CN101063629A - Judging functional failure of electromechanical by speech recognition technology - Google Patents
Judging functional failure of electromechanical by speech recognition technology Download PDFInfo
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- CN101063629A CN101063629A CNA2006100764097A CN200610076409A CN101063629A CN 101063629 A CN101063629 A CN 101063629A CN A2006100764097 A CNA2006100764097 A CN A2006100764097A CN 200610076409 A CN200610076409 A CN 200610076409A CN 101063629 A CN101063629 A CN 101063629A
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Abstract
This invention relates to one sound identification technique rapid judgment and automatic control machine, power industry power system, transmission system, automobile force device abnormal sound to judge fault and process technique. Comparing with current test method, it fully uses the sound identification technique for its sound spectrum test technique.
Description
Technical field: utilize speech recognition technology to judge the technology of power plant's turbodynamo and big-and-middle-sized water pump functional failure of electromechanical fast.
Background technology: along with developing rapidly and Computer Control Technology perfect day by day of speech recognition technology.This patent will further utilize speech recognition technology to judge functional failure of electromechanical rapidly and accurately, in the hope of quick reflection, handle rapidly.
In electromechanical industries, many electromechanical equipments, motor and water pump industry be a kind of like this phenomenon of ubiquity all: promptly theoretically, measure electromechanical equipment and motor, water pump fault judgement in the process of moving, though can use various sensors, utilize photoelectric sensing, electromagnetic sensing, hall sensing, temperature and humidity sensing, CCD sensing or the like numerous.But from cost one is that price is expensive under many circumstances, and application technology complexity, technological means are difficult to reach sometimes; The 2nd, even fault occurred, these sensors also may not one detect surely generally speaking.In case when monitoring was come out, accident had taken place, and causes very big economic loss.
Summary of the invention: at electrical equipment, in the power industry, what we noticed is a universal phenomenon: general audio frequency or the non-audio sound of electromechanical equipment when the normal operation process has certain rule, and that equipment is under audio frequency under the abnormal conditions or non-audio sound and the normal condition is inequality.Utilize this point, this patent is taught and is utilized speech recognition technology, judges equipment quickly and accurately and whether is in normal condition, feeds back to computing machine.Reach the purpose that computer controlled automatic is handled.
Illustrate: the automatic People's Bank of China staircase motor of using in the motor in the oil field, the bowl mill of cement mill, the market etc., sound during operate as normal and the sound when improper are inconsistent.Experienced old technician knows what the sound of electromechanical equipment in the work of advancing in oneself operation is, and be in sound under the improper situation be what or the like.These are all for utilizing exhibiting one's skill to the full of speech recognition technology that most suitable application scenario is provided.
Speech recognition system has a cover self study process, can be with the sound typing under the normal condition, Hou in electromechanical equipment work, in case occur learning by oneself the different voice signal of process with speech recognition, different error codes will appear in this system.Also can be with fault sound input system, which kind of equipment judging more accurately of being is, fault has taken place in which kind of state.
Different with industrial wave test method in the past is, made full use of the speech manual detection technique in the speech recognition technology, it is than time domain relative method, and the frequency domain relative method has all striden forward major step, its record and relatively be vocal print, be the strong and weak embodiment that changes of frequency of the sound wave of different time.This invention has been exactly abundant utilizes this point to be extended to the industrial detection field.
Technology implementation scheme of the present invention is:
The first step, utilize sound transducer to sampled audio signal, because the frequency range of present Electret condenser microphone sensor can reach 50HZ---the part supersonic frequency (s.f.) scope of 20KHZ, so the extra in actual applications Dynamic Recognition scope of having brought into play speech recognition technology over one's competence.
Second step, utilize the speech recognition circuit plate of existing moulding, as speech recognition circuit plate and the function in the mobile phone of present application, various normal sound signals when electromechanical equipment is worked and improper sampled audio signal, and be stored in the storer of speech recognition circuit, become the comparison sample of many standards.Utilize sound transducer that sampled audio signal is gathered in real time when working online again, the speech recognition circuit plate is compared one by one to the signal of this collection and the comparison sample of the standard in the storer.And quick identification goes out the result of comparison, for example: the similarity of signal and No. 12 sample comparison is the most approaching, and No. 12 be normal sample, sampled result display device work so at this time under normal circumstances, if the similarity of signal and No. 16 sample comparison is the most approaching, and No. 12 be improper sample, sampled result display device so at this time is operated under the improper situation, because our known No. 16 sample is the fault sample of certain class, has just known that so also the fault of certain class has appearred in this equipment.
