Next Article in Journal
Exploiting Layered Multi-Path Routing Protocols to Avoid Void Hole Regions for Reliable Data Delivery and Efficient Energy Management for IoT-Enabled Underwater WSNs
Next Article in Special Issue
3D LiDAR-Based Precision Vehicle Localization with Movable Region Constraints
Previous Article in Journal
Long-Term Stable Online Acetylene Detection by a CEAS System with Suppression of Cavity Length Drift
Previous Article in Special Issue
Visual-Acoustic Sensor-Aided Sorting Efficiency Optimization of Automotive Shredder Polymer Residues Using Circularity Determination
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Development of a Wireless Mesh Sensing System with High-Sensitivity LiNbO3 Vibration Sensors for Robotic Arm Monitoring

1
Department of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan City 71005, Taiwan
2
Institute of Mechatronic System Engineering, National University of Tainan, Tainan City 70005, Taiwan
3
Department of Mechanical Engineering and Advanced Institute of Manufacturing with High-tech Innovations, National Chung Cheng University, Chiayi County 62102, Taiwan
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(3), 507; https://doi.org/10.3390/s19030507
Submission received: 10 December 2018 / Revised: 15 January 2019 / Accepted: 23 January 2019 / Published: 26 January 2019
(This article belongs to the Special Issue I3S 2018 Selected Papers)

Abstract

In recent years, multi-axis robots are indispensable in automated factories due to the rapid development of Industry 4.0. Many related processes were required to have the increasing demand for accuracy, reproducibility, and abnormal detection. The monitoring function and immediate feedback for correction is more and more important. This present study integrated a highly sensitive lithium niobate (LiNbO3) vibration sensor as a sensor node (SN) and architecture of wireless mesh network (WMN) to develop a monitoring system (MS) for the robotic arm. The advantages of the thin-film LiNbO3 piezoelectric sensor were low-cost, high-sensitivity and good electrical compatibility. The experimental results obtained from the vibration platform show that the sensitivity achieved 50 mV/g and the reaction time within 1 ms. The results of on-site testing indicated that the SN could be configured on the relevant equipment quickly and detect the abnormal vibration in specific equipment effectively. Each SN could be used more than 10 h at the 80 Hz transmission rate under WMN architecture and the loss rate of transmission was less than 0.01% within 20 m.
Keywords: multi-axis robots; LiNbO3 vibration sensor; wireless mesh network (WMN); sensor node (SN); monitoring system (MS) multi-axis robots; LiNbO3 vibration sensor; wireless mesh network (WMN); sensor node (SN); monitoring system (MS)

Share and Cite

MDPI and ACS Style

Du, Y.-C.; Lin, D.T.W.; Jen, C.-P.; Ng, C.W.; Chang, C.-Y.; Wen, Y.-X. Development of a Wireless Mesh Sensing System with High-Sensitivity LiNbO3 Vibration Sensors for Robotic Arm Monitoring. Sensors 2019, 19, 507. https://doi.org/10.3390/s19030507

AMA Style

Du Y-C, Lin DTW, Jen C-P, Ng CW, Chang C-Y, Wen Y-X. Development of a Wireless Mesh Sensing System with High-Sensitivity LiNbO3 Vibration Sensors for Robotic Arm Monitoring. Sensors. 2019; 19(3):507. https://doi.org/10.3390/s19030507

Chicago/Turabian Style

Du, Yi-Chun, David T.W. Lin, Chun-Ping Jen, Choon Wei Ng, Chi-Ying Chang, and Ya-Xuan Wen. 2019. "Development of a Wireless Mesh Sensing System with High-Sensitivity LiNbO3 Vibration Sensors for Robotic Arm Monitoring" Sensors 19, no. 3: 507. https://doi.org/10.3390/s19030507

APA Style

Du, Y.-C., Lin, D. T. W., Jen, C.-P., Ng, C. W., Chang, C.-Y., & Wen, Y.-X. (2019). Development of a Wireless Mesh Sensing System with High-Sensitivity LiNbO3 Vibration Sensors for Robotic Arm Monitoring. Sensors, 19(3), 507. https://doi.org/10.3390/s19030507

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop