A cable fault point midpoint traveling wave ranging online positioning system based on current magnetic signal and parameter optimization variational modal decomposition

Abstract

The application discloses a cable fault point midpoint traveling wave ranging online positioning system based on current magnetic signal and parameter optimization variational modal decomposition, which comprises a perception layer, a transmission layer, a platform layer and an application layer, and the structure comprises a current magnetic signal sending end, a current magnetic signal receiving end and a man-machine interaction end. Main components include a power cable to be detected, a current magnetic signal extraction sensor, an analog signal program-controlled amplifier, an A / D converter, a microprocessor, a 4G communication module, a Web client server, a numerical calculation server and a customer display terminal. The application relates to the technical field of power cable fault ranging. By using the application, power supply is not required to be stopped, normal production is not affected, a non-contact current magnetic signal extraction sensor is used to measure current data in the cable at the first end, the midpoint and the end of the three-phase cable (mainly using midpoint data for calculation, and the first end and the end are used for auxiliary measurement to prevent excessive noise or other factors from interfering), parameter optimization variational modal decomposition is used in the numerical calculation server to calibrate a traveling wave head, the midpoint traveling wave method is used for calculation to obtain fault point position information, and man-machine interaction can be performed.

Description

Technical Field

[0001] This invention relates to the field of power cable fault location, specifically to an online positioning system for midpoint traveling wave location of cable faults based on current magnetostrictive signals and parameter-optimized variational mode decomposition. Background Technology

[0002] As power networks age, the probability of faults increases, making timely fault location crucial. This not only accelerates repair time but also speeds up subsequent operations. Addressing the shortcomings of current diagnostic methods in power cable fault location, such as incomplete detection and the need for power outages, this paper proposes an online fault location system based on midpoint traveling wave ranging using current magnetostrictive signals and parameter-optimized variational mode decomposition. This method employs midpoint traveling wave ranging, using a non-contact current magnetostrictive signal extraction sensor to extract the power cable current signal. After phase-mode transformation, the traveling wave component is obtained. Parameter-optimized variational mode decomposition is then used to acquire wavefront data, thereby calculating the fault location and transmitting the information to the user.

[0003] The traditional distance measurement method for power cables is as follows:

[0004] Single-ended ranging method: The single-ended ranging method extracts the fault electrical quantities at only one end of the line, calibrates the time when the initial fault traveling wave arrives at the measuring end and the time when the reflected wave arrives at that end, and substitutes them into the single-ended ranging formula to determine the fault location.

[0005] Two-end ranging method: The two-end ranging method extracts the fault electrical quantities at the beginning and end of the line, calibrates the arrival time of the initial fault traveling wave at the beginning and end, and substitutes them into the two-end ranging formula to determine the fault location.

[0006] The problem with both methods is that the traveling wave velocity needs to be obtained in advance for calculation, but the line parameters are greatly affected by the environment, and the traveling wave velocity will also be affected as a result.

[0007] Traditional methods for calibrating traveling wavefronts include wavelet transform and Hilbert-Huang transform. However, current methods such as wavelet transform and empirical mode decomposition (EMD) suffer from significant ranging errors and may even fail. To address these issues and apply the ranging method to practical measurements, this paper proposes an online traveling wave ranging system for cable fault midpoints based on current magnetostrictive signals and parameter-optimized variational mode decomposition. Summary of the Invention

[0008] (a) Technical problems to be solved

[0009] To address the shortcomings of existing technologies, this invention provides an online positioning system for traveling wave ranging at the midpoint of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition. This system solves the problems of inaccurate wave velocity leading to excessive measurement errors and inaccurate traveling wave head calibration leading to excessive calculation errors in commonly used ranging methods in the field of power cable ranging.

[0010] (II) Technical Solution

[0011] To achieve the above objectives, this invention provides the following technical solution: An online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition includes a sensing layer, a transmission layer, a platform layer, and an application layer. The structure includes a current magnetostrictive signal transmitter, a current magnetostrictive signal receiver, and a human-machine interface. The main components include the power cable to be detected, a current magnetostrictive signal extraction sensor, an analog signal programmable amplifier, an A / D converter, a microprocessor, a 4G communication module, a web client server, a numerical calculation server, and a client display terminal.

[0012] The output terminals of the current magnetostrictive signal extraction sensors in the current magnetostrictive signal transmitting end are all electrically connected to the input terminals of the analog signal programmable amplifier via wires. The output terminals of the analog signal programmable amplifier are electrically connected to the output terminals of the A / D converter via wires, and the output terminals of the A / D converter are electrically connected to the input terminals of the microprocessor via wires. The microprocessor transmits the current magnetostrictive signal to the current magnetostrictive signal receiving layer via a 4G communication module. After preprocessing by a denoising program, the current magnetostrictive signal enters the numerical calculation server for fault distance calculation. The numerical calculation server transmits fault location information to the human-machine interaction layer via a 4G communication module. The Web client server in the human-machine interaction layer is connected via a network client display terminal.

