Acoustic-flow velocity fusion-based fault grading diagnosis and active protection method for oil-immersed transformer

Abstract

The present application belongs to the technical field of transformer state detection, and particularly relates to a sound-flow velocity fusion oil-immersed transformer fault grading diagnosis and active protection method, which acquires sound signals of a transformer continuously, judges whether the amplitude and center frequency of the sound signals exceed a threshold value, decides whether to start a flow velocity monitoring module, and then judges whether to send a trip signal by judging whether the flow velocity exceeds a threshold value. Under the premise of ensuring no misoperation, the operation condition of the transformer is monitored in time and guidance is given. The flow velocity signal is used as the last line of defense of the transformer to replace the heavy gas protection, so as to achieve the effect of sending a trip signal when a serious fault occurs. The present application realizes active protection of the transformer based on two new digital characteristic parameters of sound and flow velocity, improves the protection range and protection sensitivity of the transformer, avoids the problems of refusal to operate or misoperation that may be caused by conventional transformer protection, and ensures timely and accurate protection response.

Description

Technical Field

[0001] This invention belongs to the field of transformer condition detection technology, and specifically relates to a method for fault classification diagnosis and active protection of oil-immersed transformers based on sound-flow velocity fusion. Background Technology

[0002] Power transformers are core main equipment in power systems, and their safe and stable operation is crucial to the stability and economy of the power system. Traditional power transformer protection criteria rely on a single physical quantity for judgment, resulting in a small protection range and low reliability. Power transformer faults are diverse in type and severity. Timely and accurate fault severity assessment and corresponding measures are essential to improving the reliability of power transformer safe operation.

[0003] Existing technologies for transformer fault detection and protection primarily rely on a single physical quantity for identification. For example, Chinese Patent Application No. CN202111630310.8, entitled "An Intelligent Searching Transformer Fault Detection and Location Device and Optimization Algorithm," collects data from a running ultrasonic sensor using a high-frequency acquisition device, analyzes real-time data, and uses auxiliary data as a criterion to calculate the risk point and location coordinates of the fault. This patent uses a single physical quantity to identify faults, resulting in a relatively weak criterion and limited protection scope. Another existing Chinese Patent Application No. CN202211281325.2, entitled "A Digital Non-Electrical Quantity Protection Method for Oil-Immersed Transformers Based on Pressure Frequency Characteristics," utilizes pressure frequency characteristics as the basis for digital non-electrical quantity protection, comparing the magnitude of the dominant pressure frequency with the action threshold value to identify the internal state of the oil-immersed transformer. While this patent also proposes a new protection method, it uses a limited amount of data, and its main purpose is to distinguish between internal and external faults, which differs from the purpose of this patent. Furthermore, an existing Chinese patent application (CN202110739031.9) entitled "A Transformer Tripping Protection Method, System, Storage Medium, and Computing Device" uses the winding start and end currents to determine whether a discharge has occurred inside the transformer. After determining the discharge, it then determines whether to perform tripping protection based on the discharge time and parameters. Compared to this invention, this invention still uses traditional electrical quantities as criteria and cannot achieve graded fault diagnosis; it can only determine whether a discharge has occurred.

[0004] Therefore, there is an urgent need for a method for fault classification diagnosis and active protection of oil-immersed transformers that integrates sound and flow velocity, to improve the protection range and sensitivity of transformers and ensure timely and accurate protection response. On the basis of ensuring safety, it can replace heavy gas protection to achieve the effect of tripping the transformer in the event of a serious fault. Under the premise of ensuring no false tripping, it can monitor the transformer's operating status in a timely and accurate manner and issue corresponding signals, provide protection strategies, and ensure the power grid's "four characteristics" requirements for relay protection. Summary of the Invention

[0005] The purpose of this invention is to provide a method for fault classification diagnosis and active protection of oil-immersed transformers based on sound-flow velocity fusion, characterized by the following steps:

[0006] Step S1: The acoustic signal acquisition module continuously acquires multiple acoustic signals within the cavity and transmits the acoustic signals to the acoustic signal analysis and first-level judgment module;

[0007] Step S2: The acoustic signal analysis and first-level judgment module calculates the amplitude and center frequency band for each acoustic signal and compares the amplitude with a preset amplitude threshold a: if there is an amplitude greater than or equal to the amplitude threshold a, proceed to step S7; otherwise, proceed to step S3.

[0008] Step S3: Compare each center frequency band calculated by the acoustic signal analysis and first-level judgment module in step S2 with the preset first frequency threshold x: If all center frequency bands are greater than or equal to the first frequency threshold x, proceed to step S11; otherwise, proceed to step S4.

[0009] Step S4: The acoustic signal analysis and first-level judgment module calculates the energy proportion of acoustic signals with frequencies below the second frequency threshold y; when the energy proportion is greater than or equal to the preset energy proportion threshold m, proceed to step S6; otherwise, proceed to step S5.

[0010] Step S5: The acoustic signal analysis and first-level judgment module continues to monitor the acoustic signal in the cavity within a second preset time; if the increase in the energy proportion of acoustic signals with frequencies below the second frequency threshold y is greater than the increase threshold, then step S6 is executed; otherwise, step S11 is executed.

[0011] Step S6: The acoustic signal analysis and first-level judgment module sends a start signal to the flow velocity signal acquisition module to start flow velocity monitoring;

[0012] Step S7: After receiving the start signal, the flow velocity signal acquisition module begins to acquire the flow velocity signal and transmits the flow velocity signal to the flow velocity signal analysis module;

[0013] Step S8: The flow velocity signal analysis module analyzes the flow velocity signal. When the flow velocity value is greater than or equal to the preset flow velocity threshold b, step S9 is executed; otherwise, step S10 is executed.

[0014] Step S9: The flow rate signal analysis module sends the analysis results to the fault classification diagnosis and active protection decision module. The fault classification diagnosis and active protection decision module sets the transformer operating status to "serious fault" and sends a trip signal to the display module. After waiting for the third preset time, step S1 is executed again.

[0015] Step S10: The flow rate signal analysis module transmits the analysis results to the fault classification diagnosis and active protection decision module. The fault classification diagnosis and active protection decision module sets the transformer operating status to "minor fault" and sends an alarm signal to the display module. After waiting for the third preset time, step S1 is executed again.

[0016] Step S11: The acoustic signal analysis and first-level judgment module transmits the analysis results to the fault classification diagnosis and active protection decision module. The fault classification diagnosis and active protection decision module sets the transformer operating status to "no fault" and does not send any signal. After waiting for the third preset time, it re-executes step S1.

[0017] In step S9, the fault classification diagnosis and active protection decision module sets the transformer operating status diagnosis to "serious fault" and sends a signal to the display module, outputting the prompt message "stop immediately to investigate the fault"; in step S10, the fault classification diagnosis and active protection decision module sets the transformer operating status to "minor fault" and sends a message to the display module, outputting the prompt message "take oil sample for further analysis"; in step S11, the fault classification diagnosis and active protection decision module sets the transformer operating status diagnosis to "no fault" and sends a signal to the display module, outputting the prompt message "no need to stop, continue monitoring".

[0018] The present invention also discloses an oil-immersed transformer fault classification diagnosis and active protection system using the method described above, characterized in that it includes: an acoustic signal acquisition module, an acoustic signal analysis and first-level judgment module, a flow velocity signal acquisition module, a flow velocity signal analysis module, and a fault classification diagnosis and active protection decision module;

[0019] The acoustic signal analysis and primary judgment module is connected to the flow velocity signal acquisition module and the fault classification diagnosis and active protection decision module, respectively; wherein, the acoustic signal acquisition module, the acoustic signal analysis and primary judgment module, the flow velocity signal acquisition module, the flow velocity signal analysis module, and the fault classification diagnosis and active protection decision module are connected in series;

[0020] The acoustic signal acquisition module is used to acquire acoustic signals during transformer operation and transmit the acoustic signals to the acoustic signal analysis and primary judgment module;

[0021] The acoustic signal analysis and primary judgment module is used to receive and process the acoustic signals from the acoustic signal acquisition module, calculate the amplitude and frequency of the acoustic signals, compare the results with the threshold, and finally transmit the analysis results to the fault classification diagnosis and active protection decision module.

[0022] The flow velocity signal acquisition module is used to measure the oil flow velocity in the cavity oil pipeline after receiving the start signal of the acoustic signal analysis and first-level judgment module, and transmit the measurement result to the flow velocity signal analysis module.

[0023] The flow velocity signal analysis module is used to receive and process the flow velocity signal from the flow velocity signal acquisition module, compare the velocity of the flow velocity signal with a threshold, and transmit the analysis results to the fault classification diagnosis and active protection decision module.

[0024] The fault classification diagnosis and active protection decision module is used to receive signals from the acoustic signal analysis and first-level judgment module and the flow velocity signal analysis module, and issue corresponding control commands based on the signals.

[0025] The beneficial effects of this invention are as follows:

[0026] This invention provides a method for fault classification diagnosis and active protection of oil-immersed transformers based on sound and flow velocity fusion. By monitoring the transformer's sound signals in real time, the fault condition is initially determined. Then, through conditionally open flow velocity monitoring, the operating status of the transformer can be sensitively and promptly monitored and guidance provided without false tripping. The flow velocity signal acts as the last line of defense for the transformer, replacing heavy gas protection to achieve the effect of tripping the transformer in the event of a serious fault. The invention also studies a device and method for joint ultrasonic and flow velocity fault identification, realizing hybrid protection of the transformer based on both ultrasonic and flow velocity characteristic parameters. This reduces the workload of substation maintenance personnel in protection and repair, improves the protection range and sensitivity of the transformer, reduces the number of unnecessary shutdowns compared to traditional methods, and ensures timely and accurate protection response. Attached Figure Description

[0027] Figure 1 This is a flowchart illustrating the method for fault classification diagnosis and active protection of oil-immersed transformers based on sound-flow velocity fusion in this invention.

[0028] Figure 2 This is a schematic diagram of the fault classification diagnosis and active protection system for oil-immersed transformers in this invention;

[0029] Among them: 11-acoustic signal acquisition module, 12-acoustic signal analysis and first-level judgment module, 21-flow velocity signal acquisition module, 22-flow velocity signal analysis module, 31-fault classification diagnosis and active protection decision module. Detailed Implementation

[0030] This invention provides a method for fault classification diagnosis and active protection of oil-immersed transformers based on sound-flow velocity fusion. The invention will be further described in detail below with reference to the accompanying drawings.

[0031] like Figure 1The embodiment of the present invention disclosed in the present invention provides a method for fault classification diagnosis and active protection of oil-immersed transformers based on sound-current velocity fusion, including:

[0032] Step S1: The acoustic signal acquisition module 11 continuously acquires multiple acoustic signals within the cavity and transmits the acoustic signals to the acoustic signal analysis and first-level judgment module 12;

[0033] In this embodiment, an acoustic signal acquisition module 11 is installed on the outer wall and inside the cavity of the oil-immersed transformer, and a flow velocity signal acquisition module 21 is installed in the oil pipeline of the cavity. The acoustic signal acquisition module 11 is connected to the acoustic signal analysis and primary judgment module 12, and the flow velocity signal acquisition module 21 is connected to the flow velocity signal analysis module 22. Finally, the fault classification diagnosis and active protection decision module 31 is connected to the acoustic signal analysis and primary judgment module 12 and the flow velocity signal analysis module 22, respectively.

