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Simultaneous Measurement of Belt Speed and Vibration Through Electrostatic Sensing and Data Fusion

Hu, Yonghui, Yan, Yong, Wang, Lijuan, Qian, Xiangchen, Wang, Xiaoyu (2016) Simultaneous Measurement of Belt Speed and Vibration Through Electrostatic Sensing and Data Fusion. IEEE Transactions on Instrumentation and Measurement, 65 (5). pp. 1130-1138. ISSN 0018-9456. (doi:10.1109/TIM.2015.2490958) (KAR id:55482)

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Accurate and reliable measurement of belt speed and vibration is of great importance in a range of industries. This paper presents a feasibility study of using an electrostatic sensor array and signal processing algorithms for the simultaneous measurement of belt speed and vibration in an online, continuous manner. The design, implementation, and assessment of an experimental system based on this concept are presented. In comparison with existing techniques, the electrostatic sensing method has the advantages of non-contact and simultaneous measurement, low cost, simple structure, and easy installation. The characteristics of electrostatic sensors are studied through finite-element modeling using a point charge moving in the sensing zone of the electrode. The sensor array is arranged in a 2 × 3 matrix, with the belt running between two rows of three identical sensing elements. The three signals in a row are cross correlated for speed calculation, and the results are then fused to give a final measurement. The vibration modes of the belt are identified by fusing the normalized spectra of vertically paired sensor signals. Experiments conducted on a two-pulley belt-driven rig show that the system can measure the belt speed with a relative error within ±2% over the range 2-10 m/s. More accurate and repeatable speed measurements are achieved for higher belt speeds and a shorter distance between the electrode and the belt. It is found that a stretched belt vibrates at the harmonics of the belt pass frequency and hence agrees the expected vibration characteristics.

Item Type: Article
DOI/Identification number: 10.1109/TIM.2015.2490958
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Tina Thompson
Date Deposited: 17 May 2016 15:07 UTC
Last Modified: 08 Dec 2022 21:07 UTC
Resource URI: (The current URI for this page, for reference purposes)
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Wang, Lijuan:
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