Oil-immersed transformer internal discharge defect identification method and system based on multiple signals

Abstract

The invention discloses a method and a system for identifying internal discharge of an oil-immersed transformer based on multiple signals. The method comprises the following steps: firstly, when a transformer runs, collecting analog signals output by a high-frequency pulse current sensor, an ultrahigh-frequency sensor and an acoustic sensor which are mounted at a transformer body, and secondly, sequentially counting timestamps and signal maximum values when the pulse current signals are higher than a starting threshold; the ultrahigh frequency signal is higher than the timestamp and the signal maximum value of the starting threshold, and the acoustic signal is higher than the timestamp and the signal maximum value of the starting threshold, then judging whether the signal maximum amplitude of the pulse current and the ultrahigh frequency signal is higher than the discharge threshold and meets the signal synchronism, and finally, judging whether the signal maximum amplitude of the pulse current and the ultrahigh frequency signal is higher than the discharge threshold and meets the signal synchronism. And judging whether the maximum amplitude of the acoustic signal is higher than the discharge threshold and meets the acoustoelectric delay synchronism or not. According to the invention, the discharge defect in the oil-immersed transformer can be identified, and the method has good anti-external interference performance.

Description

Technical Field

[0001] This invention belongs to the field of internal discharge identification technology for oil-immersed power equipment, specifically relating to a method for identifying internal discharge defects in oil-immersed transformers based on multi-signal synchronization.

[0002] Background Information Oil-immersed transformers are important power equipment in the transmission and conversion of electrical energy. If a discharge defect occurs inside the transformer and is not detected in time, it may quickly develop into an arc breakdown fault, causing the oil tank to crack due to a large amount of gas production or even causing a deflagration accident. Therefore, it is necessary to identify discharge defects inside the oil tank by using some discharge characterization parameters and take certain protective measures during partial discharge to prevent it from developing into an arc breakdown fault.

[0003] Pulse current, ultra-high frequency, and acoustic signals are all common partial discharge monitoring signals. However, due to interference from external discharges, a single signal may lead to misjudgment. By observing whether multiple signals appear synchronously and whether the time interval between their appearances conforms to the pattern of internal discharge, the influence of interference can be effectively eliminated, ensuring the reliability of internal defect identification.

[0004] CN120511621A discloses an active protection method and system for oil-immersed transformers based on pulse current characteristics. The method determines whether active protection is activated based on whether the instantaneous value of the pulse current signal at the core grounding point reaches the protection activation threshold; it determines whether the current pulse cluster is an internal discharge abnormality pulse cluster based on the characteristics of three sets of pulse current signals; and it determines whether the protection operates based on the number of abnormal discharge pulse clusters within a set period. However, this scheme, which simply sets a threshold for amplitude to determine internal discharge faults, suffers from insufficient reliability. In actual engineering sites, especially in converter stations, the background noise of pulsating current signals is high, making the detection effect using a single signal unsatisfactory.

[0005] CN117872068A discloses a method and system for identifying severe discharge defects inside oil-immersed equipment. During equipment operation, it collects digital pulse current signals output by high-frequency pulse current sensors installed at the oil tank grounding wire and / or the bushing end screen grounding wire. The signal energy and the number of pulses contained are used to determine whether high-energy cluster discharge has occurred. The presence of a severe discharge defect inside the oil tank is determined based on whether the number of high-energy cluster discharges within a set time exceeds a preset threshold. However, this method only considers changes in signal energy to determine severity, ignoring the large pulse current signals caused by external interference signals during actual operation. Therefore, this method is prone to misjudgment due to large external discharges, resulting in insufficient accuracy. Summary of the Invention