[0034] Step S2: The acoustic signal analysis and first-level judgment module 12 calculates the amplitude and center frequency band for each acoustic signal and compares the amplitude with a preset amplitude threshold a: if there is an amplitude greater than or equal to the amplitude threshold a, proceed to step S7; otherwise, proceed to step S3.

[0035] The amplitude threshold 'a' in step S2 is determined based on the sound amplitude when a significant fault occurs inside the oil-immersed transformer. The principle of initially judging whether a significant fault has occurred based on the sound signal amplitude is as follows: when a significant fault occurs inside the oil-immersed transformer, a sound signal of a certain amplitude is generated. In this embodiment, the amplitude threshold 'a' is 5V, which has been verified through extensive experiments to effectively identify significant fault states in oil-immersed transformers. It is worth noting that those skilled in the art should adjust this value according to the specific equipment model and testing environment; this invention does not specifically limit the pre-set amplitude threshold 'a'.

[0036] Step S3: Compare each center frequency band calculated by the acoustic signal analysis and first-level judgment module 12 in step S2 with the preset first frequency threshold x: If all center frequency bands are greater than or equal to the first frequency threshold x, execute step S11; otherwise, execute step S4.

[0037] The first frequency threshold x in step S3 is determined based on the sound frequency of a minor fault occurring inside the oil-immersed transformer. The principle of using the sound signal frequency threshold to initially determine whether an inter-turn short circuit has occurred is as follows: a minor fault inside the oil-immersed transformer will generate a low-frequency sound signal. In this embodiment, the first frequency threshold x is 51.5 kHz. Extensive experimental verification has shown that even when a minor fault occurs in the oil-immersed transformer, although the amplitude is less than the amplitude threshold a, a low-frequency sound signal below 51.5 kHz exists. Based on this standard, the minor fault state of the oil-immersed transformer can be identified relatively well. It is worth noting that those skilled in the art should adjust this value according to the specific equipment model and testing environment. This invention does not specifically limit the pre-set first frequency threshold x.

[0038] Step S4: The acoustic signal analysis and first-level judgment module 12 calculates the energy proportion of acoustic signals with frequencies below the second frequency threshold y; when the energy proportion is greater than or equal to the preset energy proportion threshold m, step S6 is executed; otherwise, step S5 is executed.

[0039] The principle behind determining the energy proportion of acoustic signals with frequencies below the second frequency threshold y (i.e., the amplitude proportion of cavity acoustic signals) in step S4 is as follows: when a fault occurs inside the oil-immersed transformer, a low-frequency acoustic signal with a certain amount of energy will be generated (its frequency is lower than the first frequency threshold x in step S3). Extensive experimental verification shows that the energy proportion of low-frequency acoustic signals in the cavity acoustic signal is directly proportional to the probability of a fault. In this embodiment, the second frequency threshold y is 1.98 kHz, and the energy proportion threshold m is 75%. Extensive experimental verification shows that when the energy proportion of cavity acoustic signals with frequencies below 1.98 kHz is greater than 75%, the oil-immersed transformer is highly likely to have a fault, requiring immediate action. It is worth noting that those skilled in the art should adjust these values ​​according to the specific equipment model and testing environment. This invention does not specifically limit the pre-set second frequency threshold y and energy proportion threshold m.

[0040] Step S5: The acoustic signal analysis and first-level judgment module 12 continues to monitor the acoustic signal in the cavity within a second preset time; if the increase in the energy proportion of the acoustic signal with a frequency below the second frequency threshold y is greater than the threshold, then step S6 is executed; otherwise, step S11 is executed.

[0041] To avoid interference with external acoustic signals due to loose bolts or other reasons, the acoustic signal analysis and primary judgment module 12 continues to monitor the acoustic signals inside the cavity and determines whether the increase in the amplitude ratio (i.e., energy ratio) of acoustic signals below the second frequency threshold y within a second preset time period is greater than the increase threshold, i.e., whether the energy ratio of low-frequency signals has increased. In this embodiment, the increase threshold is 10%. It is worth noting that those skilled in the art should adjust the increase threshold according to the specific equipment model and testing environment. This invention does not specifically limit the increase threshold.

