최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기IEEE transactions on industrial electronics : a publication of the IEEE Industrial Electronics Society, v.47 no.5, 2000년, pp.1021 - 1030
Liu, Xiang-Qun (Dept. of Autom. Control, Beijing Univ. of Aeronaut. & Astronaut., China) , Zhang, Hong-Yue , Liu, Jun , Yang, Jing
In this paper, fault detection and diagnosis of a permanent-magnet DC motor is discussed. Parameter estimation based on block-pulse function series is used to estimate the continuous-time model of the motor. The electromechanical parameters of the motor can be obtained from the estimated model parameters. The relative changes of electromechanical parameters are used to detect motor faults. A multilayer perceptron neural network is used to isolate faults based on the patterns of parameter changes. Experiments with a real motor validate the feasibility of the combined use of parameter estimation and neural network classification for fault detection and isolation of the motor.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.