A fault detection method, device and medium of a current sensor

Abstract

The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium of current sensor, it is related to motor system field.The application discloses a kind of fault detection methods, device and medium

Description

TECHNICAL FIELD

[0001] The present application relates to the field of motor systems, in particular to a fault detection method and device of a current sensor and a medium. BACKGROUND

[0002] In a high-speed maglev linear motor system, the current sensor, as an important part of the control system, samples the phase current and feeds it back to the control system. The accuracy of the sampling affects the stable operation of the entire maglev linear motor system. In the long-term operation of the linear motor system, harsh operating environments such as high vibration, high humidity, high temperature, overvoltage, and overcurrent are prone to cause sampling faults of the current sensor, thereby affecting the output torque of the motor system. For application environments with low reliability requirements, simple offline detection methods can clear the faults of the current sensor. However, for occasions where the reliability of the high-speed maglev system is extremely strict, it is necessary to quickly, accurately, and in real time detect the specific fault type and position of the current sensor so as to take necessary measures. Therefore, it is urgent to conduct in-depth research on the online diagnosis of the faults of the current sensor of the high-speed maglev motor system. In practice, the current sensor has various types of faults such as sampling signal gain, offset, and broken wire in the actual process.

[0003] At present, the model and knowledge-based algorithm has completed the real-time diagnosis and positioning of the faults of the current sensor. However, since the characteristics of different faults are not distinguished, only the faults of the current sensor can be diagnosed, but the specific fault type of the current sensor cannot be diagnosed, that is, the faults cannot be accurately detected.

[0004] Therefore, how to determine the fault type of the current sensor is a technical problem that needs to be solved by those skilled in the art. SUMMARY

[0005] The purpose of the present application is to provide a fault detection method, device, and medium of a current sensor for determining the fault type of the current sensor and realizing accurate detection of the faults.

[0006] To solve the above technical problems, the present application provides a fault detection method of a current sensor, comprising:

[0007] obtaining a current value collected by the current sensor;

[0008] obtaining a detection parameter for detecting the fault of the current sensor according to the current value;

[0009] determining the fault of the current sensor and the corresponding fault type according to the detection parameter and a pre-set fault diagnosis strategy, wherein the fault diagnosis strategy contains the fault type of the current sensor and the characteristics of the detection parameter under different fault types.

[0010] Preferably, the detection parameters comprise an average value of the current values, an absolute average value of the current values;

[0011] The detection parameters for detecting the current sensor fault are obtained according to the current values, comprising:

[0012] Converting the current values in the natural coordinate system into current components in the synchronous rotating coordinate system through Park transformation;

[0013] Obtaining a current modulus value according to the current components;

[0014] Obtaining a ratio of the current values to the current modulus value to normalize the current values;

[0015] Obtaining the average value and the absolute average value of the normalized current values.

[0016] Preferably, the fault of the current sensor and the corresponding fault type are determined according to the detection parameters and a preset fault diagnosis strategy, comprising:

[0017] If the average value is equal to 0 and the absolute average value is equal to a preset value, it is determined that the current sensor is normal;

[0018] If the average value is not equal to 0 or the absolute average value is not equal to the preset value, it is determined that the current sensor is faulty;

[0019] In the case of determining that the current sensor is faulty, if the average value is equal to 0 and the absolute average value is greater than the preset value, it is determined that the fault type is a gain fault;

[0020] If the average value is greater than 0 and the absolute average value is equal to the preset value, it is determined that the fault type is a positive offset fault;

[0021] If the average value is less than 0 and the absolute average value is equal to the preset value, it is determined that the fault type is a negative offset fault;

[0022] If the average value and the absolute average value are both 0, it is determined that the fault type is a broken wire fault;

[0023] If the average value is a fixed value greater than 0 and the absolute average value is greater than the preset value, it is determined that the fault type is a positive stuck fault;

[0024] If the average value is a fixed value less than 0 and the absolute average value is greater than the preset value, it is determined that the fault type is a negative stuck fault.

[0025] Preferably, the determining that the average value is equal to 0 and the determining that the absolute average value is the preset value comprise:

[0026] determining whether the average value is within a first threshold range;

[0027] if yes, determining that the average value is equal to 0;

[0028] determining whether the absolute average value is within a second threshold range;

[0029] if yes, determining that the absolute average value is equal to the preset value.

[0030] Preferably, there are multiple-phase currents in the motor, and after the determining of the fault of the current sensor and the corresponding fault type according to the detection parameter and the preset fault diagnosis strategy, the method further comprises:

[0031] in the case of determining that the gain fault occurs, obtaining a maximum absolute average value in the absolute average values of the normalized current values of each phase, and taking the phase corresponding to the maximum absolute average value as the fault phase of the gain fault;

[0032] in the case of determining that the positive offset fault occurs, obtaining a maximum average value in the average values of the normalized current values of each phase, and taking the phase corresponding to the maximum average value as the fault phase of the positive offset fault;

[0033] in the case of determining that the negative offset fault occurs, obtaining a minimum average value in the average values of the normalized current values of each phase, and taking the phase corresponding to the minimum average value as the fault phase of the negative offset fault;

[0034] in the case of determining that the positive dead-stick fault occurs, obtaining a maximum average value in the average values of the normalized current values of each phase, and taking the phase corresponding to the maximum average value as the fault phase of the positive dead-stick fault;

[0035] in the case of determining that the negative dead-stick fault occurs, obtaining a minimum average value in the average values of the normalized current values of each phase, and taking the phase corresponding to the minimum average value as the fault phase of the negative dead-stick fault.

[0036] Preferably, after the determining of the fault of the current sensor and the corresponding fault type according to the detection parameter and the preset fault diagnosis strategy, the method further comprises:

[0037] returning to the step of obtaining the current value collected by the current sensor within a preset time after the determining of the fault of the current sensor and the corresponding fault type.

[0038] Preferably, the method further comprises:

[0039] outputting prompt information for characterizing the fault phase according to the fault type.

[0040] To solve the above technical problems, the application further provides a fault detection device of a current sensor, comprising:

[0041] a first acquisition module, configured to acquire a current value collected by the current sensor;

[0042] a second acquisition module, configured to acquire a detection parameter for detecting the fault of the current sensor according to the current value;

[0043] a determination module, configured to determine the fault of the current sensor and a corresponding fault type according to the detection parameter and a pre-set fault diagnosis strategy; wherein the fault diagnosis strategy comprises the fault type of the current sensor and characteristics of the detection parameter under different fault types.

[0044] To solve the above technical problems, the application further provides a fault detection device of a current sensor, comprising:

[0045] a memory, configured to store a computer program;

[0046] a processor, configured to execute the computer program to realize the steps of the fault detection method of the current sensor.

[0047] To solve the above technical problems, the application further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to realize the steps of the fault detection method of the current sensor.

[0048] The fault detection method of the current sensor provided by the application comprises: acquiring a current value collected by a current sensor; acquiring a detection parameter for detecting the fault of the current sensor according to the current value; and determining the fault of the current sensor and a corresponding fault type according to the detection parameter and a pre-set fault diagnosis strategy; wherein the fault diagnosis strategy comprises the fault type of the current sensor and characteristics of the detection parameter under different fault types. Compared with the previous method that can only detect the fault, in the method of the application, since the fault diagnosis strategy comprises the characteristics of the detection parameter under different fault types, the corresponding fault type can be determined according to the fault diagnosis strategy based on the acquired detection parameter, the detection of multiple types of faults is realized, and the accuracy of fault detection is improved.

[0049] In addition, the application further provides a current sensor fault detection device and a computer readable storage medium, which have the same or corresponding technical features and effects as the current sensor fault detection method mentioned above. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings described below are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0051] Figure 1 A flowchart of a current sensor fault detection method provided by an embodiment of the present application is shown in FIG. 1.

[0052] Figure 2a A gain fault diagnosis result waveform diagram provided by an embodiment of the present application is shown in FIG. 2.

[0053] Figure 2b An intermediate diagnosis variable e before and after the occurrence of a gain fault provided by an embodiment of the present application is shown in FIG. 3. n Waveform diagram

[0054] Figure 2c An intermediate diagnosis variable f before and after the occurrence of a gain fault provided by an embodiment of the present application is shown in FIG. 4. n Waveform diagram

[0055] Figure 3 A structure diagram of a current sensor fault detection device provided by an embodiment of the present application is shown in FIG. 5.

[0056] Figure 4 A structure diagram of a current sensor fault detection device provided by another embodiment of the present application is shown in FIG. 6.

[0057] Figure 5 A current sensor diagnosis principle diagram provided by an embodiment of the present application is shown in FIG. 7.

[0058] Figure 6 A flowchart of a current sensor diagnosis method provided by an embodiment of the present application is shown in FIG. 8. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, but not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0060] The core of the present application is to provide a fault detection method, device and medium of a current sensor, which is used to determine the fault type of the current sensor and realize more accurate detection of the fault.

[0061] As an important part of the control system, the current sensor samples the phase current and feeds it back to the control system, and the accuracy of the sampling affects the stable operation of the entire maglev linear motor system. In the long-term operation of the linear motor system, harsh operating environments such as high vibration, high humidity, high temperature, overvoltage, and overcurrent are easy to cause sampling faults of the current sensor, thereby affecting the output torque of the motor system. In practice, the current sensor has various types of faults such as sampling signal gain, sticking, offset, and broken line. The current methods of sensor fault diagnosis based on models or knowledge are limited to detecting faults, especially for broken line fault detection, but have poor scalability for gain, sticking, offset, and broken line fault types of the current sensor, and the model-based or knowledge-based algorithms will greatly increase the computational complexity when expanding the detection range. Therefore, the signal processing-based algorithm in the present application expands the detection range of the current sensor fault of the high-speed maglev linear motor system to gain, offset, sticking, and broken line faults, and provides a more accurate and fast new way for accurately positioning the fault type and fault point of the current sensor of the high-speed maglev linear motor system.

[0062] In order for those skilled in the art to better understand the present application scheme, the present application will be further described in detail below in combination with the drawings and specific embodiments. Figure 1 A flowchart of a fault detection method of a current sensor provided by an embodiment of the present application is shown in Figure 1 The method comprises the following steps.

[0063] S10: Obtain the current value collected by the current sensor.

[0064] S11: Obtain a detection parameter for detecting the fault of the current sensor according to the current value.

[0065] S12: Determine the fault of the current sensor and the corresponding fault type according to the detection parameter and a pre-set fault diagnosis strategy.

[0066] The fault diagnosis strategy contains the fault type of the current sensor and the characteristics of the detection parameter under different fault types.

[0067] In a high-speed maglev linear motor system, phase current signals are collected by current sensors. In a three-phase motor, three current sensors are used to sample phase current signals. However, due to current limitations, two current sensors are usually used to sample phase current signals in a three-phase motor. In order to detect current sensor faults, the current values collected by the current sensors need to be obtained first. The frequency of the current signals collected by the current sensors, the time of collection, and the like are not limited, and are determined according to actual conditions. For example, in order to be able to diagnose faults in real time according to the current values collected by the current sensors, the signal values collected by the current sensors in real time are preferably obtained.

[0068] After the current values are collected, the detection parameters for detecting current sensor faults can be further determined according to the current values. The specific detection parameters determined according to the current values are not limited, and in the embodiments of the present application, the average value and the absolute average value of the current signals collected within a period of time are used as the detection parameters.

[0069] In the process of detecting the fault type according to the detection parameters, a fault diagnosis strategy is pre-set in the embodiments. Different detection parameters correspond to different fault diagnosis strategies. In practice, when the fault diagnosis strategy is determined, the current values of the current sensors when the motor system is normally operating can be used as a reference, and then different faults such as gain, offset, stuck, and broken wire are created in the motor system, and the values of the current detection parameters under each type of fault are obtained through a large number of experiments. Since the fault diagnosis strategy includes the fault type and the characteristics of the detection parameters under the corresponding fault type, the fault diagnosis strategy can be displayed in a table. When fault detection is needed, the fault and the corresponding fault type are determined according to the detection parameters and the fault diagnosis strategy.

[0070] The fault detection method for the current sensor provided in the embodiments includes: obtaining current values collected by a current sensor; obtaining detection parameters for detecting current sensor faults according to the current values; determining the fault of the current sensor and the corresponding fault type according to the detection parameters and a pre-set fault diagnosis strategy; wherein the fault diagnosis strategy includes the fault type of the current sensor and the characteristics of the detection parameters under different fault types. Compared with the previous method that can only detect faults, in the method of the embodiments, since the fault diagnosis strategy includes the characteristics of the detection parameters under different fault types, the corresponding fault type can be determined according to the fault diagnosis strategy based on the obtained detection parameters, the detection of multiple types of faults is realized, and the accuracy of fault detection is improved.

[0071] When the fault is detected according to the detection parameters, the detection parameters can be multiple. The detection parameters selected in the embodiments include the average value of the current values and the absolute average value of the current values.

[0072] The detection parameter for detecting the current sensor fault is obtained according to the current value, comprising:

[0073] The current value in the natural coordinate system is converted into a current component in the synchronous rotating coordinate system through the Park transformation;

[0074] The current modulus value is obtained according to the current component;

[0075] The ratio of the current value and the current modulus value is obtained to normalize the current value;

[0076] The average value and the absolute average value of the normalized current value are obtained.

[0077] Considering that the motor operating conditions such as no-load, light load and load mutation will affect the stator current amplitude, the phase current needs to be normalized. First, the stator current i n The current in the synchronous rotating coordinate system i d , i q is obtained through the Park transformation. The ratio of the current and the current modulus value is the normalized preprocessing of the current, and the normalized value of the phase current is obtained The Park transformation matrix T is:

[0078]

[0079] Wherein, θe represents the angle of motor rotation.