[0042] The principle of using the amplitude and frequency threshold of the acoustic signal to preliminarily determine whether an inter-turn short circuit has occurred is as follows: When a fault occurs inside the transformer, a low-frequency acoustic signal with a certain amount of energy will be generated. As the fault develops, the amplitude of the acoustic signal will continue to rise without significant frequency changes. In contrast, this phenomenon will not occur when only faults such as loose screws occur.

[0043] In this embodiment, when the amplitude of cavity acoustic signals with frequencies below 1.98 kHz accounts for less than 75%, the acoustic signal analysis and primary judgment module 12 further monitors the cavity acoustic signals. If the energy percentage of cavity acoustic signals below the second frequency threshold y increases within a second preset time, it indicates a possibility of an inter-turn short circuit, requiring the activation of the flow velocity signal acquisition module 21 for further judgment. The second preset time should be set by those skilled in the art based on sampling accuracy requirements and equipment acquisition capabilities; it is not specifically limited in this embodiment.

[0044] Step S6: The acoustic signal analysis and first-level judgment module 12 sends a start signal to the flow velocity signal acquisition module 21 to start flow velocity monitoring;

[0045] In this embodiment, the flow velocity signal acquisition module 21 is normally closed. Only when a fault occurs and the acoustic signal analysis and first-level judgment module 12 issues an open signal will the flow velocity be measured to further determine the severity of the fault. This method can effectively reduce the wear and tear on the flow velocity signal acquisition module 21, thereby improving system stability.

[0046] Step S7: After receiving the start signal, the flow velocity signal acquisition module 21 starts to acquire the flow velocity signal and transmits the flow velocity signal to the flow velocity signal analysis module 22;

[0047] Step S8: The flow velocity signal analysis module 22 analyzes the flow velocity signal. When the flow velocity value is greater than or equal to the preset flow velocity threshold b, step S9 is executed; otherwise, step S10 is executed.

[0048] In this embodiment, the flow velocity threshold b in step S8 is 3 m / s. When a transformer experiences a serious fault, the oil flow velocity can reach 3 m / s, in which case the transformer must be shut down.

[0049] In this embodiment, due to the complex on-site environment, a single signal is insufficient to accurately analyze the transformer's operating status, nor to judge its fault development and provide maintenance guidance. Therefore, it is necessary to comprehensively analyze both acoustic and flow velocity signals to judge the transformer's fault status. This avoids false alarms caused by a single acoustic signal diagnosis and accidents caused by delayed diagnosis due to the slow response of the flow velocity signal. The specific real-time process is as follows: the acoustic signal acquisition module 11 is normally open, while the flow velocity signal acquisition module 21 is normally closed. The acoustic signal has a faster response speed and is more sensitive than the flow velocity signal. When a fault occurs, the acoustic signal will activate immediately, while the flow velocity signal will activate after the fault has developed for a period of time. To judge the transformer's operating status in real time, the acoustic sensor remains normally open to monitor the acoustic signal. When an abnormal signal occurs, since the severity of the fault cannot be judged, the acoustic signal analysis and first-level judgment module 12 activates the flow velocity signal acquisition module 21 to monitor the oil flow velocity. By judging the oil flow velocity, the severity of the fault is analyzed, and corresponding guidance is given based on the severity. The two modules work together and complement each other to ensure that false alarms are reduced while responding sensitively to real faults, thereby achieving fault classification diagnosis and active protection for oil-immersed transformers.

[0050] Step S9: The flow rate signal analysis module 22 sends the analysis results to the fault classification diagnosis and active protection decision module 31. The fault classification diagnosis and active protection decision module 31 sets the transformer operating status to "serious fault" and sends a trip signal to the display module. After waiting for the third preset time, step S1 is executed again.

