scholarly journals Analysis and Calibration of Sources of Electronic Error in PSD Sensor Response

Sensors ◽  
2016 ◽  
Vol 16 (5) ◽  
pp. 619 ◽  
Author(s):  
David Rodríguez-Navarro ◽  
José Lázaro-Galilea ◽  
Ignacio Bravo-Muñoz ◽  
Alfredo Gardel-Vicente ◽  
Georgios Tsirigotis
Keyword(s):  
Micromachines ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 279
Author(s):  
Kentaro Noda ◽  
Jian Sun ◽  
Isao Shimoyama

A tensor sensor can be used to measure deformations in an object that are not visible to the naked eye by detecting the stress change inside the object. Such sensors have a wide range of application. For example, a tensor sensor can be used to predict fatigue in building materials by detecting the stress change inside the materials, thereby preventing accidents. In this case, a sensor of small size that can measure all nine components of the tensor is required. In this study, a tensor sensor consisting of highly sensitive piezoresistive beams and a cantilever to measure all of the tensor components was developed using MEMS processes. The designed sensor had dimensions of 2.0 mm by 2.0 mm by 0.3 mm (length by width by thickness). The sensor chip was embedded in a 15 mm3 cubic polydimethylsiloxane (PDMS) (polydimethylsiloxane) elastic body and then calibrated to verify the sensor response to the stress tensor. We demonstrated that 6-axis normal and shear Cauchy stresses with 5 kPa in magnitudes can be measured by using the fabricated sensor.


2006 ◽  
Author(s):  
Yongcai Yang ◽  
Junsan Ma ◽  
Rimin Pan ◽  
Xiang Yu

1996 ◽  
Vol 5 (3) ◽  
pp. 507-517 ◽  
Author(s):  
M. Wolski ◽  
C.a. Bouman ◽  
J.P. Allebach ◽  
E. Walowit

2012 ◽  
Vol 18 (7-8) ◽  
pp. 1127-1138 ◽  
Author(s):  
José A. Sánchez-Durán ◽  
Óscar Oballe-Peinado ◽  
Julián Castellanos-Ramos ◽  
Fernando Vidal-Verdú

2018 ◽  
Vol 256 ◽  
pp. 853-860 ◽  
Author(s):  
Ahmet Şenocak ◽  
Cem Göl ◽  
Tamara V. Basova ◽  
Erhan Demirbaş ◽  
Mahmut Durmuş ◽  
...  

2003 ◽  
Vol 93 (1-3) ◽  
pp. 475-485 ◽  
Author(s):  
I. Jiménez ◽  
J. Arbiol ◽  
G. Dezanneau ◽  
A. Cornet ◽  
J.R. Morante

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Aixiang He ◽  
Jun Yu ◽  
Guangfen Wei ◽  
Yi Chen ◽  
Hao Wu ◽  
...  

Because the sensor response is dependent on its operating temperature, modulated temperature operation is usually applied in gas sensors for the identification of different gases. In this paper, the modulated operating temperature of microhotplate gas sensors combined with a feature extraction method based on Short-Time Fourier Transform (STFT) is introduced. Because the gas concentration in the ambient air usually has high fluctuation, STFT is applied to extract transient features from time-frequency domain, and the relationship between the STFT spectrum and sensor response is further explored. Because of the low thermal time constant, the sufficient discriminatory information of different gases is preserved in the envelope of the response curve. Feature information tends to be contained in the lower frequencies, but not at higher frequencies. Therefore, features are extracted from the STFT amplitude values at the frequencies ranging from 0 Hz to the fundamental frequency to accomplish the identification task. These lower frequency features are extracted and further processed by decision tree-based pattern recognition. The proposed method shows high classification capability by the analysis of different concentration of carbon monoxide, methane, and ethanol.


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