A method, device and storage medium for identifying nonlinear errors of optical fiber current transformer

Abstract

The present invention discloses a method, device, and storage medium for identifying nonlinear errors in a fiber-optic current transformer. The method comprises: obtaining an output signal from the fiber-optic current transformer; decomposing the output signal using an EMD algorithm to obtain modal components and residuals; calculating zero-crossing indices of the modal components of the output signal and classifying the modal components based on the zero-crossing indices; recombining the output signal based on the classified modal components to obtain modal component signals; and performing error identification based on the modal component signals and the representation of the modal components. The present invention is suitable for extracting nonlinear errors from fiber-optic current transformers and improves the accuracy and real-time performance of feature extraction, thereby increasing the speed of error identification.

Description

Technical Field

[0001] The present invention relates to a nonlinear error identification method, device and storage medium of an optical fiber current transformer, and belongs to the technical field of fault detection. Background Art

[0002] Fiber-optic current transformers (FOCTs), with their advantages of excellent insulation, high reliability, wide frequency bandwidth, and good transient characteristics, have been widely used in HVDC transmission projects. As a measuring element in the primary system, their stable and reliable operation is crucial for relay protection, measurement and control, and energy metering. However, due to complex environmental influences such as high and low temperatures, aging, and vibration within the station, FOCTs can experience nonlinear errors such as drift and transformation ratio. These errors can cause measurement deviations, performance degradation, and even operational accidents, leading to abnormal output signals.

[0003] As an optical interferometer, FOCT has a complex internal structure and uses many optical and electronic devices. In actual field applications, it will be affected by harsh operating environments, causing equipment failure. The performance and life of each structural component in the fiber optic current transformer are the key to the long-term reliable operation of the equipment. Failure in any link will cause equipment failure. When failures occur in different parts of the fiber optic current transformer, the output signal will show different characteristics. In order to identify the error characteristics caused by the fault, the present application proposes a nonlinear error identification method, device and storage medium for fiber optic current transformer. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method, device and storage medium for identifying the nonlinear error of a fiber optic current transformer, thereby solving the problem of error feature identification of a fiber optic current transformer and providing a reference for improving the operational reliability of a fiber optic current transformer in a DC transmission project.

[0005] To achieve the above object, the present invention is implemented by adopting the following technical solutions:

[0006] In a first aspect, the present invention provides a method for identifying nonlinear errors of a fiber optic current transformer, comprising:

[0007] Obtaining the output signal of the optical fiber current transformer;

[0008] The EMD algorithm is used to decompose the output signal to obtain modal components and residuals;

[0009] calculating zero-crossing indices of modal components of the output signal, and classifying the modal components based on the zero-crossing indices;

[0010] The output signal is reorganized based on the classified modal components to obtain a modal component signal;

[0011] Error identification is performed based on the modal component signals according to the manifestation of the modal components.

[0012] Optionally, the output signal of the optical fiber current transformer includes a normal signal, a drift error signal, and a transformation ratio error signal;

[0013] The normal signal x 1 (t) is:

[0014]

[0015] Among them, t is the sampling time, K is the true value amplitude, ω is the angular frequency, is the modulation phase;

[0016] The drift error signal x 2 (t) is:

[0017]

[0018] Where f1(t) is the drift error:

[0019] f1(t)=k1(tt s )+rand1

[0020] k1 is the drift error coefficient, t s is the moment when the fault occurs, rand1 is the random noise accompanying the drift error;

[0021] The ratio error signal x 3 (t) is:

[0022]

[0023] Where f2(t) is the ratio error:

[0024]

[0025] k2 is the ratio error coefficient, and rand2 is the random noise that occurs when the ratio error occurs.