[0051] Step S10: The flow rate signal analysis module 22 transmits the analysis results to the fault classification diagnosis and active protection decision module 31. The fault classification diagnosis and active protection decision module 31 sets the transformer operating status to "minor fault" and sends an alarm signal to the display module. After waiting for the third preset time, step S1 is executed again.

[0052] Step S11: The acoustic signal analysis and first-level judgment module 12 transmits the analysis results to the fault classification diagnosis and active protection decision module 31. The fault classification diagnosis and active protection decision module 31 sets the transformer operating status to "no fault" and does not send any signal. After waiting for the third preset time, it re-executes step S1.

[0053] To prevent excessively frequent detection, a third preset time is set in this embodiment. The specific value of this time should be set by those skilled in the art based on the sampling accuracy requirements and the equipment's acquisition capabilities. No specific limitation is made in this embodiment.

[0054] To reduce the workload of substation maintenance personnel in protection and repair, and to accurately and promptly push fault information to relevant staff, this embodiment also uses a display module to show fault information and operating status to relevant staff, helping them to take timely measures to address the fault. Specific steps include:

[0055] In step S9, the fault classification diagnosis and active protection decision module 31 sets the transformer operating status diagnosis to "serious fault" and sends a signal to the display module to output the prompt message "stop the machine immediately to investigate the fault".

[0056] In step S10, the fault classification diagnosis and active protection decision module 31 sets the transformer operating status to "minor fault" and sends information to the display module, outputting the prompt message "further analysis of oil sample".

[0057] In step S11, the fault classification diagnosis and active protection decision module 31 sets the transformer operating status diagnosis to "no fault" and sends a signal to the display module to output the prompt message "no need to stop, keep monitoring".

[0058] The second embodiment of the present invention discloses an oil-immersed transformer fault classification diagnosis and active protection system that applies the sound-flow velocity fusion method for fault classification diagnosis and active protection described in the first embodiment.

[0059] like Figure 2 As shown, the oil-immersed transformer fault classification diagnosis and active protection system includes: an acoustic signal acquisition module 11, an acoustic signal analysis and first-level judgment module 12, a flow velocity signal acquisition module 21, a flow velocity signal analysis module 22, and a fault classification diagnosis and active protection decision module 31.

[0060] The acoustic signal analysis and primary judgment module 12 is connected to the flow velocity signal acquisition module 21 and the fault classification diagnosis and active protection decision module 31, respectively; wherein, the acoustic signal acquisition module 11, the acoustic signal analysis and primary judgment module 12, the flow velocity signal acquisition module 21, the flow velocity signal analysis module 22 and the fault classification diagnosis and active protection decision module 31 are connected in series.

[0061] The acoustic signal acquisition module 11 is used to acquire acoustic signals during transformer operation and transmit the acoustic signals to the acoustic signal analysis and first-level judgment module 12;

[0062] The acoustic signal analysis and first-level judgment module 12 is used to receive and process the acoustic signal from the acoustic signal acquisition module 11, calculate the amplitude and frequency of the acoustic signal, compare the results with the threshold, and finally transmit the analysis results to the fault classification diagnosis and active protection decision module 31.

[0063] The flow velocity signal acquisition module 21 is used to measure the oil flow velocity in the cavity oil pipeline after receiving the start signal of the acoustic signal analysis and first-level judgment module 12, and transmit the measurement result to the flow velocity signal analysis module 22.

[0064] The flow velocity signal analysis module 22 is used to receive and process the flow velocity signal from the flow velocity signal acquisition module 21, compare the velocity of the flow velocity signal with a threshold, and transmit the analysis results to the fault classification diagnosis and active protection decision module 31.

[0065] The fault classification diagnosis and active protection decision module 31 is used to receive signals from the acoustic signal analysis and first-level judgment module 12 and the flow velocity signal analysis module 22, and issue corresponding control commands based on the signals.

