DK2565658T3 - Fejldetektion baseret på strømsignaturanalyse af en generator - Google Patents
Fejldetektion baseret på strømsignaturanalyse af en generator Download PDFInfo
- Publication number
- DK2565658T3 DK2565658T3 DK12180667.3T DK12180667T DK2565658T3 DK 2565658 T3 DK2565658 T3 DK 2565658T3 DK 12180667 T DK12180667 T DK 12180667T DK 2565658 T3 DK2565658 T3 DK 2565658T3
- Authority
- DK
- Denmark
- Prior art keywords
- electrical signals
- generator
- fault
- detecting
- components
- Prior art date
Links
- 238000001514 detection method Methods 0.000 title claims description 28
- 238000004458 analytical method Methods 0.000 title claims description 23
- 238000000034 method Methods 0.000 claims description 31
- 238000001228 spectrum Methods 0.000 claims description 29
- 230000003595 spectral effect Effects 0.000 claims description 12
- 230000002159 abnormal effect Effects 0.000 claims description 4
- 230000009466 transformation Effects 0.000 claims 1
- 230000001131 transforming effect Effects 0.000 claims 1
- 238000012544 monitoring process Methods 0.000 description 26
- 238000005259 measurement Methods 0.000 description 12
- 238000010586 diagram Methods 0.000 description 5
- 230000035945 sensitivity Effects 0.000 description 5
- 230000005856 abnormality Effects 0.000 description 4
- 238000003745 diagnosis Methods 0.000 description 4
- 230000008030 elimination Effects 0.000 description 4
- 238000003379 elimination reaction Methods 0.000 description 4
- 230000006698 induction Effects 0.000 description 4
- 230000010355 oscillation Effects 0.000 description 4
- 238000006243 chemical reaction Methods 0.000 description 3
- 230000007547 defect Effects 0.000 description 3
- 230000005284 excitation Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000012552 review Methods 0.000 description 3
- 238000000926 separation method Methods 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 238000013459 approach Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000009877 rendering Methods 0.000 description 2
- 230000000052 comparative effect Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000002787 reinforcement Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000004804 winding Methods 0.000 description 1
Classifications
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- 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
- G01R31/34—Testing dynamo-electric machines
- G01R31/343—Testing dynamo-electric machines in operation
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D7/00—Controlling wind motors
- F03D7/02—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor
- F03D7/0264—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor for stopping; controlling in emergency situations
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D7/00—Controlling wind motors
- F03D7/02—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor
- F03D7/0272—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor by measures acting on the electrical generator
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D7/00—Controlling wind motors
- F03D7/02—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor
- F03D7/04—Automatic control; Regulation
- F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/72—Wind turbines with rotation axis in wind direction
Landscapes
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Sustainable Development (AREA)
- Sustainable Energy (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Tests Of Circuit Breakers, Generators, And Electric Motors (AREA)
Claims (11)
1. Fremgangsmåde (1000) til at detektere mekaniske fejl i en generator (150), hvilken fremgangsmåde omfatter: at erhverve elektriske signaler, som repræsenterer en driftstilstand af generatoren (150); at normalisere de elektriske signaler for at ekstrahere spektralinformation ved: at eliminere symmetriske komponenter fra et strømspektrum ved at kvadrere en øjeblikkelig værdi af et strømsignal af hver af en flerhed af faser og at summere de kvadrerede værdier; og at ekstrahere asymmetriske komponenter, som forekommer i strømspektret under unormale driftstilstande; og at detektere en fejl baseret på analysen af spektralinformationen.
2. Fremgangsmåden (1000) ifølge krav 1, hvor at detektere en fejl baseret på analysen af spektralinformationen omfatter at detektere en leje (120) -fejl eller en gearkasse (140) -fejl.
3. Fremgangsmåden (1000) ifølge et hvilket som helst af de foregående krav, hvor at erhverve elektriske signaler, som repræsenterer en driftstilstand af generatoren (150) omfatter at erhverve elektriske signaler for hver fase af flere faser af generatoren (150).
4. Fremgangsmåden (1000) ifølge et hvilket som helst af de foregående krav, hvor de elektriske signaler, som repræsenterer en driftstilstand af generatoren (150) omfatter strøm- og spændingssignaler.
5. Fremgangsmåden (1000) ifølge et hvilket som helst af de foregående krav, hvor strømspektret normaliseres baseret på mindst én af Fast Fourier-transformation, tidsfrekvensanalyse, og multimodal opløsningsanalyse.
6. Fremgangsmåden (1000) ifølge et hvilket som helst af de foregående krav, hvor strømspektret omfatter symmetriske komponenter, der udgør et generatorstrømspektrum underen normal driftstilstand af generatoren.