[0080] The normalized current is subjected to the absolute average value module and the average value calculation module to obtain the average value e n , the absolute average value f n of the normalized current value. Denoted as: e n =M[i n * ], f n =M[|i n * |].

[0081]

[0082] Wherein, M represents the average value, and ω n represents the motor angular frequency. In this embodiment, e n , f n is called intermediate diagnostic variable.

[0083] The current is normalized to obtain the intermediate diagnostic variable, which prevents the motor operating conditions such as no-load, light load and load mutation from affecting the stator current amplitude, so that the obtained intermediate variable is more accurate.

[0084] In the above embodiment, on the basis of the intermediate diagnostic variable obtained, when analyzing the fault type according to the intermediate diagnostic variable, a preferred implementation manner is that the fault of the current sensor and the corresponding fault type are determined according to the detection parameter and the pre-set fault diagnosis strategy, and the fault diagnosis strategy includes:

[0085] If the average value is equal to 0 and the absolute average value is equal to the pre-set value, it is determined that the current sensor is normal;

[0086] If the average value is not equal to 0 or the absolute average value is not equal to the pre-set value, it is determined that the current sensor is faulty;

[0087] In the case of determining that the current sensor is faulty, if the average value is equal to 0 and the absolute average value is greater than the pre-set value, it is determined that the fault type is a gain fault;

[0088] If the average value is greater than 0 and the absolute average value is equal to the pre-set value, it is determined that the fault type is a positive offset fault;

[0089] If the average value is less than 0 and the absolute average value is equal to the pre-set value, it is determined that the fault type is a negative offset fault;

[0090] If the average value and the absolute average value are both 0, it is determined that the fault type is a broken wire fault;

[0091] If the average value is a fixed value greater than 0 and the absolute average value is greater than the pre-set value, it is determined that the fault type is a positive stuck fault;

[0092] If the average value is a fixed value less than 0 and the absolute average value is greater than the pre-set value, it is determined that the fault type is a negative stuck fault.

[0093] The normalized phase currents are represented as:

[0094] i a_m = βi a +C = βI am cos(ωt+θ ori )+C

[0095] i b_m = i b

[0096] i c_m = i c

[0097] Wherein, i a , i b , i c are actual stator currents, i a_m , i b_m , i c_mis the current measured by the current sensor, β is a current sensor gain factor, C is an offset coefficient, I am is the phase current amplitude, ω is the motor angular frequency, θ ori is the initial phase angle.

[0098] For different open circuit faults, the intermediate diagnostic variable e n , f n represents the method is (assuming that the a1 phase is the fault phase):

[0099] (2A), when operating normally, the currents in each phase are symmetrical, so that e n =M[i n * ]=0, f n =M[|i n * |=ζ; wherein ζ represents a preset value; the preset value is not limited, and is determined according to actual conditions; the expression of ζ is as follows:

[0100]

[0101] (2B), when a current sensor gain fault occurs, the currents in each phase are not biased in direct current, but the amplitudes thereof are increased or decreased to different degrees. The current amplitude of the gain fault phase is increased most, so that the intermediate diagnostic variable e a1 =M[i a1 * ]=0, f a1 =M[|i a1 * |]>ζ; Figure 2a is a gain fault diagnosis result waveform diagram provided by an embodiment of the application; Figure 2b is an intermediate diagnostic variable e n waveform diagram before and after a gain fault occurs, provided by an embodiment of the application; Figure 2c is an intermediate diagnostic variable f n waveform diagram before and after a gain fault occurs, provided by an embodiment of the application.

[0102] (2C), when a current sensor positive offset fault occurs, the currents in each phase are biased in direct current, and the bias amplitude of the current in the fault phase is the largest, so that the intermediate diagnostic variable e a1 satisfies e a1 =M[i a1 * ]>0 (for a negative offset fault: e a1 =M[i a1 * ]<0). Since the direct current bias has a small influence on the absolute average value of the current waveform, the intermediate diagnostic variable f a1 =M[|i a1* |]=ζ.

[0103] (2D) When a current sensor disconnection fault occurs, the current in the faulty phase becomes zero. At this time, e a1 =M[i a1 * ] = 0, f a1 =M[|i a1 * |] = 0;

[0104] (2E) When a current sensor is stuck, the current output of the faulty phase is a fixed DC quantity, denoted as a constant c>0. At this time, e a1 =M[i a1 * ]=c>0、f a1 =M[|i a1 * |]>ζ(Negative jamming fault: e a1 =M[i a1 * ]=c<0、f a1 =M[|i a1 * |]>ζ).

