An intelligence diagnostic system for reciprocating machine

Author

Wenhua, Xu ; Kai, Fu

Author_Institution

Fac. of Mech. & Electr. Eng, Agric. Univ. of Hebei, China

Volume

2

fYear

1997

fDate

28-31 Oct 1997

Firstpage

1520

Abstract

A vibration diagnostic system for a reciprocating machine has been developed. Its main function is to monitor operation state and to diagnose faults for the reciprocating machine. The software has two parts, one in a diagnostic machine and the other in a PC. It can perform diagnosis on the spot, realize self learning and adapt to many types of machine. It takes main factor autoregressive model as a character extractor and the ANN model as classifier. With the combination of the two technologies, the system can perform data sampling, signal analysis, character extracting and fault recognition automatically. It reduces factors involved by human beings in a diagnosis process, so the accuracy of the diagnosis and the level of intelligence and automation has been raised

Keywords

autoregressive processes; computerised instrumentation; fault diagnosis; neural nets; pattern classification; ANN model; PC; autoregressive model; character extractor; data sampling; diagnosis process; diagnostic machine; intelligence diagnostic system; operation state; reciprocating machine; self learning; signal analysis; vibration diagnostic system; Character recognition; Condition monitoring; Data mining; Humans; Intelligent systems; Machine intelligence; Machine learning; Signal analysis; Signal sampling; Software performance;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4253-4

Type

conf

DOI

10.1109/ICIPS.1997.669280

Filename

669280