TY - JOUR
T1 - Fundamental insights into the electrical signals of a piezoelectric sensor in a sliding condition
AU - Shin, Kwonsik
AU - Choi, Eunmin
AU - Sim, Minkyung
AU - Kang, Minsoo
AU - Choi, Ji Woong
AU - Cha, Seung Nam
AU - Kwon, Hyuk Jun
AU - Kang, Hongki
AU - Jang, Jae Eun
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/9
Y1 - 2022/9
N2 - The piezoelectric mechanism represents a promising approach for advanced sensors that measure physical factors such as pressures, strain levels and even temperature responses to various stimuli. However, a conventional analysis of piezoelectric signals is mainly related to the peak output voltage for normal force, meaning that there remain numerous challenges to overcome when analyzing piezoelectric signals over time corresponding to complex or dynamic situations. Here, a fundamental analysis of piezoelectric signals for a dynamic change situation induced by sliding motion and resulting in the partial deformation of a piezoelectric material is introduced. Given that a piezoelectric voltage at a certain time represents the sum value of diploe moments in all piezoelectric material segments, in this respect, some parts are compressed and others are released, and we compared the electric signals between small segments and one unit cell to obtain a clue about the signal process and to confirm the mathematical formula. Based on the results of piezoelectric signal fitting with the exponential and error function, general solutions that can model piezoelectric signals were proposed to create artificial piezoelectric signals which corresponded to each small segment of the piezoelectric material. By comparing the artificial signals and actually measured signals, the general solution was optimized and the induced artificial piezoelectric signals were found to have good reliability and reproducibility. Various depth profiles with sliding motion could be calculated from the combination of artificial signals in the 0.6 mm, 0.9 mm, and 1.2 mm pressing conditions using piezoelectric integral values. In addition, the calculated depth profiles had a resolution of approximately 100 µm, and simultaneously measurable depth profiles were improved with more artificial signals.
AB - The piezoelectric mechanism represents a promising approach for advanced sensors that measure physical factors such as pressures, strain levels and even temperature responses to various stimuli. However, a conventional analysis of piezoelectric signals is mainly related to the peak output voltage for normal force, meaning that there remain numerous challenges to overcome when analyzing piezoelectric signals over time corresponding to complex or dynamic situations. Here, a fundamental analysis of piezoelectric signals for a dynamic change situation induced by sliding motion and resulting in the partial deformation of a piezoelectric material is introduced. Given that a piezoelectric voltage at a certain time represents the sum value of diploe moments in all piezoelectric material segments, in this respect, some parts are compressed and others are released, and we compared the electric signals between small segments and one unit cell to obtain a clue about the signal process and to confirm the mathematical formula. Based on the results of piezoelectric signal fitting with the exponential and error function, general solutions that can model piezoelectric signals were proposed to create artificial piezoelectric signals which corresponded to each small segment of the piezoelectric material. By comparing the artificial signals and actually measured signals, the general solution was optimized and the induced artificial piezoelectric signals were found to have good reliability and reproducibility. Various depth profiles with sliding motion could be calculated from the combination of artificial signals in the 0.6 mm, 0.9 mm, and 1.2 mm pressing conditions using piezoelectric integral values. In addition, the calculated depth profiles had a resolution of approximately 100 µm, and simultaneously measurable depth profiles were improved with more artificial signals.
KW - Depth profile measurement
KW - Piezoelectric material
KW - Piezoelectric sensor
KW - Signal analysis
KW - Signal processing
UR - http://www.scopus.com/inward/record.url?scp=85132233766&partnerID=8YFLogxK
U2 - 10.1016/j.nanoen.2022.107487
DO - 10.1016/j.nanoen.2022.107487
M3 - Article
AN - SCOPUS:85132233766
SN - 2211-2855
VL - 100
JO - Nano Energy
JF - Nano Energy
M1 - 107487
ER -