z-logo
open-access-imgOpen Access
Self-powered wireless vibration-sensing system for machining monitoring
Author(s) -
TienKan Chung,
Hao Lee,
Chia-Yung Tseng,
Wen-Tuan Lo,
Chieh-Min Wang,
Wen-Chin Wang,
Chi-Jen Tu,
Pei-Yuan Tasi,
Jui-Wen Chang
Publication year - 2013
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.2009435
Subject(s) - accelerometer , vibration , wireless , energy (signal processing) , energy harvesting , process (computing) , wireless sensor network , rectification , condition monitoring , microelectromechanical systems , engineering , electrical engineering , computer science , electronic engineering , acoustics , voltage , materials science , telecommunications , physics , computer network , optoelectronics , quantum mechanics , operating system
In this paper, we demonstrate an attachable energy-harvester-powered wireless vibration-sensing module for milling-process monitoring. The system consists of an electromagnetic energy harvester, MEMS accelerometer, and wireless module. The harvester consisting of an inductance and magnets utilizes the electromagnetic-induction approach to harvest the mechanical energy from the milling process and subsequently convert the mechanical energy to an electrical energy. Furthermore, through an energy-storage/rectification circuit, the harvested energy is capable of steadily powering both the accelerometer and wireless module. Through integrating the harvester, accelerometer, and wireless module, a self-powered wireless vibration-sensing system is achieved. The test result of the system monitoring the milling process shows the system successfully senses the vibration produced from the milling and subsequently transmits the vibration signals to the terminal computer. Through analyzing the vibration data received by the terminal computer, we establish a criterion for reconstructing the status, condition, and operating-sequence of the milling process. The reconstructed status precisely matches the real status of the milling process. That is, the system is capable of demonstrating a real-time monitoring of the milling process.

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