A method for diagnosing open-circuit faults in converters based on critical characteristics

Abstract

The present invention discloses a method for diagnosing an open-circuit fault of a converter based on critical features. The method comprises: constructing a controller adjustment model; under different control parameters, inputting the current actual current value of the converter and the steady-state current value of the fault state into the model, and the model outputting the next actual current value of the converter to construct a current trajectory; constructing a critical region according to the current trajectory; obtaining the change trend of the common current fault characteristics of the current trajectory in the critical region under the fault and healthy states and constructing a fault diagnosis quantification region, and finally performing accurate positioning fault diagnosis of the converter. The critical features of the method of the present invention can provide a basis for feature extraction and quantification in the face of uncertain disturbance factors, solve the problem that the regularity of the fault current characteristics is damaged by the controller adjustment effect, and the uncertainty of the control parameters causes the generalization ability of the diagnosis method to become weak, and can diagnose the open-circuit fault of the converter occurring under different control conditions and has a faster diagnosis speed.

Description

Technical Field

[0001] The invention relates to a method for diagnosing an open-circuit fault of a converter, and relates to the technical field of intelligent perception and operation and maintenance of electric power equipment, and in particular to a method for diagnosing an open-circuit fault of a converter based on critical characteristics. Background Art

[0002] Energy traction industry is of vital importance. With the increasing demand for high-efficiency transportation and the development of intelligent operation and maintenance technology, converter fault diagnosis has become one of the important areas of advanced technology research and application in countries around the world. As the most basic measurable signal of the system, current does not require additional sensors and circuits and is widely used in converter fault diagnosis research.

[0003] Existing fault diagnosis methods can be divided into three categories: analytical model method, data-driven method and signal processing method. The analytical model method diagnoses faults through the error between the model observation value and the measurement value. The diagnosis speed is fast, but accurate modeling is required. The strong nonlinearity of the motor drive system makes the analytical model method less practical; the data-driven method uses intelligent algorithms to evaluate the model fitness to identify faults. It does not require understanding of the system model and working mechanism, but the lack of data and the speed of fault feature relationship reasoning limit the online application of the data-driven method; the signal processing method extracts fault features from the measurement signal and identifies faults by analyzing the feature differences between different states. It can not only ensure the rapidity of online diagnosis, but also does not require accurate models and a large amount of historical data. It has a broad application prospect in the field of fault diagnosis.

[0004] The diagnostic criteria of signal processing methods mostly rely on phenomenon observation and experience summary, which requires a high degree of familiarity with the research object and is quite tricky when facing the controller adjustment effect. On the one hand, the adjustment effect of the control parameters changes the signal trajectory, resulting in weakening of the regularity of the characteristics and increasing the difficulty of extraction; on the other hand, the uncertainty of the control parameters makes it extremely difficult to quantify the criteria. Many literatures do not fully consider the impact of the controller adjustment effect. Although ignoring the transient process of feedback adjustment simplifies the complexity of analysis, it will seriously affect the practical effect for systems with important fault characteristics in the transient process, and the diagnostic accuracy and generalization ability will be greatly reduced. Summary of the invention

[0005] In order to solve the problems existing in the background technology, the present invention provides a converter open circuit fault diagnosis method based on critical characteristics.

[0006] The technical solution adopted by the present invention is:

[0007] 1. A method for diagnosing open-circuit faults of converters based on critical characteristics:

[0008] 1) Construct a controller adjustment model when the controller controls the converter.

[0009] 2) For the fault state when an open circuit fault occurs in each device in the converter, when the controller controls the converter under different sets of control parameters, the actual current value of the converter at the current moment and the steady-state current value under the current fault state are input into the controller adjustment model, and the controller adjustment model outputs the actual current value of the converter at the next moment, thereby obtaining the actual current value of the converter changing with time under each set of control parameters as the current trajectory.

