Method for accurately positioning faults in FTU (Feeder Terminal Unit) section based on adaptive variational mode decomposition

Abstract

The invention discloses a method for accurately positioning a fault in an FTU (Feeder Terminal Unit) section based on adaptive variational mode decomposition, which comprises the following steps of: acquiring first beat frequency signals and first current signals of fault points of FTU under various fault types, and establishing a one-to-one correspondence relationship between the fault types and the first beat frequency signals, extracting a signal feature of the first beat frequency signal as a first signal feature; taking the influence relation between the first current signal and the first beat frequency signal and the influence relation between the frequency modulation signal and the first beat frequency signal as a mapping relation; acquiring a second current signal of the FTU in real time, acquiring a corresponding frequency modulation signal according to the mapping relation, inputting the frequency modulation signal into the FTU, and acquiring a second beat frequency signal of the FTU; and extracting a signal feature of the second beat frequency signal as a second signal feature, matching the first signal feature with the second signal feature, obtaining a fault type corresponding to the first beat frequency signal according to the corresponding relationship, and outputting the fault type. According to the invention, the accuracy and effectiveness of FTU fault identification are improved, and the operation and maintenance efficiency of the power distribution network is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of automatic fault diagnosis of electric power systems, and in particular relates to a method for accurately locating faults in an FTU section based on adaptive variational mode decomposition. Background Art

[0002] The distribution switch monitoring terminal (FTU for short) has remote control, telemetry, telesignaling, and fault detection functions, and communicates with the distribution automation master station to provide the distribution system operation status and various parameters and information required for monitoring and control, including switch status, power parameters, phase-to-phase faults, ground faults, and parameters at the time of faults. It also executes commands issued by the distribution master station to adjust and control the distribution equipment, and realizes functions such as fault location, fault isolation, and rapid power supply restoration in non-fault areas.

[0003] At present, my country's distribution network mainly adopts a small current grounding system. When single-phase grounding occurs, it is not enough to rely solely on changes in electrical quantities to locate the fault. Since the pulse noise and the mutation characteristics of the current signal during the operation of the FTU are very similar, the recognition accuracy is affected. Since the fault current of each fault type in the FTU is not obvious enough, the accuracy and effectiveness of fault identification are affected, and it is difficult to locate the fault.

[0004] Since the pulse noise and the mutation characteristics of the current signal during the operation of the FTU are very similar, the recognition accuracy is affected. Since the fault current of each fault type in the FTU is not obvious enough, the accuracy and effectiveness of fault identification are affected, making it difficult to locate the fault. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a method for accurately locating faults within an FTU section based on adaptive variational mode decomposition, which can improve the accuracy and effectiveness of FTU fault identification and thus improve the operation and maintenance efficiency of the distribution network.

[0006] The technical solution of the present invention is:

[0007] A method for accurately locating faults in a FTU section based on adaptive variational mode decomposition comprises the following steps:

[0008] Step S1: obtaining a first beat frequency signal and a first current signal of a fault point of an FTU under various fault types, establishing a one-to-one correspondence between the fault type and the first beat frequency signal, and extracting a signal feature of the first beat frequency signal as a first signal feature;

[0009] Step S2: taking the influence relationship between the first current signal and the frequency modulation signal and the first beat frequency signal as a mapping relationship;

[0010] Step S3: collect the second current signal of the FTU in real time, obtain the corresponding frequency modulation signal according to the mapping relationship, input the frequency modulation signal into the FTU, and collect the second beat frequency signal of the FTU;

[0011] Step S4: extracting the signal feature of the second beat frequency signal as the second signal feature, matching the first signal feature with the second signal feature, obtaining the fault type corresponding to the first beat frequency signal according to the corresponding relationship, and outputting the result;

[0012] The fault types include abnormal telemetry data, abnormal active and reactive data, abnormal remote signaling data of the distribution terminal, failure of remote control of the distribution terminal, and inability of the distribution terminal to connect to the master station.

[0013] Furthermore, the step S1 is specifically as follows: simulating the fault current of the FTU under various fault types respectively, and obtaining the first beat frequency signal x of the fault point of the FTU under various fault types respectively. b1 (t) and the first current signal i1(t) and the corresponding fault location L f , the signal characteristics of the first beat frequency signal are extracted by short-time Fourier transform as the first signal characteristics, wherein the first signal characteristics include phase difference, amplitude, phase and frequency, and a one-to-one correspondence between the fault type and the first beat frequency signal is established; the expression of the first current signal i1(t) is:

[0014]

[0015] Where i1(t) represents the first current signal, A i Indicates the amplitude of the fault current signal, f i Indicates the frequency of the fault current signal, φ i represents the initial phase of the fault current signal, and n(t) represents the noise in the signal;

[0016] The fault location L f Indicates the geographical or circuit location where the fault occurred;

[0017] The expression of the first beat frequency signal is:

[0018] x b1 (t) = A b1 ·sin(2π(f i -f f )t+φ b1 ),

[0019] Among them, x b1 (t) represents the first beat frequency signal, A b1 represents the amplitude of the first beat frequency signal, f i Indicates the frequency of the fault current signal, f frepresents the frequency of the FM signal, φ b1 represents the initial phase of the first beat frequency signal;

[0020] The expression for extracting the signal feature of the first beat frequency signal by the short-time Fourier transform is:

[0021]

[0022] Among them, x b1 (t) represents the first beat frequency signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency;

[0023] The expression of the first signal characteristic is:

[0024] F1={A b1 ,φ b1 , f b1 , P b1},

[0025] Among them, F1 represents the feature set of the first beat frequency signal, that is, the first signal feature, A b1 represents the amplitude of the first beat frequency signal, φ b1 represents the phase of the first beat frequency signal, f b1 represents the frequency of the first beat signal, P b1 represents the phase difference of the first beat frequency signal;

[0026] The expression for establishing a one-to-one correspondence between the fault type and the first beat frequency signal is:

[0027] M={(T i ,F1)},i=1,2,...,n,

[0028] Among them, T i represents the fault type, and F1 represents the feature set of the first beat frequency signal.

[0029] Furthermore, the step S2 comprises the following steps:

[0030] Step S21: Establishing a simulation model of FTU;

[0031] Step S22: Retrieving the first current signal and the frequency modulation signal, analyzing the first current signal, extracting key control parameters, and obtaining a control signal of the first current signal;

[0032] Step S23: inputting the control signal of the first current signal and the control signal of the frequency modulation signal into the simulation model of the FTU to generate the first current signal and the frequency modulation signal;

[0033] Step S24: Adjust the control parameters of the control signal of the frequency modulation signal, and after obtaining different frequency modulation signals, input them into the simulation model of the FTU in sequence, and collect the first beat frequency signal of the simulation model.

[0034] Step S25: extracting the signal feature of the first beat frequency signal of the simulation model as the third signal feature;

[0035] Step S26: Calculate the similarity between the first signal feature and the third signal feature as the first similarity value of the simulated signal:

[0036] If the first similarity value is less than the first similarity threshold, it indicates that the first signal feature and the third signal feature are not the same signal;

[0037] If the first similarity value is greater than the first similarity threshold, it indicates that the first signal feature and the third signal feature are the same signal, and a fault signal data set is constructed.

[0038] The fault signal data set includes a control parameter of a control signal of a current frequency modulation signal, a control signal of a first current signal, and a fault type and a first beat frequency signal corresponding to the current first current signal.

[0039] Furthermore, the expression of the simulation model of the FTU in step S21 is:

[0040] M FTU :{(i(t), x f (t))→x b1 (t)},

[0041] Among them, M FTU represents the simulation model of FTU, describing the mapping relationship from signal input to beat frequency signal output, i(t) represents the current signal, x f (t) represents the frequency modulated signal, x b1 (t) represents the first beat frequency signal;

[0042] The control signal expression of the first current signal i1(t) in step S22 is:

[0043] C i ={A i ,φ i , f i , P i},

[0044] Among them, C i represents the key control parameter, i.e., the control parameter set of the first current signal i1(t), A i represents the amplitude of the i-th fault signal, φ i represents the phase of the i-th fault signal, f irepresents the frequency of the i-th type fault signal, P i represents the phase difference of the i-th type fault signal, i represents the index of the fault type;

[0045] The expression of the simulation model of inputting the control signal into the FTU in step S23 is:

[0046] M FTU (C i , C f )→{i1(t),x f (t), x b1 (t)},

[0047] Among them, C i represents the control parameter set of the first current signal i1(t), C f represents the frequency modulation signal control parameter, i1(t) represents the first current signal, x f (t) represents the frequency modulated signal, x b1 (t) represents the first beat frequency signal;

[0048] The expression of the control parameter of the control signal of the frequency modulation signal in step S24 is:

[0049] C f ={A f ,φ f ,f f , P f},

[0050] Among them, C f Represents the set of FM signal control parameters, A f represents the amplitude of the FM signal, φf represents the phase of the FM signal, and f f Indicates the frequency of the FM signal, P f Indicates the phase difference of the FM signal;

[0051] The expression of the first beat frequency signal of the simulation model in step S24 is:

[0052]

[0053] in, represents the first beat frequency signal generated after the jth adjustment, M FTU represents the FTU simulation model, C i represents a set of control parameters of the first current signal, represents the set of frequency modulation signal control parameters after the jth adjustment;

[0054] The method for extracting the signal feature of the first beat frequency signal of the simulation model in step S25 is to use short-time Fourier transform to extract the first beat frequency signal of the simulation model. Features:

[0055]

[0056]

[0057] in, represents the first beat frequency signal of the simulation model, w(t-τ) represents the time window function, τ represents the time shift, f represents the frequency, and F3 represents the feature set of the first beat frequency signal generated by the simulation model, that is, the third signal feature. represents the amplitude of the first beat signal generated by the model, represents the phase of the first beat signal generated by the model, represents the frequency of the first beat signal generated by the model, represents the phase difference of the first beat signal generated by the model;

[0058] The expression for calculating the similarity between the first signal feature and the third signal feature in step S26 is:

[0059]

[0060] in, represents the first similarity value of the analog signal, represents the first signal feature, i.e. the real feature, represents the third signal characteristic, namely the analog characteristic, ω j represents the feature weight, and n represents the total dimension of the feature;

[0061] The expression of the fault signal data set in step S26 is:

[0062] Dataset = {(C i , C f , T i , x b1 (t))},

[0063] Among them, C i represents a set of control parameters of the first current signal, C f represents the set of FM signal control parameters, T i Indicates the corresponding fault type, x b1 (t) represents the first beat signal.

[0064] Furthermore, step S3 includes the following steps:

[0065] Step S31: collecting the second current signal of the FTU in real time, and extracting the signal feature of the second current signal by short-time Fourier transform as the fourth signal feature;

[0066] Step S32: extracting a signal feature of the first current signal by short-time Fourier transform as a fifth signal feature;

[0067] Step S33: Calculate the similarity between the fourth signal feature and the fifth signal feature as the second similarity value:

[0068] Step S34: sequentially calculating second similarity values ​​of the fourth signal feature of the second current signal and the fifth signal feature of the first current signal under various fault types;

[0069] Step S35: sort the second similarity values ​​in descending order, and compare the highest second similarity value with the second similarity threshold:

[0070] Step S36: If the highest second similarity value is less than the second similarity threshold, the third signal feature does not match the fifth signal feature;

[0071] Step S37: if the highest second similarity value is greater than the second similarity threshold, the fourth signal feature matches the fifth signal feature successfully, the first current signal corresponding to the fifth signal feature with the highest second similarity value is selected, and the corresponding frequency modulation signal is obtained according to the mapping relationship;

[0072] Step S38: Add the frequency modulation signal to the FTU, and collect the second beat frequency signal of the FTU through the simulation model.

