CN112305462A - System for recognizing typical faults of transformer based on transformer sound - Google Patents
System for recognizing typical faults of transformer based on transformer sound Download PDFInfo
- Publication number
- CN112305462A CN112305462A CN202011236526.1A CN202011236526A CN112305462A CN 112305462 A CN112305462 A CN 112305462A CN 202011236526 A CN202011236526 A CN 202011236526A CN 112305462 A CN112305462 A CN 112305462A
- Authority
- CN
- China
- Prior art keywords
- sound
- transformer
- module
- collection
- unit
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012545 processing Methods 0.000 claims abstract description 39
- 238000001914 filtration Methods 0.000 claims description 24
- 230000005236 sound signal Effects 0.000 claims description 14
- 230000015572 biosynthetic process Effects 0.000 claims description 11
- 238000003786 synthesis reaction Methods 0.000 claims description 11
- 238000000034 method Methods 0.000 claims description 7
- 230000005540 biological transmission Effects 0.000 claims description 6
- 238000009499 grossing Methods 0.000 claims description 6
- 230000000737 periodic effect Effects 0.000 claims description 5
- 230000002194 synthesizing effect Effects 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 2
- 238000001514 detection method Methods 0.000 abstract description 7
- 238000012423 maintenance Methods 0.000 abstract description 3
- 238000004458 analytical method Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 5
- 238000012544 monitoring process Methods 0.000 description 3
- 238000003745 diagnosis Methods 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 230000005291 magnetic effect Effects 0.000 description 2
- 230000010355 oscillation Effects 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 239000008358 core component Substances 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 210000005069 ears Anatomy 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000005294 ferromagnetic effect Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/62—Testing of transformers
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
- G10L25/18—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being spectral information of each sub-band
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R1/00—Details of transducers, loudspeakers or microphones
- H04R1/08—Mouthpieces; Microphones; Attachments therefor
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R3/00—Circuits for transducers, loudspeakers or microphones
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R2203/00—Details of circuits for transducers, loudspeakers or microphones covered by H04R3/00 but not provided for in any of its subgroups
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Acoustics & Sound (AREA)
- Signal Processing (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- Health & Medical Sciences (AREA)
- Human Computer Interaction (AREA)
- Multimedia (AREA)
- General Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Power Engineering (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Testing Relating To Insulation (AREA)
Abstract
The invention discloses a system for identifying typical faults of a transformer based on sound of the transformer, which comprises a sound acquisition module, a sound processing module, a database, a comparison and judgment module, a result output module and a central processing unit, wherein the output end of the sound acquisition module is connected with the sound processing module, the sound acquisition module transmits acquired sound data to the sound processing module, the output end of the sound processing module and the database transmit processed data to the comparison and judgment module, the input end of the result output module is connected with the output end of the comparison and judgment module, and the result output module is used for outputting results of the comparison and judgment module. The power failure maintenance is not needed, and the detection time is short.
Description
Technical Field
The invention relates to the technical field of transformer fault detection, in particular to a system for recognizing a typical fault of a transformer based on transformer voice.
Background
In recent years, productivity is continuously developed in China, and as a core component of a power system, the safety and stability of a transformer are important for ensuring the normal operation of the power system. The transformer is used as an important node for voltage regulation and electric energy distribution management in a power supply and distribution line, whether the transformer can reliably and stably operate can directly influence the working condition of a power grid where the transformer is located, but the practical situation is that the operating environment of the transformer is always influenced by factors such as electricity, heat, machinery, humidity and the like, the performance of the transformer can be gradually degraded along with the extension of the service period, and when the degradation is accumulated to a certain degree, a fault can be caused, so that the power grid is in large-area power failure, the power failure of any transformer can be a catastrophic accident, direct or indirect economic loss can be caused to a power enterprise, and the normal life of people can be influenced.
At present, with the progress of a state monitoring technology, more and more state monitoring methods and more comprehensive means are provided for a transformer, and obtained data are richer and richer, but a method for judging the state of the transformer is relatively lacked, especially analysis on fault reasons is provided. In order to practically ensure that the transformer can normally and stably operate, power workers continuously explore in practice, and therefore the transformer state detection and fault diagnosis technology is summarized. The state monitoring and fault diagnosis technology of the current transformer has many kinds, mainly: the system comprises a dissolved gas state detection mode, a partial discharge analysis mode, a thermal effect analysis mode, a vibration analysis mode and the like, wherein the dissolved gas state detection mode has the defects that power failure maintenance is needed, the detection time is long, the partial discharge analysis mode is characterized in that a power transformation place is generally filled with various strong electromagnetic and radio interferences, so that an online monitoring device is unobstructed and cannot reach high resolution, the analysis depends on the familiarity degree of a map, namely the technical level of an operator, and therefore, the system for recognizing the typical fault of the transformer based on the sound of the transformer is provided.
