首页 /研究 /Fault diagnosis in robotic manipulators using artificial neural networks and fuzzy logic
MANIPULATION

Fault diagnosis in robotic manipulators using artificial neural networks and fuzzy logic

Mohamed Salah Khireddine, Kheireddine Chafaa, Noureddine Slimane, Abdelhalim Boutarfa

发表年份
2014
引用次数
9

摘要

Computational intelligence techniques are being investigated as extension of the traditional fault diagnosis methods. This paper presents a scheme for fault detection and isolation (FDI) via artificial neural networks and fuzzy logic. It deals with sensors and actuator fault of a three links scara robot. The proposed FDI approach is implemented on Matlab/Simulink software and tested under several types of faults. The obtained results improving the importance of this method. Then, the actuator and sensor fault are detected and isolated successfully.

关键词

SCARAFault detection and isolationArtificial neural networkFuzzy logicFault (geology)Computer scienceActuatorControl engineeringMATLABArtificial intelligence

相关论文

查看 MANIPULATION 分类全部论文