z-logo
open-access-imgOpen Access
Concurrent Fault Diagnosis for Rotating Machinery Based on Vibration Sensors
Author(s) -
Qinghua Zhang,
Qin Hu,
Guoxi Sun,
Xiaosheng Si,
Aisong Qin
Publication year - 2013
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2013/472675
Subject(s) - computer science , fault (geology) , vibration , bearing (navigation) , gas compressor , scale (ratio) , variety (cybernetics) , reliability engineering , control engineering , artificial intelligence , mechanical engineering , engineering , physics , quantum mechanics , seismology , geology
Rotating machinery is widely used in modern industry. It is one of the most critical components in a variety of machinery and equipment. Along with the continuous development of science and technology, the structures of rotating machinery become of larger scale, of higher speed, and more complicated, which results in higher probability of concurrent failure in practice. It is important to enable reliable, safe, and efficient operation of large-scale and critical rotating machinery, which requires us to achieve accurate diagnosis of concurrent fault, for example, rolling bearing diagnosis, gearbox diagnosis, and compressor diagnosis. In this paper, to achieve concurrent fault diagnosis for rotating machinery, which cannot be accurately diagnosed by existing methods, we develop an integrated method using artificial immune algorithm and evidential theory. © 2013 Qing-Hua Zhang et al.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom