CN103197630A - Self-learning criterion generating method of audio monitoring system - Google Patents
Self-learning criterion generating method of audio monitoring system Download PDFInfo
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- CN103197630A CN103197630A CN2013100779957A CN201310077995A CN103197630A CN 103197630 A CN103197630 A CN 103197630A CN 2013100779957 A CN2013100779957 A CN 2013100779957A CN 201310077995 A CN201310077995 A CN 201310077995A CN 103197630 A CN103197630 A CN 103197630A
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Abstract
The invention discloses a self-learning criterion generating method of an audio monitoring system. The self-learning criterion generating method of the audio monitoring system is mainly used for construction of an audio criterion in the audio monitoring system of electrical equipment and solves the problems that the differences of audio signals of different equipment and different portions under different operating states are hard to discriminated with the same criterion standard. The self-learning criterion generating method of the audio monitoring system includes that when the audio monitoring system is put into operation, audio signals of the electrical equipment under different operating states and changes of the audio signals within a certain operating period of the electrical equipment are continuously collected by means of audio sensors (pickup) installed on different equipment and different portions; a computer processing unit analyzes and compares the frequencies of the audio signals, the amplitudes of the audio signals and the changes of the frequency and the amplitude of the audio signals and generates an audio envelop line; a process reference criterion of each collecting point and a dynamic reference criterion of the switching operation are generated by means of a self-learning function; the audio signals monitored in real time is compared with the process reference criterion and the dynamic reference criterion of the switching operation in the process of real-time monitoring the electrical equipment. The audio signals are discovered to be abnormal, alarm is carried out at once. Therefore, the targeted monitoring of operating audio of the electrical equipment can be achieved.
Description
Technical field
The present invention mainly is electric equipment intelligent monitoring, refer in particular to in transformer station's electrical equipment audio frequency monitoring with reference to the structure of criterion.
Background technology
At present, the monitoring of unattended substation mainly tends to implement " five is distant " (remote measurement, remote signalling, remote control, remote regulating, remote viewing) monitoring, to realize few man on duty, unattended, to improve productivity effect.Unattended substation is that the operational factor of electrical equipment is gathered by the main means of remote monitoring at present, and on off state is controlled, and electrical equipment is carried out online detection by sensor, or the video of equipment is monitored.Almost seldom relate to the Voice Surveillance to transformer station's electrical equipment up till now.Electrical equipment can send all sound in operational process, from the variation of sound can discriminating device normal or unusual condition.When having the people on duty, mainly be by listening, see, touch, hearing equipment to be exercised supervision when its operator on duty makes an inspection tour equipment.At unattended substation, equipment audio frequency in service unusually then lacked supervision.Audio Monitoring System has solved the audio frequency monitoring problem of unattended substation, and the noise difference that produces when still moving owing to different equipment can produce electromagnetic noise as transformer ' s type equipment by iron core when moving; Capacitor can produce the resonance sound under the effect of mains by harmonics component; The GIS switchgear is then quiet relatively when operation.Same electrical equipment is also different at the electromagnetic sound that different positions produces, and the electromagnetic sound that produces when different loads has bigger difference.Electrical equipment particularly GIS switchgear the easiest variation by relative position when grid switching operation produces fault, is the emphasis of monitoring.These factors are all brought the criterion problem of Audio Monitoring System, that is to say to adopt unified criterion to carry out normal to electrical equipment and the exceptional value judgement, and the present invention is exactly the specific aim criterion problem that solves in the Audio Monitoring System.
Summary of the invention
The present invention is directed to the supervision criterion problem of electrical equipment Audio Monitoring System, invented a kind of self study criterion method of formation of Audio Monitoring System.Namely when the application Audio Monitoring System carries out the audio frequency supervision to electrical equipment, the dynamic change of sound signal during at first by the sound signal of the different running statuses of equipment in the audio sensor that is installed in electrical equipment (acoustic pickup) certain cycle of operation of continuous acquisition and equipment grid switching operation, store audio frequency, amplitude and the variation thereof that analysis collects by computer processing unit, analyze maximal value, make up the audio pack winding thread, each collection point of setting up automatically by self-learning function is the audioref criterion targetedly.