[0010] 3) constructing a critical region of the current trajectory according to the current trajectory of the converter under each set of control parameters obtained in step 2); for each fault state of the converter, when the converter is in the current fault state, using a controller under different sets of control parameters to control the converter, and obtaining the changing trends of several common current fault characteristics of the current trajectory of the converter in the critical region.

[0011] 4) When the converter is in a healthy state, the converter is controlled using a controller under different groups of control parameters to obtain the change trend of each common current fault feature of the converter that is the same as that in step 3).

[0012] 5) For each common current fault feature in step 3) and step 4), the area formed between the change trends of the common current fault features of the converter in the fault state and the healthy state is used as the fault diagnosis quantization area; finally, the fault diagnosis quantization area of ​​each common current fault feature under each fault state of the converter is obtained.

[0013] 6) Obtain each current fault feature of the converter to be diagnosed and compare it with the fault diagnosis quantization area of ​​each common current fault feature under each fault state, so as to determine the fault state of the converter to be diagnosed, and then determine the device with open circuit fault in the converter under the current fault state, and finally realize the precise positioning fault diagnosis of the converter.

[0014] In the step 1), the controller adjustment model of the controller when controlling the converter is specifically as follows:

[0015] i x (t+1)=i xn (t)+r·[i x (t)-i xn (t)]

[0016] Among them, i x (t+1) and i x (t) are the actual current values ​​of the converter at time t+1 and time t respectively; i xn (t) is the steady-state current value of the converter at time t under fault condition; r is the controller adjustment parameter, r∈[0,1].

[0017] The controller regulation model can characterize the controller regulation function in a process equivalent way based on the essential properties of the controller feedback regulation function.

[0018] In step 2), the control parameters of the controller include the proportional coefficient K p , integral coefficient K i and the differential coefficient K d , the proportional coefficient K in each group of control parameters p , integral coefficient K i and the differential coefficient K d different.

[0019] In the step 3), the critical region of the current trajectory is the region formed by the highest and lowest two current trajectories among the current trajectories in step 2), and the highest and lowest two current trajectories are the upper critical state trajectory K and the lower critical state trajectory J of the critical region, respectively, as follows:

[0020] J≤I k ≤K

[0021] I k =(i k1 ,i k2 , ..., i km , ..., i kn )

[0022] J=(J1,J2,...,J m , ..., J n )

[0023] K=(K1,K2,...,K m , ..., K n )

[0024] Among them, I k is the current trajectory of the converter under the kth group of control parameters in the preset time period [0, n], i k1 、i k2 、...、i km 、...、i kn are the current values ​​of the converter at time 1, time 2, ..., time m, ..., time n under the kth group of control parameters; J1, J2, ..., J m , ..., J n are the current values ​​of the converter at time 1, time 2, ..., time m, ..., time n in the lower critical state trajectory J; K1, K2, ..., K m , ..., K nare respectively the current values ​​of the converter in the upper critical state trajectory K at time 1, time 2, ..., time m, ..., time n.

[0025] The current trajectory within a period of time is discretized into n equally spaced points, and the current trajectory under different control parameters is recorded as {I k}(k∈N + ), the current trajectory I under the kth group of control parameters k =(i k1 ,i k2 , ..., i km , ..., i kn ), where i k1 For I k The initial state.

[0026] Assume R n is a line series set. If in R n There are two trajectories J and K in the system, such that when k takes any value, J≤I k ≤K, then {I k} exists, called R n For {I k}, and call J and K the critical region of {I k} critical state.

[0027] According to the controller adjustment characteristics and fault signal change trend analysis, the critical area is delineated, and the influence of control parameter uncertainty on fault characteristics is quantified in the form of regional envelope; the boundary of the critical area is analyzed to obtain the critical state.

[0028] In the step 3), the current fault characteristics are a number of current characteristic values ​​obtained based on the current values ​​in the current trajectory of the converter; for each fault state of the converter, when the converter is controlled by the controller under each set of control parameters, each current trajectory of the converter in the critical area and its current fault characteristics are obtained, and for each current fault characteristic, when the current fault characteristic is always within a preset numerical range under the control of each set of control parameters of the controller, then the current characteristic value is a common current fault characteristic of the converter in the current fault state, all common current fault characteristics in the current fault state are obtained, and finally all common current fault characteristics of each fault state are obtained.

