High-voltage cable fault accurate positioning and data backtracking system

Abstract

The invention relates to the technical field of power system equipment detection, and particularly discloses a high-voltage cable fault accurate positioning and data backtracking system, which comprises a front-end acquisition module for acquiring signal data information in a time period based on multiple types of sensors of key nodes on a deployed cable line; the signal processing module is used for receiving the signal data information sent by the front-end acquisition module and carrying out signal processing; the data storage and analysis module is used for acquiring the fault type and the fault point sent by the signal processing module for management analysis, calculating a cable health index through a characteristic evolution trend, and predicting a future fault trend based on historical data and a machine learning model; and the communication and display module is used for carrying out fault early warning, sending fault information to a display port and carrying out prompting, so that the reliability and the precision of fault detection are remarkably improved, and the problem of positioning errors caused by noise interference of a traditional single sensor in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system equipment detection, and in particular to a high-voltage cable fault precise positioning and data backtracking system. Background Art

[0002] The current high-voltage cable fault location technology has the following shortcomings:

[0003] 1. The positioning accuracy of the traveling wave method and pulse reflection method is limited by signal attenuation and noise interference.

[0004] 2. The existing system lacks the ability to comprehensively analyze real-time fault data and historical fault records, and is unable to efficiently utilize data for predictive maintenance.

[0005] 3. Most data acquisition devices are single-function modules and lack multi-sensor collaborative detection capabilities, resulting in poor applicability.

[0006] To solve the above problems, the present invention proposes a cable fault location system integrating multiple sensors based on the existing technology, and introduces improved algorithms in the signal processing and data analysis modules to achieve improved accuracy. Summary of the Invention

[0007] The purpose of the present invention is to provide a high-voltage cable fault accurate positioning and data backtracking system to solve the above-mentioned problems.

[0008] The purpose of the present invention can be achieved through the following technical solutions:

[0009] High-voltage cable fault precise location and data backtracking system, front-end acquisition module: Based on multiple types of sensors at key nodes deployed on the cable line, signal data information within time period t is acquired;

[0010] Signal processing module: used to receive the signal data information sent by the front-end acquisition module and perform signal processing;

[0011] Data storage and analysis module: used to obtain the fault type and fault point sent by the signal processing module for management and analysis, calculate the cable health index based on the characteristic evolution trend, and predict future fault trends based on historical data and machine learning models;

[0012] Communication and display module: used for fault early warning, sending fault information, i.e. fault distance D, to the display port and providing prompts.

[0013] As a further solution of the present invention: the multi-type sensors include a voltage sensor, a current sensor, a vibration sensor and a temperature sensor;

[0014] The working method of the front-end acquisition module includes:

[0015] The voltage sensor and current sensor are used to collect the power frequency voltage signal and current signal, namely the voltage waveform signal V(t) and the current waveform signal I(t);

[0016] The vibration wave signal a(t) generated during the discharge process is sensed and acquired through the vibration sensor;

[0017] The temperature time series data T(t) of the cable is obtained by intermittently collecting data through the temperature sensor.

[0018] As a further solution of the present invention: the signal processing module includes a signal preprocessing unit, a feature extraction unit and a fault location unit.

[0019] As a further solution of the present invention: the signal preprocessing unit is used to perform denoising on the signal data information obtained by multiple types of sensors, using wavelet transform to perform multi-scale decomposition combined with an adaptive filtering algorithm to eliminate background power frequency interference and high-frequency noise;

[0020] That is, the voltage waveform signal V(t), current waveform signal I(t), vibration wave signal a(t) and temperature time series data T(t) acquired by the front-end acquisition module are respectively input into the multi-scale decomposition combined with the adaptive filtering algorithm to calculate and obtain the hierarchical filtered signals, including the filtered voltage signal V'(t), the filtered current signal I'(t), the filtered vibration wave signal a'(t) and the filtered temperature data T'(t).