[0105] The present embodiment provides a method for determining faults and their corresponding fault types based on the characteristics of intermediate variables.

[0106] To avoid misdiagnosis of faults, in practice, a preferred implementation method includes determining that the average value is equal to 0 and determining that the absolute average value is a preset value, including:

[0107] Determine if the average value is within the first threshold range;

[0108] If so, then the average value is determined to be 0;

[0109] Determine whether the absolute average value is within the second threshold range;

[0110] If so, then the absolute average value is determined to be equal to the preset value.

[0111] To avoid misdiagnosis of faults, it is usually necessary to set a threshold range for intermediate diagnostic variables. For example, the threshold can be set to 0.05, and the average value is the intermediate diagnostic variable e. n The first threshold range is [-0.05, 0.05], and the absolute average is the intermediate diagnostic variable f. n The second threshold range is [ζ-0.05, ζ+0.05]. That is, when f is determined... n In the range [ζ-0.05, ζ+0.05], e n In the range [-0.05, 0.05], the detection system outputs f.n = ζ, e n = 0.

[0112] The threshold range provided by the embodiment can avoid misdiagnosis as much as possible.

[0113] In order to eliminate the influence of normal phase current gain or bias, a maximum value and minimum value calculation module is introduced to screen the fault phase. The preferred embodiment is that after determining the fault of the current sensor and the corresponding fault type according to the detection parameter and the pre-set fault diagnosis strategy, the fault detection method of the current sensor further comprises:

[0114] In the case of determining that a gain fault occurs, the maximum absolute average value of the absolute average values of the normalized phase current values is obtained, and the phase corresponding to the maximum absolute average value is taken as the fault phase of the gain fault;

[0115] In the case of determining that a positive offset fault occurs, the maximum average value of the average values of the normalized phase current values is obtained, and the phase corresponding to the maximum average value is taken as the fault phase of the positive offset fault;

[0116] In the case of determining that a negative offset fault occurs, the minimum average value of the average values of the normalized phase current values is obtained, and the phase corresponding to the minimum average value is taken as the fault phase of the negative offset fault;

[0117] In the case of determining that a positive stuck fault occurs, the maximum average value of the average values of the normalized phase current values is obtained, and the phase corresponding to the maximum average value is taken as the fault phase of the positive stuck fault;

[0118] In the case of determining that a negative stuck fault occurs, the minimum average value of the average values of the normalized phase current values is obtained, and the phase corresponding to the minimum average value is taken as the fault phase of the negative stuck fault.

[0119] The diagnosis variable e n , f n of the fault phase of the current sensor is respectively denoted as E n , F n , wherein E n represents an average value diagnosis variable; F n represents an absolute average value diagnosis variable. That is, E n = Max[e n ] or Min[e n ], F n = Max[f n ] or Min[f n ].

[0120] When the fault phase diagnosis is performed, the specific mode is as follows:

[0121] (3A), during normal operation, the intermediate diagnostic variable e n = 0, f n = ζ, the maximum and minimum value calculation modules do not participate in operation;

[0122] (3B), when a current sensor gain fault occurs, the intermediate diagnostic variable of the fault phase satisfies e a1 = 0, f a1 > ζ, since the current bias amplitude of the fault phase is the largest, the maximum value calculator is screened to locate the fault phase F n = Max[f n ] = F a1 ;

[0123] (3C), when a current sensor positive offset fault occurs, the current bias amplitude of the fault phase is the largest, and the maximum value calculator is screened to locate the fault phase E n = Max[e n ] = E a1 (negative offset fault: E n = Min[e n ] = E a1 );

[0124] (3D), when a current sensor wire breakage fault occurs, the intermediate diagnostic variable of the fault phase e a1 = 0, f a1 = 0, without the maximum and minimum value calculation module processing;

[0125] (3E), when a current sensor positive stuck fault occurs, the fault phase e a1 = c > 0, which can be screened by the maximum value calculator to obtain E n = Max[e n ] = E a1 (negative stuck fault: E n = Min[e n ] = E a1 ).

[0126] Table 1 is the data of the diagnostic strategy for locating the open circuit fault.

[0127] Table 1 is the data of the diagnostic strategy for locating the open circuit fault.

[0128]

[0129] In the method provided in the embodiment, the specific fault phase is determined according to the maximum and minimum values, so that the fault can be accurately located.

[0130] In the implementation, in order to improve the frequency of fault detection, the preferred embodiment is that, after determining the fault of the current sensor and the corresponding fault type according to the detection parameter and the pre-set fault diagnosis strategy, the fault detection method of the current sensor further comprises:

[0131] After determining the fault of the current sensor and the corresponding fault type, returning to acquire the current value collected by the current sensor within a preset time.

