Detection of bearing damage by statistic vibration analysis
| Parent link: | IOP Conference Series: Materials Science and Engineering Vol. 124 : Mechanical Engineering, Automation and Control Systems (MEACS2015).— 2016.— [012167, 6 p.] |
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| Autor principal: | |
| Autor Corporativo: | |
| Resumo: | Title screen The condition of bearings, which are essential components in mechanisms, is crucial to safety. The analysis of the bearing vibration signal, which is always contaminated by certain types of noise, is a very important standard for mechanical condition diagnosis of the bearing and mechanical failure phenomenon. In this paper the method of rolling bearing fault detection by statistical analysis of vibration is proposed to filter out Gaussian noise contained in a raw vibration signal. The results of experiments show that the vibration signal can be significantly enhanced by application of the proposed method. Besides, the proposed method is used to analyse real acoustic signals of a bearing with inner race and outer race faults, respectively. The values of attributes are determined according to the degree of the fault. The results confirm that the periods between the transients, which represent bearing fault characteristics, can be successfully detected. |
| Idioma: | inglês |
| Publicado em: |
2016
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| Colecção: | Mechanical Engineering Processes and Metal Treatment |
| Assuntos: | |
| Acesso em linha: | http://dx.doi.org/10.1088/1757-899X/124/1/012167 http://earchive.tpu.ru/handle/11683/33901 |
| Formato: | Recurso Electrónico Capítulo de Livro |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=648637 |
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| 200 | 1 | |a Detection of bearing damage by statistic vibration analysis |f E. A. Sikora | |
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| 225 | 1 | |a Mechanical Engineering Processes and Metal Treatment | |
| 300 | |a Title screen | ||
| 320 | |a [References: 14 tit.] | ||
| 330 | |a The condition of bearings, which are essential components in mechanisms, is crucial to safety. The analysis of the bearing vibration signal, which is always contaminated by certain types of noise, is a very important standard for mechanical condition diagnosis of the bearing and mechanical failure phenomenon. In this paper the method of rolling bearing fault detection by statistical analysis of vibration is proposed to filter out Gaussian noise contained in a raw vibration signal. The results of experiments show that the vibration signal can be significantly enhanced by application of the proposed method. Besides, the proposed method is used to analyse real acoustic signals of a bearing with inner race and outer race faults, respectively. The values of attributes are determined according to the degree of the fault. The results confirm that the periods between the transients, which represent bearing fault characteristics, can be successfully detected. | ||
| 461 | 0 | |0 (RuTPU)RU\TPU\network\2008 |t IOP Conference Series: Materials Science and Engineering | |
| 463 | 0 | |0 (RuTPU)RU\TPU\network\13617 |t Vol. 124 : Mechanical Engineering, Automation and Control Systems (MEACS2015) |o International Conference, 1–4 December 2015, Tomsk, Russia |o [proceedings] |v [012167, 6 p.] |d 2016 | |
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| 700 | 1 | |a Sikora |b E. A. |c specialist in the field of mechanical engineering |c associate Professor, Tomsk Polytechnic University, candidate of technical Sciences |f 1984- |g Evgeny Alexandrovich |3 (RuTPU)RU\TPU\pers\30704 |9 14984 | |
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