Self-powered wireless vibration-sensing system for machining monitoring

Tien-Kan Chung; Hao Lee; Chia-Yung Tseng; Wen-Tuan Lo; Chieh-Min Wang; Wen-Chin Wang; Chi-Jen Tu; Pei-Yuan Tasi; Jui-Wen Chang

doi:10.1117/12.2009435

19 April 2013 Self-powered wireless vibration-sensing system for machining monitoring

Tien-Kan Chung, Hao Lee, Chia-Yung Tseng, Wen-Tuan Lo, Chieh-Min Wang, Wen-Chin Wang, Chi-Jen Tu, Pei-Yuan Tasi, Jui-Wen Chang

Author Affiliations +

Proceedings Volume 8692, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013; 86922U (2013) https://doi.org/10.1117/12.2009435
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2013, San Diego, California, United States

Abstract

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.

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Tien-Kan Chung, Hao Lee, Chia-Yung Tseng, Wen-Tuan Lo, Chieh-Min Wang, Wen-Chin Wang, Chi-Jen Tu, Pei-Yuan Tasi, and Jui-Wen Chang "Self-powered wireless vibration-sensing system for machining monitoring", Proc. SPIE 8692, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013, 86922U (19 April 2013); https://doi.org/10.1117/12.2009435

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