[0013] Preferably, the current magnetostrictive signal extraction sensor is connected to the three phases of the power cable, and the three signals are respectively from the three phases A, B and C of the power cable.

[0014] Preferably, the signal collected by the current magnetostrictive signal sensor is sent to the analog signal programmable amplifier, and the output signal of the analog signal programmable amplifier is sent to the A / D converter.

[0015] Preferably, the digital signal output by the A / D converter is sent to the microprocessor, and the data preprocessed by the microprocessor is wirelessly transmitted to the magnetocurrent signal receiving end via the 4G communication module.

[0016] Preferably, the preprocessed current magnetostrictive signal data is sent to the numerical calculation server for fault distance calculation after a denoising process.

[0017] Preferably, the fault location information output by the numerical calculation server is wirelessly transmitted to the Web client server of the human-computer interaction terminal via a 4G communication module.

[0018] Preferably, customers can obtain cable fault location information and handling suggestions simply by accessing the Web client server through the customer display terminal, thereby carrying out maintenance operations.

[0019] Preferably, the current magnetostrictive signal extraction sensor is used to extract the current magnetostrictive signals of the three phases A, B, and C of the power cable, and the sensing layer is used for the acquisition and analysis of the current magnetostrictive signals.

[0020] Preferably, the transmission layer is used to transmit signal data to the Web server, the Web server organizes the data and sends it to the cable fault distance numerical calculation server, and the platform layer is used to perform calculation and analysis on the data from the Web server using the variational mode decomposition cable fault midpoint traveling wave ranging algorithm, and send the results back to the Web server.

[0021] Preferably, the application layer is used to display the diagnostic results on the user terminal via a web server.

[0022] Preferably, the three-phase current and voltage signals at both ends are coupled to each other, and decoupling is achieved using a newly proposed phase mode transformation matrix, which is as follows:

[0023]

[0024] The formula for calculating phase mode transformation is as follows:

[0025]

[0026] Among them, u a ,u b ,u c i a i b i c The fault voltage and current traveling waves on phases A, B, and C are respectively, u0, u α ,u β ,i0,i α i β These are the 0-mode, α-mode, and β-mode components of the voltage and current traveling waves, respectively.

[0027] Preferably, the location of power cable faults is classified:

[0028] A fault occurred on MO, and a fault occurred on ON;

[0029] In this context, MO represents the left side of the power cable, and ON represents the right side of the power cable.

[0030] Preferably, the speed calculation formula is as follows:

[0031]

[0032] The formula for calculating fault distance is:

[0033]

[0034] Where t1 is the moment when the traveling wave first passes through the midpoint, t2 is the moment when the traveling wave first passes through the midpoint after being reflected by the bus M, and t3 is the moment when the traveling wave first passes through the midpoint after being reflected by the bus N.

[0035] Preferably, the cable fault distance numerical calculation server uses variational mode decomposition optimized by the Uyghur optimization algorithm to decompose the traveling wave characteristics, uses the Teager-Kaiser energy operator for wavefront calibration, and uses the obtained time data for fault location.

[0036] (III) Beneficial Effects

[0037] This paper presents an online fault location system based on current magnetostrictive signal and parameter-optimized variational mode decomposition for midpoint traveling wave ranging of cable faults. Compared with existing technologies, it offers the following advantages: The system comprises a sensing layer, a transmission layer, a platform layer, and an application layer. The structure includes a current magnetostrictive signal transmitter, a current magnetostrictive signal receiver, and a human-machine interface. Key components include the power cable to be detected, a current magnetostrictive signal extraction sensor, an analog signal programmable amplifier, an A / D converter, a microprocessor, a 4G communication module, a web client server, a numerical calculation server, and a client display terminal. By using this invention, power interruption is unnecessary, eliminating the influence of wave velocity on traveling wave ranging, resulting in more accurate wavefront calibration. A non-contact current magnetostrictive signal extraction sensor is used to measure the current data in the cable at the beginning, midpoint, and end (primarily using midpoint data for calculation; the beginning and end are used for auxiliary measurements to prevent excessive noise or other interference). The fault location information is then obtained after calculation. Attached Figure Description

[0038] Figure 1 This is a block diagram illustrating the system structure principle of the present invention.

[0039] Figure 2 for Figure 2 This is a block diagram illustrating the structural principles of the sensing layer, transmission layer, platform layer, and application layer of the present invention.