[0073] Furthermore, the expression for extracting the signal feature of the second current signal by short-time Fourier transform in step S31 is:

[0074]

[0075] Wherein, i2(t) represents the second current signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency;

[0076] The expression of the fourth signal characteristic is:

[0077] F4={A4,φ4,f4,P4},

[0078] Wherein, F4 represents a feature set of the second current signal, that is, a fourth signal feature, A4 represents the amplitude of the second current signal, φ4 represents the phase of the second current signal, f4 represents the frequency of the second current signal, and P4 represents the phase difference of the second current signal;

[0079] The expression for extracting the signal feature of the first current signal by short-time Fourier transform in step S32 is:

[0080]

[0081] Wherein, i1(t) represents the first current signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency;

[0082] The expression of the fifth signal characteristic is:

[0083] F5={A5,φ5,f5,P5},

[0084] Wherein, F5 represents a feature set of the first current signal, that is, the fifth signal feature, A5 represents the amplitude of the first current signal, φ5 represents the phase of the first current signal, f5 represents the frequency of the first current signal, and P5 represents the phase difference of the first current signal;

[0085] The expression of the second similarity value in step S33 is:

[0086]

[0087] Wherein, S2 represents the second similarity value, represents the fourth signal characteristic, represents the fifth signal feature, ω j represents the feature weight, and k represents the total dimension of the feature;

[0088] The expression for calculating the second similarity value under various fault types in step S34 is:

[0089]

[0090] in, represents the similarity between the second current signal and the i-th type fault, The fifth signal characteristic of the i-th type fault, ω j represents the feature weight, and k represents the total dimension of the feature.

[0091] Furthermore, the step S38 includes the following steps:

[0092] Step S381: obtaining a control parameter of a control signal of a frequency modulation signal, and inputting the control signal of the frequency modulation signal into the FTU;

[0093] Step S382: Record the position and time when the FM signal is added to the FTU, and collect the second beat frequency signal of the FTU;

[0094] The expression of the frequency modulation signal is:

[0095] x f (t) = A f ·sin(2πf f t+φ f ),

[0096] Among them, xf (t) represents the frequency modulated signal, A f represents the amplitude of the FM signal, φ f represents the phase of the FM signal, f f Indicates the frequency of the FM signal;

[0097] The expression for inputting the control signal of the frequency modulation signal into the FTU is:

[0098] x b2 (t) = M FTU (C4,C f ),

[0099] C4={A4,φ4,f4,P4},

[0100] C f ={A f ,φ f f f , P f},

[0101] Among them, x b2 (t) represents the second beat frequency signal, M FTU represents the FTU simulation model, C4 represents the fourth signal characteristic control parameter, A4 represents the amplitude of the second current signal, φ4 represents the phase of the second current signal, f4 represents the frequency of the second current signal, P4 represents the phase difference of the second current signal, C f Represents the set of FM signal control parameters, A f represents the amplitude of the FM signal, φ f represents the phase of the FM signal, f f Indicates the frequency of the FM signal, P f Indicates the phase difference of the FM signal;

[0102] The second beat frequency signal x b2 The expression of (t) is:

[0103] x b2 (t) = A b2 ·sin(2π(f4-f f )t+φ b2 ),

[0104] Among them, x b2 (t) represents the second beat frequency signal, A b2 Indicates the amplitude of the second beat frequency signal, which is composed of C4 and C f f4 represents the frequency of the second current signal, f f represents the frequency of the FM signal, φ b2 Indicates the phase of the second beat signal.

[0105] Furthermore, the step S4 comprises the following steps:

[0106] Step S41: extracting a signal feature of the second beat frequency signal by short-time Fourier transform as a second signal feature;

[0107] Step S42: Calculate the similarity between the first signal feature and the second signal feature as the first similarity value of the actual collected signal:

[0108] Step S43: If the first similarity value is less than the first similarity threshold, it indicates that the first signal feature and the second signal feature are not the same signal;

[0109] Step S44: If the first similarity value is greater than the first similarity threshold, it indicates that the first signal feature matches the second signal feature successfully;

[0110] Step S45: acquiring the fault type corresponding to the first beat frequency signal according to the corresponding relationship, and outputting the fault type and the fault position corresponding to the fault type.

[0111] Furthermore, the expression for extracting the signal feature of the second beat frequency signal by short-time Fourier transform in step S41 is:

[0112]

[0113] Among them, x b2 (t) represents the second beat frequency signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency;

[0114] The expression of the second signal characteristic is:

[0115] F2={A b2 ,φ b2 , f b2 , P b2},

[0116] Among them, A b2 represents the amplitude of the second beat frequency signal, φ b2 represents the phase of the second beat frequency signal, f b2 represents the frequency of the second beat signal, P b2 represents the phase difference of the second beat frequency signal;

[0117] The calculation formula of the first similarity value of the actual collected signal in step S42 is:

[0118]

[0119] in, Indicates the first similarity value of the actual collected signal, represents the first signal characteristic, represents the second signal feature, ω j represents the feature weight, and n represents the total dimension of the feature;

[0120] In step S45, the expression for obtaining the fault type corresponding to the first beat frequency signal according to the corresponding relationship is:

[0121] M={(T i ,F1,L f )}, i = 1, 2, ..., n,

[0122] Among them, T i Indicates the fault type, F1 indicates the first signal feature, L f Indicates the fault location;

[0123] If the match is successful, the fault type mapping relationship M is output:

[0124] T=T i , L=L f ,

[0125] Wherein, T represents the matching fault type, and L represents the corresponding fault location.

[0126] The beneficial effects of the present invention are:

[0127] 1. Improve fault location accuracy: Through the extraction of beat frequency signal features and the dynamic adjustment of frequency modulation signals, the fault point can be accurately located with a small error, thereby reducing misjudgment or expansion of equipment power outages caused by inaccurate fault location, and shortening the fault repair time;

[0128] 2. Realize intelligent diagnosis of multiple fault types: The present invention can distinguish multiple fault types (such as abnormal telemetry data, abnormal telesignaling data, remote control failure, etc.) and output the corresponding fault location and type. It is suitable for complex power distribution network environments and provides support for intelligent fault diagnosis of power grids.