7. Fremgangsmåden (1000) ifølge et hvilket som helst af de foregående krav, yderligere omfattende: at erhverve et andet sæt af elektriske signaler, som repræsenterer en ikke-fejldriftstilstand af generatoren (150); at transformere de elektriske signaler, som repræsenterer driftstilstanden af generatoren, til hybride elektriske signaler under anvendelse af det andet sæt af elektriske signaler; at normalisere de hybride elektriske signaler for at ekstrahere spektralinformation; og at detektere en fejl baseret på analysen af spektralinformationen.
8. Fremgangsmåden (1000) ifølge krav 7, hvor at erhverve et andet sæt af elektriske signaler, som repræsentereren ikke-fejld riftstilstand af generatoren, omfatter at erhverve et andet sæt af elektriske signaler for hver fase af flere faser af generatoren.
9. Fremgangsmåden (1000) ifølge krav 7 eller krav 8, hvor at normalisere de hybride elektriske signaler for at ekstrahere spektralinformation omfatter: at dynamisk eliminere symmetriske komponenter fra de hybride elektriske signaler; at sammenligne en størrelse og fase af de asymmetriske komponenter i de hybride elektriske signaler med en størrelse og fase af det andet sæt af elektriske signaler; og at detektere en fejl, når de asymmetriske komponenter i de hybride elektriske signaler afviger fra størrelsen og fasen af det andet sæt af elektriske signaler.
10. Fremgangsmåden (1000) ifølge krav 9, hvor at detektere en fejl omfatter at detektere en fejl i rotoren (130) af generatoren (150).
11. System (100) til at detektere en mekanisk fejl afen generator (150), hvilket ; system omfatter: en eller flere sensorer (160) til at erhverve elektriske signaler, som repræsentereren driftstilstand af generatoren (150); en kontroller (170) til at normalisere de elektriske signaler for at ekstrahere spektralinformation, hvor nævnte kontroller (170) er i konfigureret til at implementere fremgangsmåden (100) ifølge et hvilket som helst af de foregående krav; og et fejldetektionenhedsmodul (190) til at detektere en eller flere fejl i generatoren (150) baseret på analysen af den ekstraherede spektralinformation.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US13/219,753 US8994359B2 (en) | 2011-08-29 | 2011-08-29 | Fault detection based on current signature analysis for a generator |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| DK2565658T3 true DK2565658T3 (da) | 2018-11-26 |
Family
ID=47115208
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| DK12180667.3T DK2565658T3 (da) | 2011-08-29 | 2012-08-16 | Fejldetektion baseret på strømsignaturanalyse af en generator |
Country Status (3)
| Country | Link |
|---|---|
| US (1) | US8994359B2 (da) |
| EP (1) | EP2565658B1 (da) |
| DK (1) | DK2565658T3 (da) |
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| US9618037B2 (en) | 2008-08-01 | 2017-04-11 | Honeywell International Inc. | Apparatus and method for identifying health indicators for rolling element bearings |
| US8958995B2 (en) | 2009-04-02 | 2015-02-17 | Honeywell International Inc. | System and method for monitoring rotating and reciprocating machinery |
| US8963733B2 (en) * | 2012-02-13 | 2015-02-24 | Honeywell International Inc. | System and method for blind fault detection for rotating machinery |
| US10591519B2 (en) | 2012-05-29 | 2020-03-17 | Nutech Ventures | Detecting faults in wind turbines |
| US10359473B2 (en) * | 2012-05-29 | 2019-07-23 | Nutech Ventures | Detecting faults in turbine generators |
| US9645046B2 (en) * | 2012-12-17 | 2017-05-09 | General Electric Company | Fault detection system and associated method |
| US20140303913A1 (en) * | 2013-04-08 | 2014-10-09 | General Electric Company | Broken rotor bar detection based on current signature analysis of an electric machine |
| CN103675589B (zh) * | 2013-11-19 | 2016-05-18 | 中国矿业大学 | 开关磁阻电机功率变换器短路故障母线电流诊断方法 |
| CN103808509A (zh) * | 2014-02-19 | 2014-05-21 | 华北电力大学（保定） | 一种基于人工智能算法的风机齿轮箱故障诊断方法 |
| US10317467B2 (en) * | 2014-05-19 | 2019-06-11 | Schweitzer Engineering Laboratories, Inc. | Synchronous machine monitoring and determination of a loss-of-field event using time stamped electrical and mechanical data |