Disclosure of Invention
The present invention is directed to a system for recognizing a typical transformer fault based on a transformer voice, so as to solve the above-mentioned problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides a system based on typical trouble of transformer sound identification transformer, includes sound collection module, sound processing module, database, contrast judgement module, result output module and central processing unit, sound collection module's output and sound processing module are connected, sound collection module is with the sound data transmission who gathers to sound processing module in, the data transmission after will handling of sound processing module's output, database to with contrast judgement module in, the input of result output module is connected with the output of contrast judgement module, result output module is used for exporting the result of contrast judgement module, sound collection module, sound processing module, database, contrast judgement module, result output module all are connected with central processing unit.
Preferably, the sound collection module is used for collecting sound signals of the transformer, the sound collection module comprises a collection unit, a filtering unit and a sound synthesis unit, the collection unit is connected with the filtering unit, and the filtering unit is connected with the sound synthesis unit;
preferably, the acquisition unit is used for acquiring sound signals of different frequency bands of the transformer and transmitting the acquired sound signals of different frequency bands to the filtering unit;
including the collection system of four different frequency bands in the collection unit, be respectively:
infrasonic wave sound pickup: picking up sound waves of 1HZ-200 HZ;
low-frequency sound pickup: picking up sound waves of 200HZ-3 KHZ;
high-frequency sound pickup: picking up sound waves of 3KHZ-20 KHZ;
ultrasonic sound pickup: pick up the sound wave of 20KHZ-150 KHZ.
Preferably, the filtering unit is configured to filter out sound waves belonging to non-collection frequencies in frequency bands collected by the sound collector in the collection device in four different frequency bands.
Preferably, the sound synthesizing unit is configured to synthesize sound waves of four different frequency bands.
Preferably, the sound processing module is configured to perform denoising processing on the received sound, perform fourier transform, extract sound features, and perform gaussian filtering and waveform smoothing on the sound waves.
Preferably, the comparison and judgment module is configured to compare the sound features obtained after the processing by the sound processing module with the sound features in the database, and perform fault judgment.
Preferably, the method of the transformer voice-based transformer typical fault identification system includes the following steps:
the method comprises the following steps: sound collection is carried out by utilizing a sound collection device with a wide frequency range;
step two: denoising sound, performing Fourier transform, and extracting sound features;
gaussian filtering and waveform smoothing are carried out on the sound waves, and the formula is as follows:
after DTF approximation is carried out on the signal, a periodic waveform is taken to carry out Fourier transform and then characteristic values are extracted, and the formula is as follows:
step three: and comparing the sound characteristics in the database to judge the fault.
The invention provides a system for recognizing a typical fault of a transformer based on transformer voice, which has the following beneficial effects:
the invention judges some typical faults in the operation of the transformer by using the sound signals of the non-contact acquisition transformer, can carry out real-time detection, can measure and judge the root cause and the judgment of the typical faults of the transformer on line by the non-contact sound sensing, does not need power failure maintenance, and has short detection time.
Drawings
FIG. 1 is a block diagram of the system architecture of the present invention;
FIG. 2 is a system flow diagram of the present invention;
FIG. 3 is a typical sonic plot of the scene of the present invention;
FIG. 4 is a schematic diagram of a characteristic waveform structure obtained by extracting a periodic waveform after denoising and DTF approximate analysis.
FIG. 5 is a diagram of a characteristic waveform abstracted from Fourier transform in accordance with the present invention
FIG. 6 is a schematic structural diagram of a sound collection device according to the present invention;
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
Example 1:
as shown in fig. 1-2 and fig. 6, the present invention provides a technical solution: the utility model provides a system based on typical trouble of transformer sound identification transformer, includes sound collection module, sound processing module, database, contrast judgement module, result output module and central processing unit, sound collection module's output and sound processing module are connected, sound collection module is with the sound data transmission who gathers to sound processing module in, the data transmission after will handling of sound processing module's output, database to with contrast judgement module in, the input of result output module is connected with the output of contrast judgement module, result output module is used for exporting the result of contrast judgement module, sound collection module, sound processing module, database, contrast judgement module, result output module all are connected with central processing unit.
Furthermore, the sound collection module is used for collecting sound signals of the transformer, the sound collection module comprises a collection unit, a filtering unit and a sound synthesis unit, the collection unit is connected with the filtering unit, and the filtering unit is connected with the sound synthesis unit;
furthermore, the acquisition unit is used for acquiring sound signals of different frequency bands of the transformer and transmitting the acquired sound signals of different frequency bands to the filtering unit;
including the collection system of four different frequency bands in the collection unit, be respectively:
infrasonic wave sound pickup: picking up sound waves of 1HZ-200 HZ;
low-frequency sound pickup: picking up sound waves of 200HZ-3 KHZ;
high-frequency sound pickup: picking up sound waves of 3KHZ-20 KHZ;
ultrasonic sound pickup: pick up the sound wave of 20KHZ-150 KHZ.
Furthermore, the filtering unit is used for filtering out sound waves which belong to non-collection frequencies in frequency bands picked up by sound pickups in the collection devices of four different frequency bands.
Further, the sound synthesis unit is used for synthesizing the sound waves of four different frequency bands.
Furthermore, the sound processing module is used for denoising the received sound, performing Fourier transform, extracting sound features, and simultaneously performing Gaussian filtering and waveform smoothing on the sound waves.
Further, the comparison and judgment module is used for comparing the sound characteristics obtained after the processing of the sound processing module with the sound characteristics in the database to judge the fault.
It should be noted that, in the system for identifying the typical fault of the transformer based on the sound of the transformer, when in work, the infrasonic wave pickup, the low frequency pickup, the high frequency pickup and the ultrasonic wave pickup of the collection unit in the sound collection module collect the sound signals of the transformer in different frequency bands, the sound signals of each frequency band pass through the filter device in the filter unit to filter the sound waves of non-collection frequency, then the sound synthesis unit is used for synthesis, finally the synthesized sound signals are transmitted to the sound processing module, the sound processing module carries out de-noising processing on the synthesized sound signals and carries out Fourier transform to extract the sound characteristics, the sound characteristics are transmitted to the comparison judgment module, the comparison judgment module extracts the corresponding transformer load sound characteristics from the database, compares the two, carries out fault judgment, and finally transmits the judgment result to the result output module, the invention accurately judges the overload and oil shortage states of the transformer in a non-contact sound sensing mode.
Example 2:
as shown in fig. 1 to 6, the present invention provides a technical solution: a system for identifying a typical fault of a transformer based on a transformer sound comprises the following steps:
the method comprises the following steps: sound collection is carried out by utilizing a sound collection device with a wide frequency range;
the frequency of the fault sound of the transformer is wide, from the vibration of the central ferromagnetic body to about 14Hz, to the frequency of the ultrasonic wave generated by the partial discharge to 100 KHZ.
Currently there is no single device to perform the acquisition. Therefore, 4 acquisition devices with different frequency bands are integrated for acquisition. And filtering is performed separately.
1. Infrasonic wave sound pickup: pick up sound waves of 1HZ-200 HZ.
2. Low-frequency sound pickup: pick up 200HZ-3KHZ sound wave
3. High-frequency sound pickup: pick up 3-20 KHZ sound wave
4. Ultrasonic sound pickup: pick up the sound wave of 20KHZ-150 KHZ.
Since the sound pickup picks up clutter in other frequency bands, the sound waves of non-pickup frequencies are filtered out by the filter device and then synthesized. The synthesis mode is simple to superpose after digital sampling because of the inconsistent frequency.
Step two: denoising sound, performing Fourier transform, and extracting sound features;
gaussian filtering and waveform smoothing are carried out on the sound waves, and the formula is as follows:
after DTF approximation is carried out on the signal, a periodic waveform is taken to carry out Fourier transform and then characteristic values are extracted, and the formula is as follows:
step three: and comparing the sound characteristics in the database to judge the fault.
The characteristic judgment is mainly carried out on the frequency composition of the waveform.
Description of the drawings: transformer load sound feature library:
the source of the sound is caused by the vibration of the core due to the primary coil not matching the power after the overload. Secondly, after the magnetic core is saturated, the primary coil is heated to generate self-oscillation.
The sound characteristics are as follows: consisting of two low frequency oscillations. One is caused by self oscillation of the coil, the frequency is an integral multiple of 50HZ, the sound intensity is related to the power, and the relationship between the sound intensity and the frequency decreases exponentially.
One is caused by the core. Has a relation with the mass ratio of the magnetic core and the coil, is relatively stable and is generally not more than 12 HZ. Because the large mass object vibrates, it is a representation of a sine wave.
The typical sound wave on site is shown in fig. 3, the characteristic waveform obtained by extracting the periodic waveform after denoising and DTF approximate analysis is shown in fig. 4, the characteristic waveform abstracted after fourier transform is combined is shown in fig. 5, and the sound is visually perceived as buzzing by human ears.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. The utility model provides a system based on typical trouble of transformer sound identification transformer, its characterized in that, includes sound collection module, sound processing module, database, contrast judgement module, result output module and central processing unit, sound collection module's output and sound processing module are connected, sound collection module is with the sound data transmission who gathers to sound processing module in, the data transmission after will handling of sound processing module's output, database to with contrast judgement module in, the input of result output module is connected with the output of contrast judgement module, result output module is used for exporting the result of contrast judgement module, sound collection module, sound processing module, database, contrast judgement module, result output module all are connected with central processing unit.
2. The system for identifying the typical transformer fault based on the transformer voice as claimed in claim 1, wherein: the sound collection module is used for collecting sound signals of the transformer and comprises a collection unit, a filtering unit and a sound synthesis unit, wherein the collection unit is connected with the filtering unit, and the filtering unit is connected with the sound synthesis unit.
3. The system for identifying the typical transformer fault based on the transformer voice as claimed in claim 2, wherein: the acquisition unit is used for acquiring sound signals of different frequency bands of the transformer and transmitting the acquired sound signals of different frequency bands to the filtering unit;
including the collection system of four different frequency bands in the collection unit, be respectively:
infrasonic wave sound pickup: picking up sound waves of 1HZ-200 HZ;
low-frequency sound pickup: picking up sound waves of 200HZ-3 KHZ;
high-frequency sound pickup: picking up sound waves of 3KHZ-20 KHZ;
ultrasonic sound pickup: pick up the sound wave of 20KHZ-150 KHZ.
4. The system for identifying the typical transformer fault based on the transformer voice as claimed in claim 2, wherein: the filtering unit is used for filtering sound waves which belong to non-acquisition frequencies in frequency bands picked up by the sound pickup in the acquisition devices of four different frequency bands.
5. The system for identifying the typical transformer fault based on the transformer voice as claimed in claim 2, wherein: the sound synthesis unit is used for synthesizing sound waves of four different frequency bands.
6. The system for identifying the typical transformer fault based on the transformer voice as claimed in claim 1, wherein: the sound processing module is used for denoising the received sound, carrying out Fourier transformation, extracting sound characteristics, and simultaneously carrying out Gaussian filtering and waveform smoothing on sound waves.
7. The system for identifying the typical transformer fault based on the transformer voice as claimed in claim 1, wherein: and the comparison and judgment module is used for comparing the sound characteristics obtained after the processing of the sound processing module with the sound characteristics in the database to judge the fault.