[0129] 3. Improve signal processing efficiency and robustness: Using short-time Fourier transform to extract signal features can effectively analyze non-stationary signals, avoid modal aliasing and noise interference problems in traditional methods, improve the processing ability of complex signals, maintain high accuracy under low signal-to-noise ratio or complex signal conditions, and enhance the robustness of the diagnostic system;

[0130] 4. Support online monitoring and real-time diagnosis: The present invention realizes online monitoring and real-time diagnosis by real-time acquisition of the second current signal and dynamic calculation of the beat frequency signal characteristics, quickly determines the fault type and location, meets the high requirements of power grid operation on real-time performance and response speed, and reduces the impact of faults on system operation;

[0131] 5. Compatible with multiple fault scenarios: The present invention can adapt to the feature changes in different fault scenarios by establishing a mapping relationship between frequency modulation signals and fault features, and optimize the diagnostic results through multiple adjustments, thereby improving the generalization ability and applicability of the diagnostic system and covering a wider range of power grid application scenarios;

[0132] 6. Provide reliable verification means: The present invention ensures the credibility of fault diagnosis results by comparing and verifying the simulation model with actual data, provides a reliable experimental verification method, supports system debugging and optimization, and improves the engineering feasibility of the solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0133] Figure 1 It is a schematic diagram of the process steps of a method for accurately locating faults within an FTU section based on adaptive variational modal decomposition of the present invention. DETAILED DESCRIPTION

[0134] like Figure 1 As shown, a method for accurately locating faults within a FTU section based on adaptive variational mode decomposition includes the following steps:

[0135] Step S1: obtaining a first beat frequency signal and a first current signal of a fault point of an FTU under various fault types, establishing a one-to-one correspondence between the fault type and the first beat frequency signal, and extracting a signal feature of the first beat frequency signal as a first signal feature;

[0136] Step S2: taking the influence relationship between the first current signal and the frequency modulation signal and the first beat frequency signal as a mapping relationship;

[0137] Step S3: collect the second current signal of the FTU in real time, obtain the corresponding frequency modulation signal according to the mapping relationship, input the frequency modulation signal into the FTU, and collect the second beat frequency signal of the FTU;

[0138] Step S4: extracting the signal feature of the second beat frequency signal as the second signal feature, matching the first signal feature with the second signal feature, obtaining the fault type corresponding to the first beat frequency signal according to the corresponding relationship, and outputting the result;

[0139] The fault types include abnormal telemetry data, abnormal active and reactive data, abnormal remote signaling data of the distribution terminal, failure of remote control of the distribution terminal, and inability of the distribution terminal to connect to the master station.

[0140] Specifically, the telemetry data anomalies include: the telemetry data is zero and the telemetry data does not match the actual situation; the active and reactive data anomalies include: internal wiring errors, such as reverse connection of open and closed positions, wrong connection of energy storage positions, wrong connection of common terminals, wrong connection of remote local positions, etc.; the distribution terminal telesignaling data anomalies include: failure of the switch body and the electric operating mechanism and failure of the terminal internal control circuit.

[0141] Preferably, the step S1 is specifically as follows: simulating the fault current of the FTU under various fault types respectively, and obtaining the first beat frequency signal x of the fault point of the FTU under various fault types respectively. b1 (t) and the first current signal i1(t) and the corresponding fault location L f , the signal characteristics of the first beat frequency signal are extracted by short-time Fourier transform as the first signal characteristics, wherein the first signal characteristics include phase difference, amplitude, phase and frequency, and a one-to-one correspondence between the fault type and the first beat frequency signal is established; the expression of the first current signal i1(t) is:

[0142] i1(t)=A i ·sin(2πf i t+φ i )+n(t),

[0143] Where i1(t) represents the first current signal, A i Indicates the amplitude of the fault current signal, f i Indicates the frequency of the fault current signal, φ i represents the initial phase of the fault current signal, and n(t) represents the noise in the signal;

[0144] The fault location L f Indicates the geographical or circuit location where the fault occurred;

[0145] The expression of the first beat frequency signal is:

[0146] x b1 (t) = A b1 ·sin(2π(f i -f f )t+φ b1 ),

[0147] Among them, x b1 (t) represents the first beat frequency signal, A b1 represents the amplitude of the first beat frequency signal, f i Indicates the frequency of the fault current signal, f f represents the frequency of the FM signal, φ b1 represents the initial phase of the first beat frequency signal;

[0148] The expression for extracting the signal feature of the first beat frequency signal by the short-time Fourier transform is:

[0149]

[0150] Among them, x b1 (t) represents the first beat frequency signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency;

[0151] The expression of the first signal characteristic is:

[0152] F1={A b1 ,φ b1 , f b1 , P b1},

[0153] Among them, F1 represents the feature set of the first beat frequency signal, that is, the first signal feature, A b1 represents the amplitude of the first beat frequency signal, φb1 represents the phase of the first beat frequency signal, fb1 represents the frequency of the first beat frequency signal, P b 1 represents the phase difference of the first beat frequency signal;

[0154] The expression for establishing a one-to-one correspondence between the fault type and the first beat frequency signal is:

[0155] M={(T i ,F1)},i=1,2,...,n,

[0156] Among them, T i represents the fault type, and F1 represents the feature set of the first beat frequency signal.

[0157] Preferably, step S2 comprises the following steps:

[0158] Step S21: Establishing a simulation model of FTU;

[0159] Step S22: Retrieving the first current signal and the frequency modulation signal, analyzing the first current signal, extracting key control parameters, and obtaining a control signal of the first current signal;

[0160] Step S23: inputting the control signal of the first current signal and the control signal of the frequency modulation signal into the simulation model of the FTU to generate the first current signal and the frequency modulation signal;

[0161] Step S24: Adjust the control parameters of the control signal of the frequency modulation signal, and after obtaining different frequency modulation signals, input them into the simulation model of the FTU in sequence, and collect the first beat frequency signal of the simulation model.

[0162] Step S25: extracting the signal feature of the first beat frequency signal of the simulation model as the third signal feature;

[0163] Step S26: Calculate the similarity between the first signal feature and the third signal feature as the first similarity value of the simulated signal:

[0164] If the first similarity value is less than the first similarity threshold, it indicates that the first signal feature and the third signal feature are not the same signal;

[0165] If the first similarity value is greater than the first similarity threshold, it means that the first signal feature and the third signal feature are the same signal, and a fault signal data set is constructed.