[0026] Optionally, the step of using an EMD algorithm to decompose the output signal to obtain modal components and residuals includes:

[0027] Convert the output signal x(t) of the fiber optic current transformer into the FOCT signal x i (t) is a FOCT signal sequence composed of the FOCT signal x i (t) is:

[0028] x i (t)=x(t)+ε i ωi (t)

[0029] Among them, t is the sampling time, ω i (t) is the Gaussian white noise with unit variance and mean 0 added to the i-th FOCT signal, ε i is the standard deviation of the i-th Gaussian white noise; i=1,2,…,N, N is the number of Gaussian white noises added;

[0030] For each FOCT signal x in the FOCT signal sequence i (t) is decomposed by EMD, and the average value of the decomposition is calculated to obtain the first modal component imf1(t):

[0031]

[0032] in, is the i-th FOCT signal x i EMD decomposition value of (t);

[0033] Calculate the first residual r1(t) based on the first modal component imf1(t):

[0034] r1(t)=x(t)-imf1(t)

[0035] N Gaussian white noise ω i (t) Perform EMD decomposition to obtain its modal components;

[0036] According to Gaussian white noise ω i The modal component of (t) is calculated to obtain the second modal component imf2(t):

[0037]

[0038] Calculate the second residual r2(t) based on the second modal component imf2(t):

[0039] r2(t)=r1(t)-imf2(t)

[0040] According to the above steps, the modal components and residuals of the FOCT signal sequence are calculated in sequence until the kth residual r k If the number of extreme points of (t) is greater than or equal to 2, stop EMD decomposition and get:

[0041] kth margin r k (t) is:

[0042] r k (t) = r k-1 (t)-imf k (t)

[0043] k+1th modal component imf k+1 (t) is:

[0044]

[0045] Among them, E k (·) is the kth modal component obtained by EMD decomposition.

[0046] Optionally, the zero-crossing index Z of the modal component is:

[0047]

[0048] Among them, T represents the sampling time, imf i (t) is the i-th modal component, sgn[·] is the sign function, and its expression is:

[0049]

[0050] Optionally, classifying the modal components based on the zero-crossing index includes:

[0051] If the zero-crossing index of the modal component is greater than 50, the modal component is a high-frequency signal component;

[0052] If the zero-crossing index of the modal component is less than 49, the modal component is a low-frequency signal component;

[0053] If the zero-crossing index of the modal component is equal to 49 or 50, the modal component is a power frequency signal component.

[0054] Optionally, the reorganizing the output signal based on the classified modal components to obtain the modal component signal includes:

[0055] Recombining the high-frequency signal component to obtain a recombined signal high-frequency component IMF1, recombining the power frequency signal component to obtain a recombined signal power frequency component IMF2, and recombining the low-frequency signal component and the remainder to obtain a recombined signal low-frequency component IMF3;

[0056] The modal component signals are obtained based on the recombined signal high frequency component IMF1, the recombined signal power frequency component IMF2 and the recombined signal low frequency component IMF3.

[0057] Optionally, the performing error identification based on the modal component signal according to the representation of the modal component includes:

[0058] The error type of the output signal is identified based on the recombined signal high-frequency component IMF1, the recombined signal power frequency component IMF2 and the recombined signal low-frequency component IMF3.

[0059] In a second aspect, the present invention provides a device for identifying nonlinear errors of a fiber optic current transformer, the device comprising:

[0060] A signal acquisition module, used to acquire the output signal of the optical fiber current transformer;

[0061] Signal decomposition module, used to decompose the output signal using EMD algorithm to obtain modal components and residuals;

[0062] a component classification module, configured to calculate zero-crossing indices of modal components of the output signal and classify the modal components based on the zero-crossing indices;

[0063] A component recombining module, configured to recombine the output signal based on the classified modal components to obtain a modal component signal;

[0064] The error identification module is used to perform error identification based on the modal component signal according to the expression form of the modal component.

[0065] In a third aspect, the present invention provides a nonlinear error identification device for a fiber optic current transformer, comprising a processor and a storage medium;

[0066] The storage medium is used to store instructions;

[0067] The processor is configured to operate according to the instructions to execute the steps of any of the above methods.

[0068] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of any of the above methods when executed by a processor.

