Data cleansing for energy-saving: a case of Cyber-Physical Machine Tools health monitoring system

Deng, Changyi, Guo, Ruifeng, Liu, Chao, Zhong, Ray Y. and Xu, Xun 2017. Data cleansing for energy-saving: a case of Cyber-Physical Machine Tools health monitoring system. International Journal of Production Research 56 (1-2) , pp. 1000-1015. 10.1080/00207543.2017.1394596

Full text not available from this repository.

Abstract

Cyber-Physical Production Systems (CPPS) often use wireless sensor networks (WSNs) for monitoring purposes. However, data from WSNs may be inaccurate and unreliable due to power exhaustion, noise and other issues. In order to achieve a reliable and accurate data acquisition while ensuring low energy consumption and long lifetime of WSNs, data cleansing algorithms for energy-saving are proposed in this research. The cleansing algorithms are computationally lightweight in local sensors and energy-efficient due to low energy consumption in communications. Dynamic voltage scaling and dynamic power management are adopted for reducing energy consumption, without compromising the performance at system level. A low-power protocol for sink node communication is proposed at network level. A health monitoring system for a Cyber-Physical Machine Tool (a typical example of CPPS) is designed. Experiment results show that the proposed energy-saving data cleansing algorithm yields high-performance and effective monitoring.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Publisher:	Taylor & Francis
ISSN:	0020-7543
Date of First Compliant Deposit:	21 May 2019
Date of Acceptance:	27 September 2017
Last Modified:	13 Mar 2021 02:34
URI:	https://orca.cardiff.ac.uk/id/eprint/122760

Citation Data

Cited 26 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item