The LESGIRgram: A New Method to Select the Optimal Demodulation Frequency Band for Rolling Bearing Faults
Resonance demodulation of vibration signals is a common method for extracting fault information from rolling bearings. Nonetheless, demodulation quality is dependent on frequency band location. Established methods such as the Fast Kurtogram, Autogram, SKRgram, etc. have achieved satisfactory results...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Machines |
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| Online Access: | https://www.mdpi.com/2075-1702/11/12/1052 |
| _version_ | 1797380257842462720 |
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| author | Tian Tian Guiji Tang Xiaolong Wang |
| author_facet | Tian Tian Guiji Tang Xiaolong Wang |
| author_sort | Tian Tian |
| collection | DOAJ |
| description | Resonance demodulation of vibration signals is a common method for extracting fault information from rolling bearings. Nonetheless, demodulation quality is dependent on frequency band location. Established methods such as the Fast Kurtogram, Autogram, SKRgram, etc. have achieved satisfactory results in some cases, but the results are not good in the presence of strong white Gaussian noise and random impulses. To solve these issues, an algorithm that selects the optimal demodulation frequency band (ODFB) based on the ratio of the logarithmic envelope spectrum Gini coefficient (LESGIRgram) is proposed. The core idea of this paper is to capture the difference between the LESGIgrams of health and fault signals and accordingly locate the frequency bands that contain the most fault information. Initially, the baseline is constructed by calculating the logarithmic envelope spectrum Gini coefficient matrix of the health bearing (<i>LESGI<sub>baseline</sub></i>). Next, the LESGI matrix of the fault bearing (<i>LESGI<sub>measured</sub></i>) is computed. The ratio of <i>LESGI<sub>measured</sub></i> to <i>LESGI<sub>baseline</sub></i> is calculated, and the ODFB can be selected with the maximum LESGIR. The fault signal is then filtered using this derived ODFB, and envelope analysis is performed to extract fault features. The proposed algorithm for detecting rolling bearing faults has been verified for accuracy and effectiveness through simulation and experimental data. |
| first_indexed | 2024-03-08T20:34:47Z |
| format | Article |
| id | doaj.art-6896961b4c5f478d8baa1b2a91c1e269 |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-08T20:34:47Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-6896961b4c5f478d8baa1b2a91c1e2692023-12-22T14:21:54ZengMDPI AGMachines2075-17022023-11-011112105210.3390/machines11121052The LESGIRgram: A New Method to Select the Optimal Demodulation Frequency Band for Rolling Bearing FaultsTian Tian0Guiji Tang1Xiaolong Wang2School of Energy, Power and Mechanical Engineering, North China Electric Power University, Baoding 071000, ChinaSchool of Energy, Power and Mechanical Engineering, North China Electric Power University, Baoding 071000, ChinaSchool of Energy, Power and Mechanical Engineering, North China Electric Power University, Baoding 071000, ChinaResonance demodulation of vibration signals is a common method for extracting fault information from rolling bearings. Nonetheless, demodulation quality is dependent on frequency band location. Established methods such as the Fast Kurtogram, Autogram, SKRgram, etc. have achieved satisfactory results in some cases, but the results are not good in the presence of strong white Gaussian noise and random impulses. To solve these issues, an algorithm that selects the optimal demodulation frequency band (ODFB) based on the ratio of the logarithmic envelope spectrum Gini coefficient (LESGIRgram) is proposed. The core idea of this paper is to capture the difference between the LESGIgrams of health and fault signals and accordingly locate the frequency bands that contain the most fault information. Initially, the baseline is constructed by calculating the logarithmic envelope spectrum Gini coefficient matrix of the health bearing (<i>LESGI<sub>baseline</sub></i>). Next, the LESGI matrix of the fault bearing (<i>LESGI<sub>measured</sub></i>) is computed. The ratio of <i>LESGI<sub>measured</sub></i> to <i>LESGI<sub>baseline</sub></i> is calculated, and the ODFB can be selected with the maximum LESGIR. The fault signal is then filtered using this derived ODFB, and envelope analysis is performed to extract fault features. The proposed algorithm for detecting rolling bearing faults has been verified for accuracy and effectiveness through simulation and experimental data.https://www.mdpi.com/2075-1702/11/12/1052optimal demodulation frequency bandthe improved Gini coefficientSKRgramrolling bearingfault diagnosis |
| spellingShingle | Tian Tian Guiji Tang Xiaolong Wang The LESGIRgram: A New Method to Select the Optimal Demodulation Frequency Band for Rolling Bearing Faults Machines optimal demodulation frequency band the improved Gini coefficient SKRgram rolling bearing fault diagnosis |
| title | The LESGIRgram: A New Method to Select the Optimal Demodulation Frequency Band for Rolling Bearing Faults |
| title_full | The LESGIRgram: A New Method to Select the Optimal Demodulation Frequency Band for Rolling Bearing Faults |
| title_fullStr | The LESGIRgram: A New Method to Select the Optimal Demodulation Frequency Band for Rolling Bearing Faults |
| title_full_unstemmed | The LESGIRgram: A New Method to Select the Optimal Demodulation Frequency Band for Rolling Bearing Faults |
| title_short | The LESGIRgram: A New Method to Select the Optimal Demodulation Frequency Band for Rolling Bearing Faults |
| title_sort | lesgirgram a new method to select the optimal demodulation frequency band for rolling bearing faults |
| topic | optimal demodulation frequency band the improved Gini coefficient SKRgram rolling bearing fault diagnosis |
| url | https://www.mdpi.com/2075-1702/11/12/1052 |
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