[0166] The fault signal data set includes a control parameter of a control signal of a current frequency modulation signal, a control signal of a first current signal, and a fault type and a first beat frequency signal corresponding to the current first current signal.

[0167] More preferably, the expression of the simulation model of the FTU in step S21 is:

[0168] M FTU :{(i(t), x f (t))→x b1 (t)},

[0169] Among them, M FTU represents the simulation model of FTU, describing the mapping relationship from signal input to beat frequency signal output, i(t) represents the current signal, x f (t) represents the frequency modulated signal, x b1 (t) represents the first beat frequency signal;

[0170] The control signal expression of the first current signal i1(t) in step S22 is:

[0171] C i ={A i ,φ i , f i , P i},

[0172] Among them, C i represents the key control parameter, i.e., the control parameter set of the first current signal i1(t), A i represents the amplitude of the i-th fault signal, φ i represents the phase of the i-th fault signal, f i represents the frequency of the i-th type fault signal, P i represents the phase difference of the i-th type fault signal, i represents the index of the fault type;

[0173] The expression of the simulation model of inputting the control signal into the FTU in step S23 is:

[0174] M FTU (C i , C f )→{i1(t),x f (t),x b1 (t)},

[0175] Among them, C i represents the control parameter set of the first current signal i1(t), Cf represents the frequency modulation signal control parameter, i1(t) represents the first current signal, x f (t) represents the frequency modulated signal, x b1 (t) represents the first beat frequency signal;

[0176] The expression of the control parameter of the control signal of the frequency modulation signal in step S24 is:

[0177] C f ={A f ,φ f , f f ,P f},

[0178] Among them, C f Represents the set of FM signal control parameters, A f represents the amplitude of the FM signal, φ f represents the phase of the FM signal, f f Indicates the frequency of the FM signal, P f Indicates the phase difference of the FM signal;

[0179] The expression of the first beat frequency signal of the simulation model in step S24 is:

[0180]

[0181] in, represents the first beat frequency signal generated after the jth adjustment, M FTU represents the FTU simulation model, C i represents a set of control parameters of the first current signal, represents the set of frequency modulation signal control parameters after the jth adjustment;

[0182] The method for extracting the signal feature of the first beat frequency signal of the simulation model in step S25 is to use short-time Fourier transform to extract the first beat frequency signal of the simulation model. Features:

[0183]

[0184] in, represents the first beat frequency signal of the simulation model, w(t-τ) represents the time window function, τ represents the time shift, f represents the frequency, and F3 represents the feature set of the first beat frequency signal generated by the simulation model, that is, the third signal feature. represents the amplitude of the first beat signal generated by the model, represents the phase of the first beat signal generated by the model, represents the frequency of the first beat signal generated by the model, represents the phase difference of the first beat signal generated by the model;

[0185] The expression for calculating the similarity between the first signal feature and the third signal feature in step S26 is:

[0186]

[0187] in, represents the first similarity value of the analog signal, represents the first signal feature, i.e. the real feature, represents the third signal characteristic, namely the analog characteristic, ω j represents the feature weight, and n represents the total dimension of the feature;

[0188] The expression of the fault signal data set in step S26 is:

[0189] Dataset = {(C i , C f ,T i , x b1 (t))},

[0190] Among them, C i represents a set of control parameters of the first current signal, C f represents the set of FM signal control parameters, T i Indicates the corresponding fault type, x b1 (t) represents the first beat signal.

[0191] Preferably, step S3 comprises the following steps:

[0192] Step S31: collecting the second current signal of the FTU in real time, and extracting the signal feature of the second current signal by short-time Fourier transform as the fourth signal feature;

[0193] Step S32: extracting a signal feature of the first current signal by short-time Fourier transform as a fifth signal feature;

[0194] Step S33: Calculate the similarity between the fourth signal feature and the fifth signal feature as the second similarity value:

[0195] Step S34: sequentially calculating second similarity values ​​of the fourth signal feature of the second current signal and the fifth signal feature of the first current signal under various fault types;

[0196] Step S35: sort the second similarity values ​​in descending order, and compare the highest second similarity value with the second similarity threshold:

[0197] Step S36: If the highest second similarity value is less than the second similarity threshold, the third signal feature does not match the fifth signal feature;

[0198] Step S37: if the highest second similarity value is greater than the second similarity threshold, the fourth signal feature matches the fifth signal feature successfully, the first current signal corresponding to the fifth signal feature with the highest second similarity value is selected, and the corresponding frequency modulation signal is obtained according to the mapping relationship;

[0199] Step S38: Add the frequency modulation signal to the FTU, and collect the second beat frequency signal of the FTU through the simulation model.

[0200] More preferably, the expression for extracting the signal feature of the second current signal by short-time Fourier transform in step S31 is:

[0201]

[0202] Wherein, i2(t) represents the second current signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency;

[0203] The expression of the fourth signal characteristic is:

[0204] F4={A4,φ4,f4,P4},

[0205] Wherein, F4 represents a feature set of the second current signal, that is, a fourth signal feature, A4 represents the amplitude of the second current signal, φ4 represents the phase of the second current signal, f4 represents the frequency of the second current signal, and P4 represents the phase difference of the second current signal;

[0206] The expression for extracting the signal feature of the first current signal by short-time Fourier transform in step S32 is:

[0207]

[0208] Wherein, i1(t) represents the first current signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency;

[0209] The expression of the fifth signal characteristic is:

[0210] F5={A5,φ5,f5,P5},

[0211] Wherein, F5 represents a feature set of the first current signal, that is, the fifth signal feature, A5 represents the amplitude of the first current signal, φ5 represents the phase of the first current signal, f5 represents the frequency of the first current signal, and P5 represents the phase difference of the first current signal;

[0212] The expression of the second similarity value in step S33 is:

[0213]

[0214] Wherein, S2 represents the second similarity value, represents the fourth signal characteristic, represents the fifth signal feature, ω j represents the feature weight, and k represents the total dimension of the feature;

[0215] The expression for calculating the second similarity value under various fault types in step S34 is:

[0216]

[0217] in, represents the similarity between the second current signal and the i-th type fault, The fifth signal characteristic of the i-th type fault, ω j represents the feature weight, and k represents the total dimension of the feature.

[0218] More preferably, the step S38 comprises the following steps:

[0219] Step S381: obtaining a control parameter of a control signal of a frequency modulation signal, and inputting the control signal of the frequency modulation signal into the FTU;

[0220] Step S382: Record the position and time when the FM signal is added to the FTU, and collect the second beat frequency signal of the FTU;

[0221] The expression of the frequency modulation signal is:

[0222] x f (t) = A f ·sin(2πf f t+φ f ),

[0223] Among them, x f (t) represents the frequency modulated signal, A f represents the amplitude of the FM signal, φ f represents the phase of the FM signal, f f Indicates the frequency of the FM signal;

[0224] The expression for inputting the control signal of the frequency modulation signal into the FTU is:

[0225] x b2 (t) = M FTU (C4, C f ),

[0226] C4={A4,φ4,f4,P4},

[0227] C f ={A f ,φ f , f f , Pf},

[0228] Among them, x b2 (t) represents the second beat frequency signal, M FTU represents the FTU simulation model, C4 represents the fourth signal characteristic control parameter, A4 represents the amplitude of the second current signal, φ4 represents the phase of the second current signal, f4 represents the frequency of the second current signal, P4 represents the phase difference of the second current signal, C f Represents the set of FM signal control parameters, A f represents the amplitude of the FM signal, φ f represents the phase of the FM signal, f f Indicates the frequency of the FM signal, P f Indicates the phase difference of the FM signal;

[0229] The second beat frequency signal x b2 The expression of (t) is:

[0230] x b2 (t) = A b2 ·sin(2π(f4-f f )t+φ b2 ),

[0231] Among them, x b2 (t) represents the second beat frequency signal, A b2 Indicates the amplitude of the second beat frequency signal, which is composed of C4 and C f f4 represents the frequency of the second current signal, f f represents the frequency of the FM signal, φ b2 Indicates the phase of the second beat signal.

[0232] Preferably, step S4 comprises the following steps:

[0233] Step S41: extracting a signal feature of the second beat frequency signal by short-time Fourier transform as a second signal feature;

[0234] Step S42: Calculate the similarity between the first signal feature and the second signal feature as the first similarity value of the actual collected signal:

[0235] Step S43: If the first similarity value is less than the first similarity threshold, it indicates that the first signal feature and the second signal feature are not the same signal;

[0236] Step S44: If the first similarity value is greater than the first similarity threshold, it indicates that the first signal feature matches the second signal feature successfully;

[0237] Step S45: acquiring the fault type corresponding to the first beat frequency signal according to the corresponding relationship, and outputting the fault type and the fault position corresponding to the fault type.

[0238] More preferably, the expression for extracting the signal feature of the second beat frequency signal by short-time Fourier transform in step S41 is:

[0239]

[0240] Among them, x b2 (t) represents the second beat frequency signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency;

[0241] The expression of the second signal characteristic is:

[0242] F2={A b2 ,φ b2 , f b2 , P b2},

[0243] Among them, A b2 represents the amplitude of the second beat frequency signal, φ b2 represents the phase of the second beat frequency signal, f b2 represents the frequency of the second beat signal, P b2 represents the phase difference of the second beat frequency signal;

[0244] The calculation formula of the first similarity value of the actual collected signal in step S42 is:

[0245]

[0246] in, Indicates the first similarity value of the actual collected signal, represents the first signal characteristic, represents the second signal feature, ω j represents the feature weight, and n represents the total dimension of the feature;

[0247] In step S45, the expression for obtaining the fault type corresponding to the first beat frequency signal according to the corresponding relationship is:

[0248] M={(T i ,F1,L f )}, i = 1, 2, ..., n,

[0249] Among them, T i Indicates the fault type, F1 indicates the first signal feature, L f Indicates the fault location;

[0250] If the match is successful, the fault type mapping relationship M is output:

[0251] T=T i , L=L f ,

[0252] Wherein, T represents the matching fault type, and L represents the corresponding fault location.

[0253] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for accurately locating faults within a FTU section based on adaptive variational mode decomposition, characterized in that: The following steps are involved: Step S1: obtaining a first beat frequency signal and a first current signal of a fault point of an FTU under various fault types, establishing a one-to-one correspondence between the fault type and the first beat frequency signal, and extracting a signal feature of the first beat frequency signal as a first signal feature; Step S2: taking the influence relationship between the first current signal and the frequency modulation signal and the first beat frequency signal as a mapping relationship; Step S3: collect the second current signal of the FTU in real time, obtain the corresponding frequency modulation signal according to the mapping relationship, input the frequency modulation signal into the FTU, and collect the second beat frequency signal of the FTU; Step S4: extracting the signal feature of the second beat frequency signal as the second signal feature, matching the first signal feature with the second signal feature, obtaining the fault type corresponding to the first beat frequency signal according to the corresponding relationship, and outputting the result; The fault types include abnormal telemetry data, abnormal active and reactive data, abnormal remote signaling data of the distribution terminal, failure of remote control of the distribution terminal, and inability of the distribution terminal to connect to the master station.

2. According to claim 1, a method for accurately locating faults within a FTU section based on adaptive variational mode decomposition is characterized in that: The step S1 specifically includes: simulating the fault current of the FTU under various fault types respectively, and obtaining the first beat frequency signal x of the fault point of the FTU under various fault types respectively. b1 (t) and the first current signal i1(t) and the corresponding fault location L f , the signal characteristics of the first beat frequency signal are extracted by short-time Fourier transform as the first signal characteristics, wherein the first signal characteristics include phase difference, amplitude, phase and frequency, and a one-to-one correspondence between the fault type and the first beat frequency signal is established; the expression of the first current signal i1(t) is: i1(t)=A i ·sin(2πf i t+φ i )+n(t), Where i1(t) represents the first current signal, A i Indicates the amplitude of the fault current signal, f i Indicates the frequency of the fault current signal, φ i represents the initial phase of the fault current signal, and n(t) represents the noise in the signal; The fault location L f Indicates the geographical or circuit location where the fault occurred; The expression of the first beat frequency signal is: x b1 (t)=A b1 ·sin(2π(f i -f f )t+φ b1 ), Among them, x b1 (t) represents the first beat frequency signal, A b1 represents the amplitude of the first beat frequency signal, f i Indicates the frequency of the fault current signal, f f represents the frequency of the FM signal, φ b1 represents the initial phase of the first beat frequency signal; The expression for extracting the signal feature of the first beat frequency signal by the short-time Fourier transform is: Among them, x b1 (t) represents the first beat frequency signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency; The expression of the first signal characteristic is: F1={A b1 ,φ b1 ,f b1 ,P b1 }, Among them, F1 represents the feature set of the first beat frequency signal, that is, the first signal feature, A b1 represents the amplitude of the first beat frequency signal, φ b1 represents the phase of the first beat frequency signal, f b1 represents the frequency of the first beat signal, P b1 represents the phase difference of the first beat frequency signal; The expression for establishing a one-to-one correspondence between the fault type and the first beat frequency signal is: M={(T i ,F1)},i=1,2,...,n, Among them, T i represents the fault type, and F1 represents the feature set of the first beat frequency signal.

3. The method for accurately locating faults within a FTU section based on adaptive variational mode decomposition according to claim 1 is characterized in that: The step S2 comprises the following steps: Step S21: Establishing a simulation model of FTU; Step S22: Retrieving the first current signal and the frequency modulation signal, analyzing the first current signal, extracting key control parameters, and obtaining a control signal of the first current signal; Step S23: inputting the control signal of the first current signal and the control signal of the frequency modulation signal into the simulation model of the FTU to generate the first current signal and the frequency modulation signal; Step S24: Adjust the control parameters of the control signal of the frequency modulation signal, and after obtaining different frequency modulation signals, input them into the simulation model of the FTU in sequence, and collect the first beat frequency signal of the simulation model. Step S25: extracting the signal feature of the first beat frequency signal of the simulation model as the third signal feature; Step S26: Calculate the similarity between the first signal feature and the third signal feature as the first similarity value of the simulated signal: If the first similarity value is less than the first similarity threshold, it indicates that the first signal feature and the third signal feature are not the same signal; If the first similarity value is greater than the first similarity threshold, it indicates that the first signal feature and the third signal feature are the same signal, and a fault signal data set is constructed. The fault signal data set includes a control parameter of a control signal of a current frequency modulation signal, a control signal of a first current signal, and a fault type and a first beat frequency signal corresponding to the current first current signal.

4. The method for accurately locating faults within a FTU section based on adaptive variational mode decomposition according to claim 3 is characterized in that: The expression of the simulation model of the FTU in step S21 is: M F T U :{(i(t),x f (t))→x b1 (t)}, Among them, M FTU represents the simulation model of FTU, describing the mapping relationship from signal input to beat frequency signal output, i(t) represents the current signal, x f (t) represents the frequency modulated signal, x b1 (t) represents the first beat frequency signal; The control signal expression of the first current signal i1(t) in step S22 is: C i ={A i ,φ i ,f i ,P i }, Among them, C i represents the key control parameter, i.e., the control parameter set of the first current signal i1(t), A i represents the amplitude of the i-th fault signal, φ i represents the phase of the i-th fault signal, f i represents the frequency of the i-th type fault signal, P i represents the phase difference of the i-th type fault signal, i represents the index of the fault type; The expression of the simulation model of inputting the control signal into the FTU in step S23 is: M FTU (C i ,C f )→{i1(t),x f (t),x b1 (t)}, Among them, C i represents the control parameter set of the first current signal i1(t), C f represents the frequency modulation signal control parameter, i1(t) represents the first current signal, x f (t) represents the frequency modulated signal, x b1 (t) represents the first beat frequency signal; The expression of the control parameter of the control signal of the frequency modulation signal in step S24 is: C f ={A f ,φ f ,f f ,P f }, Among them, C f Represents the set of frequency modulation signal control parameters, A f represents the amplitude of the FM signal, φ f represents the phase of the FM signal, f f Indicates the frequency of the FM signal, P f Indicates the phase difference of the FM signal; The expression of the first beat frequency signal of the simulation model in step S24 is: in, represents the first beat frequency signal generated after the jth adjustment, M FTU represents the FTU simulation model, C i represents a set of control parameters of the first current signal, represents the set of frequency modulation signal control parameters after the jth adjustment; The method for extracting the signal feature of the first beat frequency signal of the simulation model in step S25 is to use short-time Fourier transform to extract the first beat frequency signal of the simulation model. Features: in, represents the first beat frequency signal of the simulation model, w(t-τ) represents the time window function, τ represents the time shift, f represents the frequency, and F3 represents the feature set of the first beat frequency signal generated by the simulation model, that is, the third signal feature. represents the amplitude of the first beat signal generated by the model, represents the phase of the first beat signal generated by the model, represents the frequency of the first beat signal generated by the model, represents the phase difference of the first beat signal generated by the model; The expression for calculating the similarity between the first signal feature and the third signal feature in step S26 is: in, represents the first similarity value of the analog signal, represents the first signal feature, i.e. the real feature, represents the third signal characteristic, namely the analog characteristic, ω j represents the feature weight, and n represents the total dimension of the feature; The expression of the fault signal data set in step S26 is: Dataset={(C i ,C f ,T i ,x b1 (t))}, Among them, C i represents a set of control parameters of the first current signal, C f represents the set of FM signal control parameters, T i Indicates the corresponding fault type, x b1 (t) represents the first beat signal.