In the 3rd step, the result that the speech recognition circuit plate analysis is gone out is by display screen, or converts visual picture to microcomputer and show, and carries out voice suggestion with equipment such as loudspeaker simultaneously.
Below be we be used on the turbodynamo of power plant utilize speech recognition technology to judge steam turbine work the time the online measuring technique embodiment of fault.Speech recognition circuit is being started to walk the turbodynamo in the power plant, operation, normal and improper sound wave under the various states such as parking all collects in the storer of speech recognition circuit as sample space, and in generator operation, constantly gather the sound wave sample and compare with it, when detect with improper sound wave coupling as a result the time report to the police.
Fig. 1: this figure utilizes speech recognition technology cognitron electric fault principle as figure
Fig. 2: this figure is an equipment synoptic diagram of using this technology.
Fig. 3: this figure be this figure be used on the turbodynamo of power plant utilize speech recognition technology to judge steam turbine work the time the work synoptic diagram of fault.The first step: will go into the speech recognition circuit plate normally earlier, and deposit its storer in improper audio signal sample.Second step: sample is put in order numbering.The 3rd step: online in real time is carried out continual voice signal sampling, imports sound circuit at any time and compares, and calculate the result.The 4th step: be shown to the result on the computer screen or on the LCD display, voice suggestion simultaneously.
Fig. 4: sound circuit plate panel and keypad synoptic diagram.These keys are the system switching key, and the training key is sound collecting self study key when normal and improper when being initial, and operating ratio is a comparison key when running without interruption to key continuously, and single operating ratio is a comparison key when manually moving to key.
Claims (2)
1. turbodynamo that utilizes speech recognition technology to judge power plant fast, the technology of big-and-middle-sized pump motor fault, this is to utilize the application extension of speech recognition technology aspect the fault detect of electrical category.
2 technology according to claim 1, it is characterized in that: different with industrial wave test method in the past is, made full use of the speech manual detection technique in the speech recognition technology, it is than time domain relative method, the frequency domain relative method has all striden forward major step, its record and relatively be vocal print, be the strong and weak embodiment that changes of frequency of the sound wave of different time.This invention has been exactly abundant utilizes this point to be extended to the industrial detection field.
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| Application Number | Priority Date | Filing Date | Title |
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| CNA2006100764097A CN101063629A (en) | 2006-04-25 | 2006-04-25 | Judging functional failure of electromechanical by speech recognition technology |
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| CNA2006100764097A CN101063629A (en) | 2006-04-25 | 2006-04-25 | Judging functional failure of electromechanical by speech recognition technology |
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Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102157148A (en) * | 2010-12-31 | 2011-08-17 | 东莞电子科技大学电子信息工程研究院 | DTW (dynamic time warping) voice recognition-based truck examining method |
| CN101580198B (en) * | 2008-05-14 | 2013-04-10 | 株式会社日立制作所 | Elevator abnormity detector |
| CN103177732A (en) * | 2013-03-26 | 2013-06-26 | 航天科技控股集团股份有限公司 | Sound comparison processing detection system and detection method based on digital signal processor (DSP) |
| CN103258544A (en) * | 2013-04-15 | 2013-08-21 | 深圳市海云天科技股份有限公司 | Recording testing method, recording testing device, examination terminal and examination system |
| CN103744021A (en) * | 2013-12-23 | 2014-04-23 | 煤炭科学研究总院 | Apparatus and method for motor fault monitoring |
| CN103863188A (en) * | 2014-04-03 | 2014-06-18 | 安徽师范大学 | Vehicle voice recognition signal online self-diagnosis method |
| CN105244038A (en) * | 2015-09-30 | 2016-01-13 | 金陵科技学院 | Ore dressing equipment fault abnormity audio analyzing and identifying method based on HMM |
| CN109785460A (en) * | 2019-01-03 | 2019-05-21 | 深圳壹账通智能科技有限公司 | Vehicle trouble recognition methods, device, computer equipment and storage medium |
| CN110741266A (en) * | 2017-06-07 | 2020-01-31 | 维迪科研究所 | Method and apparatus for fault detection and protection of power switch electronics |
| CN110988534A (en) * | 2019-12-03 | 2020-04-10 | 北京特种机械研究所 | Performance test method for universal servo system |
| CN112397088A (en) * | 2019-08-12 | 2021-02-23 | 美光科技公司 | Predictive maintenance of automotive engines |
| CN112880812A (en) * | 2021-01-19 | 2021-06-01 | 广州特种机电设备检测研究院 | Escalator fault detection method, system and storage medium |
| CN113790911A (en) * | 2021-08-18 | 2021-12-14 | 中国长江电力股份有限公司 | Abnormal sound detection method based on sound frequency spectrum statistical law |
| TWI755929B (en) * | 2020-11-12 | 2022-02-21 | 力晶積成電子製造股份有限公司 | Seal tightness detection system and seal tightness detection method |
| US11830296B2 (en) | 2019-12-18 | 2023-11-28 | Lodestar Licensing Group Llc | Predictive maintenance of automotive transmission |
| US11853863B2 (en) | 2019-08-12 | 2023-12-26 | Micron Technology, Inc. | Predictive maintenance of automotive tires |
-
2006
- 2006-04-25 CN CNA2006100764097A patent/CN101063629A/en active Pending
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101580198B (en) * | 2008-05-14 | 2013-04-10 | 株式会社日立制作所 | Elevator abnormity detector |
| CN102157148A (en) * | 2010-12-31 | 2011-08-17 | 东莞电子科技大学电子信息工程研究院 | DTW (dynamic time warping) voice recognition-based truck examining method |
| CN103177732A (en) * | 2013-03-26 | 2013-06-26 | 航天科技控股集团股份有限公司 | Sound comparison processing detection system and detection method based on digital signal processor (DSP) |
| CN103177732B (en) * | 2013-03-26 | 2015-05-20 | 航天科技控股集团股份有限公司 | Sound comparison processing detection system and detection method based on digital signal processor (DSP) |
| CN103258544A (en) * | 2013-04-15 | 2013-08-21 | 深圳市海云天科技股份有限公司 | Recording testing method, recording testing device, examination terminal and examination system |
| CN103744021A (en) * | 2013-12-23 | 2014-04-23 | 煤炭科学研究总院 | Apparatus and method for motor fault monitoring |
| CN103863188A (en) * | 2014-04-03 | 2014-06-18 | 安徽师范大学 | Vehicle voice recognition signal online self-diagnosis method |
| CN105244038A (en) * | 2015-09-30 | 2016-01-13 | 金陵科技学院 | Ore dressing equipment fault abnormity audio analyzing and identifying method based on HMM |
| CN110741266A (en) * | 2017-06-07 | 2020-01-31 | 维迪科研究所 | Method and apparatus for fault detection and protection of power switch electronics |
| CN109785460A (en) * | 2019-01-03 | 2019-05-21 | 深圳壹账通智能科技有限公司 | Vehicle trouble recognition methods, device, computer equipment and storage medium |
| CN112397088A (en) * | 2019-08-12 | 2021-02-23 | 美光科技公司 | Predictive maintenance of automotive engines |
| US11853863B2 (en) | 2019-08-12 | 2023-12-26 | Micron Technology, Inc. | Predictive maintenance of automotive tires |
| CN110988534A (en) * | 2019-12-03 | 2020-04-10 | 北京特种机械研究所 | Performance test method for universal servo system |
| CN110988534B (en) * | 2019-12-03 | 2022-09-16 | 北京特种机械研究所 | Performance test method for universal servo system |
| US11830296B2 (en) | 2019-12-18 | 2023-11-28 | Lodestar Licensing Group Llc | Predictive maintenance of automotive transmission |
| TWI755929B (en) * | 2020-11-12 | 2022-02-21 | 力晶積成電子製造股份有限公司 | Seal tightness detection system and seal tightness detection method |
| CN112880812A (en) * | 2021-01-19 | 2021-06-01 | 广州特种机电设备检测研究院 | Escalator fault detection method, system and storage medium |
| CN113790911A (en) * | 2021-08-18 | 2021-12-14 | 中国长江电力股份有限公司 | Abnormal sound detection method based on sound frequency spectrum statistical law |
| CN113790911B (en) * | 2021-08-18 | 2023-05-16 | 中国长江电力股份有限公司 | Abnormal sound detection method based on sound spectrum statistics rule |
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