[0040] Figure 3 , Figure 4 Schematic diagram of the midpoint traveling wave method

[0041] Figure 5 Flowchart of variational mode decomposition algorithm optimized for the Black-crowned Tern Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Please see Figure 1-5 This invention provides a technical solution: an online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition.

[0044] The system comprises a sensing layer, a transmission layer, a platform layer, and an application layer. The structure includes a current magnetostrictive signal transmitter, a current magnetostrictive signal receiver, and a human-machine interface. Key components include the power cable to be detected, a current magnetostrictive signal extraction sensor, an analog signal programmable amplifier, an A / D converter, a microprocessor, a 4G communication module, a web client server, a numerical calculation server, and a client display terminal.

[0045] In this embodiment of the invention, the output terminals of the current magnetostrictive signal extraction sensors in the current magnetostrictive signal transmitting end are electrically connected to the input terminals of the analog signal programmable amplifier via wires. The output terminals of the analog signal programmable amplifier are electrically connected to the output terminals of the A / D converter via wires, and the output terminals of the A / D converter are electrically connected to the input terminals of the microprocessor via wires. The microprocessor transmits the current magnetostrictive signal to the current magnetostrictive signal receiving layer via a 4G communication module. After preprocessing by a denoising program, the current magnetostrictive signal enters the numerical calculation server for fault distance calculation. The numerical calculation server transmits fault location information to the human-machine interaction layer via a 4G communication module. The Web client server in the human-machine interaction layer is connected via a network client display terminal.

[0046] In this embodiment of the invention, the signal collected by the current magnetostrictive signal sensor is sent to an analog signal programmable amplifier, and the output signal of the analog signal programmable amplifier is sent to an A / D converter. The digital signal output by the A / D converter is sent to a microprocessor, and the data, after preprocessing by the microprocessor, is wirelessly transmitted to the current magnetostrictive signal receiving end via a 4G communication module. The preprocessed current magnetostrictive signal data is then sent to a numerical calculation server for fault distance calculation after a noise reduction process. The fault location information output by the numerical calculation server is wirelessly transmitted to the Web client server of the human-machine interface via the 4G communication module. The customer only needs to access the Web client server through the customer display terminal to obtain cable fault location information and handling suggestions, thereby performing maintenance operations.

[0047] In this embodiment of the invention, a current magnetostrictive signal extraction sensor is used to extract the current magnetostrictive signals of the three phases A, B, and C of the power cable, and the sensing layer is used for the acquisition and analysis of the current magnetostrictive signals. The transmission layer is used to transmit the signal data to a web server, which then processes the data and sends it to a cable fault distance numerical calculation server. The platform layer is used to perform calculations and analyses on the data from the web server using a variational mode decomposition-based traveling wave ranging algorithm for cable fault midpoints, and sends the results back to the web server. The application layer is used to display the diagnostic results on the user terminal via the web server.

[0048] In this embodiment of the invention, the three-phase current and voltage signals at both ends are coupled to each other, and decoupling is achieved using a newly proposed phase mode transformation matrix, which is as follows:

[0049]

[0050] The formula for calculating phase mode transformation is as follows:

[0051]

[0052] Among them, u a ,u b ,u c i a i b i c The fault voltage and current traveling waves on phases A, B, and C are respectively, u0, u α ,u β ,i0,i α i β These are the 0-mode, α-mode, and β-mode components of the voltage and current traveling waves, respectively.

[0053] In this embodiment of the invention, the location of power cable faults is classified as follows: faults occur on MO and faults occur on ON.

[0054] In this context, MO represents the left side of the power cable, and ON represents the right side of the power cable.

[0055] The formula for calculating speed is:

[0056]

[0057] The formula for calculating fault distance is:

[0058]

[0059] Where t1 is the moment when the traveling wave first passes through the midpoint, t2 is the moment when the traveling wave first passes through the midpoint after being reflected by the bus M, and t3 is the moment when the traveling wave first passes through the midpoint after being reflected by the bus N.

[0060] In this embodiment of the invention, the cable fault distance numerical calculation server uses variational mode decomposition optimized by the tern optimization algorithm to decompose the traveling wave characteristics, uses the Teager-Kaiser energy operator to calibrate the wavefront, and uses the obtained time data to locate the fault.

[0061] In summary, by using this invention, power outages are not required, online monitoring is possible, normal production is not affected, the influence of wave velocity on traveling wave ranging is eliminated, and wavefront calibration is more accurate. This method obtains traveling wavefront data by extracting and processing the power cable current signal, and uses the midpoint traveling wave method to solve the ranging error problem caused by inaccurate wave velocity in traditional traveling wave ranging methods. Furthermore, parameter optimization variational mode decomposition makes wavefront calibration more accurate.

