Abnormal evaluation method, device and system for digital device of electronic transformer

Abstract

The present invention discloses an abnormal evaluation method, device and system for a digital device of an electronic transformer. The method includes: parsing the transmission message of the digital device, extracting zero-sequence voltage and zero-sequence current, and if the zero-sequence voltage and zero-sequence current exceed a preset threshold, performing an abnormal judgment on the digital device: collecting zero-sequence voltage and zero-sequence current data of a plurality of cycles and processing them to generate a feature vector matrix and performing dimensionality reduction processing; respectively calculating the Euclidean distances between the feature vector matrix X and the abnormal feature matrix X of the digital device pre-set inside the distribution terminal s , the single-phase ground fault feature matrix X d , and combining the time observation window to judge whether the digital device is abnormal. This method can effectively distinguish the single-phase ground fault of the electronic transformer from the abnormal state of the digital device, and solve the difficult problem of judging the poor contact state of the digital device of the on-pole switch built-in electronic transformer.

Description

Technical Field

[0001] The present invention relates to the technical field of instrument transformers, and particularly to an abnormal evaluation method, device and system for an electronic instrument transformer digital device. Background Art

[0002] The invention patent (application number: CN201710146205.4, publication number: CN106896253A) discloses a pluggable electronic instrument transformer digital device, which is generally installed in high-voltage measurement equipment close to the 6-35 kV high-voltage line end. A typical application scenario is a pole-mounted switch on a 10 kV distribution line. The device is built into the switch. After the voltage and current on the line are collected by the electronic instrument transformer, they are converted into digital signals in the FT3 format and transmitted to the digital distribution terminal installed under the electric pole through isolated twisted pairs.

[0003] Since this digital device directly works in the pole-mounted switch at the top of the electric pole, for easy replacement, a pluggable interface is used to connect to the switch device. Due to the harsh installation environment of the pole-mounted switch, improper operations are likely to occur during the replacement and maintenance of the digital device, which may easily lead to loose connection at the interface between the device and the switch. When installing, the switch may collide or vibrate violently when the switch operates, which may easily cause abnormal poor contact at the interface between the digital device and the switch. When the digital device is abnormal, the sudden change of the generated signal is likely to trigger misoperation of the switch. Therefore, it is necessary to judge whether there is poor contact in the digital device in the distribution terminal. If the poor contact occurs in the part where the digital device obtains power from the switch, it can be judged by whether the communication between the device and the distribution terminal is disconnected; if the poor contact occurs in the signal detection interface part of the digital device, at this time, the working state of the device is normal, but the transmitted data is abnormal, and the fault data is very similar to the single-phase grounding fault data. How to effectively judge the abnormal state of poor contact of the digital device has become a technical difficulty.

[0004] At present, most of the technical evaluations of the fault states of electronic instrument transformers are for the electronic instrument transformers applied in smart substations, and are not applicable to the fault state evaluation of the digital devices of the electronic instrument transformers of 10 kV pole-mounted switches.

[0005] The invention patent (application number: CN201610875462.7, publication number: CN107885179A) discloses a fault discrimination method for electronic instrument transformers, which mainly utilizes the information sharing advantage among the transformer groups in the smart substation and comprehensively compares the operation data of each group of transformers to judge the faulty transformer. Since the working scenario environment of the digital device is much harsher than that of the smart substation and belongs to an isolated system without information sharing, it is impossible to use the working states of multiple instrument transformers for comparative evaluation.

[0006] The invention patent (application number: CN202110229142.5, publication number: CN113050017A) discloses an intelligent monitoring and fault diagnosis system for the error state of electronic transformers. This method directly monitors the errors of the electronic transformer body. In the application scenario of the 10kV voltage level, since the transformer body is a passive device, the possibility of abnormality is very small. At the same time, the error precision drift does not have an absolute impact on the fault judgment of the 10kV line switch. However, the probability of abnormality of the digital device is higher. Due to the particularity of the working scenario and functional requirements of the digital device built in the 10kV pole-mounted switch, the current error evaluation method for the transformer body is not applicable.

