Fault detection methods and devices for rotary transformers

Abstract

This invention provides a fault detection method and apparatus for a rotary transformer, applied to a controller. The controller is connected to a rotary transformer under test. The rotary transformer under test is used to detect the speed signal of an external permanent magnet synchronous motor. The method includes: acquiring a current measurement value detected by a sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test; inputting the current measurement value and the speed signal into a preset residual evaluation function of the permanent magnet synchronous motor; and outputting an evaluation result indicating whether a fault exists in the rotary transformer under test. This method improves the accuracy of fault detection of the rotary transformer within the permanent magnet synchronous motor by detecting the current measurement value detected by the sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test through a preset residual evaluation function.

Description

Technical Field

[0001] This invention relates to the field of AC motor technology, and in particular to a fault detection method and apparatus for a rotary transformer. Background Technology

[0002] A permanent magnet synchronous motor (PMSM) is a type of synchronous motor that uses permanent magnets to establish an excitation magnetic field. Compared to other motors, PMSMs have a simple structure, and in particular, the transmission gears do not wear. Therefore, they have advantages such as low noise, simple maintenance, high reliability, and high power efficiency. Currently, PMSMs are widely used in metallurgy, rubber, petroleum, textiles, household appliances, and aerospace. The core control parameter of a PMSM is its rotational speed, and the main sensors are a sampling resistor and a rotary transformer. The rotary transformer measures the motor's rotational speed signal and is the core sensor of the motor. However, due to long-term operation, the rotary transformer is highly susceptible to failure, causing abnormal control inputs, which can severely damage the PMSM and even lead to catastrophic accidents. Therefore, researching fault detection methods for rotary transformers is essential. Here, prior art with publication number CN113484802A discloses a fault detection method and device for a rotary transformer, which determines whether a break fault has occurred in the two transmission lines based on the amplitude form of the first and second output signals of the rotary transformer; another prior art with publication number CN108761264A discloses a method, device, and system for detecting encoder wiring faults in a rotary transformer, which analyzes the occurrence of encoder wiring faults by comparing the difference between the actual rotor angle and the theoretical rotor angle. However, the above methods are for detecting rotary transformer faults with large amplitudes. In practical applications, due to factors such as increased background noise or small early fault amplitudes, the motor may experience a more difficult-to-detect minute fault. When using traditional methods to detect it, the fault may hardly cause a significant change in the corresponding signal, making it impossible to determine whether a fault has occurred. Therefore, there is an urgent need to develop new rotary transformer fault detection methods to improve the reliability of permanent magnet synchronous motors.

[0003] Overall, existing fault detection methods for rotary transformers still suffer from inaccurate detection results. Summary of the Invention

[0004] The purpose of this invention is to provide a fault detection method and apparatus for a rotary transformer, so as to improve the accuracy of fault detection for a rotary transformer of a permanent magnet synchronous motor.

[0005] In a first aspect, embodiments of the present invention provide a fault detection method for a rotary transformer, wherein the method is applied to a controller; the controller is connected to a rotary transformer under test; the rotary transformer under test is used to detect the speed signal of an external permanent magnet synchronous motor; the method includes: acquiring a current measurement value detected by a sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test; inputting the current measurement value and the speed signal into a preset residual evaluation function of the permanent magnet synchronous motor; and outputting an evaluation result indicating whether the rotary transformer under test has a fault.

[0006] In conjunction with the first aspect, the present invention provides a first possible implementation of the first aspect, wherein the residual evaluation function is constructed through the following steps: constructing a permanent magnet synchronous motor model based on the operating principle of the permanent magnet synchronous motor; constructing a Kalman filter based on the permanent magnet synchronous motor model; designing a residual generator based on the Kalman filter; the residual generator having a residual window; and constructing the residual evaluation function of the permanent magnet synchronous motor based on the residual generator.