| CN107076639B (zh) * | 2014-09-05 | 2019-09-24 | Abb瑞士股份有限公司 | 监测涡轮发电机中的扭转振荡 |
| GB201421135D0 (en) | 2014-11-28 | 2015-01-14 | Rolls Royce Plc | Assessment method |
| US9618583B2 (en) * | 2015-03-10 | 2017-04-11 | Mitsubishi Electric Research Laboratories, Inc | Fault detection in induction motors based on current signature analysis |
| US9702938B2 (en) * | 2015-03-18 | 2017-07-11 | Caterpillar Inc. | Method and apparatus for detecting phase imbalance of an electrical component in a machine |
| US10429419B2 (en) * | 2015-03-26 | 2019-10-01 | The University Of Akron | System and method for iterative condition monitoring and fault diagnosis of electric machines |
| ES2613902B1 (es) * | 2015-11-26 | 2018-03-14 | Gamesa Innovation & Technology, S.L. | Método y sistemas de monitorización en tiempo real del estado del aislamiento de los devanados de generadores eólicos |
| CN105628383B (zh) * | 2016-02-01 | 2017-02-22 | 东南大学 | 基于改进型lssvm迁移学习的轴承故障诊断方法和系统 |
| US10273940B2 (en) | 2016-05-12 | 2019-04-30 | General Electric Company | System and method for detecting pitch bearing damage in a wind turbine |
| JP6665062B2 (ja) * | 2016-08-31 | 2020-03-13 | Ntn株式会社 | 状態監視装置 |
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| US10852214B2 (en) | 2017-05-19 | 2020-12-01 | Nutech Ventures | Detecting faults in wind turbines |
| US10495693B2 (en) * | 2017-06-01 | 2019-12-03 | General Electric Company | Wind turbine fault detection using acoustic, vibration, and electrical signals |
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| US10656051B2 (en) | 2017-07-26 | 2020-05-19 | Caterpillar Inc. | System and method for detecting wear or failure of genset power system coupling |
| US11473564B2 (en) | 2018-01-18 | 2022-10-18 | General Electric Company | System and method for monitoring a wind turbine pitch bearing |
| WO2019167086A1 (en) * | 2018-03-01 | 2019-09-06 | Aurobinda Routray | A system for assessment of multiple faults in induction motors |
| CN109061474A (zh) | 2018-10-15 | 2018-12-21 | 株洲中车时代电气股份有限公司 | 一种电机轴承故障诊断装置 |
| GB2589761B (en) | 2019-01-08 | 2021-12-08 | Panoramic Power Ltd | A method for determining an alternate current motor fault in a non-variable frequency device based on current analysis |
| CN111819452A (zh) * | 2019-02-02 | 2020-10-23 | 深圳市大疆创新科技有限公司 | 电机运行状态的获取方法和装置 |
| US20220187809A1 (en) * | 2019-03-26 | 2022-06-16 | Jfe Steel Corporation | Process state monitoring device and process state monitoring method |
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| US11099101B2 (en) | 2019-05-03 | 2021-08-24 | Mitsubishi Electric Research Laboratories, Inc. | Method for estimating bearing fault severity for induction motors |
| CN110779724B (zh) * | 2019-11-20 | 2022-03-11 | 重庆邮电大学 | 一种基于频域组稀疏降噪的轴承故障诊断方法 |
| CN110907170B (zh) * | 2019-11-30 | 2021-03-16 | 华能如东八仙角海上风力发电有限责任公司 | 一种风电机组齿轮箱轴承温度状态监测与故障诊断方法 |
| CN113125953B (zh) * | 2020-01-15 | 2022-12-09 | 江苏龙源风电技术培训有限公司 | 一种风力发电机组故障判断方法及其故障判断设备 |
| EP4107391A4 (en) * | 2020-02-18 | 2024-03-27 | Margaret Paietta | METHOD AND SYSTEM FOR MONITORING THE CONDITION OF WIND TURBINE COMPONENTS |
| CN111456915A (zh) * | 2020-03-30 | 2020-07-28 | 上海电气风电集团股份有限公司 | 风机机舱内部部件的故障诊断装置及方法 |
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| CN114415026B (zh) * | 2022-03-28 | 2022-06-24 | 爱科赛智能科技(浙江)有限公司 | 一种基于电流和相位识别的电机故障诊断系统及方法 |
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| US7941281B2 (en) * | 2008-12-22 | 2011-05-10 | General Electric Company | System and method for rotor blade health monitoring |
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2011
- 2011-08-29 US US13/219,753 patent/US8994359B2/en active Active
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2012
- 2012-08-16 DK DK12180667.3T patent/DK2565658T3/da active
- 2012-08-16 EP EP12180667.3A patent/EP2565658B1/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| EP2565658A1 (en) | 2013-03-06 |
| US8994359B2 (en) | 2015-03-31 |
| US20130049733A1 (en) | 2013-02-28 |
| CN103033745A (zh) | 2013-04-10 |
| EP2565658B1 (en) | 2018-10-10 |
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