5. The method for accurately locating faults within a FTU section based on adaptive variational mode decomposition according to claim 1 is characterized in that: The step S3 comprises the following steps: Step S31: collecting the second current signal of the FTU in real time, and extracting the signal feature of the second current signal by short-time Fourier transform as the fourth signal feature; Step S32: extracting a signal feature of the first current signal by short-time Fourier transform as a fifth signal feature; Step S33: Calculate the similarity between the fourth signal feature and the fifth signal feature as the second similarity value: Step S34: sequentially calculating second similarity values ​​of the fourth signal feature of the second current signal and the fifth signal feature of the first current signal under various fault types; Step S35: sort the second similarity values ​​in descending order, and compare the highest second similarity value with the second similarity threshold: Step S36: If the highest second similarity value is less than the second similarity threshold, the third signal feature does not match the fifth signal feature; Step S37: if the highest second similarity value is greater than the second similarity threshold, the fourth signal feature matches the fifth signal feature successfully, the first current signal corresponding to the fifth signal feature with the highest second similarity value is selected, and the corresponding frequency modulation signal is obtained according to the mapping relationship; Step S38: Add the frequency modulation signal to the FTU, and collect the second beat frequency signal of the FTU through the simulation model.

6. The method for accurately locating faults within a FTU section based on adaptive variational mode decomposition according to claim 5 is characterized in that: The expression for extracting the signal feature of the second current signal by short-time Fourier transform in step S31 is: Wherein, i2(t) represents the second current signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency; The expression of the fourth signal characteristic is: F4={A4,φ4,f4,P4}, Wherein, F4 represents a feature set of the second current signal, that is, a fourth signal feature, A4 represents the amplitude of the second current signal, φ4 represents the phase of the second current signal, f4 represents the frequency of the second current signal, and P4 represents the phase difference of the second current signal; The expression for extracting the signal feature of the first current signal by short-time Fourier transform in step S32 is: Wherein, i1(t) represents the first current signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency; The expression of the fifth signal characteristic is: F5={A5,φ5,f5,P5}, Wherein, F5 represents a feature set of the first current signal, that is, the fifth signal feature, A5 represents the amplitude of the first current signal, φ5 represents the phase of the first current signal, f5 represents the frequency of the first current signal, and P5 represents the phase difference of the first current signal; The expression of the second similarity value in step S33 is: Wherein, S2 represents the second similarity value, represents the fourth signal characteristic, represents the fifth signal feature, ω j represents the feature weight, and k represents the total dimension of the feature; The expression for calculating the second similarity value under various fault types in step S34 is: in, represents the similarity between the second current signal and the i-th type fault, The fifth signal characteristic of the i-th type fault, ω j represents the feature weight, and k represents the total dimension of the feature.

7. The method for accurately locating faults within a FTU section based on adaptive variational mode decomposition according to claim 5 is characterized in that: The step S38 comprises the following steps: Step S381: obtaining a control parameter of a control signal of a frequency modulation signal, and inputting the control signal of the frequency modulation signal into the FTU; Step S382: Record the position and time when the FM signal is added to the FTU, and collect the second beat frequency signal of the FTU; The expression of the frequency modulation signal is: x f (t)=A f ·sin(2πf f t+φ f ), Among them, x f (t) represents the frequency modulated signal, A f represents the amplitude of the FM signal, φ f represents the phase of the FM signal, f f Indicates the frequency of the FM signal; The expression for inputting the control signal of the frequency modulation signal into the FTU is: x b2 (t)=M FTU (C4,C f ), C4={A4,φ4,f4,P4}, C f ={A f ,φ f ,f f ,P f }, Among them, x b2 (t) represents the second beat frequency signal, M FTU represents the FTU simulation model, C4 represents the fourth signal characteristic control parameter, A4 represents the amplitude of the second current signal, φ4 represents the phase of the second current signal, f4 represents the frequency of the second current signal, P4 represents the phase difference of the second current signal, C f Represents the set of frequency modulation signal control parameters, A f represents the amplitude of the FM signal, φ f represents the phase of the FM signal, f f Indicates the frequency of the FM signal, P f Indicates the phase difference of the FM signal; The second beat frequency signal x b2 The expression of (t) is: x b2 (t)=A b2 ·sin(2π(f4-f f )t+φ b2 ), Among them, x b2 (t) represents the second beat frequency signal, A b2 Indicates the amplitude of the second beat frequency signal, which is composed of C4 and C f f4 represents the frequency of the second current signal, f f represents the frequency of the FM signal, φ b2 Indicates the phase of the second beat signal.

8. The method for accurately locating faults within a FTU section based on adaptive variational mode decomposition according to claim 1 is characterized in that: The step S4 comprises the following steps: Step S41: extracting a signal feature of the second beat frequency signal by short-time Fourier transform as a second signal feature; Step S42: Calculate the similarity between the first signal feature and the second signal feature as the first similarity value of the actual collected signal: Step S43: If the first similarity value is less than the first similarity threshold, it indicates that the first signal feature and the second signal feature are not the same signal; Step S44: If the first similarity value is greater than the first similarity threshold, it indicates that the first signal feature matches the second signal feature successfully; Step S45: acquiring the fault type corresponding to the first beat frequency signal according to the corresponding relationship, and outputting the fault type and the fault position corresponding to the fault type.

9. The method for accurately locating faults within a FTU section based on adaptive variational mode decomposition according to claim 8, characterized in that: The expression for extracting the signal feature of the second beat frequency signal by short-time Fourier transform in step S41 is: Among them, x b2 (t) represents the second beat frequency signal, w(t-τ) represents the time window function, τ represents the time shift, and f represents the frequency; The expression of the second signal characteristic is: F2={A b2 ,φ b2 ,f b2 ,P b2 }, Among them, A b2 represents the amplitude of the second beat frequency signal, φ b2 represents the phase of the second beat frequency signal, f b2 represents the frequency of the second beat signal, P b2 represents the phase difference of the second beat frequency signal; The calculation formula of the first similarity value of the actual collected signal in step S42 is: in, Indicates the first similarity value of the actual collected signal, represents the first signal characteristic, represents the second signal feature, ω j represents the feature weight, and n represents the total dimension of the feature; In step S45, the expression for obtaining the fault type corresponding to the first beat frequency signal according to the corresponding relationship is: M={(T i ,F1,L f )},i=1,2,...,n, Among them, T i Indicates the fault type, F1 indicates the first signal feature, L f Indicates the fault location; If the match is successful, the fault type mapping relationship M is output: T=T i ,L=L f , Wherein, T represents the matching fault type, and L represents the corresponding fault location.

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