[0007] In conjunction with the first possible implementation of the first aspect, this embodiment of the invention provides a second possible implementation of the first aspect, wherein the step of constructing a permanent magnet synchronous motor model based on the operating principle of the permanent magnet synchronous motor described above includes: constructing a permanent magnet synchronous motor model according to the following first formula: Among them, i d Let i be the d-axis current of the aforementioned permanent magnet synchronous motor. q Let ω be the q-axis current of the aforementioned permanent magnet synchronous motor. m T represents the rotational speed of the aforementioned permanent magnet synchronous motor. l The load torque of the aforementioned permanent magnet synchronous motor, u d Let u be the d-axis voltage of the aforementioned permanent magnet synchronous motor. q R is the q-axis voltage of the aforementioned permanent magnet synchronous motor. s L is the stator phase resistance of the aforementioned permanent magnet synchronous motor. d Let L be the d-axis inductance of the aforementioned permanent magnet synchronous motor. q Let p be the q-axis inductance of the aforementioned permanent magnet synchronous motor, ψ be the excitation flux linkage of the permanent magnet in the aforementioned permanent magnet synchronous motor, and p be the excitation flux linkage of the permanent magnet in the aforementioned permanent magnet synchronous motor. n Let J be the number of pole pairs of the permanent magnet synchronous motor, J be the total moment of inertia of the permanent magnet synchronous motor, and μ be the total viscosity coefficient of the permanent magnet synchronous motor. For the above i d The derivative, For the above i d The derivative, For the above ω m The derivative, For the above Tl The derivative; if i d =0, simplifying the first formula above, we get the following second formula: Among them, A c B represents the first preset coefficient. c This represents the second preset coefficient; transforming the above second formula, we obtain the following third formula: Discretizing the third formula using the forward Euler method yields the fourth and fifth formulas. These four and fifth formulas are used to define the permanent magnet synchronous motor model. The fourth formula is: x(k+1)=Ax(k)+Bu(k)+w(k), where x(k)=[i q (k) ω m (k) T l (k)] T x(k) represents the state value of the above permanent magnet synchronous motor model at time k, i q (k) represents the value of the d-axis current of the aforementioned permanent magnet synchronous motor at time k, ω m (k) represents the rotational speed of the aforementioned permanent magnet synchronous motor at time k, T l (k) represents the load torque of the permanent magnet synchronous motor at time k, x(k+1) represents the state value of the permanent magnet synchronous motor model at time k+1, A is the third preset coefficient, B is the fourth preset coefficient, x(k) is the value of the permanent magnet synchronous motor model at time k, u(k) is the preset input value of the permanent magnet synchronous motor model at time k, and w(k) is the first preset zero-mean Gaussian white noise; the fifth formula is: y(k)=Cx(k)+v(k)+Ff(k), y(k)=[y1(k) y2(k)] T Where y(k) is the data input of the permanent magnet synchronous motor model at time k, y1(k) is the measured current value, and y2(k) is the speed signal. v(k) represents the second preset zero-mean Gaussian white noise.

[0008] In conjunction with the second possible implementation of the first aspect, this embodiment of the invention provides a third possible implementation of the first aspect, wherein the step of constructing the Kalman filter based on the above permanent magnet synchronous motor model includes: constructing the following sixth formula based on the above fourth formula: in, Let be the posterior estimate of the above permanent magnet synchronous motor model at time k-1. This is the prior estimate of the above permanent magnet synchronous motor model at time k; based on the sixth formula above, calculate the following seventh formula: P(k|k-1)=AP(k-1)A T +Q wWhere P(k-1) is the posterior estimation error covariance matrix of the Kalman filter at time k-1, and P(k|k-1) is the preset prior estimation error covariance matrix at time k, Q w Let P be the covariance matrix of the first preset zero-mean Gaussian white noise; according to the seventh formula above, calculate the following eighth formula: -1 (k)=P -1 (k|k-1)+C T Q v C, where P(k) is the posterior estimation error covariance matrix of the Kalman filter at time k. Q v The covariance matrix of the second preset zero-mean Gaussian white noise is given above; according to the eighth formula above, the following ninth formula is calculated: in, Let k be the posterior estimate of the Kalman filter at time k; let the sixth, seventh, eighth and ninth formulas be used as the Kalman filter.

[0009] In conjunction with the third possible implementation of the first aspect, this embodiment of the invention provides a fourth possible implementation of the first aspect, wherein the step of designing the residual generator based on the above-described Kalman filter includes: calculating the following tenth formula based on the above-described Kalman filter: Where s(k) is the single-step residual of the Kalman filter at time k; according to the tenth formula above, the following eleventh formula is calculated: S(k) = Q v -CP(k)C T Where S(k) is the covariance matrix of s(k) above; according to the eleventh formula above, calculate the twelfth formula below: Wherein, τ is the fifth preset coefficient; the above twelfth formula is determined as the above residual generator.