[0007] The invention patent (application number: CN201910486805.4, publication number: CN110277762A) discloses a differential protection blocking system and method for abnormal data acquisition of electronic transformers, which mainly processes abnormal current data. The 10kV distribution line switch device needs to accurately detect and isolate single-phase grounding faults, while the intelligent substation switch does not have such requirements. When a single-phase grounding fault occurs, both voltage and current will have transient mutations, and when the digital device is abnormal, voltage and current will also have transient mutations, triggering mis-triggering of grounding faults. The current technology is mainly applied to electronic sensors in intelligent substations and does not consider distinguishing the transient mutations of normal power grid single-phase grounding faults from those caused by sensor devices. It is easy to misinterpret the transient mutations caused by normal single-phase grounding faults as abnormal states of transformers, resulting in missed or misjudged faults. Summary of the Invention

[0008] The present invention proposes an abnormal evaluation method, device and medium for the digital device of an electronic transformer, and its purpose is to effectively distinguish single-phase grounding faults of electronic transformers from abnormal states of digital devices, and solve the difficult problem of judging the poor contact state of the digital device of the electronic transformer built in the pole-mounted switch.

[0009] The technical solution of the present invention is as follows:

[0010] An abnormal evaluation method for the digital device of an electronic transformer includes the following steps:

[0011] S1: Analyze the transmission message of the digital device, extract the zero-sequence voltage u0 and zero-sequence current i0, and judge whether the zero-sequence voltage and zero-sequence current exceed the preset threshold. If they exceed the preset threshold, go to step S2 for abnormal identification of the digital device;

[0012] S2: Collect a plurality of cycle zero-sequence voltages and zero-sequence currents to form a zero-sequence voltage vector U0 and a zero-sequence current vector I0, and generate a feature vector matrix X0. Perform dimensionality reduction processing on the X0 matrix to obtain a dimensionality reduction matrix X;

[0013] S3: Calculate the Euclidean distances between matrix X and the characteristic matrices X of different types of poor contacts in the power grid during abnormal operation of the digital device, and between matrix X and the characteristic matrices X of different types of poor contacts in the power grid during single-phase grounding fault respectively. Then, based on the calculated Euclidean distance values and combined with the observation time window, determine whether an abnormality occurs in the digital device. s Calculate the Euclidean distances between matrix X and the characteristic matrices X of different types of poor contacts in the power grid during abnormal operation of the digital device, and between matrix X and the characteristic matrices X of different types of poor contacts in the power grid during single-phase grounding fault respectively. Then, based on the calculated Euclidean distance values and combined with the observation time window, determine whether an abnormality occurs in the digital device. d Specifically, step S3 includes:

[0014] Specifically, step S3 includes:

[0015] Calculate the Euclidean distances between matrix X and X s and between X and X d respectively according to the following formula:

[0016]

[0017]

[0018] Take the minimum value L s of all calculated L d and L smin and L dmin . If L smin < L dmin , then calculate the abnormal probability of the digital device through the following formula:

[0019]

[0020] where T S is the total time from the triggering of the zero-sequence voltage or zero-sequence current abnormal threshold to the end of the event, T A is the observation time window, and α is the time coefficient.

[0021] After the observation time ends, if β is greater than the set value, an alarm for digital device abnormality is issued.

[0022] Specifically, the method for generating the feature vector matrix X0 in step S2 is:

[0023] Perform Fourier transform and normalization on the zero-sequence voltage vector U0 and the zero-sequence current vector I0 respectively to obtain the frequency-domain output:

[0024] FU0 = FFT(U0) / FU max

[0025] FI0 = FFT(I0) / FI max

[0026] where FU max and FI max are the numerical points with the largest amplitudes in the collected data segment respectively.

