Adaptive neuro-fuzzy prediction of operation of the bucket wheel drive based on wear of cutting elements. (August 2020)

• Record Type: Journal Article
• Authors: Miletić, Filip; Jovančić, Predrag D.; Milovančević, Milos; Ignjatović, Dragan
• Is Part Of: Advances in engineering software. Volume 146(2020)
• Publication Date: 2020-08
• Subjects: Bucket wheel drive -- Wear -- Cutting element -- ANFIS; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2020.102824
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: The capacity of the rotor excavator. To the correct and sharp teeth when the capacity is the highest. Teeth become clogged due to abrasive wear. To establish dependence of cutting elements and operation of the bucket wheel drive. Abstract: 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 (R 2 = 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.