[0010] In conjunction with the fourth possible implementation of the first aspect, this embodiment of the invention provides a fifth possible implementation of the first aspect, wherein the step of constructing the residual evaluation function of the permanent magnet synchronous motor according to the residual generator includes: calculating the covariance matrix of the residual generator; and constructing the residual evaluation function of the permanent magnet synchronous motor according to the covariance matrix of the residual generator and the residual generator.

[0011] In conjunction with the fifth possible implementation of the first aspect, this embodiment of the invention provides a sixth possible implementation of the first aspect, wherein the step of calculating the covariance matrix of the residual generator includes: calculating the covariance matrix of the residual generator according to the following thirteenth formula: Where R(k) is the covariance matrix of the residual generator mentioned above.

[0012] In conjunction with the sixth possible implementation of the first aspect, this embodiment of the invention provides a seventh possible implementation of the first aspect, wherein the step of constructing the residual evaluation function of the permanent magnet synchronous motor based on the covariance matrix of the residual generator and the residual generator includes: constructing the residual evaluation function of the permanent magnet synchronous motor according to the following fourteenth formula: J(k)=r T (k)R -1 (k)r(k), where J(k) is the residual evaluation function mentioned above.

[0013] In conjunction with the fifth possible implementation of the first aspect, this embodiment of the invention provides an eighth possible implementation of the first aspect, wherein the step of inputting the aforementioned current measurement value and the aforementioned speed signal into a preset residual evaluation function of the permanent magnet synchronous motor, and outputting an evaluation result indicating whether the rotary transformer under test has a fault, includes: inputting the aforementioned current measurement value and the aforementioned speed signal into the preset residual evaluation function of the permanent magnet synchronous motor to obtain a residual evaluation result; if the aforementioned residual evaluation result is greater than a preset threshold in the aforementioned residual evaluation function, outputting that the rotary transformer has a fault; if the aforementioned residual evaluation result is less than or equal to the aforementioned preset threshold, outputting that the rotary transformer does not have a fault.

[0014] Secondly, embodiments of the present invention provide a fault detection device for a rotary transformer, wherein the device is applied to a controller; the controller is connected to a rotary transformer under test; the rotary transformer under test is used to detect the speed signal of an external permanent magnet synchronous motor; the device includes: a data acquisition module, used to acquire a current measurement value detected by a sampling resistor of the permanent magnet synchronous motor and a speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test; and a fault judgment module, used to input the current measurement value and the speed signal into a preset residual evaluation function of the permanent magnet synchronous motor, and output an evaluation result indicating whether the rotary transformer under test has a fault.

[0015] The embodiments of the present invention bring the following beneficial effects:

[0016] The present invention provides a method and apparatus for fault detection of a rotary transformer, applied to a controller; the controller is connected to a rotary transformer under test; the rotary transformer under test is used to detect the speed signal of an external permanent magnet synchronous motor; the method includes: acquiring a current measurement value detected by a sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test; inputting the current measurement value and the speed signal into a preset residual evaluation function of the permanent magnet synchronous motor, and outputting an evaluation result indicating whether the rotary transformer under test has a fault. This method improves the accuracy of fault detection of the rotary transformer within the permanent magnet synchronous motor by detecting the current measurement value detected by the sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test through a preset residual evaluation function.

[0017] Other features and advantages disclosed in this embodiment will be set forth in the following description, or some features and advantages may be inferred from the description or determined without doubt, or may be learned by practicing the techniques described above.

[0018] To make the above-mentioned objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating a fault detection method for a rotary transformer provided in an embodiment of the present invention;

[0021] Figure 2 A flowchart illustrating the construction process of a residual evaluation function for a permanent magnet synchronous motor provided in an embodiment of the present invention;

[0022] Figure 3 This is a schematic diagram of the structure of a fault detection device for a rotary transformer provided in an embodiment of the present invention;

[0023] Figure 4 This invention provides a schematic diagram of an electronic device structure.

