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논문검색

A New Surveillance Method of Machine Status using Big Data

원문정보

초록

영어

As the development of science and technology, especially the network and IT techniques, lots of enterprises are facing the floods of data, which brings new challenges such as the storage, processing, and application under the new era. As in the industry area, the data will increase in tremendous level and their relations are more and more complex. That results in great issues when enterprises are contemplating to using the rich information or knowledge hidden from the huge data sets. In order to investigate the trends of the machine status from big data, this paper examines the coal milling machine’s abrasion, which is usually monitored. The surveillance is changing along with the time, which is able to reflect the abrasion trends so that the machine maintenance and breakdown could be easily carried out. Given the characteristics of big data in industrial field, this method proposes a multi-scale system with the entropy and energy to reflect the machine status in large scales. Two experiments are carried out to examine the methods. It is founded that, as the time increasing, the changes are becoming larger.

목차

Abstract
 1. Introduction
 2. Multi-scale System
 3. The Multi-scale Real System
  3.1. Characteristics
  3.2. Scale Entropy and Energy
  3.3. Problem Description
 4. Multi-scale Status Surveillance based on Big Data
  4.1 Standard Model
  4.2. Residual Multi-scale Analysis
 5. Experiments and Discussions
 6. Conclusions
 References

저자정보

  • Fuzhen Xie School of Mechanical Engineering Xinyu University, Jiangxi Xinyu 338004, China

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