[0027] Perform histogram statistics on FU0 and FI0, with an m hz frequency domain interval, and statistically analyze the frequency domain data distribution greater than each frequency band:

[0028] DU0 = histogram(FU0)

[0029] DI0 = histogram(FI0)

[0030] Combine FU0, FI0, DU0, and DI0 into a feature vector matrix:

[0031]

[0032] Furthermore, when the digital device is abnormal, the characteristic matrix X of different types of poor contacts in the power grid s and when there is a single-phase grounding fault, the characteristic matrix X of different types of poor contacts in the power grid d are preset inside the distribution terminal.

[0033] The characteristic matrix X s is obtained as follows:

[0034] P1: Apply external standard voltage and current signals, and manually simulate different types of poor contacts in the power grid when the digital device is abnormal. For each type of poor contact, generate a characteristic matrix V:

[0035]

[0036] Among them, FU0 and FI0 are the frequency domain outputs of the zero-sequence voltage vector and zero-sequence current vector of the power quantity acquisition data, and DU0 and DI0 are the frequency domain data distributions of each frequency band of the zero-sequence voltage vector and zero-sequence current vector;

[0037] P2: Perform dimensionality reduction processing on the matrix V to obtain the covariance matrix:

[0038] C = V T V = PλP -1

[0039] Obtain the eigenvalues λ of the matrix C, and take the first N largest eigenvalues of the λ vector to form the dimensionality reduction transformation matrix P;

[0040] P3: Perform dimensionality reduction transformation on the 4×M length characteristic matrix V to obtain the N×4 length characteristic matrix X of different types of poor contacts in the power grid when the digital device is abnormal s :

[0041] X s = V T P;

[0042] The characteristic matrix X dThe acquisition method is as follows: Apply external standard voltage and current signals, and artificially simulate different types of poor contacts in the power grid during single-phase grounding faults respectively. For each type of poor contact, a characteristic matrix is generated, and the characteristic matrices X of different types of poor contacts in the power grid during single-phase grounding faults are obtained according to the steps P2 to P3. d 。

[0043] Further, the different types of poor contacts in the power grid described in step S3 include poor contact of phase A of current, poor contact of phases AB of current, poor contact of phases BC of current, poor contact of phases ABC of current, poor contact of phase A of voltage, poor contact of phases AB of voltage, poor contact of phases BC of voltage, and poor contact of phases ABC of voltage.

[0044] Further, T A is set to 72 hours, the value of α is 4, and the set value of β is 70%.

[0045] Further, the value of M is set to 50, and the value of N is 25.

[0046] A chip device includes at least one processor and a memory communicatively connected to the at least one processor. The memory stores a computer program executable by the at least one processor. When the computer program is executed by the at least one processor, the abnormal evaluation method of the digital device is implemented.

[0047] A computer-readable storage medium stores a computer program thereon. When the computer program is executed by a processor, the abnormal evaluation method of the digital device is implemented.

[0048] An abnormal evaluation system for an electronic transformer digital device based on the chip device includes an electronic transformer, a digital device, and a distribution terminal. The digital device is communicatively connected to the electronic transformer and the distribution terminal respectively. The distribution terminal includes a digital message processing circuit and the chip device communicatively connected. The digital message processing circuit is communicatively connected to the digital device.

[0049] The electronic transformer is used to convert external voltage and current signals into analog small signals and transmit them to the digital device. The digital device is used to encode the analog small signals and transmit data messages to the digital message processing circuit. The digital message processing circuit is used to decode the received data messages and forward them to the chip device. The chip device is used to execute the abnormal evaluation method of the digital device.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] (1) By performing characteristic modeling on the frequency domain of zero-sequence voltage and zero-sequence current, the characteristic differences between the anomalies of the digital device and the single-phase grounding fault of the power grid are amplified, effectively distinguishing the voltage and current changes caused by the single-phase grounding fault of the power grid from those caused by the anomalies of the digital device, solving the difficult problem of judging the poor contact state of the digital device with built-in electronic current transformers on the pole-mounted switch, and thus improving the accuracy of transformer fault judgment;

[0052] (2) Perform dimensionality reduction processing on the power matrix, reducing the amount of calculation and improving the calculation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a flowchart of the present invention;

