Adaptive neuro-fuzzy prediction of operation of the bucket wheel drive based on wear of cutting elements
Објеката
- Тип
- Рад у часопису
- Верзија рада
- објављена верзија
- Језик
- енглески
- Креатор
- Filip Miletić, Predrag D. Jovančić, Milos Milovančević, Dragan Ignjatović
- Извор
- Advances in Engineering Software
- Издавач
- Elsevier BV
- Датум издавања
- 2020
- Сажетак
- The capacity of the rotor excavator depends largely on the operation of the subsystem for digging. There is a great contribution to the correct and sharp teeth when the capacity is the highest. In the function of time, the teeth become clogged due to abrasive wear, or changes in their geometric shape. To analyze the bucket wheel drive in depend on wear of the cutting elements in this study adaptive neuro fuzzy inference system (ANFIS) approach was implemented. ANFIS is a type of artificial neural network combined with fuzzy logic inference which is suitable for nonlinear data samples. The main goal of the study was to establish dependence on how the wear of cutting elements affects the operation of the bucket wheel drive. According to the results prediction of the horizontal frequency has the highest accuracy (R2= 0.7612, r = 0.8724, RMSE = 91.4881). Combining specific energy consumption and vibration on the input pair of the shaft would make a major step forward from existing scientific knowledge.
- том
- 146
- Број
- -
- doi
- 10.1016/j.advengsoft.2020.102824
- issn
- 0965-9978
- Subject
- Pogon rotornog točka, habanje, rezni elementi, ANFIS
- Bucket wheel drive, Wear, Cutting element, ANFIS
- Шира категорија рада
- M20
- Ужа категорија рада
- М21а
- Права
- Затворени приступ
- Лиценца
- Creative Commons – Attribution-NonComercial 4.0 International
- Формат
Filip Miletić, Predrag D. Jovančić, Milos Milovančević, Dragan Ignjatović. "Adaptive neuro-fuzzy prediction of operation of the bucket wheel drive based on wear of cutting elements" in Advances in Engineering Software, Elsevier BV (2020). https://doi.org/10.1016/j.advengsoft.2020.102824
This item was submitted on 7. децембар 2021. by [anonymous user] using the form “Рад у часопису” on the site “Радови”: http://dr.rgf.bg.ac.rs/s/repo
Click here to view the collected data.