[0029] The current characteristic values ​​include the average value, absolute value, DC component of the current, absolute average value, Fourier coefficient, wavelet coefficient and other characteristic quantities obtained by transformation of each current in the current trajectory of the converter. The common current fault characteristics after the converter open circuit fault occurs under different control parameters are determined by integrating the controller adjustment characteristics, the quantitative model of the fault signal change trend and the critical state analysis results; when defining the critical area, various fault states that may occur in the actual system must be covered, and at least one common characteristic must be guaranteed to exist in the critical area. Select the appropriate critical state and realize the analysis of the critical state. When selecting the critical state, the difficulty of analysis, the difference between the critical state fault characteristics and the healthy state characteristics, etc. must be considered to avoid misdiagnosis and missed diagnosis.

[0030] In the step 6), for each fault state of the converter and its common current fault characteristics, when the change trend of each current fault characteristic of the converter to be fault diagnosed is within a fault diagnosis quantization area of ​​each common current fault characteristic, the converter is diagnosed to be in the current fault state, thereby determining the device with open circuit fault in the converter.

[0031] Through integrated processing of the changing trends of fault characteristics, the characteristic values ​​are processed by logical operations and other means, and diagnostic functions are designed to enhance the difference and extractability of characteristics after faults occur in different locations, thus achieving accurate positioning of converter faults.

[0032] 2. An electronic device comprises: a memory and a processor coupled to each other, wherein the memory stores program data, and the processor calls the program data to execute the method as described above.

[0033] 3. A computer-readable storage medium having program data stored thereon, wherein the program data implements the method described above when executed by a processor.

[0034] The beneficial effects of the present invention are:

[0035] 1. The present invention proposes a fault diagnosis method based on critical characteristics, which can solve the problem of weakening of regularity of fault characteristics caused by control and regulation.

[0036] 2. The present invention adopts a process equivalence approach to eliminate the problem of high analytical complexity and difficulty in quantifying fault diagnosis criteria caused by uncertainty in control parameters.

[0037] 3. The present invention adopts a method of analyzing the common characteristics of critical domains to extract fault features, enhance feature differences, and improve diagnostic accuracy and speed.

[0038] In summary, the present invention can provide a theoretical basis for feature extraction and criterion quantification when facing uncertain disturbance factors, solve the problem that the regularity of fault current characteristics is damaged due to the adjustment effect of the controller, and the uncertainty of control parameters leads to the weakening of the generalization ability of the diagnosis method. It can diagnose converter open-circuit faults occurring under different control conditions and has a faster diagnosis speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A topological structure diagram of a two-level converter used in the specific implementation of the method of the present invention;

[0040] Figure 2 It is the work flow chart of the method of the present invention;

[0041] Figure 3 The power device S of the two-level converter in the specific implementation case of the present invention is a1 Current waveform before and after an open circuit fault occurs, where: Figure 3 (a) is the proportionality coefficient K p =28.2, integral coefficient K i =3726, differential coefficient K d = 0 when the current waveform, Figure 3 (b) is the proportionality coefficient K p =14.1, integral coefficient K i =1863, differential coefficient K d =0 current waveform. DETAILED DESCRIPTION

[0042] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0043] like Figure 1 As shown, the converter open circuit fault diagnosis method based on critical characteristics of the present invention is specifically as follows:

[0044] 1) Construct a controller adjustment model when the controller controls the converter, as follows:

[0045] i x (t+1)=i xn (t)+r·[i x (t)-i xn (t)]

[0046] Among them, i x (t+1) and i x (t) are the actual current values ​​of the converter at time t+1 and time t respectively; i xn (t) is the steady-state current value of the converter at time t under fault condition; r is the controller adjustment parameter, r∈[0,1].

