each other.

[0119] The communication interface 803 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0120] Bus 810 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 810 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0121] The fault diagnosis device for the rotary transformer can execute the fault diagnosis method for the rotary transformer in this application embodiment based on a voltage signal, thereby achieving a combination of... Figure 3 The method for diagnosing faults in a rotary transformer is described.

[0122] Furthermore, in conjunction with the fault diagnosis method for the rotary transformer described in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the fault diagnosis methods for the rotary transformer described in the above embodiments.

[0123] This application also provides a computer program product, including a computer program that, when executed, implements any of the fault diagnosis methods for rotary transformers described in the above embodiments.

[0124] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0125] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0126] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0127] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0128] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method of failure diagnosis of a rotary transformer, characterized by, The method comprises the following steps: receiving a voltage signal of the resolver output; inputting the voltage signal into an angular velocity observer, and calculating a corresponding rotation angular velocity of the resolver through the angular velocity observer; determining a fault diagnosis time corresponding to the resolver according to the rotation angular velocity; performing fault diagnosis on the resolver according to the fault diagnosis time and the voltage signal; the step of performing fault diagnosis on the resolver according to the fault diagnosis time and the voltage signal comprises the following steps: constructing a sliding time window according to the fault diagnosis time and a preset data processing time; performing fault diagnosis on the resolver according to the sliding time window and the voltage signal; the voltage signal is a maximum value in a plurality of target voltage signals in the sliding time window; taking an i-th target voltage value in the target voltage signals as a maximum voltage value, and starting to accumulate a counter, wherein i is a positive integer; determining a voltage larger value between an i+1-th target voltage value and the i-th target voltage value, and updating the maximum voltage value through the voltage larger value; when a value accumulated by the counter is different from a window length corresponding to the sliding time window, updating the i-th target voltage value with the i+1-th target voltage value, and returning to the step of taking the i-th target voltage value in the target voltage signals as the maximum voltage value and starting to accumulate the counter, until the value accumulated by the counter is the same as the window length corresponding to the sliding time window, and taking the maximum voltage value as the maximum value in the target voltage signals.

2. The method of claim 1, wherein, After the step of constructing the sliding time window according to the fault diagnosis time and the preset data processing time, the method further comprises the following steps: determining a larger value between a window length corresponding to the sliding time window and a preset window length threshold, and updating the larger value as the window length corresponding to the sliding time window; the step of performing fault diagnosis on the resolver according to the sliding time window and the voltage signal comprises the following steps: performing fault diagnosis on the resolver according to the updated sliding time window and the voltage signal.

3. The method of claim 1, wherein, the step of performing fault diagnosis on the resolver according to the sliding time window and the voltage signal comprises the following steps: cutting the voltage signal according to the sliding time window to obtain a target voltage signal after cutting; determining a maximum value in the target voltage signal according to the sliding time window and the target voltage signal; performing fault diagnosis on the resolver according to the maximum value and a preset voltage threshold.

4. The method of claim 1, wherein, the step of determining a voltage larger value between the i+1-th target voltage value and the i-th target voltage value, and updating the maximum voltage value through the voltage larger value comprises the following steps: determining a first voltage larger value between the i+1-th target voltage value and the i-th target voltage value; obtaining a historical maximum voltage value of a previous sliding time window; Determine a second voltage greater value between the first voltage greater value and the historical maximum voltage value, and update the maximum voltage value by the second voltage greater value.

5. A fault diagnosis device for a rotary transformer, characterized in that, The device comprises: A receiving module is configured to receive a voltage signal output by the resolver; A calculating module is configured to input the voltage signal into an angular velocity observer, and calculate a corresponding rotation angular velocity of the resolver by the angular velocity observer; A determining module is configured to determine a fault diagnosis time corresponding to the resolver according to the rotation angular velocity; A diagnosing module is configured to perform fault diagnosis on the resolver according to the fault diagnosis time and the voltage signal, and construct a sliding time window according to the fault diagnosis time and a preset data processing time, perform fault diagnosis on the resolver according to the sliding time window and the voltage signal, take a maximum value of a plurality of target voltage signals in the sliding time window as the voltage signal, take an i-th target voltage value in the target voltage signals as a maximum voltage value, and start accumulating a counter, where i is a positive integer, determine a voltage greater value between an i+1-th target voltage value and the i-th target voltage value, and update the maximum voltage value by the voltage greater value, and when a value accumulated by the counter is different from a window length corresponding to the sliding time window, update the i-th target voltage value by the i+1-th target voltage value, and return to the step of taking the i-th target voltage value in the target voltage signals as the maximum voltage value, and start accumulating the counter, until the value accumulated by the counter is the same as the window length corresponding to the sliding time window, and take the maximum voltage value as the maximum value of the target voltage signals.

6. A failure diagnosis device of a rotary transformer characterized by comprising: The device comprises a processor and a memory storing computer program instructions; The processor executes the computer program instructions to implement the resolver fault diagnosis method according to any one of claims 1-4.

7. A computer readable storage medium characterized by The computer readable storage medium stores computer program instructions, and the computer program instructions are executed by a processor to implement the resolver fault diagnosis method according to any one of claims 1-4.

8. A computer program product, characterised in that, The instructions in the computer program product are executed by a processor of an electronic device, so that the electronic device performs the resolver fault diagnosis method according to any one of claims 1-4.

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