Damage Identification of Large Generator Stator Insulation Based on PZT Sensor Systems and Hybrid Features of Lamb Waves
Large generators are the principal pieces of equipment in power systems, and their operation reliability critically depends on the stator insulation. Damages in stator insulation will gradually lead to the failure and breakdown of generator. Due to the advantages of Lamb waves in Structural health m...
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| Format: | Article |
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MDPI AG
2018-08-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/9/2745 |
| _version_ | 1811184811286462464 |
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| author | Ruihua Li Hao Li Bo Hu |
| author_facet | Ruihua Li Hao Li Bo Hu |
| author_sort | Ruihua Li |
| collection | DOAJ |
| description | Large generators are the principal pieces of equipment in power systems, and their operation reliability critically depends on the stator insulation. Damages in stator insulation will gradually lead to the failure and breakdown of generator. Due to the advantages of Lamb waves in Structural health monitoring (SHM), in this study, a distributed piezoelectric (PZT) sensor system and hybrid features of the Lamb waves are introduced to identify stator insulation damage of large generator. A hierarchical probability damage-imaging (PDI) algorithm is proposed to tackle the material inhomogeneity and anisotropy of the stator insulation. The proposed method includes three steps: global detection using correlation coefficients, local detection using Time of flight (ToF) along with the amplitude of damage-scattered Lamb wave, and final images fusion. Wavelet Transform was used to extract the ToF of Lamb wave in terms of the time-frequency domain. Finite Element Modeling (FEM) simulation and experimental work were carried out to identify four typical stator insulation damages for validation, including inner void, inner delamination, puncture, and crack. Results show that the proposed method can precisely identify the location of stator insulation damage, and the reconstruction image can be used to identify the size of stator insulation damage. |
| first_indexed | 2024-04-11T13:18:47Z |
| format | Article |
| id | doaj.art-0c819fe0e12443e198f5c8ab13e376c9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T13:18:47Z |
| publishDate | 2018-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0c819fe0e12443e198f5c8ab13e376c92022-12-22T04:22:16ZengMDPI AGSensors1424-82202018-08-01189274510.3390/s18092745s18092745Damage Identification of Large Generator Stator Insulation Based on PZT Sensor Systems and Hybrid Features of Lamb WavesRuihua Li0Hao Li1Bo Hu2Department of Electrical Engineering, Tongji University, Shanghai 201804, ChinaCollege of Electrical Engineering, Shanghai University of Electrical Power, Shanghai 200090, ChinaDepartment of Electrical Engineering, Tongji University, Shanghai 201804, ChinaLarge generators are the principal pieces of equipment in power systems, and their operation reliability critically depends on the stator insulation. Damages in stator insulation will gradually lead to the failure and breakdown of generator. Due to the advantages of Lamb waves in Structural health monitoring (SHM), in this study, a distributed piezoelectric (PZT) sensor system and hybrid features of the Lamb waves are introduced to identify stator insulation damage of large generator. A hierarchical probability damage-imaging (PDI) algorithm is proposed to tackle the material inhomogeneity and anisotropy of the stator insulation. The proposed method includes three steps: global detection using correlation coefficients, local detection using Time of flight (ToF) along with the amplitude of damage-scattered Lamb wave, and final images fusion. Wavelet Transform was used to extract the ToF of Lamb wave in terms of the time-frequency domain. Finite Element Modeling (FEM) simulation and experimental work were carried out to identify four typical stator insulation damages for validation, including inner void, inner delamination, puncture, and crack. Results show that the proposed method can precisely identify the location of stator insulation damage, and the reconstruction image can be used to identify the size of stator insulation damage.http://www.mdpi.com/1424-8220/18/9/2745rotating machine insulationrotating machine insulation testingcrack detectionacoustic signal processingacoustic applications |
| spellingShingle | Ruihua Li Hao Li Bo Hu Damage Identification of Large Generator Stator Insulation Based on PZT Sensor Systems and Hybrid Features of Lamb Waves Sensors rotating machine insulation rotating machine insulation testing crack detection acoustic signal processing acoustic applications |
| title | Damage Identification of Large Generator Stator Insulation Based on PZT Sensor Systems and Hybrid Features of Lamb Waves |
| title_full | Damage Identification of Large Generator Stator Insulation Based on PZT Sensor Systems and Hybrid Features of Lamb Waves |
| title_fullStr | Damage Identification of Large Generator Stator Insulation Based on PZT Sensor Systems and Hybrid Features of Lamb Waves |
| title_full_unstemmed | Damage Identification of Large Generator Stator Insulation Based on PZT Sensor Systems and Hybrid Features of Lamb Waves |
| title_short | Damage Identification of Large Generator Stator Insulation Based on PZT Sensor Systems and Hybrid Features of Lamb Waves |
| title_sort | damage identification of large generator stator insulation based on pzt sensor systems and hybrid features of lamb waves |
| topic | rotating machine insulation rotating machine insulation testing crack detection acoustic signal processing acoustic applications |
| url | http://www.mdpi.com/1424-8220/18/9/2745 |
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