[0132] The value of the preset time is not limited and is determined according to actual conditions.

[0133] The embodiment provided in the present application returns to acquire the current value collected by the current sensor after one-time fault diagnosis, and performs fault diagnosis again according to the current value, thereby improving the frequency of fault detection and enabling the user to learn about the fault in a timely manner.

[0134] In order to facilitate the user to learn about the result of fault detection, the preferred embodiment is that, the fault detection method of the current sensor further comprises:

[0135] Outputting prompt information for indicating that the fault phase has a fault according to the fault type.

[0136] The content of the prompt information, the method adopted by the prompt information, and the frequency of the prompt information are not limited and are determined according to actual conditions. In order to enable the user to distinguish the specific fault type according to the prompt information, different prompt information can be set for different types of faults, and the user can learn about the type of fault through different prompt information.

[0137] In the method provided in the present application, the user can intuitively learn about the existence of the fault through the prompt information.

[0138] In the above embodiment, the fault detection method of the current sensor is described in detail, and the present application further provides an embodiment of a fault detection device of the current sensor. It should be noted that the embodiment of the device part is described from two angles, one is based on the functional module, and the other is based on the hardware.

[0139] Figure 3 The structural diagram of the fault detection device of the current sensor provided in an embodiment of the present application. The embodiment is based on the functional module and comprises:

[0140] The first acquisition module 10 is configured to acquire the current value collected by the current sensor.

[0141] The second acquisition module 11 is configured to acquire the detection parameter for detecting the fault of the current sensor according to the current value.

[0142] The determining module 12 is configured to determine the fault of the current sensor and the corresponding fault type according to the detection parameter and the preset fault diagnosis strategy; wherein the fault diagnosis strategy comprises the fault type of the current sensor and the characteristics of the detection parameter under different fault types.

[0143] Since the embodiments of the device part correspond to the embodiments of the method part, the embodiments of the device part are described in the description of the embodiments of the method part, and will not be described here.

[0144] The fault detection device of the current sensor provided in the embodiment comprises the following steps: the first acquisition module acquires the current value collected by the current sensor; the second acquisition module acquires the detection parameter for detecting the fault of the current sensor according to the current value; and the determining module determines the fault of the current sensor and the corresponding fault type according to the detection parameter and the preset fault diagnosis strategy; wherein the fault diagnosis strategy comprises the fault type of the current sensor and the characteristics of the detection parameter under different fault types. In the device of the embodiment, since the fault diagnosis strategy comprises the characteristics of the detection parameter under different fault types, the corresponding fault type can be determined according to the fault diagnosis strategy based on the acquired detection parameter, the detection of multiple types of faults is realized, and the accuracy of fault detection is improved.

[0145] Figure 4 The structure diagram of the fault detection device of the current sensor provided in another embodiment of the present application. The embodiment is based on the hardware angle, as shown in Figure 4 The fault detection device of the current sensor comprises:

[0146] The memory 20 is configured to store the computer program.

[0147] The processor 21 is configured to execute the computer program to realize the steps of the fault detection method of the current sensor mentioned in the above embodiments.

[0148] The fault detection device of the current sensor provided in the embodiment can include but is not limited to a smart phone, a tablet computer, a notebook computer or a desktop computer, etc.

[0149] The processor 21 can include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one of a hardware form of a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic array (PLA), etc. The processor 21 can also include a main processor and a coprocessor. The main processor is a processor for processing data in a wake-up state, also referred to as a central processing unit (CPU). The coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 21 can be integrated with a graphics processing unit (GPU) for rendering and drawing content to be displayed by the display screen. In some embodiments, the processor 21 can further include an artificial intelligence (AI) processor for processing machine learning-related computing operations.

[0150] The memory 20 can include one or more computer-readable storage media, which can be non-transitory. The memory 20 can further include a high-speed random access memory, and a nonvolatile memory such as one or more disk storage devices, flash storage devices. In this embodiment, the memory 20 is at least used to store the following computer program 201, wherein the computer program is loaded and executed by the processor 21, and can implement the related steps of the fault detection method of the current sensor disclosed in any of the preceding embodiments. In addition, the resources stored by the memory 20 can further include an operating system 202 and data 203, etc., and the storage mode can be temporary storage or permanent storage. The operating system 202 can include Windows, Unix, Linux, etc. The data 203 can include but is not limited to the data involved in the fault detection method of the current sensor mentioned above, etc.

[0151] In some embodiments, the fault detection apparatus of the current sensor can further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26.

[0152] Those skilled in the art can understand that the structure shown in the above embodiments does not constitute a limitation on the fault detection apparatus of the current sensor, and can include more or fewer components than those shown in the drawings. Figure 4 The structure shown in the above embodiments does not constitute a limitation on the fault detection apparatus of the current sensor, and can include more or fewer components than those shown in the drawings.

[0153] The current sensor fault detection device provided by the embodiment of the present application comprises a memory and a processor, and the processor can realize the following method when executing the program stored in the memory: the current sensor fault detection method, and the effects are the same as above.

[0154] The present application also provides an embodiment corresponding to a computer readable storage medium. The computer readable storage medium stores a computer program, and the computer program is executed by a processor to realize the steps recorded in the above method embodiment.

[0155] It can be understood that if the method in the above embodiment is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and executes all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0156] The computer readable storage medium provided by the present application comprises the current sensor fault detection method mentioned above, and the effects are the same as above.

[0157] Finally, in order to make the personnel in the technical field better understand the present application scheme, the present application is further described in detail below in combination with the accompanying drawings. Figure 5 , the specific embodiments and the specific embodiments. Figure 6 Figure 5 The present application provides a current sensor diagnostic schematic diagram. As shown in Figure 5 , the phase circuit i n After Park transformation, the current i d , i q , the vector module value is calculated to obtain The current is normalized, and the absolute value calculator obtains The average value calculator M[x] obtains f n , Max[f n ], Min[f n ] to determine F n ; the phase circuit i n After current normalization, e The average value calculator M[x] obtains e n , Max[e n ], Min[e​n ]determining E n .

[0158] Figure 6 A flow chart of a current sensor diagnostic method provided by an embodiment of the present application. As shown in the figure, the method comprises: Figure 6

[0159] S13: extracting phase current;

[0160] S14: normalization, average value processing;

[0161] S15: judging e n =0; if not, entering step S16, if yes, entering step S22;

[0162] S16: judging e n >0; if not, entering step S17, if yes, entering step S26;

[0163] S17: judging f n ≈ζ; if not, entering step S18, if yes, entering step S20;

[0164] S18: obtaining E n (Min[e n ]);

[0165] S19: stuck fault (C<0);

[0166] S20: obtaining E n (Min[e n ]);

[0167] S21: offset fault (C<0);

[0168] S22: judging f n =0; if yes, entering step S23; if not, entering step S24;

[0169] S23: determining open circuit fault;

[0170] S24: judging f n ≈ζ; if not, entering step S25; if yes, returning to step S13;

[0171] S25: determining gain fault;

[0172] S26: judging f n ≈ζ; if yes, entering step S27; if not, entering step S29;

[0173] S27: obtaining E n (Max[e n ]); ​

[0174] S28: Offset fault (C>0);

[0175] S29: Find E n (Max[e n ]);

[0176] S30: Stuck fault (C>0).

[0177] In this embodiment, phase current is used as the detection variable, and intermediate diagnostic variables en and f are used. n Determine the fault type via E n F n By locating the fault phase, a comprehensive diagnosis of current sensor gain, offset, open circuit, and jamming faults can be achieved. Compared with existing technologies, this application has comprehensive diagnostic capabilities, and its principle can be easily extended to any motor system. Furthermore, it should be noted that while this application detects current sensor gain, offset, open circuit, and jamming faults, in practice, the method of this embodiment can also be used to diagnose other types of faults.

[0178] The foregoing has provided a detailed description of a fault detection method, apparatus, and medium for a current sensor provided in this application. The various embodiments in the specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make several improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0179] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only 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 one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A fault detection method for a current sensor, characterized in that, include: Obtain the current value collected by the current sensor; Based on the current value, detection parameters for detecting faults in the current sensor are obtained; the detection parameters include the average value of the current value and the absolute average value of the current value. The fault of the current sensor and the corresponding fault type are determined based on the detection parameters and a pre-set fault diagnosis strategy; wherein, the fault diagnosis strategy includes the fault type of the current sensor and the characteristics of the detection parameters under different fault types. The step of determining the fault of the current sensor and the corresponding fault type based on the detection parameters and a pre-set fault diagnosis strategy includes: If the average value is equal to 0 and the absolute average value is equal to a preset value, then the current sensor is determined to be normal. If the average value is not equal to 0 or the absolute average value is not equal to the preset value, then the current sensor is determined to be faulty. If the current sensor is determined to be faulty, and the average value is equal to 0, and the absolute average value is greater than the preset value, then the fault type is determined to be a gain fault. If the average value is greater than 0 and the absolute average value is equal to the preset value, then the fault type is determined to be a positive offset fault. If the average value is less than 0 and the absolute average value is equal to the preset value, then the fault type is determined to be a negative offset fault. If both the average value and the absolute average value are 0, then the fault type is determined to be a disconnection fault. If the average value is a fixed value greater than 0, and the absolute average value is greater than the preset value, then the fault type is determined to be a positive jamming fault. If the average value is a fixed value less than 0, and the absolute average value is greater than the preset value, then the fault type is determined to be a negative jam fault.

