Abstract
This paper presents the development of wireless condition monitoring system for rotating machinery powered by a hybrid vibration based energy harvester. The self-powered condition monitoring system consists of three parts. The first part of the system is the energy harvester, the second part is the power management and the third part is the android based user interface. The system used a hybrid energy harvester (piezoelectric and electromagnetic) to harvest energy from the vibrating machine at a resonance frequency of 50±2 Hz and 0.25g ms-2 of acceleration. The maximum output power from the hybrid harvester was 3.00 mW at 200 kΩ of load resistor. The power management circuit efficiency was 85% with output power of 2.55 mW. An accelerometer sensor and a temperature sensor were connected to the power management unit to sense the vibration and temperature level of the machine. Data from the sensors were transmitted through the wireless Bluetooth dongle to the android phone for end user monitoring. An android application was developed to receive the acceleration and temperature condition monitoring. At maximum power, initial charging duration of the supercapacitor was 130 seconds, and duration for recharging to 8.2V was 15 seconds. Therefore, the self-powered system managed to transmit data to the android application 15 second’s intervals.
Metadata
Item Type: | Article |
---|---|
Creators: | Creators Email / ID Num. Mohd Resali, Mohd Sofwan UNSPECIFIED Salleh, Hanim UNSPECIFIED |
Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TJ Mechanical engineering and machinery > Machine construction (General) |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Mechanical Engineering |
Journal or Publication Title: | Journal of Mechanical Engineering (JMechE) |
UiTM Journal Collections: | UiTM Journal > Journal of Mechanical Engineering (JMechE) |
ISSN: | 18235514 |
Volume: | SI 4 |
Number: | 2 |
Page Range: | pp. 249-267 |
Keywords: | vibration, energy harvesting, condition monitoring, hybrid |
Date: | 2017 |
URI: | https://ir.uitm.edu.my/id/eprint/39047 |