Please use this identifier to cite or link to this item:
http://localhost:8080/xmlui/handle/123456789/6405
Title: | Review Article Comparison of Fault Diagnosis Approaches in Industrial Wireless Networks: A Review |
Authors: | Al Mashhadany, Yousif Lilo, Moneer Ali Bin Haji Abu, Aminudin Latiff, L.A. |
Keywords: | Artificial intelligence challenges fault diagnosis industries |
Issue Date: | 2016 |
Publisher: | Research Journal of Applied Sciences, Engineering and Technology 12(12): 1190-1195, 2016 ISSN: 2040-7459; e-ISSN: 2040-7467 |
Abstract: | Wireless sensor networks have received increasing research attention and they can be found in every field of life. The industrial wireless sensor network is one of the boosting and emerging technologies for machine fault diagnosis and monitoring. This study provides a review on vibration fault diagnosis approaches in industrial wireless applications and discusses the causes of machine faults and challenges. Several advanced vibration approaches have been used to quantify machine operating conditions. These approaches provide a fault diagnosis mechanism and expert maintenance solutions through analysis of vibration. The review also shows a broad scope of research for developing a robust fault diagnosis approaches in the field of industrial wireless sensor networks. |
URI: | http://localhost:8080/xmlui/handle/123456789/6405 |
ISSN: | 2040-7467 |
Appears in Collections: | الهندسة الكهربائية |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.