[0024] Icons: 31-Data acquisition module; 32-Fault diagnosis module; 41-Memory; 42-Processor; 43-Bus; 44-Communication interface. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0026] In practical applications, due to factors such as increased background noise or small early fault amplitudes, this motor may experience subtle faults that are more difficult to detect. When using traditional methods for detection, the fault may not cause significant changes in the corresponding signal, making it impossible to determine whether a fault has occurred. Therefore, there is an urgent need to develop new methods for detecting rotary transformer faults to improve the reliability of permanent magnet synchronous motors.

[0027] Based on this, embodiments of the present invention provide a method and apparatus for fault detection of a rotary transformer, which can improve the accuracy of fault detection of rotary transformers in permanent magnet synchronous motors. To facilitate understanding of the embodiments of the present invention, a method for fault detection of a rotary transformer disclosed in the embodiments of the present invention will first be introduced.

[0028] Example 1

[0029] like Figure 1 This is a flowchart illustrating a fault detection method for a rotary transformer according to an embodiment of the present invention. The method is applied to a controller; the controller is connected to the rotary transformer under test; the rotary transformer under test is used to detect the speed signal of an external permanent magnet synchronous motor. Figure 1 As seen, the method includes the following steps:

[0030] Step S101: Obtain the current measurement value detected by the sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test.

[0031] In this embodiment, the rotary transformer to be tested is placed inside the permanent magnet synchronous motor to detect the speed signal of the permanent magnet synchronous motor.

[0032] Step S102: Input the above current measurement value and the above speed signal into the preset residual evaluation function of the above permanent magnet synchronous motor, and output the evaluation result of whether the above-tested rotary transformer has a fault.

[0033] In this implementation, the residual evaluation function is constructed based on the operating principle of the permanent magnet synchronous motor.

[0034] The present invention provides a fault detection method for a rotary transformer, applied to a controller. The controller is connected to a rotary transformer under test. The rotary transformer under test is used to detect the speed signal of an external permanent magnet synchronous motor. The method includes: acquiring a current measurement value detected by a sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test; inputting the current measurement value and the speed signal into a preset residual evaluation function of the permanent magnet synchronous motor; and outputting an evaluation result indicating whether the rotary transformer under test has a fault. This method improves the fault detection accuracy of the rotary transformer within the permanent magnet synchronous motor by detecting the current measurement value detected by the sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test through a preset residual evaluation function.

[0035] Example 2

[0036] exist Figure 1 Based on the method shown, this invention also provides another fault detection method for rotary transformers. This method specifically describes the construction process of the residual evaluation function for permanent magnet synchronous motors. Figure 2 This is a flowchart illustrating the construction process of a residual evaluation function for a permanent magnet synchronous motor, as provided in an embodiment of the present invention.

[0037] like Figure 2 As seen, the residual evaluation function of the aforementioned permanent magnet synchronous motor is constructed through the following steps:

[0038] Step S201: Based on the operating principle of the permanent magnet synchronous motor described above, construct a permanent magnet synchronous motor model.

[0039] In this embodiment, the permanent magnet synchronous motor model is constructed according to the following first formula:

[0040]

[0041] Among them, i d Let i be the d-axis current of the aforementioned permanent magnet synchronous motor. q Let ω be the q-axis current of the aforementioned permanent magnet synchronous motor. m T represents the rotational speed of the aforementioned permanent magnet synchronous motor. l The load torque of the aforementioned permanent magnet synchronous motor, u d Let u be the d-axis voltage of the aforementioned permanent magnet synchronous motor. q R is the q-axis voltage of the aforementioned permanent magnet synchronous motor. s L is the stator phase resistance of the aforementioned permanent magnet synchronous motor. d Let L be the d-axis inductance of the aforementioned permanent magnet synchronous motor. q Let p be the q-axis inductance of the aforementioned permanent magnet synchronous motor, ψ be the excitation flux linkage of the permanent magnet in the aforementioned permanent magnet synchronous motor, and p be the excitation flux linkage of the permanent magnet in the aforementioned permanent magnet synchronous motor. nLet J be the number of pole pairs of the permanent magnet synchronous motor, J be the total moment of inertia of the permanent magnet synchronous motor, and μ be the total viscosity coefficient of the permanent magnet synchronous motor. For the above i d The derivative, For the above i d The derivative, For the above ω m The derivative, For the above T l The derivative;

[0042] If i d =0, simplifying the first formula above, we get the following second formula:

[0043]

[0044] Among them, A c B represents the first preset coefficient. c This indicates the second preset coefficient;

[0045] Transforming the second formula above, we obtain the following third formula:

[0046]

[0047] Discretize the third formula above using the forward Euler method to obtain the fourth and fifth formulas below;

[0048] The fourth and fifth formulas above are used to determine the permanent magnet synchronous motor model mentioned above.

[0049] The fourth formula above is: x(k+1)=Ax(k)+Bu(k)+w(k)

[0050] Where, x(k)=[i q (k) ω m (k) T l (k)] T x(k) represents the state value of the above permanent magnet synchronous motor model at time k, i q (k) represents the value of the d-axis current of the aforementioned permanent magnet synchronous motor at time k, ω m (k) represents the rotational speed of the aforementioned permanent magnet synchronous motor at time k, T l (k) represents the load torque of the permanent magnet synchronous motor at time k, x(k+1) represents the state value of the permanent magnet synchronous motor model at time k+1, A is the third preset coefficient, B is the fourth preset coefficient, x(k) is the value of the permanent magnet synchronous motor model at time k, u(k) is the preset input value of the permanent magnet synchronous motor model at time k, and w(k) is the first preset zero-mean Gaussian white noise;

[0051] The fifth formula above is: y(k)=Cx(k)+v(k)+Ff(k), y(k)=[y1(k) y2(k)] T ;

[0052] Where y(k) is the data input of the permanent magnet synchronous motor model at time k, y1(k) is the measured current value, and y2(k) is the speed signal. v(k) represents the second preset zero-mean Gaussian white noise.

[0053] Step S202: Construct a Kalman filter based on the above permanent magnet synchronous motor model.

[0054] In this embodiment, based on the fourth formula, the following sixth formula is constructed:

[0055]

[0056] in, Let be the posterior estimate of the above permanent magnet synchronous motor model at time k-1. This is the prior estimate of the above permanent magnet synchronous motor model at time k;

[0057] Based on the sixth formula above, calculate the following seventh formula:

[0058] P(k|k-1)=AP(k-1)A T +Q w

[0059] Where P(k-1) is the posterior estimation error covariance matrix of the Kalman filter at time k-1, and P(k|k-1) is the preset prior estimation error covariance matrix at time k. w The covariance matrix of the aforementioned first preset zero-mean Gaussian white noise;

[0060] Based on the seventh formula above, calculate the following eighth formula:

[0061] P -1 (k)=P -1 (k|k-1)+C T Q v C

[0062] Where P(k) is the posterior estimation error covariance matrix of the Kalman filter at time k. Q v The covariance matrix of the aforementioned second preset zero-mean Gaussian white noise;

[0063] Based on the eighth formula above, calculate the following ninth formula:

[0064]

[0065] in, Let be the posterior estimate of the Kalman filter at time k.

[0066] Formulas 6, 7, 8, and 9 above are defined as the Kalman filter.

[0067] Step S203: Based on the above Kalman filter, design a residual generator; the residual generator has a residual window.

[0068] Here, the steps for designing the residual generator based on the Kalman filter described above include:

[0069] Based on the Kalman filter described above, calculate the following tenth formula:

[0070]

[0071] Where s(k) is the single-step residual of the Kalman filter at time k;

[0072] Based on the tenth formula above, calculate the eleventh formula as follows:

[0073] S(k)=Q v -CP(k)C T ;

[0074] Where S(k) is the covariance matrix of the above s(k);

[0075] Based on the eleventh formula above, calculate the twelfth formula below:

[0076]

[0077] Wherein, τ is the fifth preset coefficient;

[0078] The twelfth formula above is used as the residual generator.

[0079] Step S204: Based on the above residual generator, construct the residual evaluation function of the above permanent magnet synchronous motor.

[0080] In actual operation, step S204 includes: first, calculating the covariance matrix of the residual generator; then, constructing the residual evaluation function of the permanent magnet synchronous motor based on the covariance matrix and the residual generator.

[0081] In one embodiment, the step of calculating the covariance matrix of the residual generator includes:

[0082] Calculate the covariance matrix of the residual generator described above using the following formula (Equation XIII):

[0083]

[0084] Where R(k) is the covariance matrix of the residual generator mentioned above.

[0085] Furthermore, the step of constructing the residual evaluation function of the permanent magnet synchronous motor based on the covariance matrix of the residual generator and the residual generator itself includes:

[0086] Based on the following fourteenth formula, construct the residual evaluation function for the above permanent magnet synchronous motor:

[0087] J(k)=r T (k)R -1 (k)r(k)

[0088] Where J(k) is the residual evaluation function mentioned above.

[0089] In practical operation, the steps of inputting the aforementioned current measurement value and speed signal into a preset residual evaluation function of the permanent magnet synchronous motor, and outputting an evaluation result indicating whether the rotary transformer under test has a fault, include: First, inputting the aforementioned current measurement value and speed signal into the preset residual evaluation function of the permanent magnet synchronous motor to obtain a residual evaluation result. Second, if the residual evaluation result is greater than a preset threshold in the residual evaluation function, outputting that the rotary transformer has a fault. Finally, if the residual evaluation result is less than or equal to the preset threshold, outputting that the rotary transformer does not have a fault.

[0090] The present invention provides a fault detection method for a rotary transformer, applied to a controller; the controller is connected to a rotary transformer under test; the rotary transformer under test is used to detect the speed signal of an external permanent magnet synchronous motor; the method includes: acquiring a current measurement value detected by a sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test; inputting the current measurement value and the speed signal into a preset residual evaluation function of the permanent magnet synchronous motor, and outputting an evaluation result indicating whether the rotary transformer under test has a fault; wherein, the residual evaluation function of the permanent magnet synchronous motor is constructed through the following steps: constructing a permanent magnet synchronous motor model based on the operating principle of the permanent magnet synchronous motor; constructing a Kalman filter based on the permanent magnet synchronous motor model; designing a residual generator based on the Kalman filter; the residual generator having a residual window; and constructing the residual evaluation function of the permanent magnet synchronous motor based on the residual generator. This method constructs a preset residual evaluation function based on the operating principle of the permanent magnet synchronous motor, and uses the residual evaluation function to detect the current measurement value detected by the sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test, thereby further improving the fault detection accuracy of the rotary transformer in the permanent magnet synchronous motor.

[0091] Example 3

[0092] This invention also provides a fault detection device for a rotary transformer. Figure 3 This is a schematic diagram of a fault detection device for a rotary transformer according to an embodiment of the present invention. The device is applied to a controller; the controller is connected to the rotary transformer under test; the rotary transformer under test is used to detect the speed signal of an external permanent magnet synchronous motor. Figure 3 As seen above, the aforementioned device includes:

[0093] The data acquisition module 31 is used to acquire the current measurement value detected by the sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test.

[0094] The fault judgment module 32 is used to input the above-mentioned current measurement value and the above-mentioned speed signal into the preset residual evaluation function of the above-mentioned permanent magnet synchronous motor, and output the evaluation result of whether the above-mentioned rotary transformer under test has a fault.

[0095] The data acquisition module 31 and the fault judgment module 32 are connected.

[0096] The fault detection device for a rotary transformer provided in this embodiment of the invention has the same technical features as the fault detection method for a rotary transformer provided in the above embodiments, and therefore can solve the same technical problems and achieve the same technical effects. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the method described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0097] Example 4

[0098] This embodiment provides an electronic device, including a processor and a memory. The memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the steps of a fault detection method for a rotary transformer.

[0099] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of a fault detection method for a rotary transformer.

[0100] See Figure 4 The diagram shows the structure of an electronic device, which includes a memory 41 and a processor 42. The memory 41 stores a computer program that can run on the processor 42. When the processor executes the computer program, it implements the steps provided by the above-mentioned fault detection method for a rotary transformer.

[0101] like Figure 4 As shown, the device also includes a bus 43 and a communication interface 44, with the processor 42, the communication interface 44 and the memory 41 connected via the bus 43; the processor 42 is used to execute executable modules, such as computer programs, stored in the memory 41.

[0102] The memory 41 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 44 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.

[0103] Bus 43 can be an ISA bus, PCI bus, or EISA bus, etc. Buses can be divided into address buses, data buses, control buses, etc. For ease of representation, Figure 4 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0104] The memory 41 stores the program, and the processor 42 executes the program after receiving the execution instruction. The method executed by the fault detection device for the rotary transformer disclosed in any of the foregoing embodiments of the present invention can be applied to the processor 42, or implemented by the processor 42. The processor 42 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor 42 or by instructions in the form of software. The processor 42 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this invention can be directly manifested as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory 41, and processor 42 reads information from memory 41 and, in conjunction with its hardware, completes the steps of the above method.