[0062] Furthermore, any content not described in detail herein is prior art known to those skilled in the art. It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0063] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition, characterized in that: The system comprises a perception layer, a transmission layer, a platform layer, and an application layer. It includes a current magnetostrictive signal transmitter, a current magnetostrictive signal receiver, and a human-machine interface. The components include the power cable to be tested, a non-contact current magnetostrictive signal extraction sensor, an analog signal programmable amplifier, an A / D converter, a microprocessor, a 4G communication module, a web client server, a numerical calculation server, and a client display terminal; The output terminals of the current magnetostrictive signal extraction sensors in the current magnetostrictive signal transmitting end are electrically connected to the input terminals of the analog signal programmable amplifiers via wires. The output terminals of the analog signal programmable amplifiers are electrically connected to the output terminals of the A / D converters via wires, and the output terminals of the A / D converters are electrically connected to the input terminals of the microprocessors via wires. The microprocessors transmit the current magnetostrictive signals to the current magnetostrictive signal receiving layer via a 4G communication module. After preprocessing by a denoising program, the current magnetostrictive signals enter the numerical calculation server, where variational mode decomposition is optimized using the U-Tern optimization algorithm, and wavefront calibration is performed using the Teager-Kaiser energy operator. Based on the midpoint traveling wave method, the traveling wave velocity is calculated online at three times (t1, t2, and t3) using the midpoint traveling wave method. The numerical calculation server transmits fault location information to the human-machine interaction layer via a 4G communication module. The Web client server in the human-machine interaction terminal is connected via a network client display terminal. The three-phase current and voltage signals at both ends are coupled to each other, and decoupling is achieved using a phase-mode transformation matrix, which is as follows: ， The cable fault distance numerical calculation server uses variational mode decomposition optimized by the Uyghur optimization algorithm to decompose the traveling wave characteristics, uses the Teager-Kaiser energy operator for wavefront calibration, and uses the obtained time data for fault location.

2. The online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition according to claim 1, characterized in that: The current magnetostrictive signal extraction sensor is connected to the three phases of the power cable, and the three signals are respectively from the three phases A, B and C of the power cable.

3. The online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition according to claim 2, characterized in that: The signal collected by the current magnetostrictive signal sensor is sent to the analog signal programmable amplifier, and the output signal of the analog signal programmable amplifier is sent to the A / D converter.

4. The online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition according to claim 3, characterized in that: The digital signal output by the A / D converter is sent to the microprocessor, and the data preprocessed by the microprocessor is wirelessly transmitted to the magnetocurrent signal receiving end through the 4G communication module. The preprocessed current magnetostrictive signal data is sent to the numerical calculation server for fault distance calculation after a noise reduction process. The fault location information output by the numerical calculation server is wirelessly transmitted to the Web client server of the human-computer interaction terminal via a 4G communication module.

5. The online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition according to claim 4, characterized in that: Customers can obtain cable fault location information and handling suggestions by simply accessing the Web client server through the customer display terminal, thereby enabling them to perform maintenance operations.

6. The online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition according to claim 1, characterized in that: The current magnetostrictive signal extraction sensor is used to extract the current magnetostrictive signals of the three phases A, B, and C of the power cable, and the sensing layer is used for the acquisition and analysis of the current magnetostrictive signals.

7. The online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition according to claim 1, characterized in that: The transmission layer is used to transmit signal data to the Web server. The Web server organizes the data and sends it to the cable fault distance numerical calculation server. The platform layer is used to perform calculation and analysis on the data from the Web server using the variational mode decomposition cable fault midpoint traveling wave ranging algorithm, and sends the results back to the Web server.

8. The online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition according to claim 1, characterized in that: The application layer is used to display the diagnostic results on the user terminal via a web server.

9. The online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition according to claim 1, characterized in that: The formula for calculating phase mode transformation is as follows: ， Among them, u a ,u b ,u c i a i b i c The fault voltage and current traveling waves on phases A, B, and C are respectively, u0, u α ,u β ,i0,i α i β These are the 0-mode, α-mode, and β-mode components of the voltage and current traveling waves, respectively.

10. The online positioning system for midpoint traveling wave ranging of cable fault points based on current magnetostrictive signals and parameter-optimized variational mode decomposition according to claim 1, characterized in that: Classify the location of power cable faults: A fault occurred on MO, and a fault occurred on ON; Where MO represents the left side of the power cable and ON represents the right side of the power cable; The formula for calculating speed is: ， The formula for calculating fault distance is: ， Where t1 is the moment when the traveling wave first passes through the midpoint, t2 is the moment when the traveling wave first passes through the midpoint after being reflected by the bus M, and t3 is the moment when the traveling wave first passes through the midpoint after being reflected by the bus N.

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