8. The system for identifying the typical transformer fault based on the transformer voice as claimed in claim 1, wherein: the method for identifying the typical fault of the transformer based on the sound of the transformer comprises the following steps:
the method comprises the following steps: sound collection is carried out by utilizing a sound collection device with a wide frequency range;
step two: denoising sound, performing Fourier transform, and extracting sound features;
gaussian filtering and waveform smoothing are carried out on the sound waves, and the formula is as follows:
after DTF approximation is carried out on the signal, a periodic waveform is taken to carry out Fourier transform and then characteristic values are extracted, and the formula is as follows:
step three: and comparing the sound characteristics in the database to judge the fault.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011236526.1A CN112305462A (en) | 2020-11-09 | 2020-11-09 | System for recognizing typical faults of transformer based on transformer sound |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011236526.1A CN112305462A (en) | 2020-11-09 | 2020-11-09 | System for recognizing typical faults of transformer based on transformer sound |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112305462A true CN112305462A (en) | 2021-02-02 |
Family
ID=74326505
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011236526.1A Pending CN112305462A (en) | 2020-11-09 | 2020-11-09 | System for recognizing typical faults of transformer based on transformer sound |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112305462A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113053412A (en) * | 2021-02-04 | 2021-06-29 | 国网江苏省电力有限公司检修分公司 | Sound-based transformer fault identification method |
| CN113253156A (en) * | 2021-05-17 | 2021-08-13 | 国网江苏省电力有限公司检修分公司 | Sound monitoring-based latent defect diagnosis method for transformer |
| CN115762558A (en) * | 2022-11-18 | 2023-03-07 | 沃克斯迅达电梯有限公司 | Performance detection system and method for escalator production |
| WO2024032345A1 (en) * | 2022-08-12 | 2024-02-15 | 国网江苏省电力有限公司泰州供电分公司 | Sound collection device configured to monitor voiceprint, and preparation method |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103712679A (en) * | 2013-12-05 | 2014-04-09 | 国网上海市电力公司 | Converter transformer operating state on-line audio analyzing and monitoring system |
| CN204241581U (en) * | 2014-09-02 | 2015-04-01 | 国家电网公司 | Transformer allophone analytical equipment |
| CN105223453A (en) * | 2015-11-03 | 2016-01-06 | 广东电网有限责任公司佛山供电局 | Based on substation transformer trouble-shooter and the method for multiple attribute synthetical evaluation |
| CN206258250U (en) * | 2016-08-31 | 2017-06-16 | 中国南方电网有限责任公司超高压输电公司广州局 | A kind of voltage direct-current transmission valve cooling system Fault Diagnosis of Rotating Equipment Based instrument |
| CN107424626A (en) * | 2017-08-04 | 2017-12-01 | 上海振华重工电气有限公司 | A kind of gantry crane trolley track sound monitoring and fault finding system |
| CN206832355U (en) * | 2017-05-16 | 2018-01-02 | 国网新疆电力公司昌吉供电公司 | Substation transformer audio monitoring device |
| CN109029582A (en) * | 2018-08-17 | 2018-12-18 | 国网江苏省电力有限公司盐城供电分公司 | A kind of Power Transformer Faults on-line detecting system based on many kinds of parameters acquisition |
| CN109507510A (en) * | 2018-11-28 | 2019-03-22 | 深圳桓轩科技有限公司 | A kind of transformer fault diagnosis system |
| CN109557412A (en) * | 2018-11-27 | 2019-04-02 | 华翔翔能电气股份有限公司 | A kind of method for recognizing sound-groove and system of transformer fault |
| KR20200060179A (en) * | 2018-11-22 | 2020-05-29 | 고려대학교 세종산학협력단 | Transformer fault diagnosis with sound information |
| CN111308240A (en) * | 2020-02-26 | 2020-06-19 | 海盐南原电力工程有限责任公司 | High-voltage equipment sound fault detection device and detection method thereof |
-
2020
- 2020-11-09 CN CN202011236526.1A patent/CN112305462A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103712679A (en) * | 2013-12-05 | 2014-04-09 | 国网上海市电力公司 | Converter transformer operating state on-line audio analyzing and monitoring system |
| CN204241581U (en) * | 2014-09-02 | 2015-04-01 | 国家电网公司 | Transformer allophone analytical equipment |
| CN105223453A (en) * | 2015-11-03 | 2016-01-06 | 广东电网有限责任公司佛山供电局 | Based on substation transformer trouble-shooter and the method for multiple attribute synthetical evaluation |
| CN206258250U (en) * | 2016-08-31 | 2017-06-16 | 中国南方电网有限责任公司超高压输电公司广州局 | A kind of voltage direct-current transmission valve cooling system Fault Diagnosis of Rotating Equipment Based instrument |
| CN206832355U (en) * | 2017-05-16 | 2018-01-02 | 国网新疆电力公司昌吉供电公司 | Substation transformer audio monitoring device |