[0047] The controller regulation model can characterize the controller regulation function in a process equivalent way based on the essential properties of the controller feedback regulation function.

[0048] 2) For the fault state when an open circuit fault occurs in each device in the converter, when the controller under different sets of control parameters controls the converter, the actual current value of the converter at the current moment and the steady-state current value under the current fault state are input into the controller adjustment model, and the controller adjustment model outputs the actual current value of the converter at the next moment, thereby obtaining the actual current value of the converter changing with time under each set of control parameters as the current trajectory; the control parameters of the controller include the proportional coefficient K p , integral coefficient K i and the differential coefficient K d , the proportional coefficient K in each group of control parameters p , integral coefficient K i and the differential coefficient K d different.

[0049] 3) constructing a critical region of the current trajectory according to the current trajectory of the converter under each set of control parameters obtained in step 2); for each fault state of the converter, when the converter is in the current fault state, using a controller under different sets of control parameters to control the converter, and obtaining the changing trends of several common current fault characteristics of the current trajectory of the converter in the critical region.

[0050] The critical region of the current trajectory is the region formed by the highest and lowest two current trajectories among the current trajectories in step 2), and the highest and lowest two current trajectories are the upper critical state trajectory K and the lower critical state trajectory J of the critical region, respectively, as follows:

[0051] J≤I k ≤K

[0052] I k =(i k1 ,i k2 , ..., i km , ..., i kn )

[0053] J=(J1,J2,...,J m , ..., J n )

[0054] K=(K1,K2,...,K m , ..., K n )

[0055] Among them, I k is the current trajectory of the converter under the kth group of control parameters in the preset time period [0, n], i k1 、ik2 、...、i km 、...、i kn are the current values ​​of the converter at time 1, time 2, ..., time m, ..., time n under the kth group of control parameters; J1, J2, ..., J m , ..., J n are the current values ​​of the converter at time 1, time 2, ..., time m, ..., time n in the lower critical state trajectory J; K1, K2, ..., K m , ..., K n are respectively the current values ​​of the converter in the upper critical state trajectory K at time 1, time 2, ..., time m, ..., time n.

[0056] The current trajectory within a period of time is discretized into n equally spaced points, and the current trajectory under different control parameters is recorded as {I k}(k∈N + ), the current trajectory I under the kth group of control parameters k =(i k1 ,i k2 , ..., i km , ..., i kn ), where i k1 For I k The initial state.

[0057] Assume R n is a line series set. If in R n There are two trajectories J and K in the system, such that when k takes any value, J≤I k ≤K, then {I k} exists, called R n For {I k}, and call J and K the critical region of {I k} critical state.

[0058] According to the controller adjustment characteristics and fault signal change trend analysis, the critical area is delineated, and the influence of control parameter uncertainty on fault characteristics is quantified in the form of regional envelope; the boundary of the critical area is analyzed to obtain the critical state.

[0059] The current fault characteristics are several current characteristic values ​​obtained based on the current values ​​in the current trajectory of the converter; for each fault state of the converter, when the converter is controlled by the controller under each set of control parameters, each current trajectory of the converter in the critical area and its current fault characteristics are obtained. For each current fault characteristic, when the current fault characteristic is always within the preset numerical range under the control of each set of control parameters of the controller, the current characteristic value is a common current fault characteristic of the converter in the current fault state, all common current fault characteristics in the current fault state are obtained, and finally all common current fault characteristics of each fault state are obtained.

[0060] The current characteristic values ​​include the average value, absolute value, DC component of the current, absolute average value, Fourier coefficient, wavelet coefficient and other characteristic quantities obtained by transformation of each current in the current trajectory of the converter. The common current fault characteristics after the converter open circuit fault occurs under different control parameters are determined by integrating the controller adjustment characteristics, the quantitative model of the fault signal change trend and the critical state analysis results; when defining the critical area, various fault states that may occur in the actual system must be covered, and at least one common characteristic must be guaranteed to exist in the critical area. Select the appropriate critical state and realize the analysis of the critical state. When selecting the critical state, the difficulty of analysis, the difference between the critical state fault characteristics and the healthy state characteristics, etc. must be considered to avoid misdiagnosis and missed diagnosis.

[0061] 4) When the converter is in a healthy state, the converter is controlled using a controller under different groups of control parameters to obtain the change trend of each common current fault feature of the converter that is the same as that in step 3).

[0062] 5) For each common current fault feature in step 3) and step 4), the area formed between the change trends of the common current fault features of the converter in the fault state and the healthy state is used as the fault diagnosis quantization area; finally, the fault diagnosis quantization area of ​​each common current fault feature under each fault state of the converter is obtained.

[0063] 6) Obtain each current fault feature of the converter to be diagnosed and compare it with the fault diagnosis quantization area of ​​each common current fault feature under each fault state, so as to determine the fault state of the converter to be diagnosed, and then determine the device with open circuit fault in the converter under the current fault state, and finally realize the precise positioning fault diagnosis of the converter.

[0064] For each fault state of the converter and its common current fault characteristics, when the change trend of each current fault characteristic of the converter to be fault diagnosed is within a respective fault diagnosis quantization area with a common current fault characteristic, the converter is diagnosed to be in the current fault state, thereby determining the device with an open circuit fault in the converter.

[0065] Through integrated processing of the changing trends of fault characteristics, the characteristic values ​​are processed by logical operations and other means, and diagnostic functions are designed to enhance the difference and extractability of characteristics after faults occur in different locations, thus achieving accurate positioning of converter faults.

[0066] The specific embodiments of the present invention are as follows:

[0067] The present invention can be applied to various converters, such as a two-level converter, a midpoint clamped three-level converter, an active midpoint clamped three-level converter, etc. Figure 2 As shown in FIG. 1 , a topological structure of a two-level converter used in a specific implementation of the present invention is shown. The devices of the two-level converter include six insulated-gate bipolar transistor (IGBT) devices (S a1 , S a2 , S b1 , S b2 , S c1 , S c2 ), the specific implementation method of the converter fault diagnosis based on critical characteristics of the present invention is as follows:

[0068] 1) Starting from the essential properties of the controller feedback regulation, the controller regulation is characterized in a process equivalent way; the converter recovery process is regarded as a typical first-order circuit full response process. When the excitation voltage is equal to the q-axis voltage steady-state value v q0 When:

[0069]

[0070] Among them, i qf2 is the q-axis current of the converter; I mq is the expected value of the q-axis current of the converter; I mq0 is the initial value of the q-axis current in the current state; e is a natural constant; R is the resistance value of the converter; t is time; L q is the q-axis inductance of the converter.

[0071] 2) According to the controller adjustment characteristics and fault signal change trend analysis, the critical area is delineated, and the influence of control parameter uncertainty on fault characteristics is quantified in the form of regional envelope; a1 At the moment of open circuit fault, the b-phase current i bf1 The amplitude is Imb Then the current amplitude of phase b will gradually increase to have:

[0072] i bf_n |≤|i bf1 |≤|i bf_m

[0073]

[0074] Among them, i bf1 is the b-phase current of the converter; i bf_m and i bf_n are the b-phase current i of the converter respectively bf1 The upper and lower critical states; i cf_m and i cf_n are the c-phase current i of the converter respectively cf1 The upper and lower critical states; I mb is the probability device S a1 When an open circuit fault occurs, the current i of phase b of the converter is bf1 The amplitude of ω is the electrical angular velocity of the motor.

[0075] 3) Analyze the boundary of the critical area; combine the controller adjustment characteristics, the quantitative model of the fault signal change trend and the critical state analysis results to determine the common fault characteristics after the converter open circuit fault occurs under different control parameters; suppose the x-phase current i xf The absolute value of |i xf The average value of | is I xf , (x∈a,b,c; represents three phases); thus the current error value is obtained as follows:

[0076]

[0077] Among them, ε ba is the b-phase current i of the converter bf The average value of the absolute value I bf and a phase current i af The average value of the absolute value I af The difference between ca is the c-phase current i of the converter cf The average value of the absolute value I cf and a phase current i af The average value of the absolute value I af The difference between bc is the b-phase current i of the converter bf The average value of the absolute value I bf and c-phase current i cf The average value of the absolute value I cf The difference between .

