Application of the Dither Technology in a Fault Detection System

Author:

Chen Na1,Yang Shao Pu2,Pan Cun Zhi2

Affiliation:

1. Beijing Jiaotong University

2. Shijiazhuang Tiedao University

Abstract

In a fault detection system A/D conversion is a necessary step, in which quantization issues are unavoidable. Problems about quantization effects can be solved properly by using the dither technique. Firstly quantization problems of A/D conversion in a fault diagnosis system are discussed. Then the principle of dithering technique is introduced from the view of probability statistics. In further more, it is tested that fault signals whose amplitude is less than the quantization interval can be extracted, and that coherent harmonic interference in quantizing process can also be eliminated. Finally the result shows that by using dither technique the system can gain an enhanced level of fault detection with a faint signal-to-noise ratio loss, which has a direct guidance on engineering design in sensor-signal-sampling system.

Publisher

Trans Tech Publications, Ltd.

Reference8 articles.

1. J.D. Wu and S.Y. Liao: submitted to Expert Systems with Applications (2010).

2. A.B. Qiu, C.L. Wen and B. Jiang: submitted to Chinese Journal of Electronics (2010). (In Chinese).

3. J . Zhang, Y.M. Bo and M. lv: submitted to Journal of Nanjing University of Science and Technology (Natural Science) (2010). (In Chinese).

4. P. Zhang, in: Fault detection approaches for sampled-data systems. Beijing, Tsinghua University Publishers (2002). (In Chinese).

5. S.X. Ding, in: Model-based fault diagnosis techniques: design schemes, Algorithms, and tools. Berlin Heidelberg, Springer-Verlag (2008).

Cited by 1 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

1. Enhancement of MRI-based Signal-to-Noise Ratio with Noise Scrambling;Proceedings of the 2022 9th International Conference on Biomedical and Bioinformatics Engineering;2022-11-10

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