In the audio frequency supervision to electrical equipment after this, the sound signal of real-time online collection and each collection point of automatically setting up by self-learning function before this targetedly the audioref criterion compare, in case the frequency of discovery sound signal and amplitude exceed the scope with reference to criterion, the cacophonia of starting outfit operation in time warning function.To concentrator station or chain of command in production report, in order to equipment is taked further to check diagnosis, equipment breakdown takes place in prevention by the distant communication function.
The present invention has following advantage:
1, the audioref criterion is by being installed in different equipment, the audio sensor of different parts (acoustic pickup) collection foundation, criterion is corresponding with device location, solve the operation sound difference of different equipment, different parts, be difficult to the problem of differentiating with unified criterion.Be to generate by self-learning function at the relative position of electrical equipment with reference to criterion, with strong points, have
The position comparability
2, be by continuous acquisition electrical equipment in certain cycle of operation by audio sensor (acoustic pickup) with reference to criterion
Different running statuses are by self studyGenerate, reflected the variation range of equipment at each running status subaudio frequencies such as heavy duty, underloadings, letter has covered the various running status processes of equipment, has
The process comparability
3, the dynamic reference criterion of Audio Monitoring System is passed through equipment by audio sensor (acoustic pickup)
During grid switching operationThe collection of sound signal is analyzed relatively
The dynamic change scope of sound signal, the dynamic reference criterion of generation has reflected that equipment exists
During grid switching operationThe dynamic change of sound signal has
Dynamic comparability
Description of drawings
Fig. 1 is complete equipment figure.
Fig. 2 is static process self study criterion product process figure.
Fig. 3 is dynamic process self study criterion product process figure.
Embodiment
When using Audio Monitoring System that electrical equipment is exercised supervision, when maybe the equipment that need supervise increases, at first by substation server and scrambler the installation addresses of each audio sensor (acoustic pickup) is edited, the different running statuses according to monitored equipment arrange the self study cycle then.Start static process self study criterion generate pattern at unit audio sensor (acoustic pickup), enter self study criterion acquisition state, the sound signal of equipment is gathered and stored.Treat phase in self study week knot Bouquet, carry out analyzing and processing by the sound signal that computer processor is gathered each unit audio sensor (acoustic pickup).Find out the audiorange of each collection point normal value as the static process audioref criterion of this collection point equipment operation.After this mode of operation is switched to the audio frequency monitor state, electrical equipment is carried out the audio frequency supervision.The sound signal that each collection point audio sensor (acoustic pickup) real-time online collects is compared with corresponding static process audioref criterion, start alert program immediately in case note abnormalities, the abnormal signal reporting equipment supervision of equipment operation audio frequency or production commander department, request is taked further to check to equipment and is handled.
In order to solve the dynamic reference criterion problem of equipment grid switching operation, after static process audioref criterion generates, start dynamic process self study criterion generate pattern at unit audio sensor (acoustic pickup), enter dynamic self study criterion acquisition state.Then quilt supervision equipment is carried out the several times grid switching operation, gather and store the dynamic audio frequency signal by audio sensor (acoustic pickup).Treat self study cycle knot speed, by computer processor the sound signal that each unit audio sensor (acoustic pickup) collects is carried out analyzing and processing, find out the audio frequency variation range of each collection point normal value as the dynamic process audioref criterion of this collection point equipment operation.After this mode of operation is switched to the audio frequency monitor state.To the grid switching operation of electrical equipment the time, the sound signal of each collection point audio sensor (acoustic pickup) real-time online collection is compared with corresponding dynamic process audioref criterion, start alert program immediately in case note abnormalities, the supervision of the audio frequency abnormal signal reporting equipment of equipment or production commander department, whether request to the equipment operating process processing takes place to check unusually.
The above only is preferred implementation of the present invention, and protection scope of the present invention also not only is confined to above-described embodiment, and all technical schemes that belongs under the thinking of the present invention all belong to protection scope of the present invention.Should be pointed out that for those skilled in the art in the some improvements and modifications that do not break away under the principle of the invention prerequisite, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (4)
1. the self study criterion method of formation of an Audio Monitoring System, namely when the application Audio Monitoring System carries out the audio frequency supervision to electrical equipment, the at first variation of sound signal when the sound signal of the different running statuses of electrical equipment and equipment grid switching operation in audio sensor (acoustic pickup) the certain cycle of operation of continuous acquisition by being installed in distinct device, different parts, analyze frequency, the amplitude variations scope of comparing audio signal, by the audioref criterion of automatic each collection point set up of self-learning function.