[0054] Figure 2 is a flowchart for presetting the abnormal characteristic matrix of the digital device;

[0055] Figure 3 is a flowchart for presetting the characteristic matrix of the single-phase grounding fault of the power grid;

[0056] Figure 4 is a schematic structural diagram of the abnormal evaluation system of the digital device according to the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0057] The technical solution of the present invention will be described in detail below with reference to the drawings:

[0058] As Figure 1 , an abnormal evaluation method for an electronic current transformer digital device includes the following steps:

[0059] S1: Analyze the transmission message of the digital device and extract all the real-time data of voltage and current at time k. Whether there is poor contact in any phase voltage and current channel caused by the digital device will bring zero-sequence voltage and zero-sequence current. Therefore, extract the zero-sequence voltage u0 and zero-sequence current i0 from the obtained real-time data, and judge whether the zero-sequence voltage and zero-sequence current exceed the preset threshold. If they exceed the preset threshold, go to step S2 for abnormal identification of the digital device; if no abnormality is finally identified, perform the power grid fault detection process.

[0060] S2: Collect the zero-sequence voltage and zero-sequence current of 10 cycles to form a zero-sequence voltage vector U0 and a zero-sequence current vector I0. Perform Fourier transform and normalization on the zero-sequence voltage vector U0 and the zero-sequence current vector I0 respectively to obtain the frequency domain output:

[0061] FU0 = FFT(U0) / FU max

[0062] FI0 = FFT(I0) / FI max

[0063] Among them, FU max and FI max are respectively the numerical points with the largest amplitudes in the acquired data segment.

[0064] Perform histogram statistics on FU0 and FI0, with a frequency domain interval of 5 Hz, and statistically analyze the frequency domain data distribution greater than each frequency band:

[0065] DU0 = histogram(FU0)

[0066] DI0 = histogram(FI0)

[0067] Combine FU0, FI0, DU0, and DI0 into a feature vector matrix:

[0068]

[0069] Perform dimensionality reduction on the X0 matrix to obtain the dimensionality reduction matrix X = X0 T P0, where P0 is the dimensionality reduction transformation matrix.

[0070] Specifically, calculate the covariance matrix:

[0071] C0 = X0 T X0 = P0λ0P0 -1

[0072] Obtain the eigenvalues λ0 of the matrix C0, take the first N largest eigenvalues from the λ0 vector, so as to obtain the dimensionality reduction transformation matrix P0 composed of the first N largest eigenvalues. Perform dimensionality reduction transformation on the 4×M-length feature matrix X0 to obtain the transformed N×4 matrix X:

[0073] X = X0 T P.

[0074] S3: Calculate the Euclidean distances between the matrix X and the feature matrices X of different types of poor contact in the power grid when the digital device in the power distribution terminal 2 malfunctions respectively, and the Euclidean distances between the matrix X and the feature matrices X of different types of poor contact in the power grid during single-phase grounding faults preset in the power distribution terminal 2 s and the Euclidean distances between the matrix X and the feature matrices X of different types of poor contact in the power grid during single-phase grounding faults preset in the power distribution terminal 2 d :

[0075]

[0076]

[0077] For all the calculated L s and L d take the minimum value L smin and L dmin , if L smin < L dmin, the abnormal probability of the digital device is calculated by the following formula:

[0078]

[0079] where, T S is the total time from the triggering of the zero-sequence voltage or zero-sequence current abnormal threshold to the end of the event, T A is the observation time window, and α is the time coefficient. For the abnormal characteristics of the digital device, T A is set to 72 hours, and α is taken as 4. That is, if the total zero-sequence abnormal time within 72 hours accounts for one-fourth, it is considered as the critical point where the probability of a normal power grid fault may decrease while the probability of device abnormality increases.

[0080] After the observation time ends, if β is greater than 70%, an abnormal alarm for the digital device is issued.

