Experimental Study Comparing the Effectiveness of Physical Isolation and ANN Digital Compensation Methodologies at Eliminating the Stress Wave Effect Error on Piezoelectric Pressure Sensor
Stress wave, accompanied by explosion shock wave overpressure measurement and dynamic pressure calibration on shock tube, could cause error signals in the piezoelectric pressure sensor (PPS) used for measuring and calibrating. We may call this error the stress wave effect (SWE). In this paper, the S...
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doaj-cae866a453cc4609a3205777fd1eb4642020-11-25T02:34:38ZengMDPI AGSensors1424-82202020-04-01202397239710.3390/s20082397Experimental Study Comparing the Effectiveness of Physical Isolation and ANN Digital Compensation Methodologies at Eliminating the Stress Wave Effect Error on Piezoelectric Pressure SensorLei Feng0Tiehua Ma1School of Electrical and Control Engineering, North University of China, Taiyuan 030051, ChinaSchool of Electrical and Control Engineering, North University of China, Taiyuan 030051, ChinaStress wave, accompanied by explosion shock wave overpressure measurement and dynamic pressure calibration on shock tube, could cause error signals in the piezoelectric pressure sensor (PPS) used for measuring and calibrating. We may call this error the stress wave effect (SWE). In this paper, the SWE and its isolation from PPS were studied by using a split Hopkinson pressure bar (SHPB). In the experimental study of SWE, when increasing the input stress, the corresponding output signal of the PPS was analyzed, and the existence of SWE was verified using the result of the spectrum analysis of the output signal. The stress wave isolation pedestal used in the stress wave isolation experiment was made of nylon and plexiglass polymer materials. The effects of the isolation pedestal’s materials and length on the stress wave isolation were analyzed using the study results. Finally, an artificial neural network (ANN) was trained with the data of the SWE study and was further applied to compensate the SWE error of the PPS output signal. The compensating results were compared with the isolating results, and the advantages and disadvantages of the digital compensation and physical isolation methods were analyzed.https://www.mdpi.com/1424-8220/20/8/2397piezoelectric pressure sensor (PPS), stress wave effect (SWE), split Hopkinson pressure bar (SHPB), physical isolationdigital compensationartificial neural network (ANN) |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lei Feng Tiehua Ma |
spellingShingle |
Lei Feng Tiehua Ma Experimental Study Comparing the Effectiveness of Physical Isolation and ANN Digital Compensation Methodologies at Eliminating the Stress Wave Effect Error on Piezoelectric Pressure Sensor Sensors piezoelectric pressure sensor (PPS), stress wave effect (SWE), split Hopkinson pressure bar (SHPB), physical isolation digital compensation artificial neural network (ANN) |
author_facet |
Lei Feng Tiehua Ma |
author_sort |
Lei Feng |
title |
Experimental Study Comparing the Effectiveness of Physical Isolation and ANN Digital Compensation Methodologies at Eliminating the Stress Wave Effect Error on Piezoelectric Pressure Sensor |
title_short |
Experimental Study Comparing the Effectiveness of Physical Isolation and ANN Digital Compensation Methodologies at Eliminating the Stress Wave Effect Error on Piezoelectric Pressure Sensor |
title_full |
Experimental Study Comparing the Effectiveness of Physical Isolation and ANN Digital Compensation Methodologies at Eliminating the Stress Wave Effect Error on Piezoelectric Pressure Sensor |
title_fullStr |
Experimental Study Comparing the Effectiveness of Physical Isolation and ANN Digital Compensation Methodologies at Eliminating the Stress Wave Effect Error on Piezoelectric Pressure Sensor |
title_full_unstemmed |
Experimental Study Comparing the Effectiveness of Physical Isolation and ANN Digital Compensation Methodologies at Eliminating the Stress Wave Effect Error on Piezoelectric Pressure Sensor |
title_sort |
experimental study comparing the effectiveness of physical isolation and ann digital compensation methodologies at eliminating the stress wave effect error on piezoelectric pressure sensor |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-04-01 |
description |
Stress wave, accompanied by explosion shock wave overpressure measurement and dynamic pressure calibration on shock tube, could cause error signals in the piezoelectric pressure sensor (PPS) used for measuring and calibrating. We may call this error the stress wave effect (SWE). In this paper, the SWE and its isolation from PPS were studied by using a split Hopkinson pressure bar (SHPB). In the experimental study of SWE, when increasing the input stress, the corresponding output signal of the PPS was analyzed, and the existence of SWE was verified using the result of the spectrum analysis of the output signal. The stress wave isolation pedestal used in the stress wave isolation experiment was made of nylon and plexiglass polymer materials. The effects of the isolation pedestal’s materials and length on the stress wave isolation were analyzed using the study results. Finally, an artificial neural network (ANN) was trained with the data of the SWE study and was further applied to compensate the SWE error of the PPS output signal. The compensating results were compared with the isolating results, and the advantages and disadvantages of the digital compensation and physical isolation methods were analyzed. |
topic |
piezoelectric pressure sensor (PPS), stress wave effect (SWE), split Hopkinson pressure bar (SHPB), physical isolation digital compensation artificial neural network (ANN) |
url |
https://www.mdpi.com/1424-8220/20/8/2397 |
work_keys_str_mv |
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