[0021] As a further solution of the present invention: the multi-scale decomposition combined with the adaptive filtering algorithm is:

[0022]

[0023] Where, x(n): signal data information;

[0024] y(n): decomposed filtered signal;

[0025] w k (n): adaptive weight coefficient;

[0026] M: filter order.

[0027] As a further solution of the present invention: the feature extraction unit is used to extract features from the hierarchically filtered signals to obtain feature time points;

[0028] Including: extracting features from the filtered voltage signal, including;

[0029] Derivate the filtered voltage signal V'(t) and obtain a value greater than the jump value Y v time point;

[0030] Find At this time, the first time point is the emission time point t0 of the jump, and the second time point is the reflection time point t V .

[0031] As a further solution of the present invention: the feature extraction unit is used to extract features from the hierarchically filtered signals to obtain feature time points;

[0032] Also included: feature extraction of the filtered current signal, including:

[0033] B01: Perform first-order differentiation on the filtered current signal to enhance the wave head, i.e.

[0034] B02: The time point at which the enhanced filtered current signal wave begins is obtained, recorded as the starting time point t e ; Then obtain the enhanced filtered current signal greater than the strong wave threshold Y I All time point values ​​of , and take the minimum time point value as the terminal time point t f ;

[0035] Right now:

[0036] As a further solution of the present invention: the feature extraction unit is used to extract features from the hierarchically filtered signals to obtain feature time points;

[0037] Also included: feature extraction of filtered vibration wave signals on the cable, including:

[0038] C01: Hilbert envelope extraction of filtered vibration wave signal:

[0039] A xeb (t)=|Η(a'(t))|

[0040] Where H is the Hilbert transform;

[0041] C02: Obtain the first time point where the filtered vibration wave signal is greater than the filter transformation threshold Y after Hilbert transformation, and record it as the impact time point t a .

[0042] As a further solution of the present invention: the fault location unit performs fault location based on the feature time points extracted from the features and the filtered temperature data;

[0043] include:

[0044] 001: Based on the emission time t0 and the reflection time t V To locate the voltage point, Get the voltage positioning point distance dV , that is, the distance from the fault point to the transmission point; where v(T) is the temperature-corrected wave velocity;

[0045] 002: Based on the starting time point t e and terminal time point t f Locate the current point by Get the current positioning point distance d I , where v(T) is the temperature-corrected wave velocity;

[0046] 003: By setting up multiple vibration sensors, obtain the impact time point t obtained by two adjacent sensors when the vibration wave propagates in two directions when the fault occurs a1 and t a2 ;

[0047] pass Calculate the vibration positioning point d A ;

[0048] Where Q is the distance between two adjacent vibration sensors; v A is the propagation speed of the vibration wave in the cable;

[0049] 004: Then through D = λ V ×d V +λ I ×d I +λ A ×d A Calculate the fault distance D; where λ V ,λ I and λ A are weight coefficients respectively, and λ V ,λ I and λ A are both greater than 0 and less than 1, λ V +λ I +λ A =1.

[0050] As a further solution of the present invention: the temperature correction wave velocity, v(T) = v0×[1+ω(T-T0)], wherein v0 is the reference wave velocity of 160m / μs; ω is the correction coefficient, which is about 10 -3 / ℃; T0 is the reference ambient temperature; T is the current cable temperature.

[0051] Beneficial effects of the present invention:

[0052] In the present invention, by using voltage, current, vibration and temperature sensors to obtain multi-dimensional data, filtering, amplifying and efficiently extracting fault features from the collected signals, and combining high-frequency noise filtering and fast pulse reflection signal analysis algorithms, the reliability and accuracy of fault detection are significantly improved, overcoming the positioning error problem caused by noise interference of traditional single sensors in the existing technology.

[0053] In addition, the remote communication module and data storage module can be expanded as needed to improve practicality. Through intelligent analysis of historical data, cable health status reports can be generated to provide fault warnings. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The present invention will be further described below with reference to the accompanying drawings.