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] Embodiments of the present invention provide a method, device, and storage medium for identifying nonlinear errors in a fiber-optic current transformer (FOCT). The method utilizes an EMD algorithm to decompose the FOCT's output signal, yielding different numbers of modal components for different error signals. Due to the varying number of modal components, a unified metric cannot be used for identification. The method calculates the zero-crossing rate index for each modal component, recombines the modal signal into three groups, and constructs a modal component signal with a stable number of decomposition results. Different error signals exhibit distinct characteristics in the three components. The drift error's fault signature is primarily concentrated in IMF3, manifesting as a signal with an upward drift. The ratio error's error signature is concentrated in IMF2, manifesting as a ratio signal with an increasing ratio. By determining the distinct characteristics of the three recombined component signals, the error state characteristics of the FOCT can be accurately determined and error identification performed. This method is suitable for extracting nonlinear errors from FOCTs and improves the accuracy and real-time performance of feature extraction, thereby accelerating error identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 This is a flow chart of a method for identifying nonlinear errors of a fiber optic current transformer provided by an embodiment of the present invention;

[0072] Figure 2 2. It is a schematic diagram comparing the IMF3 component of the drift error signal reconstruction result and the residual signal provided by an embodiment of the present invention;

[0073] Figure 3 3 is a schematic diagram comparing the ratio of the IMF2 component of the transformation ratio error signal reconstruction result and the reference signal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0074] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention.

[0075] Example 1:

[0076] like Figure 1 As shown, the present invention provides a method for identifying nonlinear errors of an optical fiber current transformer, comprising the following steps:

[0077] (1) Obtaining the output signal of the optical fiber current transformer;

[0078] This example focuses on drift and nonlinear errors related to the transformer's ratio. FOCTs are affected by temperature and vibration, which can degrade the performance of their internal magneto-optical materials. Over time, some components age, causing the transformer's primary and secondary signal ratios to gradually change and accuracy to decrease. This causes signal measurements to vary over time, leading to nonlinear errors.

[0079] Drift error manifests as a gradually increasing drift amount. When the light source, optical fiber, and other materials inside the FOCT are affected by external factors, the device parameters change, causing the output current signal to deviate from the normal signal. Furthermore, the FOCT output signal is proportional to the amplitude of the modulation signal. When a fault in the modulation circuit causes the amplitude to change, this can lead to a FOCT ratio error.

[0080] Specifically:

[0081] The output signal of the optical fiber current transformer includes a normal signal, a drift error signal, and a ratio error signal;

[0082] 1.1. Normal signal x 1 (t) is:

[0083]

[0084] Among them, t is the sampling time, K is the true value amplitude, ω is the angular frequency, is the modulation phase;

[0085] 1.2. Containing drift error signal x 2 (t) is:

[0086]

[0087] Where f1(t) is the drift error:

[0088] f1(t)=k1(tt s )+rand1

[0089] k1 is the drift error coefficient, t s is the moment when the fault occurs, rand1 is the random noise accompanying the drift error;

[0090] 1.3、Contains the ratio error signal x 3 (t) is:

[0091]

[0092] Where f2(t) is the ratio error:

[0093]

[0094] k2 is the ratio error coefficient, and rand2 is the random noise that occurs when the ratio error occurs.

[0095] (2) Use the EMD algorithm to decompose the output signal to obtain modal components and residuals; specifically:

[0096] 2.1. Convert the output signal x(t) of the fiber optic current transformer into the FOCT signal x i (t) composed of FOCT signal sequence, FOCT signal x i (y) is:

[0097] x i (y)=x(t)+ε i ω i (t)

[0098] Among them, t is the sampling time, ω i (t) is the Gaussian white noise with unit variance and mean 0 added to the i-th FOCT signal, ε i is the standard deviation of the i-th Gaussian white noise; i=1,2,…,N, N is the number of Gaussian white noises added;

[0099] 2.1. For each FOCT signal x in the FOCT signal sequence i (t) is decomposed by EMD, and the average value of the decomposition is calculated to obtain the first modal component imf1(t):

[0100]

[0101] in, is the i-th FOCT signal x i EMD decomposition value of (t);

[0102] 2.2. Calculate the first residual r1(t) based on the first modal component imf1(t):

[0103] r1(t)=x(t)-imf1(t)