2. the self study criterion method of formation of Audio Monitoring System according to claim 1 is characterized in that: the criterion standard of Audio Monitoring System is by continuous acquisition electrical equipment in certain cycle of operation by audio sensor (acoustic pickup)
Different running statusesThe sound signal of (comprising heavy duty and light running state) process, by analyzing frequency, the amplitude variations scope of comparing audio signal, the process that generates is with reference to criterion automatically.
3. the self study criterion method of formation of Audio Monitoring System according to claim 1 is characterized in that: the criterion standard of Audio Monitoring System by audio sensor (acoustic pickup) by to equipment
Dynamic during grid switching operationThe collection of sound signal is analyzed relatively
The dynamic change scope of sound signal, the dynamic reference criterion of generation.
4. the self study criterion method of formation of Audio Monitoring System according to claim 1, it is characterized in that: the criterion standard of Audio Monitoring System is by the variation range of passing through to analyze the comparing audio signal after the electrical equipment sound signal in the audio sensor that is installed in distinct device, different parts (acoustic pickup) certain cycle of operation of continuous acquisition, the audioref criterion at distinct device, different parts that generates automatically.
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| CN201310077995.7A CN103197630B (en) | 2013-03-12 | 2013-03-12 | The self study criterion method of formation of Audio Monitoring System |
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| CN201310077995.7A CN103197630B (en) | 2013-03-12 | 2013-03-12 | The self study criterion method of formation of Audio Monitoring System |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104301688A (en) * | 2014-10-29 | 2015-01-21 | 杭州凯达电力建设有限公司 | Method and system for monitoring sounds |
| CN106289404A (en) * | 2016-08-27 | 2017-01-04 | 薛晓辉 | A kind of device saving Building Power Distribution facility power consumption |
| CN113376457A (en) * | 2021-05-10 | 2021-09-10 | 首钢京唐钢铁联合有限责任公司 | Equipment operation state detection method, system, device, equipment and medium |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| EP4403830A1 (en) | 2023-01-23 | 2024-07-24 | Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. | Cooking appliance and method |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102270879A (en) * | 2010-06-02 | 2011-12-07 | 李景禄 | Equipment audio monitoring system of unattended substation |
| CN102322943A (en) * | 2011-06-13 | 2012-01-18 | 河北省电力公司超高压输变电分公司 | Detection system and method for sound abnormality of power equipment |
| CN102692887A (en) * | 2011-09-14 | 2012-09-26 | 吉林省电力有限公司通化供电公司 | Device for monitoring online state of power transformer based on audio identification technology |
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2013
- 2013-03-12 CN CN201310077995.7A patent/CN103197630B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102270879A (en) * | 2010-06-02 | 2011-12-07 | 李景禄 | Equipment audio monitoring system of unattended substation |
| CN102322943A (en) * | 2011-06-13 | 2012-01-18 | 河北省电力公司超高压输变电分公司 | Detection system and method for sound abnormality of power equipment |
| CN102692887A (en) * | 2011-09-14 | 2012-09-26 | 吉林省电力有限公司通化供电公司 | Device for monitoring online state of power transformer based on audio identification technology |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104301688A (en) * | 2014-10-29 | 2015-01-21 | 杭州凯达电力建设有限公司 | Method and system for monitoring sounds |
| CN106289404A (en) * | 2016-08-27 | 2017-01-04 | 薛晓辉 | A kind of device saving Building Power Distribution facility power consumption |
| CN106289404B (en) * | 2016-08-27 | 2019-02-26 | 薛晓辉 | A kind of device for saving Building Power Distribution facility power consumption |
| CN113376457A (en) * | 2021-05-10 | 2021-09-10 | 首钢京唐钢铁联合有限责任公司 | Equipment operation state detection method, system, device, equipment and medium |
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Effective date of registration: 20210127 Address after: Room 1808, Huafeng building, Xinzhou Road, Futian District, Shenzhen, Guangdong 518000 Patentee after: Shenzhen Youpeng Electromechanical Equipment Co.,Ltd. Address before: Room 302, building 22, west of Changsha University of technology, 45 Chiling Road, Tianxin District, Changsha City, Hunan Province, 410076 Patentee before: Li Jinglu |
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