Title
Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review.
Abstract
Condition monitoring can reduce machine breakdown losses, increase productivity and operation safety, and therefore deliver significant benefits to many industries. The emergence of wireless sensor networks (WSNs) with smart processing ability play an ever-growing role in online condition monitoring of machines. WSNs are cost-effective networking systems for machine condition monitoring. It avoids cable usage and eases system deployment in industry, which leads to significant savings. Powering the nodes is one of the major challenges for a true WSN system, especially when positioned at inaccessible or dangerous locations and in harsh environments. Promising energy harvesting technologies have attracted the attention of engineers because they convert microwatt or milliwatt level power from the environment to implement maintenance-free machine condition monitoring systems with WSNs. The motivation of this review is to investigate the energy sources, stimulate the application of energy harvesting based WSNs, and evaluate the improvement of energy harvesting systems for mechanical condition monitoring. This paper overviews the principles of a number of energy harvesting technologies applicable to industrial machines by investigating the power consumption of WSNs and the potential energy sources in mechanical systems. Many models or prototypes with different features are reviewed, especially in the mechanical field. Energy harvesting technologies are evaluated for further development according to the comparison of their advantages and disadvantages. Finally, a discussion of the challenges and potential future research of energy harvesting systems powering WSNs for machine condition monitoring is made.
Year
DOI
Venue
2018
10.3390/s18124113
SENSORS
Keywords
Field
DocType
energy harvesting systems,machine condition monitoring,wireless sensor networks,maintenance-free
Energy harvesting,Electronic engineering,Machine condition monitoring,Engineering,Wireless sensor network
Journal
Volume
Issue
ISSN
18
12
1424-8220
Citations 
PageRank 
References 
2
0.44
22
Authors
5
Name
Order
Citations
PageRank
Xiaoli Tang193.55
Xianghong Wang223.14
Robert Cattley320.44
Fengshou Gu42323.43
Andrew Ball57217.29