[0055] Figure 1 It is a system block diagram of the present invention;

[0056] Figure 2 It is a schematic diagram of the workflow of the signal processing module in the present invention. DETAILED DESCRIPTION

[0057] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0058] See also Figure 1 and Figure 2 As shown, the present invention is a high-voltage cable fault accurate positioning and data backtracking system, comprising:

[0059] Front-end acquisition module:

[0060] Signal data information within a time period t is acquired based on multiple types of sensors at key nodes on the deployed cable line; wherein the multiple types of sensors include voltage sensors, current sensors, vibration sensors, and temperature sensors. Specifically:

[0061] The voltage sensor and current sensor are used to collect the power frequency voltage signal and current signal, namely the voltage waveform signal V(t) and the current waveform signal I(t);

[0062] The vibration wave signal a(t) generated during the discharge process is sensed and acquired through the vibration sensor;

[0063] The temperature time series data T(t) of the cable is obtained by intermittently collecting data through the temperature sensor;

[0064] It should be noted that multiple types of sensors use a synchronization mechanism to achieve time alignment of data and ensure the accuracy of signal data information fusion;

[0065] Then the front-end acquisition module sends the signal data information to the signal processing module;

[0066] Signal processing module:

[0067] The signal processing module includes a signal preprocessing unit, a feature extraction unit and a fault location unit; it is used to receive the signal data information sent by the front-end acquisition module and perform signal processing;

[0068] Specifically:

[0069] The signal preprocessing unit performs denoising on the signal data information obtained by multiple types of sensors, using wavelet transform for multi-scale decomposition combined with adaptive filtering algorithm to eliminate background power frequency interference and high-frequency noise;

[0070] The multi-scale decomposition combined with the adaptive filtering algorithm is:

[0071] Where, x(n): signal data information;

[0072] y(n): decomposed filtered signal;

[0073] w k (n): adaptive weight coefficient;

[0074] M: filter order;

[0075] That is, the voltage waveform signal V(t), current waveform signal I(t), vibration wave signal a(t) and temperature time series data T(t) acquired by the front-end acquisition module are respectively fed into a multi-scale decomposition combined with an adaptive filtering algorithm to calculate and obtain hierarchical filtered signals, including filtered voltage signal V'(t), filtered current signal I'(t), filtered vibration wave signal a'(t) and filtered temperature data T'(t); and the hierarchical filtered signals are sent to a feature extraction unit;

[0076] The feature extraction unit extracts features from the hierarchically filtered signals to obtain feature time points;

[0077] include:

[0078] A: Extract the characteristics of the filtered voltage signal. During the transmission process, if a fault point occurs, the fault point will reflect the voltage signal, causing a jump at that point. Then, find the reflection time point t in the filtered voltage signal waveform. V ;

[0079] Derivate the filtered voltage signal V'(t) and obtain a value greater than the jump value Yv time point;

[0080] Find At this time, the first time point is the emission time point t0 of the jump, and the second time point is the reflection time point t V ;

[0081] B: Extract features from the filtered current signal. During the transmission process, if a fault occurs, the current traveling wave propagates along both ends of the cable, generating a wave head at the sensor. Therefore, the steps for extracting features from the filtered current signal include:

[0082] B01: Perform first-order differentiation on the filtered current signal to enhance the wave head, i.e.

[0083] B02: The time point at which the enhanced filtered current signal wave begins is obtained, recorded as the starting time point t e ; Then obtain the enhanced filtered current signal greater than the strong wave threshold Y I All time point values ​​of , and take the minimum time point value as the terminal time point t f ;

[0084] Right now:

[0085] C: Extract the features of the filtered vibration wave signal on the cable. If the cable is internally discharged or broken down to generate mechanical vibration, the mechanical vibration wave is a high-frequency short-time signal. The steps for extracting the filtered vibration wave signal are as follows:

[0086] C01: Hilbert envelope extraction of filtered vibration wave signal:

[0087] A xeb (t)=|Η(a'(t))|

[0088] Where H is the Hilbert transform;