[0081] Preferably, before the distribution terminal 2 is put into operation, it is necessary to pre-set the characteristic matrix X s of different types of poor contacts in the power grid when the digital device is abnormal and the characteristic matrix X d of different types of poor contacts in the power grid during single-phase ground fault.

[0082] Such as Figure 2 , the acquisition method of the characteristic matrix X s of different types of poor contacts in the power grid when the digital device is abnormal is as follows:

[0083] P1: Apply external standard voltage and current signals to the switch, and manually simulate different types of poor contacts in the power grid when the digital device is abnormal. The different types of poor contacts in the power grid include current A-phase poor contact, current AB-phase poor contact, current BC-phase poor contact, current ABC-phase poor contact, voltage A-phase poor contact, voltage AB-phase poor contact, voltage BC-phase poor contact, and voltage ABC-phase poor contact.

[0084] For each type of poor contact, a characteristic matrix V is generated:

[0085]

[0086] where, FU0 and FI0 are the frequency-domain outputs of the zero-sequence voltage vector and zero-sequence current vector of the power quantity acquisition data, and DU0 and DI0 are the frequency-domain data distributions of each frequency band of the zero-sequence voltage vector and zero-sequence current vector.

[0087] P2: Considering the calculation performance limitation of the distribution terminal 2, to reduce the calculation amount, the matrix V is dimension-reduced, and the covariance matrix is obtained:

[0088] C = V T V = PλP -1

[0089] Find the eigenvalues λ of matrix C, and take the first N largest eigenvalues of the λ vector to obtain the dimensionality reduction transformation matrix P composed of the first N largest eigenvalues.

[0090] P3: Perform dimensionality reduction transformation on the eigenmatrix V with a length of 4×M to obtain the eigenmatrix X of different types of poor contacts in the power grid when the digital device is abnormal, with a length of N×4. s :

[0091] X s = V T P.

[0092] Preferably, the value of M is set to 50, and the value of N is 25.

[0093] Such as Figure 3 , the method for obtaining the eigenmatrix X of different types of poor contacts in the power grid during single-phase grounding faults is as follows: Apply external standard voltage and current signals to the switch, and manually simulate different types of poor contacts in the power grid during single-phase grounding faults in the factory through a relay protection device. Each type of poor contact generates an eigenmatrix, and the eigenmatrix X of different types of poor contacts in the power grid during single-phase grounding faults is obtained according to the steps P2 - P3. d . d .

[0094] Store the eigenmatrices X of 8 types of abnormal poor contact situations simulated manually s , eigenmatrix X d into the internal fixed memory of the distribution terminal 2.

[0095] Based on the above abnormal evaluation method of the electronic current transformer digital device, the present invention also provides a chip device and a computer-readable storage medium.

[0096] In this embodiment, the chip device 2-1 includes at least one processor and a memory communicatively connected to the at least one processor. The memory stores the preset eigenmatrix X s , eigenmatrix X d and a computer program executable by the at least one processor. When the computer program is executed, it needs to call the preset eigenmatrix X s and eigenmatrix X d , and when the computer program is executed by the at least one processor, it implements the abnormal evaluation method of the digital device in the above embodiment.

[0097] Similarly, the computer-readable storage medium provided by the present invention stores a computer program thereon, and when the computer program is executed by a processor, it implements the abnormal evaluation method of the digital device in the above embodiment.

[0098] Such as Figure 4As shown in the figure, the present invention also provides an abnormal evaluation system for a digital electronic transformer device based on the chip device, including an electronic voltage transformer 1-3, an electronic current transformer 1-2, a digital device 1-1, and a distribution terminal 2. The digital device 1-1 is respectively communicatively connected to the electronic voltage transformer 1-3, the electronic current transformer 1-2, and the distribution terminal 2. The distribution terminal 2 includes a digital message processing circuit 2-2 and the chip device 2-1 which are communicatively connected. The digital device 1-1 is communicatively connected to the digital message processing circuit 2-2 through an isolated twisted pair wire.