[0006] To address the problems existing in the prior art, the purpose of this invention is to provide a method for identifying internal discharge defects in oil-immersed transformers with multi-signal synchronization. This method can reliably identify internal discharges in the oil tank using pulse current, ultra-high frequency signals, and acoustic signals, providing a reference for condition monitoring and active protection of oil-immersed transformers.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows: The first aspect of this invention discloses a method for identifying internal discharge defects in an oil-immersed transformer based on multiple signals, comprising the following steps: Step 1: The program starts running, and the pulse current signal is above the first start threshold timestamp. and the maximum value of the pulse current signal The timestamp of the UHF signal exceeding the second startup threshold and the maximum value of ultra-high frequency signals The timestamp when the acoustic signal exceeds the third start-up threshold and maximum acoustic signal value Assigning a value of 0 to an intermediate variable n The value is assigned to 0; Step 2: Real-time acquisition of pulse current signals during transformer operation UHF signals Acoustic signals ,in t This is the time difference between the current moment and the start moment of the program; Step 3: Based on the real-time acquired transformer pulse current signal UHF signals Acoustic signals Determine the maximum value of the pulse current signal and timestamp UHF signal maximum value and timestamp , and maximum acoustic signal and timestamp ; Step 4: Comparison With the first action threshold ,Compare With the second action threshold ,Compare and The absolute value of the time difference and the fourth time threshold ,if and and Then the intermediate variable n If the value is 1, proceed to step 5; otherwise, proceed to step 6. Step 5: Compare the current time. tand Time difference and the fourth time threshold ,if Then the intermediate variable n If the value is assigned to 0, proceed to step 6; otherwise, proceed directly to step 6. Step 6: Comparison With the third action threshold ,Compare and Time difference and the fifth time threshold ,if and and If the result is positive, it is considered that an internal discharge defect has occurred, and the program ends; otherwise, return to step 2.

[0008] More preferably, In step 3, compare the current time. t and Time difference and first time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. The absolute value and the first starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to .

[0009] More preferably, First time threshold Values ​​range from 10 to 200 µs; First Start-up Threshold ,in, k For reliability coefficient, This represents the maximum absolute value of the noise floor of the pulse current signal when there is no discharge.

[0010] More preferably, In step 3, compare the current time. t and Time difference and second time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. The absolute value and the second starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to .

[0011] More preferably, Second time threshold Values ​​range from 1 to 10 µs; Second Start-up Threshold In the formula, k For reliability coefficient, This represents the maximum absolute value of the UHF signal noise floor when there is no discharge.

[0012] More preferably, In step 3, compare the current time. t and Time difference and third time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. The absolute value and the third starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to .

[0013] More preferably, The third time threshold Value ranges from 3 to 10 ms; The third start threshold In the formula, k For reliability coefficient, This represents the maximum absolute value of the acoustic signal noise floor when there is no discharge.

[0014] More preferably, Reliability coefficient k The value is 2.

[0015] More preferably, In step 4, the first action threshold Second action threshold The calculation method for is as follows:

[0016]

[0017] Fourth Time Threshold Values ​​range from 1 to 50 µs; In the formula, m The reliability coefficient ranges from 10 to 20. This represents the maximum absolute value of the noise floor of the pulse current signal when there is no discharge. This represents the maximum absolute value of the UHF signal noise floor when there is no discharge.

[0018] More preferably, In step 6, the third action threshold In the formula, m The reliability coefficient ranges from 10 to 20. This represents the maximum absolute value of the acoustic signal noise floor when there is no discharge.

[0019] More preferably, The fifth time threshold The calculation method is as follows:

[0020] In the formula, x This is the maximum distance from a point inside the transformer tank to the location where the acoustic sensor is placed. v The equivalent speed of sound in the fuel tank; p This is the reliability coefficient.

[0021] More preferably, v The value ranges from 1.3 to 5 m / ms; p The value range is 0.5 to 1.

