Title :
Research on fault diagnosis of HT-60 drilling rig based on neural network expert system
Author :
Liu, Yin ; Zhang, Weiming ; Liao, Zhixin
Author_Institution :
Fac. of Mech. & Electron. Inf., China Univ. of Geosci., Wuhan, China
Abstract :
Combining the characteristics of drilling rig fault, a solution of fault diagnosis expert system based on artificial neural network is proposeed. The fault diagnosis system is designed for HT-60 drilling rig, which acquires knowledge by neural network and diagnoses by expert system. The system with characteristics of self-learning and self-adaptive can acquire knowledge from existing data in order to achieve the purpose of expanding knowledge, which maks up the inadequacies of traditional expert system. Through analyzing a variety of common faults and solutions, the software interface is established by using the Force Control software to achieve fault diagnosis which is based on artificial neural network expert system.
Keywords :
control engineering computing; diagnostic expert systems; drilling (geotechnical); electrical engineering computing; fault diagnosis; mechanical engineering computing; neural nets; HT-60 drilling rig fault diagnosis; artificial neural network expert system; force control software interface; Area measurement; Drilling; Torque; HT-60 drilling rig; expert system; fault diagnosis; neural network;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5619156