2. The fault detection method for a current sensor according to claim 1, characterized in that, The step of obtaining the detection parameters for detecting the fault of the current sensor based on the current value includes: The current value located in the natural coordinate system is converted into a current component located in the synchronous rotating coordinate system by the Park transformation. The current magnitude is obtained based on the current components; The ratio of the current value to the current magnitude is obtained in order to normalize the current value; Obtain the average value and the absolute average value of the current value after normalization.

3. The fault detection method for a current sensor according to claim 2, characterized in that, Determining that the average value is equal to 0 and determining that the absolute average value is the preset value includes: Determine whether the average value is within the first threshold range; If so, then the average value is determined to be equal to 0; Determine whether the absolute average value is within the second threshold range; If so, then the absolute average value is determined to be equal to the preset value.

4. The fault detection method for a current sensor according to claim 3, characterized in that, The motor contains multiphase current. After determining the fault of the current sensor and the corresponding fault type based on the detection parameters and a pre-set fault diagnosis strategy, the method further includes: In the event that the gain fault has occurred, the maximum absolute average value among the absolute average values ​​of the normalized phase current values ​​is obtained, and the phase corresponding to the maximum absolute average value is taken as the fault phase in which the gain fault has occurred. If the positive offset fault is determined to have occurred, the maximum average value among the average values ​​of the normalized phase current values ​​is obtained, and the phase corresponding to the maximum average value is taken as the fault phase in which the positive offset fault occurred. If the negative offset fault is determined to have occurred, the minimum average value among the average values ​​of the normalized phase current values ​​is obtained, and the phase corresponding to the minimum average value is taken as the fault phase in which the negative offset fault occurred. If the positive jamming fault is determined to have occurred, the maximum average value among the average values ​​of the normalized phase current values ​​is obtained, and the phase corresponding to the maximum average value is taken as the fault phase in which the positive jamming fault occurred. If the negative jamming fault is determined to have occurred, the minimum average value among the average values ​​of the normalized phase current values ​​is obtained, and the phase corresponding to the minimum average value is taken as the fault phase in which the negative jamming fault occurred.

5. The fault detection method for a current sensor according to any one of claims 1 to 4, characterized in that, After determining the fault of the current sensor and the corresponding fault type based on the detection parameters and a pre-set fault diagnosis strategy, the method further includes: After determining the fault of the current sensor and the corresponding fault type, the process returns to the step of acquiring the current value collected by the current sensor within a preset time.

6. The fault detection method for a current sensor according to claim 4, characterized in that, The method further includes: Output a prompt message indicating that the faulty phase has failed, based on the fault type.

7. A fault detection device for a current sensor, characterized in that, include: The first acquisition module is used to acquire the current value collected by the current sensor; The second acquisition module is used to acquire detection parameters for detecting faults in the current sensor based on the current value; the detection parameters include the average value of the current value and the absolute average value of the current value; The determination module is used to determine the fault of the current sensor and the corresponding fault type based on the detection parameters and a pre-set fault diagnosis strategy; wherein, the fault diagnosis strategy includes the fault type of the current sensor and the characteristics of the detection parameters under different fault types. The determining module is specifically used for: If the average value is equal to 0 and the absolute average value is equal to a preset value, then the current sensor is determined to be normal. If the average value is not equal to 0 or the absolute average value is not equal to the preset value, then the current sensor is determined to be faulty. If the current sensor is determined to be faulty, and the average value is equal to 0, and the absolute average value is greater than the preset value, then the fault type is determined to be a gain fault. If the average value is greater than 0 and the absolute average value is equal to the preset value, then the fault type is determined to be a positive offset fault. If the average value is less than 0 and the absolute average value is equal to the preset value, then the fault type is determined to be a negative offset fault. If both the average value and the absolute average value are 0, then the fault type is determined to be a disconnection fault. If the average value is a fixed value greater than 0, and the absolute average value is greater than the preset value, then the fault type is determined to be a positive jamming fault. If the average value is a fixed value less than 0, and the absolute average value is greater than the preset value, then the fault type is determined to be a negative jam fault.

8. A fault detection device for a current sensor, characterized in that, include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of the fault detection method for a current sensor as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the fault detection method for a current sensor as described in any one of claims 1 to 6.

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