[0099] The electronic voltage transformer 1-3, the electronic current transformer 1-2, and the digital device 1-1 are installed inside the digital primary-secondary integrated pole-mounted switch 1, and the distribution terminal 2 is installed under the electric pole.

[0100] During normal operation, the external 10 kV voltage and current are connected to the electronic voltage transformer 1-3 and the electronic current transformer 1-2 through the switch terminals. The electronic voltage transformer 1-3 and the electronic current transformer 1-2 convert the external 10 kV voltage and current of the switch into analog small signals and transmit them to the digital device 1-1. The digital device 1-1 samples and encodes the small signals into digital messages in FT3 format and transmits them to the digital message processing circuit 2-2. The digital message processing circuit 2-2 decodes the received data message and forwards it to the chip device 2-1, and the chip device 2-1 executes the abnormal evaluation method of the digital device.

[0101] The difficulty in identifying whether the digital device is in a poor contact state lies in that its abnormal waveform is often very similar to the waveform of a normal single-phase grounding fault in the power grid, and it is very easy to be judged as a normal single-phase grounding fault or a zero-sequence overcurrent fault. If judged only from the transient waveform in a certain period, the characteristic difference is very small. This method utilizes the differential characteristic that the high-frequency information contained in the zero-sequence voltage and zero-sequence current caused by a conventional power grid grounding fault is much greater than the high-frequency information of the zero-sequence waveform caused by the abnormality of the digital device. By performing characteristic modeling on the frequency domain of the zero-sequence voltage and zero-sequence current, the characteristic difference between the abnormality of the digital device and the normal power grid fault is amplified: if the zero-sequence voltage and zero-sequence current exceed the limit, the abnormal identification process of the digital device is started. After accumulating the data volume of several cycles, the data volume is characterized, and the preset digital device fault characteristic data and the characteristic data of various types of single-phase grounding faults in the power grid are called from the memory library, and the Euclidean distance calculation is performed one by one, and the fault probability is calculated, so as to effectively distinguish the voltage and current changes caused by a normal power grid grounding fault from the changes caused by the abnormality of the digital device, and solve the difficult problem of judging the poor contact state of the digital device.

Claims

1. An abnormal evaluation method for a digital device of an electronic current transformer, characterized in that, It includes the following steps: S1: Analyze the transmission message of the digital device, extract the zero-sequence voltage u0 and zero-sequence current i0, and determine whether the zero-sequence voltage and zero-sequence current exceed the preset threshold. If they exceed the preset threshold, go to step S2 for abnormal identification of the digital device; S2: Collect several cycle zero-sequence voltages and zero-sequence currents to form a zero-sequence voltage vector U0 and a zero-sequence current vector I0, and generate a feature vector matrix X0. Perform dimensionality reduction processing on the X0 matrix to obtain a dimensionality reduction matrix X; The method for generating the feature vector matrix X0 described in step S2 is: Perform Fourier transform and normalization on the zero-sequence voltage vector U0 and the zero-sequence current vector I0 respectively to obtain the frequency-domain output: FU0 = FFT(U0) / FU max FI0 = FFT(I0) / FI max Among them, FU max and FI max are respectively the numerical points with the largest amplitude in the acquired data segment; Perform histogram statistics on FU0 and FI0, with m hz as the frequency-domain interval, and statistically analyze the frequency-domain data distribution greater than each frequency band: DU0 = histogram(FU0) DI0 = histogram(FI0) Combine FU0, FI0, DU0, and DI0 into a feature vector matrix: S3: Calculate the Euclidean distances between matrix X and the characteristic matrices X of different types of poor contacts in the power grid during abnormal operation of the digital device, and between matrix X and the characteristic matrices X of different types of poor contacts in the power grid during single-phase grounding faults. Based on the calculated Euclidean distance values and combined with the observation time window, determine whether there is an abnormality in the digital device; s and between matrix X and the characteristic matrices X of different types of poor contacts in the power grid during single-phase grounding faults; d Based on the calculated Euclidean distance values and combined with the observation time window, determine whether there is an abnormality in the digital device; The specific content of step S3 includes: Calculate the Euclidean distances between matrix X and X s and between X and X d respectively according to the following formula: For all calculated L s and L d take the minimum value L smin and L dmin , if L smin < L dmin , then calculate the abnormal probability of the digital device through the following formula: Among them, T S is the total time from the triggering of the zero-sequence voltage or zero-sequence current abnormal threshold to the end of the event, T A is the observation time window, and α is the time coefficient; After the observation time ends, if β is greater than the set value, perform abnormal alarm on the digital device.

2. The abnormal evaluation method of the digital device of the electronic transformer according to claim 1, characterized in that: The characteristic matrix X of different types of poor contact in the power grid when the digital device is abnormal s and the characteristic matrix X of different types of poor contact in the power grid during single-phase grounding faults d are preset inside the distribution terminal (2); Feature matrix X s The acquisition method is as follows: P1: Apply external standard voltage and current signals, and manually simulate different types of poor contacts in the power grid when the digital device is abnormal. Generate a feature matrix V for each type of poor contact: Among them, FU0 and FI0 are the frequency-domain outputs of the zero-sequence voltage vector and zero-sequence current vector of the power quantity acquisition data, and DU0 and DI0 are the frequency-domain data distributions of each frequency band of the zero-sequence voltage vector and zero-sequence current vector; P2: Perform dimensionality reduction processing on the matrix V to obtain the covariance matrix: C = V T V = PλP -1 Obtain the eigenvalues λ of the matrix C, and select the first N largest eigenvalues from the λ vector to form a dimensionality reduction transformation matrix P; P3: Perform dimensionality reduction transformation on the feature matrix V with a length of 4×M to obtain the feature matrix X of different types of poor electrical contacts in the power grid when the digital device is abnormal, with a length of N×4 s : X s = V T P; Feature matrix X d The acquisition method is as follows: apply external standard voltage and current signals, respectively simulate different types of poor contacts in the power grid during single-phase grounding faults manually, generate a feature matrix for each type of poor contact, and obtain the feature matrix X of different types of poor contacts in the power grid during single-phase grounding faults according to the steps P2 to P3 d .

3. The abnormal evaluation method of the digital device of the electronic transformer according to claim 1, wherein: The different types of poor contacts in the power grid described in step S3 include current A-phase poor contact, current AB-phase poor contact, current BC-phase poor contact, current ABC-phase poor contact, voltage A-phase poor contact, voltage AB-phase poor contact, voltage BC-phase poor contact, and voltage ABC-phase poor contact.

4. The abnormal evaluation method of the digital device of the electronic transformer according to claim 1, characterized in that: T A Set to 72 hours, the value of α is 4, and the set value of β is 70%.

5. The abnormal evaluation method of the electronic transformer digital device according to claim 2, characterized in that: The value of M is set to 50, and the value of N is 25.

6. A chip device, characterized in that: It includes at least one processor and a memory communicatively connected to the at least one processor. The memory stores a computer program executable by the at least one processor. When the computer program is executed by the at least one processor, it implements the abnormal evaluation method of the digital device as described in any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the abnormal evaluation method of the digital device as described in any one of claims 1 to 5.

8. An abnormal evaluation system for a digital device of an electronic current transformer based on the chip device as described in claim 6, characterized in that: It includes an electronic current transformer, a digital device (1-1), and a distribution terminal (2). The digital device (1-1) is communicatively connected to the electronic current transformer and the distribution terminal (2) respectively. The distribution terminal (2) includes a digital message processing circuit (2-2) and the chip device (2-1) communicatively connected. The digital message processing circuit (2-2) is communicatively connected to the digital device (1-1); The electronic transformer is used to convert external voltage and current signals into analog small signals and transmit them to the digital device (1-1). The digital device (1-1) is used to encode the analog small signals and transmit data packets to the digital packet processing circuit (2-2). The digital packet processing circuit (2-2) is used to decode the received data packets and forward them to the chip device (2-1). The chip device (2-1) is used to execute the abnormal evaluation method of the digital device.

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