Electro-Magnetic-Acoustic Transducers for Automatic Monitoring and Health Assessment of Transmission Lines

Author:

Shoureshi Rahmat A.1,Lim Sun-Wook1,Dolev Eli1,Sarusi Benny1

Affiliation:

1. School of Engineering and Computer Science, University of Denver, 2050 E. Iliff Ave., Boettcher Center East, Rm #228, Denver, CO 80208

Abstract

This paper presents analysis, design, development, and experimental verification of a non-destructive monitoring system for diagnosis of mechanical integrity of electric conductors based on the concept of Electro-Magnetic-Acoustic Transducers (EMAT). Electric conductors, in general, are exposed to harsh environments. Such conductors include electric transmission lines, anchor rods, and ground mat risers. For automatic failure detection and assessment of mechanical integrity of these conductors, in addition to an effective transducer, feature extraction and pattern recognition techniques have to be employed. Details of the sensor design, neural-based signature analysis, feature extraction, and experimental results of fault detection techniques are presented.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Reference22 articles.

1. Blitz, J., 1991, Electrical and magnetic methods of nondestructive testing, Adam Hilger.

2. Migliori, A., John, L. and Sarrao, 1997, Resonant Ultrasound Spectroscopy, John Wiley & Sons, Inc.

3. Maldague, P. V., 1997, Infrared Methodology and Technology, Gordon and Breach Science Publishers.

4. Baldi, P., and Hornik, K., 1989, “Neural networks and principal component analysis: Learning from examples without local minima,” IEEE Trans. Neural Netw., 2, pp. 53–58.

5. Foldiak, P., 1989, “Adaptive network for optimal linear feature extraction,” Proceedings of IEEE International Joint Conference on Neural Networks, Washington, D.C., 1, pp. 401–405.

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3