[0089] C02: Obtain the first time point where the filtered vibration wave signal is greater than the filter transformation threshold Y after Hilbert transformation, and record it as the impact time point t a ;

[0090] The fault location unit performs fault location based on the feature time points extracted from the features and the filtered temperature data;

[0091] include:

[0092] 001: Based on the emission time t0 and the reflection time t V To locate the voltage point, Get the voltage positioning point distance d V, that is, the distance from the fault point to the transmission point; where v(T) is the temperature-corrected wave velocity, v(T) = v0 × [1 + ω(T-T0)], where v0 is the reference wave velocity of 160 m / μs; ω is the correction coefficient, which is approximately 10 -3 / ℃; T0 is the reference ambient temperature; T is the current cable temperature;

[0093] 002: Based on the starting time point t e and terminal time point t f Locate the current point by Get the current positioning point distance d I , where v(T) is the temperature-corrected wave velocity;

[0094] 003: By setting up multiple vibration sensors, obtain the impact time point t obtained by two adjacent sensors when the vibration wave propagates in two directions when the fault occurs a1 and t a2 ;

[0095] pass Calculate the vibration positioning point d A ;

[0096] Where Q is the distance between two adjacent vibration sensors; v A is the propagation speed of the vibration wave in the cable;

[0097] 004: Then through D = λ V ×d V +λ I ×d I +λ A ×d A Calculate the fault distance D; where λ V ,λ I and λ A are weight coefficients respectively, and λ V ,λ I and λ A are both greater than 0 and less than 1, λ V +λ I +λ A =1; the weight coefficient is set by those skilled in the art and is adjusted based on signal strength and confidence;

[0098] Data storage and analysis module:

[0099] It is used to obtain the fault type and fault point sent by the signal processing module for management analysis, calculate the cable health index based on the characteristic evolution trend, and predict future fault trends based on historical data and machine learning models;

[0100] Communication and display module:

[0101] It is used for fault early warning, sending fault information, i.e. fault distance D, to the display port and giving prompts.

[0102] By using voltage, current, vibration and temperature sensors to obtain multi-dimensional data, filtering, amplifying and efficiently extracting fault features from the collected signals, and combining high-frequency noise filtering and fast pulse reflection signal analysis algorithms, the reliability and accuracy of fault detection are significantly improved, overcoming the positioning error problem caused by noise interference from traditional single sensors in existing technologies.

[0103] In addition, the remote communication module and data storage module can be expanded as needed to improve practicality. Through intelligent analysis of historical data, cable health status reports can be generated to provide fault warnings.

[0104] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. High-voltage cable fault precise location and data backtracking system, characterized by: include: Front-end acquisition module: acquires signal data information within a time period t based on multiple types of sensors at key nodes on the deployed cable lines; Signal processing module: used to receive the signal data information sent by the front-end acquisition module and perform signal processing; Data storage and analysis module: used to obtain the fault type and fault point sent by the signal processing module for management and analysis, calculate the cable health index based on the characteristic evolution trend, and predict future fault trends based on historical data and machine learning models; Communication and display module: used for fault warning, sending fault information to the display port and providing prompts.

2. The high-voltage cable fault precise location and data backtracking system according to claim 1 is characterized in that: The multi-type sensors include voltage sensors, current sensors, vibration sensors and temperature sensors; The working method of the front-end acquisition module includes: The voltage sensor and current sensor are used to collect the power frequency voltage signal and current signal, namely the voltage waveform signal V(t) and the current waveform signal I(t); The vibration wave signal a(t) generated during the discharge process is sensed and acquired through the vibration sensor; The temperature time series data T(t) of the cable is obtained by intermittently collecting data through the temperature sensor.

3. The high-voltage cable fault precise location and data backtracking system according to claim 2 is characterized in that: The signal processing module includes a signal preprocessing unit, a feature extraction unit and a fault location unit.

