Earticle

초록

영어

This paper presents a computationally efficient graphics processing unit (GPU) implementation of a reliable fault diagnosis method using two-dimensional (2D) representation of vibration signals. The fault diagnosis method first converts time-domain vibration signals into 2D gray-level images to exploit texture information from the converted images. Then, the global dominant neighborhood structure (GNS) map is utilized to extract texture features by averaging local neighborhood structure (LNS) maps of central pixels. In addition, the principle component analysis (PCA) algorithm is employed to select only the most dominant features. Finally, the selected features are used as inputs to a one-against-all multi-class support vector machine (OAA-MCSVM) to identify each fault of the induction motor. Despite the fact that the 2D fault diagnosis methodology shows satisfactory classification accuracy, its computational complexity limits its use in real-time applications. To accelerate the 2D fault diagnosis method, this paper utilizes an NVIDIA GeForce GTX 580 GPU, where all tasks are executed in parallel. The experimental results indicate that the proposed GPU-based approach achieves about 118.5 faster operation than the equivalent sequential CPU implementation while maintaining 100% classification accuracy.

목차

Abstract
 1. Introduction
 2. Vibration Signals of an Induction Motor
 3. GNS Map-Based 2D Fault-Diagnosis Method
 4. GPU Map-Based Implementation of the 2D Fault Diagnosis Method
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Jia Uddin [ School of Electrical Engineering, University of Ulsan, South Korea ]
• Dinh Nguyen Van [ School of Electrical Engineering, Hanoi University of Science and Technology, Vietnam ]
• Jong-Myon Kim [ School of Electrical Engineering, University of Ulsan, South Korea ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605