[0022] The second aspect of the present invention discloses a multi-signal-based internal discharge defect identification system for oil-immersed transformers based on the identification method, including an initial assignment module, a multi-signal real-time acquisition module, a multi-signal maximum value and timestamp calculation module, and an internal defect fault judgment module. The initial assignment module sets the timestamp of the pulse current signal exceeding the first startup threshold when the program starts running. and the maximum value of the pulse current signal The timestamp of the UHF signal exceeding the second startup threshold and the maximum value of ultra-high frequency signals The timestamp when the acoustic signal exceeds the third start-up threshold and maximum acoustic signal value Assigning a value of 0 to an intermediate variable n The value is assigned to 0; The real-time signal acquisition module acquires the transformer pulse current signal in real time during transformer operation. UHF signals Acoustic signals ,in t This is the time difference between the current moment and the start moment of the program; The multi-signal maximum value and timestamp calculation module is based on the real-time acquired transformer pulse current signal. UHF signals Acoustic signals Determine the maximum value of the pulse current signal and timestamp UHF signal maximum value and timestamp , and maximum acoustic signal and timestamp ; The internal defect fault diagnosis module is based on the maximum value of the pulse current signal. and timestamp UHF signal maximum value and timestamp , and maximum acoustic signal and timestamp Determine whether the transformer has an internal discharge defect.

[0023] A third aspect of the present invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory; characterized in that: the processor executes the computer program to implement the steps of the method for identifying internal discharge defects in an oil-immersed transformer based on multiple signals.

[0024] The fourth aspect of the present invention discloses a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of the method for identifying internal discharge defects in an oil-immersed transformer based on multiple signals.

[0025] The present invention has the following beneficial technical effects compared with the prior art: A single partial discharge signal may be misjudged due to interference conditions. For example, when the circuit is closed under no-load conditions, the interference amplitude of the pulse current signal is high. When the circuit is operated under on-load conditions, the interference amplitude of the ultra-high frequency signal or pulse current signal is high. When an external short circuit generates a through current, the interference amplitude of the acoustic signal is high. This invention uses the characteristics of three parameters to make a comprehensive judgment, which can effectively solve the problem of misjudgment caused by interference conditions and increase reliability. Attached Figure Description

[0026] Figure 1 This is a flowchart of the method for identifying internal discharge defects in oil-immersed transformers based on multiple signals according to an embodiment of the present invention; Figure 2 It is a time-domain waveform diagram of the multi-parameter signal during internal discharge; Figure 3 This is the time-domain waveform diagram of a multi-parameter signal under external interference. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0028] This invention discloses a method for identifying internal discharge defects in oil-immersed transformers based on multiple signals, comprising the following steps: Step 1: The program starts running, and the pulse current signal is above the first start threshold timestamp. and the maximum value of the pulse current signal The timestamp of the UHF signal exceeding the second startup threshold and the maximum value of ultra-high frequency signals The timestamp when the acoustic signal exceeds the third start-up threshold and maximum acoustic signal value Assigning a value of 0 to an intermediate variable n The value is assigned to 0; Step 2: Real-time acquisition of pulse current signals during transformer operation UHF signals Acoustic signals ,in t This is the time difference between the current moment and the start moment of the program; During transformer operation, analog signals from high-frequency pulse current sensors, ultra-high-frequency sensors, and acoustic sensors installed on the transformer body are acquired by a signal acquisition device to obtain digital pulse current signals. UHF signal Acoustic signals .

[0029] In this invention, the high-frequency pulse current signal refers to a frequency range of 3M-30MHz, the ultra-high frequency sensor signal frequency range is 300M-1.5GHz, and the acoustic signal frequency range is 10-250kHz.

[0030] Step 3: Based on the real-time acquired transformer pulse current signal UHF signals Acoustic signals Determine the maximum value of the pulse current signal and timestamp UHF signal maximum value and timestamp , and maximum acoustic signal and timestamp ; Compare the current time t and Time difference and first time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. The absolute value and the first starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to ; Compare the current time t and Time difference and second time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. The absolute value and the second starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to ; Compare the current time t and Time difference and third time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. The absolute value and the third starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to ; In a preferred embodiment of the present invention, the first to third activation thresholds , , The calculation method is as follows:

[0031]

[0032]

[0033] In the formula, k The reliability coefficient is set to 2. This represents the maximum absolute value of the noise floor of the pulse current signal when there is no discharge. This represents the maximum absolute value of the noise floor of the ultra-high frequency signal when there is no discharge. This represents the maximum absolute value of the acoustic signal noise floor when there is no discharge.

