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Methodologies Of Using Neural Network And Fuzzy Logic Technologies For Motor Incipient Fault Detection by Mo-yuen Chow (North Carolina State Univ, Usa) at Abbey's Bookshop,
Methodologies Of Using Neural Network And Fuzzy Logic Technologies For Motor Incipient Fault Detection...
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Mo-yuen Chow (North Carolina State Univ, Usa)

Methodologies Of Using Neural Network And Fuzzy Logic Technologies For Motor Incipient Fault Detection

Mo-yuen Chow (North Carolina State Univ, Usa)

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English
World Scientific Publishing Co Pte Ltd
27 November 1997
Fuzzy set theory; Engines & power transmission; Neural networks & fuzzy systems
Introducing neural-network and fuzzy-logic technologies, this volume describes the advantages and challenges of using these technologies to solve motor fault-detection problems, and discusses several design considerations and methodologies in applying these techniques to motor-incipient fault detection.
By:  
Imprint:   World Scientific Publishing Co Pte Ltd
Country of Publication:   Singapore
Dimensions:   Height: 230mm,  Width: 160mm,  Spine: 14mm
Weight:   354g
ISBN:   9789810232658
ISBN 10:   9810232659
Pages:   160
Publication Date:  
Audience:   College/higher education ,  Professional and scholarly ,  Professional & Vocational ,  A / AS level ,  Further / Higher Education
Format:   Hardback
Publisher's Status:   Active
Introduction to motor incipient fault detection; brief description of artificial neural networks; brief description of fuzzy logic; motor fault detection illustration; design and training considerations of motor fault detection artificial neural networks; motor-incipient fault detection neural/fuzzy system; fuzzy set theoretic approach of the motor-incipient fault detection; future detection.

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