Title :
Data-Driven Fault Detection and Diagnosis Based on Envionment/Platform Simulation
Author :
Zhigang Yao ; Li Cheng
Author_Institution :
Opt. & Electron., Shijiazhuang Mech. Eng. Coll., Shijiazhuang, China
Abstract :
Motivated by the fact that individual unit of complex systems is not able to operate when it is isolated from the original plant. Functional duplicated platform of the original system based on CAN-Bus and hardware simulation is addressed in this study. the platform can provide all environmental stimulation signals for offline detection and diagnosis of individual unit. Meanwhile, based on dataflow, qualitative and quantitative knowledge of integrated system, construction of fault diagnosis system with knowledge active pushing, is proposed. This approach can realize integrated detection and diagnosis of faulty units by integrating server on environment platform. the effectiveness of proposed scheme is validated by experiments that have high availability and reliability, which shows its potential usage for fault detection and diagnosis of complex systems.
Keywords :
controller area networks; digital simulation; fault diagnosis; industrial control; large-scale systems; production equipment; CAN-bus; complex system; data-driven fault detection; dataflow; envionment-platform simulation; environmental stimulation signal; fault diagnosis system; faulty units; functional duplicated platform; hardware simulation; knowledge active pushing; offline detection; qualitative knowledge; quantitative knowledge; Circuit faults; Computational modeling; Computers; Data acquisition; Data models; Fault diagnosis; Servers; deteciton and diagnosis; environment platform; integration; knowledge pushing;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2646-9
DOI :
10.1109/ISCID.2012.264
