DocumentCode
2477303
Title
Status Recognition for Electrical Parameters of ESPCP Based on Biomimetic Pattern Recognition
Author
Shi Hai-tao ; Yu Yun-hua ; Kong Qian-qian
Author_Institution
Coll. of Inf. & Control Eng., China Univ. of Pet. (East China), Dongying, China
fYear
2010
fDate
22-23 May 2010
Firstpage
1
Lastpage
3
Abstract
Various fault types and difficult diagnosis restricted the improvement of economic benefit and system efficiency of electrical submersible progressing cavity pump (ESPCP) production system. A novel method for status recognition of electrical parameters in fault diagnosis of ESPCP based on biomimetic pattern recognition (BPR) is presented. Application results show the proposed BPR classifier produces significant accuracy for classification of ESPCP electrical parameters. Compared with the results based on support vector machine (SVM), the proposed method is more efficiency.
Keywords
biomimetics; fault diagnosis; pattern recognition; pumps; ESPCP electrical parameters; biomimetic pattern recognition; electrical submersible progressing cavity pump production system; fault diagnosis; support vector machine; Biomimetics; Business process re-engineering; Electrostatic precipitators; Frequency; Neurons; Pattern recognition; Petroleum; Shape; Support vector machine classification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems and Applications (ISA), 2010 2nd International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5872-1
Electronic_ISBN
978-1-4244-5874-5
Type
conf
DOI
10.1109/IWISA.2010.5473236
Filename
5473236
Link To Document