| CN107424626A (en) * | 2017-08-04 | 2017-12-01 | 上海振华重工电气有限公司 | A kind of gantry crane trolley track sound monitoring and fault finding system |
| CN109029582A (en) * | 2018-08-17 | 2018-12-18 | 国网江苏省电力有限公司盐城供电分公司 | A kind of Power Transformer Faults on-line detecting system based on many kinds of parameters acquisition |
| KR20200060179A (en) * | 2018-11-22 | 2020-05-29 | 고려대학교 세종산학협력단 | Transformer fault diagnosis with sound information |
| CN109557412A (en) * | 2018-11-27 | 2019-04-02 | 华翔翔能电气股份有限公司 | A kind of method for recognizing sound-groove and system of transformer fault |
| CN109507510A (en) * | 2018-11-28 | 2019-03-22 | 深圳桓轩科技有限公司 | A kind of transformer fault diagnosis system |
| CN111308240A (en) * | 2020-02-26 | 2020-06-19 | 海盐南原电力工程有限责任公司 | High-voltage equipment sound fault detection device and detection method thereof |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113053412A (en) * | 2021-02-04 | 2021-06-29 | 国网江苏省电力有限公司检修分公司 | Sound-based transformer fault identification method |
| CN113053412B (en) * | 2021-02-04 | 2023-12-22 | 国网江苏省电力有限公司检修分公司 | Transformer fault identification method based on sound |
| CN113253156A (en) * | 2021-05-17 | 2021-08-13 | 国网江苏省电力有限公司检修分公司 | Sound monitoring-based latent defect diagnosis method for transformer |
| CN113253156B (en) * | 2021-05-17 | 2023-01-06 | 国网江苏省电力有限公司检修分公司 | Sound monitoring-based latent defect diagnosis method for transformer |
| WO2024032345A1 (en) * | 2022-08-12 | 2024-02-15 | 国网江苏省电力有限公司泰州供电分公司 | Sound collection device configured to monitor voiceprint, and preparation method |
| CN115762558A (en) * | 2022-11-18 | 2023-03-07 | 沃克斯迅达电梯有限公司 | Performance detection system and method for escalator production |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112305462A (en) | System for recognizing typical faults of transformer based on transformer sound | |
| CN102841296B (en) | Online monitoring system and method for partial discharge of intelligent switch cabinet based on ultra-high frequency detection | |
| CN105911499B (en) | Ultrasonic wave shelf depreciation metering system and method under site environment | |
| CN113124929A (en) | Transformer substation multi-parameter signal acquisition comprehensive analysis system and method | |
| CN106950477A (en) | A kind of built-in very high frequency(VHF) partial discharge detection device and method | |
| CN204256093U (en) | The On-line Fault monitoring device of cable splice in a kind of 10 ~ 35kV power distribution network | |
| CN102116824A (en) | Distributed local discharge on-line monitoring method and device for high voltage cable system | |
| CN204832421U (en) | It takes electric detection means to put based on pulse wide band hyperfrequency office | |
| CN109782112B (en) | Transformer multi-parameter fault monitoring system and detection method | |
| CN114217149A (en) | Transformer acoustic fingerprint uninterrupted power detection and state early warning method | |
| CN208537479U (en) | A kind of rolling bearing fault diagnosis device based on acoustic emission detection | |
| CN205091401U (en) | Transformer winding vibration frequency response test system | |
| CN104655967A (en) | Extraction method for vibration signal characteristic quantity of winding of distribution transformer | |
| CN202041614U (en) | Insulation defect local discharging signal identifying device of ultrahigh voltage cable line | |
| CN206531923U (en) | Embedded partial discharge monitoring intelligence instrument based on pulse current method | |
| CN203561591U (en) | Device for detecting dirt of insulator by combining image analysis with ultrasonic principle | |
| CN206804798U (en) | A kind of built-in very high frequency(VHF) partial discharge detection device | |
| CN219161436U (en) | Voiceprint monitoring system | |
| CN106705937A (en) | Differential-capacitor-based voltage tower inclination monitoring system and method | |
| CN216484779U (en) | High temperature pressure vessel damage positioning device based on ultrasonic guided waves | |
| CN206132970U (en) | Ultrasonic wave partial discharge measurement system under site environment | |
| CN111398676B (en) | Method for judging oscillation propagation path through subsynchronous/supersynchronous oscillation frequency | |
| CN106872869A (en) | Embedded partial discharge monitoring intelligence instrument based on pulse current method | |
| CN113776649A (en) | Piezoelectric self-energy-taking-based passive wireless monitoring method and system for transformer vibration | |
| CN110231541B (en) | Method for carrying out inverse calculation on equivalent electrical parameters of system based on online monitoring of damped oscillation waves |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20210202 |
|
| WD01 | Invention patent application deemed withdrawn after publication |