[0066] In this embodiment, depending on the judgment result, monitoring guidance is given directly or a signal is sent to the flow velocity signal acquisition module 21 and the information is received from the flow velocity signal analysis module 22. Finally, guidance is given based on the results of acoustic signal analysis, the first-level judgment module 12 and the flow velocity signal analysis module 22.

[0067] In this implementation, the signal acquisition section includes an acoustic signal acquisition module 11 and a flow velocity signal acquisition module 21 to obtain more comprehensive fault information of the transformer; the signal analysis section includes an acoustic signal analysis and primary judgment module 12 and a flow velocity signal analysis module 22, wherein:

[0068] The acoustic signal analysis and first-level judgment module 12 is used to analyze the acoustic signals acquired in the acoustic signal acquisition module 11, and transmits the final results to the fault classification diagnosis and active protection decision module 31 through multi-segment analysis of the amplitude and frequency of the acoustic signals.

[0069] The flow velocity signal analysis module 22 is used to analyze the flow velocity signal acquired in the flow velocity signal acquisition module 21. By analyzing the magnitude of the flow velocity signal and the threshold, the final result is obtained and transmitted to the fault classification diagnosis and active protection decision module 31.

[0070] Upon receiving an anomaly signal from the acoustic signal acquisition module 11, the acoustic signal analysis and primary judgment module 12 analyzes the frequency and amplitude of the signal and transmits the analysis results to the fault classification diagnosis and active protection decision module 31. If the analysis result indicates no fault, the fault classification diagnosis and active protection decision module 31 directly issues guidance, bypassing the flow velocity signal acquisition module 21. If the analysis result suggests a possible fault, the acoustic signal analysis and primary judgment module 12 retains the fault information and sends a signal to the flow velocity signal acquisition module 21 to measure the flow velocity information, which is then analyzed by the flow velocity signal analysis module 22. Finally, the analysis results are transmitted back to the fault classification diagnosis and active protection decision module 31. The fault classification diagnosis and active protection decision module 31 issues a final signal upon receiving the signal from the flow velocity signal analysis module 22. The two modules cooperate to avoid false alarms caused by a single acoustic signal diagnosis and to prevent accidents caused by untimely diagnosis due to a slow flow velocity signal response. The complementary nature of these modules ensures reduced false alarms while providing sensitive responses to genuine faults, thereby achieving fault classification diagnosis and active protection for oil-immersed transformers.

Claims

1. A method for fault classification diagnosis and active protection of oil-immersed transformers based on sound-flow velocity fusion, characterized in that, Includes the following steps: Step S1: The acoustic signal acquisition module (11) continuously acquires multiple acoustic signals in the cavity and transmits the acoustic signals to the acoustic signal analysis and first-level judgment module (12); Step S2: The acoustic signal analysis and first-level judgment module (12) calculates the amplitude and center frequency band for each acoustic signal and compares the amplitude with the preset amplitude threshold a: when there is an amplitude greater than or equal to the amplitude threshold a, step S7 is executed; Otherwise, proceed to step S3; Step S3: Compare the center frequency bands calculated by the acoustic signal analysis and first-level judgment module (12) in step S2 with the preset first frequency threshold x: When all center frequency bands are greater than or equal to the first frequency threshold x, execute step S11; Otherwise, proceed to step S4; Step S4: The acoustic signal analysis and first-level judgment module (12) calculates the energy ratio of acoustic signals with frequencies below the second frequency threshold y; when the energy ratio is greater than or equal to the preset energy ratio threshold m, step S6 is executed; otherwise, step S5 is executed. Step S5: The acoustic signal analysis and first-level judgment module (12) continues to monitor the acoustic signal in the cavity within the second preset time; if the increase in the energy proportion of the acoustic signal with a frequency below the second frequency threshold y is greater than the increase threshold, then step S6 is executed; otherwise, step S11 is executed. Step S6: The acoustic signal analysis and first-level judgment module (12) sends a start signal to the flow velocity signal acquisition module (21) to start flow velocity monitoring; Step S7: After receiving the start signal, the flow velocity signal acquisition module (21) starts to acquire the flow velocity signal and transmits the flow velocity signal to the flow velocity signal analysis module (22); Step S8: The flow velocity signal analysis module (22) analyzes the flow velocity signal. When the flow velocity value is greater than or equal to the preset flow velocity threshold b, step S9 is executed; otherwise, step S10 is executed. Step S9: The flow rate signal analysis module (22) sends the analysis results to the fault classification diagnosis and active protection decision module (31). The fault classification diagnosis and active protection decision module (31) sets the transformer operating status to "serious fault" and sends a trip signal to the display module. After waiting for the third preset time, step S1 is executed again. Step S10: The flow rate signal analysis module (22) transmits the analysis results to the fault classification diagnosis and active protection decision module (31). The fault classification diagnosis and active protection decision module (31) sets the transformer operating status to "minor fault" and sends an alarm signal to the display module. After waiting for the third preset time, step S1 is executed again. Step S11: The acoustic signal analysis and first-level judgment module (12) transmits the analysis results to the fault classification diagnosis and active protection decision module (31). The fault classification diagnosis and active protection decision module (31) sets the transformer operating status to "no fault" and does not send any signal. After waiting for the third preset time, it re-executes step S1.