[0104] 2.3、N Gaussian white noise ω i (t) Perform EMD decomposition to obtain its modal components;

[0105] 2.4, according to Gaussian white noise ω i The modal component of (t) is calculated to obtain the second modal component imf2(t):

[0106]

[0107] 2.5. Calculate the second residual r2(t) based on the second modal component imf2(t):

[0108] r2(t)=r1(t)-imf2(t)

[0109] 2.6. According to the above steps, the modal components and residuals of the FOCT signal sequence are calculated in sequence until the kth residual r kIf the number of extreme points of (t) is greater than or equal to 2, stop EMD decomposition and get:

[0110] kth margin r k (t) is:

[0111] r k (t) = r k-1 (t)-imf k (t)

[0112] k+1th modal component imf k+1 (t) is:

[0113]

[0114] Among them, E k (·) is the kth modal component obtained by EMD decomposition.

[0115] In this embodiment, the standard deviation ε of the i-th Gaussian white noise i Take 0.02, and the number of Gaussian white noise N is 50.

[0116] The normal signal, the signal containing drift error and the signal containing ratio error are decomposed using the EMD algorithm to obtain the modal components of the three signals.

[0117] The number of modal components obtained by decomposing the normal signal is k=14;

[0118] The number of modal components obtained by decomposing the drift error signal is k=12;

[0119] The number of modal components obtained by decomposing the signal containing the ratio error is k=14.

[0120] (3) calculating the zero-crossing index of the modal components of the output signal and classifying the modal components based on the zero-crossing index;

[0121] The zero-crossing index Z of the modal component is:

[0122]

[0123] Among them, T represents the sampling time, imf i (t) is the i-th modal component, sgn[·] is the sign function, and its expression is:

[0124]

[0125] Classify the modal components:

[0126] According to the frequency of the collected current signal is 50Hz,

[0127] If the zero-crossing index of the modal component is greater than 50, the modal component is a high-frequency signal component;

[0128] If the zero-crossing index of the modal component is less than 49, the modal component is a low-frequency signal component;

[0129] If the zero-crossing index of the modal component is equal to 49 or 50, the modal component is a power frequency signal component;

[0130] In this embodiment,

[0131] For normal signals, the zero-crossing index Z of imf5 is 49, the zero-crossing index Z of imf6 is 50, and the 10 -imf 14 The zero-crossing index Z of the other component signals is less than 49, and the zero-crossing index Z of the other component signals is greater than 50.

[0132] For signals with drift errors, the zero-crossing index Z of imf5 is 49, the zero-crossing index Z of imf6 is 50, and the 10 -imf 14 The zero-crossing index Z of the other component signals is less than 49, and the zero-crossing index Z of the other component signals is greater than 50.

[0133] For signals containing ratio error, the zero-crossing index Z of imf5 is 49, the zero-crossing index Z of imf6 is 50, and the zero-crossing index Z of imf 10 -imf 14 The zero-crossing index Z of the other component signals is less than 49, and the zero-crossing index Z of the other component signals is greater than 50.

[0134] (4) reorganizing the output signal based on the classified modal components to obtain the modal component signal;

[0135] Recombining the high-frequency signal component to obtain a recombined signal high-frequency component IMF1, recombining the power frequency signal component to obtain a recombined signal power frequency component IMF2, and recombining the low-frequency signal component and the remainder to obtain a recombined signal low-frequency component IMF3;

[0136] The modal component signals are obtained based on the recombined signal high frequency component IMF1, the recombined signal power frequency component IMF2 and the recombined signal low frequency component IMF3.

[0137] In this embodiment,

[0138] For normal signals, recombining imf1-imf4 and imf7-imf9 obtains the high-frequency component IMF1 of the recombined signal, recombining imf5-imf6 obtains the power frequency component IMF2 of the recombined signal, and recombining imf 10 -imf 14 Get the recombined signal low frequency component IMF3;

[0139] For the signal containing drift error, recombining imf1-imf4, imf7-imf9 obtains the high frequency component IMF1 of the recombined signal, recombining imf5-imf6 obtains the power frequency component IMF2 of the recombined signal, and recombining imf 10 -imf 14 Get the recombined signal low frequency component IMF3;

[0140] For the signal containing ratio error, recombining imf1-imf4, imf7-imf9 obtains the high-frequency component IMF1 of the recombined signal, recombining imf5-imf6 obtains the power frequency component IMF2 of the recombined signal, and recombining imf 10 -imf 14 Get the recombined signal low frequency component IMF3;

[0141] For the margin r k (t), which is a monotonic signal itself, is therefore added as a low-frequency component to the reconstructed signal low-frequency component IMF3.

[0142] (5) Error identification is performed based on the modal component signal and the manifestation of the modal component.

[0143] The error type of the output signal is identified based on the recombined signal high-frequency component IMF1, the recombined signal power frequency component IMF2 and the recombined signal low-frequency component IMF3.

[0144] like Figure 2 As shown in Figure 1, for a signal containing drift error, f1(t) is taken as the residual component (the difference between the drift error and the reference signal). This is compared with the IMF3 component extracted by this algorithm. The low-frequency IMF3 component of the reconstructed signal can well represent the drift error, demonstrating the effectiveness of the algorithm in extracting drift errors.

[0145] like Figure 3 As shown in the figure, for a signal containing a ratio error, the ratio of f2(t) to x(t) is taken as the ratio. The ratio of IMF2 obtained by this algorithm to the reference signal is calculated and compared. The reconstructed signal's power frequency component, IMF2, can well represent the ratio error, demonstrating the algorithm's effectiveness in extracting ratio errors.

[0146] Example 2:

[0147] An embodiment of the present invention provides a device for identifying nonlinear errors of a fiber optic current transformer, comprising:

[0148] A signal acquisition module, used to acquire the output signal of the optical fiber current transformer;

[0149] Signal decomposition module, used to decompose the output signal using EMD algorithm to obtain modal components and residuals;

[0150] a component classification module, configured to calculate zero-crossing indices of modal components of the output signal and classify the modal components based on the zero-crossing indices;

[0151] A component recombining module, configured to recombine the output signal based on the classified modal components to obtain a modal component signal;

[0152] The error identification module is used to perform error identification based on the modal component signal according to the expression form of the modal component.

[0153] Example 3:

[0154] Based on the first embodiment, the present invention provides a nonlinear error identification device for a fiber optic current transformer, including a processor and a storage medium;

[0155] The storage medium is used to store instructions;

[0156] The processor is configured to operate according to the instructions to execute the steps of the above method.

[0157] Example 4:

[0158] Based on the first embodiment, the embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the above method are implemented.

[0159] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0160] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0161] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0162] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0163] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for identifying nonlinear errors in optical fiber current transformers, characterized in that: include: Obtaining the output signal of the optical fiber current transformer; The EMD algorithm is used to decompose the output signal to obtain modal components and residuals; calculating zero-crossing indices of modal components of the output signal, and classifying the modal components based on the zero-crossing indices; The output signal is reorganized based on the classified modal components to obtain a modal component signal; Error identification is performed based on the modal component signals according to the manifestation of the modal components; Among them, the zero-crossing index Z of the modal component is: Among them, T represents the sampling time, imf i (t) is the i-th modal component, sgn[·] is the sign function, and its expression is: Classifying the modal components based on the zero-crossing index includes: If the zero-crossing index of the modal component is greater than 50, the modal component is a high-frequency signal component; If the zero-crossing index of the modal component is less than 49, the modal component is a low-frequency signal component; If the zero-crossing index of the modal component is equal to 49 or 50, the modal component is a power frequency signal component.

2. The method for identifying nonlinear errors of an optical fiber current transformer according to claim 1, wherein: The output signal of the optical fiber current transformer includes a normal signal, a drift error signal and a ratio error signal; The normal signal x 1 (t) is: Among them, t is the sampling time, K is the true value amplitude, ω is the angular frequency, is the modulation phase; The drift error signal x 2 (t) is: Where f1(t) is the drift error: f1(t)=k1(t-t s )+rand1 k1 is the drift error coefficient, t s is the moment when the fault occurs, rand1 is the random noise accompanying the drift error; The ratio error signal x 3 (t) is: Where f2(t) is the ratio error: k2 is the ratio error coefficient, and rand2 is the random noise that occurs when the ratio error occurs.