[0034] Step 4: Comparison With the first action threshold ,Compare With the second action threshold ,Compare and The absolute value of the time difference and the fourth time threshold ,if and and Then the intermediate variable n If the value is 1, proceed to step 5; otherwise, proceed to step 6. Step 5: Compare the current time. t and Time difference and the fourth time threshold ,if Then the intermediate variable n If the value is assigned to 0, proceed to step 6; otherwise, proceed directly to step 6. Step 6: Comparison With the third action threshold ,Compare and Time difference and the fifth time threshold ,if and and If the result is positive, it is considered that an internal discharge defect has occurred, and the program ends; otherwise, return to step 2.

[0035] In a preferred embodiment of the present invention, the first to fifth time thresholds , , , , The value can be obtained in the following ways: The value is determined based on experimental experience regarding the duration of the pulse current signal excited by a single discharge, and is typically between 10 and 200 μs. The value is selected based on experimental experience regarding the duration of the ultra-high frequency signal excited by a single discharge, ranging from 1 to 10 μs. The value is determined based on experimental experience regarding the duration of the acoustic signal excited by a single discharge, and is typically between 3 and 10 ms. The reference value is set to the synchronization capability of the acquisition device in acquiring pulse current signals and ultra-high frequency signals, ranging from 1 to 50 µs. The calculation method is as follows:

[0036] In the formula, x This is the maximum distance from a point inside the transformer tank to the location where the acoustic sensor is placed. v The equivalent velocity of sound in the fuel tank is taken as 1.3~5 m / ms; p The reliability coefficient ranges from 0.5 to 1.

[0037] This application also discloses a multi-signal-based internal discharge defect identification system for oil-immersed transformers based on the identification method, including an initial assignment module, a multi-signal real-time acquisition module, a multi-signal maximum value and timestamp calculation module, and an internal defect fault judgment module. The initial assignment module sets the timestamp of the pulse current signal exceeding the first startup threshold when the program starts running. and the maximum value of the pulse current signal The timestamp of the UHF signal exceeding the second startup threshold and the maximum value of ultra-high frequency signals The timestamp when the acoustic signal exceeds the third start-up threshold and maximum acoustic signal value Assigning a value of 0 to an intermediate variable n The value is assigned to 0; The real-time signal acquisition module acquires the transformer pulse current signal in real time during transformer operation. UHF signals Acoustic signals ,int This is the time difference between the current moment and the start moment of the program; The multi-signal maximum value and timestamp calculation module is based on the real-time acquired transformer pulse current signal. UHF signals Acoustic signals Determine the maximum value of the pulse current signal and timestamp UHF signal maximum value and timestamp , and maximum acoustic signal and timestamp ; The internal defect fault diagnosis module is based on the maximum value of the pulse current signal. and timestamp UHF signal maximum value and timestamp , and maximum acoustic signal and timestamp Determine whether the transformer has an internal discharge defect.

[0038] And a computer device, including a memory, a processor, and a computer program stored in the memory; characterized in that: the processor executes the computer program to implement the steps of the multi-signal-based oil-immersed transformer internal discharge defect identification method.

[0039] A computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the multi-signal-based oil-immersed transformer internal discharge defect identification method.

[0040] This invention requires acquiring analog signals from a high-frequency pulse current sensor, an ultra-high-frequency sensor, and an acoustic sensor installed on the transformer body during transformer operation, to obtain digital pulse current signals. UHF signal Acoustic signals Secondly, the timestamps when the pulse current signal exceeds the start-up threshold are counted sequentially. and signal maximum value The UHF signal exceeds the start-up threshold timestamp and signal maximum value The timestamp of the acoustic signal exceeding the start-up threshold and signal maximum value Then, determine whether the maximum amplitude of the pulse current and the ultra-high frequency signal exceeds the discharge threshold and whether the signal synchronization is satisfied. Finally, determine whether the maximum amplitude of the acoustic signal exceeds the discharge threshold and whether the acoustic-electric delay synchronization is satisfied to determine whether an internal discharge defect has occurred. If an internal discharge defect has occurred, protective measures need to be taken in time.