[0105] Furthermore, this embodiment of the invention also provides a machine-readable storage medium storing machine-executable instructions. When these machine-executable instructions are invoked and executed by the processor 42, they cause the processor 42 to implement the aforementioned fault detection method for the rotary transformer.

[0106] The electronic devices and computer-readable storage media provided in the embodiments of the present invention have the same technical features, so they can also solve the same technical problems and achieve the same technical effects.

[0107] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, 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 of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0108] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

Claims

1. A fault detection method for a rotary transformer, characterized in that, The method is applied to a controller; the controller is connected to a rotary transformer under test; the rotary transformer under test is used to detect the speed signal of an external permanent magnet synchronous motor; the method includes: Acquire the current measurement value detected by the sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test; The measured current value and the speed signal are input into the preset residual evaluation function of the permanent magnet synchronous motor, and the evaluation result of whether the rotary transformer under test has a fault is output. The residual evaluation function is constructed through the following steps: Based on the operating principle of the permanent magnet synchronous motor, a model of the permanent magnet synchronous motor is constructed; Based on the permanent magnet synchronous motor model, a Kalman filter is constructed; Based on the Kalman filter, a residual generator is designed; the residual generator has a residual window. The step of designing the residual generator based on the Kalman filter includes: Based on the Kalman filter, calculate the following tenth formula: in, Let K be the single-step residual of the Kalman filter at time k; The fifth formula is: , ; in, This represents the state value of the permanent magnet synchronous motor model at time k. This is the data input for the permanent magnet synchronous motor model at time k. The measured current value, Here, f(k) represents the rotational speed signal, and f(k) represents the fault signal of the rotary transformer under test. , v(k) represents the second preset zero-mean Gaussian white noise; Based on the tenth formula, calculate the following eleventh formula: ； in, For the The covariance matrix; Let K be the posterior estimation error covariance matrix of the Kalman filter at time k. , The covariance matrix of the second preset zero-mean Gaussian white noise; in, Let be the posterior estimate of the Kalman filter at time k; Based on the eleventh formula, calculate the following twelfth formula: in, This is the fifth preset coefficient; The twelfth formula is defined as the residual generator; Calculate the covariance matrix of the residual generator according to the following formula (XIII): in, Let be the covariance matrix of the residual generator; Based on the following fourteenth formula, construct the residual evaluation function of the permanent magnet synchronous motor: in, Let be the residual evaluation function.

2. The fault detection method for a rotary transformer according to claim 1, characterized in that, Based on the operating principle of the permanent magnet synchronous motor, the steps for constructing a permanent magnet synchronous motor model include: Construct a permanent magnet synchronous motor model based on the following first formula: in, Let be the d-axis current of the permanent magnet synchronous motor. Let be the q-axis current of the permanent magnet synchronous motor. The rotational speed of the permanent magnet synchronous motor is given. The load torque of the permanent magnet synchronous motor Let be the d-axis voltage of the permanent magnet synchronous motor. Let be the q-axis voltage of the permanent magnet synchronous motor. The stator phase resistance of the permanent magnet synchronous motor is given. The d-axis inductance of the permanent magnet synchronous motor is... Let be the q-axis inductance of the permanent magnet synchronous motor. The excitation flux linkage of the permanent magnet in the permanent magnet synchronous motor is referred to as "the magnetic flux linkage". Let be the number of pole pairs of the permanent magnet synchronous motor. The total moment of inertia loaded on the permanent magnet synchronous motor, The total viscosity coefficient of the permanent magnet synchronous motor is given. For the The derivative, For the The derivative, For the The derivative, For the The derivative; if =0, simplifying the first formula yields the following second formula: in, This represents the first preset coefficient. Indicates the second preset coefficient; Transforming the second formula yields the following third formula: Discretize the third formula using the forward Euler method to obtain the following fourth and fifth formulas; The fourth and fifth formulas are used as the model for the permanent magnet synchronous motor. The fourth formula is: in, , This represents the state value of the permanent magnet synchronous motor model at time k. This represents the value of the d-axis current of the permanent magnet synchronous motor at time k. This represents the rotational speed of the permanent magnet synchronous motor at time k. This represents the load torque of the permanent magnet synchronous motor at time k. This represents the state value of the permanent magnet synchronous motor model at time k+1, where A is the third preset coefficient and B is the fourth preset coefficient. Let be the value of the permanent magnet synchronous motor model at time k. The preset input value for the permanent magnet synchronous motor model at time k is... The first preset value is zero-mean Gaussian white noise; The fifth formula is: , ; in, This is the data input for the permanent magnet synchronous motor model at time k. The measured current value, The rotational speed signal, , v(k) represents the second preset zero-mean Gaussian white noise.