4. The high-voltage cable fault precise location and data backtracking system according to claim 3 is characterized in that: The signal preprocessing unit is used to perform denoising on the signal data information obtained by multiple types of sensors, using wavelet transform to perform multi-scale decomposition combined with an adaptive filtering algorithm to eliminate background power frequency interference and high-frequency noise; That is, the voltage waveform signal V(t), current waveform signal I(t), vibration wave signal a(t) and temperature time series data T(t) acquired by the front-end acquisition module are respectively introduced into the multi-scale decomposition combined with the adaptive filtering algorithm to calculate the hierarchical filtered signals, including the filtered voltage signal V ’ (t), filtered current signal I ’ (t), filtered vibration wave signal a ’ (t) and filtered temperature data T ’ (t).

5. The high-voltage cable fault precise location and data backtracking system according to claim 4 is characterized in that: The multi-scale decomposition combined with the adaptive filtering algorithm is: Where, x(n): signal data information; y(n): decomposed filtered signal; w k (n): adaptive weight coefficient; M: filter order.

6. The high-voltage cable fault precise location and data backtracking system according to claim 3 is characterized in that: The feature extraction unit is used to extract features from the hierarchically filtered signals to obtain feature time points; Including: extracting features from the filtered voltage signal, including; The filtered voltage signal V ’ (t) Take the derivative and obtain a value greater than the jump value Y v time point; Find At this time, the first time point is the emission time point t0 of the jump, and the second time point is the reflection time point t V .

7. The high-voltage cable fault precise location and data backtracking system according to claim 6 is characterized in that: The feature extraction unit is used to extract features from the hierarchically filtered signals to obtain feature time points; Also included: feature extraction of the filtered current signal, including: B01: Perform first-order differentiation on the filtered current signal to enhance the wave head, i.e. B02: The time point at which the enhanced filtered current signal wave begins is obtained, recorded as the starting time point t e ; Then obtain the enhanced filtered current signal greater than the strong wave threshold Y I All time point values ​​of , and take the minimum time point value as the terminal time point t f ; Right now:

8. The high-voltage cable fault precise location and data tracing system according to claim 7 is characterized in that: The feature extraction unit is used to extract features from the hierarchically filtered signals to obtain feature time points; Also included: feature extraction of filtered vibration wave signals on the cable, including: C01: Hilbert envelope extraction of filtered vibration wave signal: A xeb (t)=|Η(a’(t))| Where H is the Hilbert transform; C02: Obtain the first time point where the filtered vibration wave signal is greater than the filter transformation threshold Y after Hilbert transformation, and record it as the impact time point t a .

9. The high-voltage cable fault precise location and data backtracking system according to claim 8 is characterized in that: The fault location unit performs fault location based on the feature time points extracted by the features and the filtered temperature data; include: 001: Based on the emission time t0 and the reflection time t V To locate the voltage point, Get the voltage positioning point distance d V , that is, the distance from the fault point to the transmission point; where v(T) is the temperature-corrected wave velocity; 002: Based on the starting time point t e and terminal time point t f Locate the current point by Get the current positioning point distance d I , where v(T) is the temperature-corrected wave velocity; 003: By setting up multiple vibration sensors, obtain the impact time point t obtained by two adjacent sensors when the vibration wave propagates in two directions when the fault occurs a1 and t a2 ; pass Calculate the vibration positioning point d A ; Where Q is the distance between two adjacent vibration sensors; v A is the propagation speed of the vibration wave in the cable; 004: Then through D = λ V ×d V +λ I ×d I +λ A ×d A Calculate the fault distance D; where λ V ,λ I and λ A are weight coefficients respectively, and λ V ,λ I and λ A are both greater than 0 and less than 1, λ V +λ I +λ A =1.

10. The high-voltage cable fault precise location and data tracing system according to claim 9, characterized in that: The temperature-corrected wave velocity is v(T)=v0×[1+ω(T-T0)], where v0 is the reference wave velocity of 160 m / μs; ω is the correction coefficient, which is approximately 10 -3 / ℃; T0 is the reference ambient temperature; T is the current cable temperature.

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