[0041] Example 1: As Figure 1 As shown, this embodiment of the method for identifying internal discharge defects in oil-immersed transformers based on multi-signal synchronization includes the following steps: Step 1: The program starts running, and the pulse current signal is above the start threshold timestamp. and signal maximum value The timestamp of the ultra-high frequency signal exceeding the start-up threshold and signal maximum value The timestamp when the acoustic signal exceeds the start-up threshold and signal maximum value Assigning a value of 0 to an intermediate variable n The value is assigned to 0; Step 2: During transformer operation, the signal acquisition device collects the analog signals output by the high-frequency pulse current sensor, ultra-high frequency sensor, and acoustic sensor installed on the transformer body to obtain digital pulse current signals. UHF signal Acoustic signals ,in t This is the time difference between the current moment and the start moment of the program; Step 3: Compare the current time. t and Time difference and time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. absolute value and starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to ; Step 4: Compare the current time. t and Time difference and time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. absolute value and starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to ; Step 5: Compare the current time. t and Time difference and time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. absolute value and starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to ; Step 6: Comparison Action threshold ,Compare Action threshold ,Compare and The absolute value of the time difference and the time threshold ,if and and Then the intermediate variable n Set the value to 1; otherwise proceed to step 8. Step 7: Comparison t and Time difference and time threshold ,if Then the intermediate variable n If the value is set to 0, otherwise proceed to step 8; Step 8: Comparison Action threshold ,Compare and Time difference and time threshold ,if and and If the result is positive, it is considered that an internal discharge defect has occurred, and the program ends; otherwise, return to step 2.

[0042] The value is 50us. The value is 10us. Take 5ms. The value is 20us. The value is 5ms.

[0043] The feasibility of the method of this invention is illustrated by taking the internal discharge defect of a 400kV oil-immersed transformer as an example. When a partial discharge occurs inside the transformer, the high-frequency pulse current sensor installed at the grounding wire of the bushing end screen, the ultra-high frequency sensor installed on the top surface of the tank wall, and the acoustic sensor installed on the side of the tank wall can simultaneously measure the partial discharge signal. The signal amplitude is high and occurs synchronously. The amplitude of the high-frequency signal reaches 2000mV, the ultra-high frequency signal reaches 610mV, and the acoustic signal reaches 55mV, all exceeding the start-up and operation thresholds. The duration of the high-frequency signal reaches 100us, the ultra-high frequency signal is 30us, and the acoustic signal is 4ms. The time difference between the high-frequency signal and the ultra-high frequency signal is 15us, and the time difference between the high-frequency signal and the acoustic signal is 3ms, which meets the criteria of the method proposed in this invention and is identified as internal discharge. The time-domain waveform is as follows: Figure 2 As shown, when the fuel tank is discharged externally, the signal does not appear synchronously, and the amplitude of the high-frequency signal does not exceed the action threshold, such as... Figure 3 As shown, this invention can identify internal discharges and avoid misjudging external discharges, prompting maintenance personnel to take timely measures.

[0044] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0045] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0046] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0047] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0048] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for identifying internal discharge defects in oil-immersed transformers based on multiple signals, characterized in that, Includes the following steps: Step 1: The program starts running, and the pulse current signal is above the first start threshold timestamp. and the maximum value of the pulse current signal The timestamp of the UHF signal exceeding the second startup threshold and the maximum value of ultra-high frequency signals The timestamp when the acoustic signal exceeds the third start-up threshold and maximum acoustic signal value Assigning a value of 0 to an intermediate variable n The value is assigned to 0; Step 2: Real-time acquisition of pulse current signals during transformer operation UHF signals Acoustic signals ,in t This is the time difference between the current moment and the start moment of the program; Step 3: Based on the real-time acquired transformer pulse current signal UHF signals Acoustic signals Determine the maximum value of the pulse current signal and timestamp UHF signal maximum value and timestamp , and maximum acoustic signal and timestamp ; Step 4: Comparison With the first action threshold ,Compare With the second action threshold ,Compare and The absolute value of the time difference and the fourth time threshold ,if and and Then the intermediate variable n If the value is 1, proceed to step 5; otherwise, proceed to step 6. Step 5: Compare the current time. t and Time difference and the fourth time threshold ,if Then the intermediate variable n If the value is assigned to 0, proceed to step 6; otherwise, proceed directly to step 6. Step 6: Comparison With the third action threshold ,Compare and Time difference and the fifth time threshold ,if and and If the result is positive, it is considered that an internal discharge defect has occurred, and the program ends; otherwise, return to step 2.

2. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 1, characterized in that: In step 3, compare the current time. t and Time difference and first time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. The absolute value and the first starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to .

3. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 2, characterized in that: First time threshold Values ​​range from 10 to 200 µs; First Start-up Threshold ,in, k For reliability coefficient, This represents the maximum absolute value of the noise floor of the pulse current signal when there is no discharge.

4. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 2, characterized in that: In step 3, compare the current time. t and Time difference and second time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. The absolute value and the second starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to .

5. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 4, characterized in that: Second time threshold Values ​​range from 1 to 10 µs; Second Start-up Threshold In the formula, k For reliability coefficient, This represents the maximum absolute value of the UHF signal noise floor when there is no discharge.

6. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 4, characterized in that: In step 3, compare the current time. t and Time difference and third time threshold ,if Then Assign a value of 0, Set the value to 0 and compare the real-time sampled values. The absolute value and the third starting threshold ,if and Then the current time t Assign to Compare real-time sampled values The absolute value and the maximum value of the signal ,if Then Assign to .

7. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 6, characterized in that: The third time threshold Value ranges from 3 to 10 ms; The third start threshold In the formula, k For reliability coefficient, This represents the maximum absolute value of the acoustic signal noise floor when there is no discharge.

8. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 3, 5, or 7, characterized in that: Reliability coefficient k The value is 2.

9. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 1, characterized in that: In step 4, the first action threshold Second action threshold The calculation method for is as follows: Fourth Time Threshold Values ​​range from 1 to 50 µs; In the formula, m The reliability coefficient ranges from 10 to 20. This represents the maximum absolute value of the noise floor of the pulse current signal when there is no discharge. This represents the maximum absolute value of the UHF signal noise floor when there is no discharge.

10. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 9, characterized in that: In step 6, the third action threshold In the formula, m The reliability coefficient ranges from 10 to 20. This represents the maximum absolute value of the acoustic signal noise floor when there is no discharge.

11. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 10, characterized in that: The fifth time threshold The calculation method is as follows: In the formula, x This is the maximum distance from a point inside the transformer tank to the location where the acoustic sensor is placed. v The equivalent speed of sound in the fuel tank; p This is the reliability coefficient.

12. The method for identifying internal discharge defects in an oil-immersed transformer according to claim 11, characterized in that: V The value ranges from 1.3 to 5 m / ms; p The value range is 0.5 to 1.

13. A multi-signal-based internal discharge defect identification system for oil-immersed transformers based on the identification method according to any one of claims 1-12, comprising an initial assignment module, a multi-signal real-time acquisition module, a multi-signal maximum value and timestamp calculation module, and an internal defect fault judgment module; characterized in that: The initial assignment module sets the timestamp of the pulse current signal exceeding the first startup threshold when the program starts running. and the maximum value of the pulse current signal The timestamp of the UHF signal exceeding the second startup threshold and the maximum value of ultra-high frequency signals The timestamp when the acoustic signal exceeds the third start-up threshold and maximum acoustic signal value Assigning a value of 0 to an intermediate variable n The value is assigned to 0; The real-time signal acquisition module acquires the transformer pulse current signal in real time during transformer operation. UHF signals Acoustic signals ,in t This is the time difference between the current moment and the start moment of the program; The multi-signal maximum value and timestamp calculation module is based on the real-time acquired transformer pulse current signal. UHF signals Acoustic signals Determine the maximum value of the pulse current signal and timestamp UHF signal maximum value and timestamp , and maximum acoustic signal and timestamp ; The internal defect fault diagnosis module is based on the maximum value of the pulse current signal. and timestamp UHF signal maximum value and timestamp , and maximum acoustic signal and timestamp Determine whether the transformer has an internal discharge defect.

14. A computer device comprising a memory, a processor, and a computer program stored in the memory; characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1-12.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1-12.

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