2. The method for fault classification diagnosis and active protection of oil-immersed transformers based on sound-flow velocity fusion according to claim 1, characterized in that, In step S9, the fault classification diagnosis and active protection decision module (31) sets the transformer operating status diagnosis to "serious fault" and sends a signal to the display module, outputting the prompt message "stop immediately to investigate the fault"; in step S10, the fault classification diagnosis and active protection decision module (31) sets the transformer operating status to "minor fault" and sends a message to the display module, outputting the prompt message "take oil sample for further analysis"; in step S11, the fault classification diagnosis and active protection decision module (31) sets the transformer operating status diagnosis to "no fault" and sends a signal to the display module, outputting the prompt message "no need to stop, keep monitoring".

3. A fault classification diagnosis and active protection system for oil-immersed transformers using the method described in claim 1, characterized in that, include: The system includes an acoustic signal acquisition module (11), an acoustic signal analysis and primary judgment module (12), a flow velocity signal acquisition module (21), a flow velocity signal analysis module (22), and a fault classification diagnosis and active protection decision module (31). The acoustic signal analysis and first-level judgment module (12) is connected to the flow velocity signal acquisition module (21) and the fault classification diagnosis and active protection decision module (31) respectively; wherein, the acoustic signal acquisition module (11), the acoustic signal analysis and first-level judgment module (12), the flow velocity signal acquisition module (21), the flow velocity signal analysis module (22) and the fault classification diagnosis and active protection decision module (31) are connected in series; The acoustic signal acquisition module (11) is used to acquire acoustic signals during transformer operation and transmit the acoustic signals to the acoustic signal analysis and first-level judgment module (12); The acoustic signal analysis and first-level judgment module (12) is used to receive and process the acoustic signal from the acoustic signal acquisition module (11), calculate the amplitude and frequency of the acoustic signal, compare the results with the threshold, and finally transmit the analysis results to the fault classification diagnosis and active protection decision module (31). The flow velocity signal acquisition module (21) is used to measure the oil flow velocity in the cavity oil pipeline after receiving the start signal from the acoustic signal analysis and first-level judgment module (12), and transmit the measurement result to the flow velocity signal analysis module (22). The flow velocity signal analysis module (22) is used to receive and process the flow velocity signal from the flow velocity signal acquisition module (21), compare the velocity of the flow velocity signal with the threshold, and transmit the analysis results to the fault classification diagnosis and active protection decision module (31). The fault classification diagnosis and active protection decision module (31) is used to receive signals from the acoustic signal analysis and first-level judgment module (12) and the flow velocity signal analysis module (22), and issue corresponding control commands based on the signals.

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