Defect detection in dc motors by applying neuro-fuzzy networks - Linh, Trần Hoài; Nhượng, Đinh Văn; Tuệ, Đặng Văn (Journal of Computer Science and Cybernetics, 2012)
DC electrical motor is one of the most popular motors used. However, like other devices, during the working time the DC motors may experience different types of defects. Designing devices for fast defect detection is necessary in order to support the safe working processes. In this article, the authors will present a solution to detect the problems in DC electrical motors by applying neuro-fuzzy networks and using only the instantaneous values of angle velocity of the motor. The TSK (Takaga – Sugeno – Kang) with 8 inference rules to process the angle velocity signals will allow to detect the failures and their parameters with the accuracy higher than 95%.