Detecting finger gestures with a wrist worn piezoelectric sensor array

Author(s):  
Riley Booth ◽  
Peter Goldsmith
Author(s):  
Qibo Mao ◽  
Yuande Wang ◽  
Shizuo Huang

In this study, a new methodology is presented to detect the sensor fault for piezoelectric array based on the filtered frequency response function (FRF) shapes. The proposed method does not require prior knowledge about healthy piezoelectric array. First, the imaginary parts of FRFs from the piezoelectric array during vibration are measured and normalized to obtain the FRF shapes in different frequencies. Then the irregularities in these FRF shapes are extracted by using high-pass filter with properly chosen cut-off frequency. These abnormal irregularities on the filtered FRF shape curves indicate the location of the faulty sensor, due to the irregularity of FRF shapes introduced by the faulty piezoelectric element. The proposed sensor fault method is experimentally demonstrated on a clamped-clamped steel beam mounted with piezoelectric buzzer array. Two common piezoelectric sensor fault types including sensor breakage and debonding are evaluated. The experimental results indicate that the proposed method has great potential in the detection of the sensor fault for piezoelectric array as it is simple and does not require the FRF data of the healthy sensor array as a baseline.


2011 ◽  
Vol 421 ◽  
pp. 674-678
Author(s):  
Min Ming Tong ◽  
Le Jian An ◽  
Shou Feng Tang ◽  
Zi Hui Ren

A piezoelectric sensor array is introduced for the analysis of gas in mine. This sensor array is made of three different gas-sensitive piezoelectric sensors to detect an explosive gas mixture of methane, butane and hexane. The gas analysis is very important to reliable warning of explosion risk in mine. Because of cross sensing to gas for each sensor of sensor array, we use BP neural network in the artificial neural networks to process the sensing signal to get the concentration of methane, butane and hexane in the combustible gas mixture. Experimental results show that the analysis error is less than 5% and meets the requirements of safety monitoring.


2017 ◽  
Vol 29 (17) ◽  
pp. 3436-3443 ◽  
Author(s):  
Hwee Kwon Jung ◽  
Gyuhae Park

This article presents a technique for detecting structural impact and damage by integrating passive and active-sensing approaches. An L-shaped piezoelectric sensor array was used to detect and localize impacts by measuring the response of structures. It was found that since this method does not require prior knowledge of structures such as the direction-dependent wave velocity profiles, accurate results could be achieved even on anisotropic structures. This sensor array was then extended to include an active-sensing approach, and the same sensor array was used for damage detection by measuring scattering and reflected waves. A series of experiments was carried out to demonstrate the proposed techniques. The superior capability of the proposed techniques was experimentally demonstrated.


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