The Remote Fault Intelligent Diagnosis System Based on B/S Structure

Abstract:

The feasibility and superiority of the remote fault diagnosis system based on B/S structure is analyzed in this paper. The B/S structure is introduced and compared with C/S structure briefly. The paper summarize frame and main function module of the remote fault diagnosis system and introduce its key technology, such as data acquisition technology, data transmission technology between server and client, intelligent diagnosis technology, database technology etc. The hybrid model of support vector machine (SVM) and hidden markov models(HMM) is used as a intelligent diagnosis method of the system, and a new design which could improve the integrity and privacy of the system database data is applied. According to the diagnostic results to all kinds of simulated faults in the Bently vibration test bed, it shows the system is not only stable, reliable and high accuracy, but also has a certain application value to engineering.

• Periodical: Advanced Materials Research (Volumes 328-330)
• Pages: 1067-1071
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.328-330.1067
• Online since: September 2011
• Authors: Jia Liu, Chun Liang Zhang, Jian Li, Sen Li, Yue Hua Xiong
• Keywords: B/S Structure, Database, Fault Diagnosis

References

[1] T.M. Ren: Software Development Technology Base on B/S Structure, (Xidian University Publications, China 2006).

[2] L.R. Rabiner. A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. IEEE Feb 77(2): 257~286, (1989).

DOI: 10.1109/5.18626

[3] S.R. Gunn. Support Vector Machines for Classification and Regression[EB/OL]. (1998) [2010. 09. 16].

[4] Christopher J.C. Burges: Data Mining and Knowledge Discovery, 1998(2), p.121.

[5] Hsu C W, Chang C C, Lin C J. A Practical Guide to Support Vector Classification [EB/OL]. (2003) [2010. 09. 16].