[0078] 4) Analysis step 3) The changing trend of the common fault characteristics after the converter open circuit fault occurs under different control parameters in the converter health mode is shown in Table 1.

[0079] Table 1 Fault characteristic change trend of different devices after opening

[0080]

[0081] in, af >、 bf > and cf > are the a-phase current i of the converter respectively af , b-phase current i bf and c-phase current i cf δ1, δ2 and λ are the first, second and third fault diagnosis thresholds respectively.

[0082] 5) According to the critical state analysis results under the fault mode in step 3) and the difference in the fault characteristic change trend under the healthy mode in step 4), the fault diagnosis criteria are quantified, as shown in Table 2.

[0083] Table 2 Fault characteristic change trend of different devices after opening and in healthy state

[0084]

[0085] 6) Design a diagnostic function F according to the difference in the fault characteristic change trend in step 5) to achieve accurate positioning of the converter fault.

[0086] Table 3 Fault diagnosis function F of different devices after open circuit and in healthy state

[0087]

[0088] The parameters of the converter open circuit fault test platform and the surface mounted permanent magnet synchronous motor according to the embodiment of the present invention are shown in Table 4 below.

[0089] Table 4 Parameters of surface mounted permanent magnet synchronous motor

[0090]

[0091] The power device S of the two-level converter a1 Take the open circuit fault as an example for diagnosis. Figure 3 As shown in (a), the test conditions are speed 1000r / min and load torque 6Nm. In the healthy state, ε ba , ε ca , ε bc are all near 0. After the fault occurs, ε ba , ε ca ​​​are all greater than 0 and gradually increase, which is clearly different from the characteristics in a healthy state. Based on this, it can be determined that phase a has a fault. af > less than 0, can be located at S a1 Open circuit, the diagnosis time is 1.5ms (about 0.1T), such as Figure 3 As shown in (b), the test conditions are speed 1000r / min and load torque 6Nm. In the healthy state, ε ba , ε ca , ε bc are all near 0. After the fault occurs, ε ba , ε ca are all greater than 0 and gradually increase, which is clearly different from the characteristics in a healthy state. Based on this, it can be determined that phase a has a fault. af > less than 0, can be located at S a1 Open circuit, the diagnosis time is 0.9ms (about 0.06T). The results show that: the characteristic quantity ε ba , ε ca and af >The results are consistent with the calculation results in Table 2, which verifies the correctness of the theoretical analysis; the converter open circuit fault diagnosis method based on critical characteristics has a good diagnostic effect for faults under different control parameters; the converter open circuit fault diagnosis method based on critical characteristics has a high diagnostic speed under different control parameters.

[0092] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.​​​

Claims

1. A method for diagnosing open-circuit faults of a converter based on critical characteristics, characterized in that: include: 1) Constructing a controller adjustment model when the controller controls the converter; 2) For the fault state when an open circuit fault occurs in each device in the converter, when the controller under different sets of control parameters controls the converter, the actual current value of the converter at the current moment and the steady-state current value under the current fault state are input into the controller adjustment model, and the controller adjustment model outputs the actual current value of the converter at the next moment, thereby obtaining the actual current value of the converter changing with time under each set of control parameters as the current trajectory; 3) constructing a critical region of the current trajectory according to the current trajectory of the converter under each group of control parameters obtained in step 2); for each fault state of the converter, when the converter is in the current fault state, using controllers under different groups of control parameters to control the converter, and obtaining a change trend of several common current fault characteristics of the current trajectory of the converter in the critical region; 4) When the converter is in a healthy state, the converter is controlled using a controller under different groups of control parameters to obtain a change trend of each common current fault feature of the converter that is the same as that in step 3); 5) for each common current fault feature in step 3) and step 4), the region formed between the change trends of the common current fault features of the converter in the fault state and the healthy state is used as the fault diagnosis quantization region; Finally, a fault diagnosis quantization region of each common current fault feature under each fault state of the converter is obtained; 6) Obtain each current fault feature of the converter to be diagnosed and compare it with the fault diagnosis quantization area of ​​each common current fault feature under each fault state, determine the fault state of the converter to be diagnosed, and then determine the device with open circuit fault in the converter under the current fault state, and finally realize accurate positioning fault diagnosis of the converter.

