Implementation of a Non-Linear Regression Model in Rolling Bearing Diagnostics
2022
Аутори
Savić, BiljanaUrošević, Vlade
Ivković, Nebojša
Milicević, Ivan
Popović, Marko
Gubeljak, Nenad
Šiniković, Goran
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
The reliable operation of a mechanical system is dependent on the condition of installed rolling bearings. This paper presents a measuring system and equipment for analyzing the condition of rolling bearings. The developed system is a modular device (VibroLog) for measuring several diagnostic parameters for bearings, including vibration, number of revolutions, temperature and sound pressure. The device is a data collector and analyzer. Software in the Java programming language for the analysis and presentation of data obtained by VibroLog has also been developed. This paper is concerned with the development of a mathematical model for the evaluation and prediction of the qualitative state of rolling bearings in real operating conditions. It also presents results of measurement and mathematical modelling of the results. The model was formed by non-linear regression analysis as one of the most widely used statistical techniques. The analysis of the experimental data showed that the rate ...of change of a variable is proportional to its actual value. The model was tested on several rolling bearings having different degrees of damage. The developed model makes it possible to evaluate and predict the condition of the bearing by measuring the sound pressure level, which is simpler than vibration measurement in real operating conditions. During testing, the model generated results within the prediction error limits. The developed vibrodiagnostic system and the created model enable condition assessment and prediction for a wide range of rolling bearings.
Кључне речи:
rolling bearings / prediction / non-linear regression analysis / diagnosticsИзвор:
Tehnički vjesnik, 2022, 29, 1, 314-321Издавач:
- Univ Osijek, Tech Fac, Slavonski Brod
Финансирање / пројекти:
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200132 (Универзитет у Крагујевцу, Технички факултет, Чачак) (RS-MESTD-inst-2020-200132)
DOI: 10.17559/TV-20201231113711
ISSN: 1330-3651
WoS: 000739837900011
Scopus: 2-s2.0-85123215678
Колекције
Институција/група
Mašinski fakultetTY - JOUR AU - Savić, Biljana AU - Urošević, Vlade AU - Ivković, Nebojša AU - Milicević, Ivan AU - Popović, Marko AU - Gubeljak, Nenad AU - Šiniković, Goran PY - 2022 UR - https://machinery.mas.bg.ac.rs/handle/123456789/3687 AB - The reliable operation of a mechanical system is dependent on the condition of installed rolling bearings. This paper presents a measuring system and equipment for analyzing the condition of rolling bearings. The developed system is a modular device (VibroLog) for measuring several diagnostic parameters for bearings, including vibration, number of revolutions, temperature and sound pressure. The device is a data collector and analyzer. Software in the Java programming language for the analysis and presentation of data obtained by VibroLog has also been developed. This paper is concerned with the development of a mathematical model for the evaluation and prediction of the qualitative state of rolling bearings in real operating conditions. It also presents results of measurement and mathematical modelling of the results. The model was formed by non-linear regression analysis as one of the most widely used statistical techniques. The analysis of the experimental data showed that the rate of change of a variable is proportional to its actual value. The model was tested on several rolling bearings having different degrees of damage. The developed model makes it possible to evaluate and predict the condition of the bearing by measuring the sound pressure level, which is simpler than vibration measurement in real operating conditions. During testing, the model generated results within the prediction error limits. The developed vibrodiagnostic system and the created model enable condition assessment and prediction for a wide range of rolling bearings. PB - Univ Osijek, Tech Fac, Slavonski Brod T2 - Tehnički vjesnik T1 - Implementation of a Non-Linear Regression Model in Rolling Bearing Diagnostics EP - 321 IS - 1 SP - 314 VL - 29 DO - 10.17559/TV-20201231113711 ER -
@article{ author = "Savić, Biljana and Urošević, Vlade and Ivković, Nebojša and Milicević, Ivan and Popović, Marko and Gubeljak, Nenad and Šiniković, Goran", year = "2022", abstract = "The reliable operation of a mechanical system is dependent on the condition of installed rolling bearings. This paper presents a measuring system and equipment for analyzing the condition of rolling bearings. The developed system is a modular device (VibroLog) for measuring several diagnostic parameters for bearings, including vibration, number of revolutions, temperature and sound pressure. The device is a data collector and analyzer. Software in the Java programming language for the analysis and presentation of data obtained by VibroLog has also been developed. This paper is concerned with the development of a mathematical model for the evaluation and prediction of the qualitative state of rolling bearings in real operating conditions. It also presents results of measurement and mathematical modelling of the results. The model was formed by non-linear regression analysis as one of the most widely used statistical techniques. The analysis of the experimental data showed that the rate of change of a variable is proportional to its actual value. The model was tested on several rolling bearings having different degrees of damage. The developed model makes it possible to evaluate and predict the condition of the bearing by measuring the sound pressure level, which is simpler than vibration measurement in real operating conditions. During testing, the model generated results within the prediction error limits. The developed vibrodiagnostic system and the created model enable condition assessment and prediction for a wide range of rolling bearings.", publisher = "Univ Osijek, Tech Fac, Slavonski Brod", journal = "Tehnički vjesnik", title = "Implementation of a Non-Linear Regression Model in Rolling Bearing Diagnostics", pages = "321-314", number = "1", volume = "29", doi = "10.17559/TV-20201231113711" }
Savić, B., Urošević, V., Ivković, N., Milicević, I., Popović, M., Gubeljak, N.,& Šiniković, G.. (2022). Implementation of a Non-Linear Regression Model in Rolling Bearing Diagnostics. in Tehnički vjesnik Univ Osijek, Tech Fac, Slavonski Brod., 29(1), 314-321. https://doi.org/10.17559/TV-20201231113711
Savić B, Urošević V, Ivković N, Milicević I, Popović M, Gubeljak N, Šiniković G. Implementation of a Non-Linear Regression Model in Rolling Bearing Diagnostics. in Tehnički vjesnik. 2022;29(1):314-321. doi:10.17559/TV-20201231113711 .
Savić, Biljana, Urošević, Vlade, Ivković, Nebojša, Milicević, Ivan, Popović, Marko, Gubeljak, Nenad, Šiniković, Goran, "Implementation of a Non-Linear Regression Model in Rolling Bearing Diagnostics" in Tehnički vjesnik, 29, no. 1 (2022):314-321, https://doi.org/10.17559/TV-20201231113711 . .