3. The fault detection method for a rotary transformer according to claim 2, characterized in that, The steps for constructing a Kalman filter based on the permanent magnet synchronous motor model include: Based on the fourth formula, the following sixth formula is constructed: in, Let be the posterior estimate of the permanent magnet synchronous motor model at time k-1. This is the prior estimate of the permanent magnet synchronous motor model at time k; Based on the sixth formula, calculate the following seventh formula: in, Let be the posterior estimation error covariance matrix of the Kalman filter at time k-1. Let k be the prior estimation error covariance matrix at time k. The covariance matrix of the first preset zero-mean Gaussian white noise; Based on the seventh formula, calculate the following eighth formula: in, Let K be the posterior estimation error covariance matrix of the Kalman filter at time k. , The covariance matrix of the second preset zero-mean Gaussian white noise; Based on the eighth formula, calculate the following ninth formula: in, Let be the posterior estimate of the Kalman filter at time k; The sixth formula, the seventh formula, the eighth formula, and the ninth formula are determined as the Kalman filter.

4. The fault detection method for a rotary transformer according to claim 1, characterized in that, The steps of inputting the measured current value and the speed signal into a preset residual evaluation function of the permanent magnet synchronous motor, and outputting an evaluation result on whether the rotary transformer under test has a fault, include: The measured current value and the speed signal are input into the preset residual evaluation function of the permanent magnet synchronous motor to obtain the residual evaluation result; If the residual evaluation result is greater than the preset threshold in the residual evaluation function, output that the rotary transformer has a fault; If the residual evaluation result is less than or equal to the preset threshold, the output is that the rotary transformer has no fault.

5. A fault detection device for a rotary transformer, characterized in that, The device is applied to a controller; the controller is connected to a rotary transformer under test; the rotary transformer under test is used to detect the speed signal of an external permanent magnet synchronous motor; the device includes: The data acquisition module is used to acquire the current measurement value detected by the sampling resistor of the permanent magnet synchronous motor and the speed signal of the permanent magnet synchronous motor detected by the rotary transformer under test; The fault diagnosis module is used to input the measured current value and the speed signal into the preset residual evaluation function of the permanent magnet synchronous motor, and output the evaluation result of whether the rotary transformer under test has a fault. The residual evaluation function is constructed through the following steps: Based on the operating principle of the permanent magnet synchronous motor, a model of the permanent magnet synchronous motor is constructed; Based on the permanent magnet synchronous motor model, a Kalman filter is constructed; Based on the Kalman filter, a residual generator is designed; the residual generator has a residual window. The step of designing the residual generator based on the Kalman filter includes: Based on the Kalman filter, calculate the following tenth formula: in, Let K be the single-step residual of the Kalman filter at time k; The fifth formula is: , ; in, This represents the state value of the permanent magnet synchronous motor model at time k. This is the data input for the permanent magnet synchronous motor model at time k. The measured current value, Here, f(k) represents the rotational speed signal, and f(k) represents the fault signal of the rotary transformer under test. , v(k) represents the second preset zero-mean Gaussian white noise; Based on the tenth formula, calculate the following eleventh formula: ； in, For the The covariance matrix; Let K be the posterior estimation error covariance matrix of the Kalman filter at time k. , The covariance matrix of the second preset zero-mean Gaussian white noise; in, Let be the posterior estimate of the Kalman filter at time k; Based on the eleventh formula, calculate the following twelfth formula: in, This is the fifth preset coefficient; The twelfth formula is defined as the residual generator; Calculate the covariance matrix of the residual generator according to the following formula (XIII): in, Let be the covariance matrix of the residual generator; Based on the following fourteenth formula, construct the residual evaluation function of the permanent magnet synchronous motor: in, Let be the residual evaluation function.

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