2. The method for diagnosing an open circuit fault of a converter based on critical characteristics according to claim 1, characterized in that: In the step 1), the controller adjustment model of the controller when controlling the converter is specifically as follows: i x (t+1)=i xn (t)+r·[i x (t)-i xn (t)] Among them, i x (t+1) and i x (t) are the actual current values ​​of the converter at time t+1 and time t respectively; i xn (t) is the steady-state current value of the converter at time t under fault condition; r is the controller adjustment parameter, r∈[0,1].

3. The method for diagnosing an open circuit fault of a converter based on critical characteristics according to claim 1, characterized in that: In step 2), the control parameters of the controller include the proportional coefficient K p , integral coefficient K i and the differential coefficient K d , the proportional coefficient K in each group of control parameters p , integral coefficient K i and the differential coefficient K d different.

4. The method for diagnosing an open circuit fault of a converter based on critical characteristics according to claim 1, characterized in that: In the step 3), the critical region of the current trajectory is the region formed by the highest and lowest two current trajectories among the current trajectories in step 2), and the highest and lowest two current trajectories are the upper critical state trajectory K and the lower critical state trajectory J of the critical region, respectively, as follows: J≤I k ≤K I k =(i k1 ,i k2 ,...,i km ,...,i kn ) J\(J1,J2,...,J m ,...,J n ) K=(K1,K2,...,K m ,...,K n ) Among them, I k is the current trajectory of the converter under the kth group of control parameters in the preset time period [0, n], i k1 、i k2 、...、i km 、...、i kn are the current values ​​of the converter at time 1, time 2, ..., time m, ..., time n under the kth group of control parameters; J1, J2, ..., J m , ..., J n are the current values ​​of the converter at time 1, time 2, ..., time m, ..., time n in the lower critical state trajectory J; K1, K2, ..., K m , ..., K n are respectively the current values ​​of the converter in the upper critical state trajectory K at time 1, time 2, ..., time m, ..., time n.

5. The method for diagnosing an open circuit fault of a converter based on critical characteristics according to claim 1, characterized in that: In the step 3), the current fault characteristics are a number of current characteristic values ​​obtained based on the current values ​​in the current trajectory of the converter; for each fault state of the converter, when the converter is controlled by the controller under each set of control parameters, each current trajectory of the converter in the critical area and its current fault characteristics are obtained, and for each current fault characteristic, when the current fault characteristic is always within a preset numerical range under the control of each set of control parameters of the controller, then the current characteristic value is a common current fault characteristic of the converter in the current fault state, all common current fault characteristics in the current fault state are obtained, and finally all common current fault characteristics of each fault state are obtained.

6. The method for diagnosing an open circuit fault of a converter based on critical characteristics according to claim 1, characterized in that: In the step 6), for each fault state of the converter and its common current fault characteristics, when the change trend of each current fault characteristic of the converter to be fault diagnosed is within a fault diagnosis quantization area of ​​each common current fault characteristic, the converter is diagnosed to be in the current fault state, thereby determining the device with open circuit fault in the converter.

7. An electronic device, characterized in that: include: A memory and a processor coupled to each other, wherein the memory stores program data, and the processor calls the program data to execute the method according to any one of claims 1 to 6.

8. A computer-readable storage medium having program data stored thereon, characterized in that: When the program data is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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