Time–Frequency Envelope Analysis for Fault Detection of Rotating Machinery Signals with Impulsive Noise
Envelope analysis is a widely used tool for fault detection in rotating machines. In envelope analysis, impulsive noise contaminates the measured signal, making it difficult to extract the features of defects. This paper proposes a time–frequency envelope analysis that overcomes the effects of impul...
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| Format: | Article |
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MDPI AG
2021-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/12/5373 |
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| author | Dong-Hyeon Lee Chinsuk Hong Weui-Bong Jeong Sejin Ahn |
| author_facet | Dong-Hyeon Lee Chinsuk Hong Weui-Bong Jeong Sejin Ahn |
| author_sort | Dong-Hyeon Lee |
| collection | DOAJ |
| description | Envelope analysis is a widely used tool for fault detection in rotating machines. In envelope analysis, impulsive noise contaminates the measured signal, making it difficult to extract the features of defects. This paper proposes a time–frequency envelope analysis that overcomes the effects of impulsive noises. Envelope analysis is performed by dividing the signal into several sections through a time window. The effect of impulsive noises is eliminated by using the frequency characteristics of the short time rectangular wave. The proposed method was verified through simulation and experimental data. The simulation was conducted by mathematically modeling a cyclo-stationary process that characterizes rotating machinery signals. In addition, the effectiveness of the method was verified by the measured data of normal and defective air-conditioners produced on the actual assembly line. This simple proposed method is effective enough to detect the faults. In the future, the approaches of big data and deep learning will be required for the development of the prognostic health-management framework. |
| first_indexed | 2024-03-10T10:34:34Z |
| format | Article |
| id | doaj.art-dc5cb65636f94e819a2296fff17ba2d2 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T10:34:34Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-dc5cb65636f94e819a2296fff17ba2d22023-11-21T23:26:59ZengMDPI AGApplied Sciences2076-34172021-06-011112537310.3390/app11125373Time–Frequency Envelope Analysis for Fault Detection of Rotating Machinery Signals with Impulsive NoiseDong-Hyeon Lee0Chinsuk Hong1Weui-Bong Jeong2Sejin Ahn3School of Mechanical Engineering, Pusan National University, Busan 46241, KoreaSchool of Mechanical Engineering, Ulsan College, Ulsan 44022, KoreaSchool of Mechanical Engineering, Pusan National University, Busan 46241, KoreaDivision of Energy & Electric Engineering, Uiduk University, Gyeongju 38004, KoreaEnvelope analysis is a widely used tool for fault detection in rotating machines. In envelope analysis, impulsive noise contaminates the measured signal, making it difficult to extract the features of defects. This paper proposes a time–frequency envelope analysis that overcomes the effects of impulsive noises. Envelope analysis is performed by dividing the signal into several sections through a time window. The effect of impulsive noises is eliminated by using the frequency characteristics of the short time rectangular wave. The proposed method was verified through simulation and experimental data. The simulation was conducted by mathematically modeling a cyclo-stationary process that characterizes rotating machinery signals. In addition, the effectiveness of the method was verified by the measured data of normal and defective air-conditioners produced on the actual assembly line. This simple proposed method is effective enough to detect the faults. In the future, the approaches of big data and deep learning will be required for the development of the prognostic health-management framework.https://www.mdpi.com/2076-3417/11/12/5373fault detectionimpulsive noise environmentrotating machineryenvelope analysis |
| spellingShingle | Dong-Hyeon Lee Chinsuk Hong Weui-Bong Jeong Sejin Ahn Time–Frequency Envelope Analysis for Fault Detection of Rotating Machinery Signals with Impulsive Noise Applied Sciences fault detection impulsive noise environment rotating machinery envelope analysis |
| title | Time–Frequency Envelope Analysis for Fault Detection of Rotating Machinery Signals with Impulsive Noise |
| title_full | Time–Frequency Envelope Analysis for Fault Detection of Rotating Machinery Signals with Impulsive Noise |
| title_fullStr | Time–Frequency Envelope Analysis for Fault Detection of Rotating Machinery Signals with Impulsive Noise |
| title_full_unstemmed | Time–Frequency Envelope Analysis for Fault Detection of Rotating Machinery Signals with Impulsive Noise |
| title_short | Time–Frequency Envelope Analysis for Fault Detection of Rotating Machinery Signals with Impulsive Noise |
| title_sort | time frequency envelope analysis for fault detection of rotating machinery signals with impulsive noise |
| topic | fault detection impulsive noise environment rotating machinery envelope analysis |
| url | https://www.mdpi.com/2076-3417/11/12/5373 |
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