3. The method for identifying nonlinear errors of a fiber optic current transformer according to claim 1, wherein: Decomposing the output signal using the EMD algorithm to obtain modal components and residuals includes: Convert the output signal x(t) of the fiber optic current transformer into the FOCT signal x i (t) is a FOCT signal sequence composed of the FOCT signal x i (t) is: x i (t)=x(t)+ε i ω i (t) Among them, t is the sampling time, ω i (t) is the Gaussian white noise with unit variance and mean 0 added to the i-th FOCT signal, ε i is the standard deviation of the i-th Gaussian white noise; i=1,2,…,N, N is the number of Gaussian white noises added; For each FOCT signal x in the FOCT signal sequence i (t) is decomposed by EMD, and the average value of the decomposition is calculated to obtain the first modal component imf1(t): in, is the i-th FOCT signal x i EMD decomposition value of (t); Calculate the first residual r1(t) based on the first modal component imf1(t): r1(t)=x(t)-imf1(t) N Gaussian white noise ω i (t) Perform EMD decomposition to obtain its modal components; According to Gaussian white noise ω i The modal component of (t) is calculated to obtain the second modal component imf2(t): Calculate the second residual r2(t) based on the second modal component imf2(t): r2(t)=r1(t)-imf2(t) According to the above steps, the modal components and residuals of the FOCT signal sequence are calculated in sequence until the kth residual r k If the number of extreme points of (t) is greater than or equal to 2, stop EMD decomposition and get: kth margin r k (t) is: r k (t)=r k-1 (t)-imf k (t) k+1th modal component imf k+1 (t) is: Among them, E k (·) is the kth modal component obtained by EMD decomposition.

4. The method for identifying nonlinear errors of a fiber optic current transformer according to claim 1, wherein: The step of recombining the output signal based on the classified modal components to obtain the modal component signal comprises: Recombining the high-frequency signal component to obtain a recombined signal high-frequency component IMF1, recombining the power frequency signal component to obtain a recombined signal power frequency component IMF2, and recombining the low-frequency signal component and the remainder to obtain a recombined signal low-frequency component IMF3; The modal component signals are obtained based on the recombined signal high frequency component IMF1, the recombined signal power frequency component IMF2 and the recombined signal low frequency component IMF3.

5. The method for identifying nonlinear errors of an optical fiber current transformer according to claim 4, wherein: The error identification based on the modal component signal according to the expression form of the modal component includes: The error type of the output signal is identified based on the recombined signal high-frequency component IMF1, the recombined signal power frequency component IMF2 and the recombined signal low-frequency component IMF3.

6. A nonlinear error identification device for a fiber optic current transformer, characterized in that: The device comprises: A signal acquisition module, used to acquire the output signal of the optical fiber current transformer; Signal decomposition module, used to decompose the output signal using EMD algorithm to obtain modal components and residuals; a component classification module, configured to calculate zero-crossing indices of modal components of the output signal and classify the modal components based on the zero-crossing indices; A component recombining module, configured to recombine the output signal based on the classified modal components to obtain a modal component signal; An error identification module, configured to perform error identification based on the modal component signal and the representation of the modal component; Among them, the zero-crossing index Z of the modal component is: Among them, T represents the sampling time, imf i (t) is the i-th modal component, sgn[·] is the sign function, and its expression is: Classifying the modal components based on the zero-crossing index includes: If the zero-crossing index of the modal component is greater than 50, the modal component is a high-frequency signal component; If the zero-crossing index of the modal component is less than 49, the modal component is a low-frequency signal component; If the zero-crossing index of the modal component is equal to 49 or 50, the modal component is a power frequency signal component.

7. A nonlinear error identification device for a fiber optic current transformer, characterized in that: including processors and storage media; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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