Acoustic Emission-Based Detection in Restricted-Access Areas Using Multiple PZT Disc Sensors

Lu Cheng; Ali Nokhbatolfoghahai; Roger M. Groves; Milan Veljkovic

doi:10.1007/978-3-031-07254-3_62

Acoustic Emission-Based Detection in Restricted-Access Areas Using Multiple PZT Disc Sensors

Lu Cheng^*, Ali Nokhbatolfoghahai, Roger M. Groves, Milan Veljkovic

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

The performance of the Acoustic Emission (AE) technique is significantly dependent on the sensors attached to the structural surface. Although conventional commercially AE sensors, like R15a and WSa sensors, have been extensively employed in monitoring many different structures, they are unavailable in restricted-assess areas. In contrast, thin PZT sensors are small, inexpensive and lightweight. These thin PZT sensors have a great potential for passive sensing to detect AE signals. However, their utility in AE monitoring is limited due to their low signal-to-noise ratio and information incompleteness because of their simple construction. This work discusses the issues and possible solutions with regards to the specific selection and application of thin PZT sensors for passive sensing. The compatibility of different thin PZT sensors and conventional bulky sensors is investigated using pencil break lead (PBL) tests. The comparison between the recorded signals is carried out in both the time domain and frequency domain for these sensors. To improve the reliability and performance of the thin PZT sensors, a methodology employing multiple thin PZT sensors of different sizes is proposed based on machine learning techniques and sensor data fusion.

Original language	English
Title of host publication	European Workshop on Structural Health Monitoring, EWSHM 2022, Volume 1
Editors	Piervincenzo Rizzo, Alberto Milazzo
Publisher	Springer
Pages	619-629
Number of pages	11
ISBN (Electronic)	978-3-031-07254-3
ISBN (Print)	978-3-031-07253-6
DOIs	https://doi.org/10.1007/978-3-031-07254-3_62
Publication status	Published - 2023
Event	10th European Workshop on Structural Health Monitoring, EWSHM 2022 - Palermo, Italy Duration: 4 Jul 2022 → 7 Jul 2022

Publication series

Name	Lecture Notes in Civil Engineering
Volume	253 LNCE
ISSN (Print)	2366-2557
ISSN (Electronic)	2366-2565

Conference

Conference	10th European Workshop on Structural Health Monitoring, EWSHM 2022
Country/Territory	Italy
City	Palermo
Period	4/07/22 → 7/07/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

Acoustic emission technique
Data fusion
Machine learning
Restricted-assess areas
Thin PZT sensors

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10.1007/978-3-031-07254-3_62

Acoustic Emission-Based Detection in Restricted-Access Areas Using Multiple PZT Disc SensorsFinal published version, 1.9 MB

Cite this

Cheng, L., Nokhbatolfoghahai, A., Groves, R. M., & Veljkovic, M. (2023). Acoustic Emission-Based Detection in Restricted-Access Areas Using Multiple PZT Disc Sensors. In P. Rizzo, & A. Milazzo (Eds.), European Workshop on Structural Health Monitoring, EWSHM 2022, Volume 1 (pp. 619-629). (Lecture Notes in Civil Engineering; Vol. 253 LNCE). Springer. https://doi.org/10.1007/978-3-031-07254-3_62

@inproceedings{1915f606f00a451b8ecf02c6a15b6c0f,

title = "Acoustic Emission-Based Detection in Restricted-Access Areas Using Multiple PZT Disc Sensors",

abstract = "The performance of the Acoustic Emission (AE) technique is significantly dependent on the sensors attached to the structural surface. Although conventional commercially AE sensors, like R15a and WSa sensors, have been extensively employed in monitoring many different structures, they are unavailable in restricted-assess areas. In contrast, thin PZT sensors are small, inexpensive and lightweight. These thin PZT sensors have a great potential for passive sensing to detect AE signals. However, their utility in AE monitoring is limited due to their low signal-to-noise ratio and information incompleteness because of their simple construction. This work discusses the issues and possible solutions with regards to the specific selection and application of thin PZT sensors for passive sensing. The compatibility of different thin PZT sensors and conventional bulky sensors is investigated using pencil break lead (PBL) tests. The comparison between the recorded signals is carried out in both the time domain and frequency domain for these sensors. To improve the reliability and performance of the thin PZT sensors, a methodology employing multiple thin PZT sensors of different sizes is proposed based on machine learning techniques and sensor data fusion.",

keywords = "Acoustic emission technique, Data fusion, Machine learning, Restricted-assess areas, Thin PZT sensors",

author = "Lu Cheng and Ali Nokhbatolfoghahai and Groves, {Roger M.} and Milan Veljkovic",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. ; 10th European Workshop on Structural Health Monitoring, EWSHM 2022 ; Conference date: 04-07-2022 Through 07-07-2022",

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doi = "10.1007/978-3-031-07254-3_62",

language = "English",

isbn = "978-3-031-07253-6",

series = "Lecture Notes in Civil Engineering",

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Cheng, L, Nokhbatolfoghahai, A, Groves, RM & Veljkovic, M 2023, Acoustic Emission-Based Detection in Restricted-Access Areas Using Multiple PZT Disc Sensors. in P Rizzo & A Milazzo (eds), European Workshop on Structural Health Monitoring, EWSHM 2022, Volume 1. Lecture Notes in Civil Engineering, vol. 253 LNCE, Springer, pp. 619-629, 10th European Workshop on Structural Health Monitoring, EWSHM 2022, Palermo, Italy, 4/07/22. https://doi.org/10.1007/978-3-031-07254-3_62

Acoustic Emission-Based Detection in Restricted-Access Areas Using Multiple PZT Disc Sensors. / Cheng, Lu; Nokhbatolfoghahai, Ali; Groves, Roger M. et al.
European Workshop on Structural Health Monitoring, EWSHM 2022, Volume 1. ed. / Piervincenzo Rizzo; Alberto Milazzo. Springer, 2023. p. 619-629 (Lecture Notes in Civil Engineering; Vol. 253 LNCE).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Nokhbatolfoghahai, Ali

AU - Groves, Roger M.

AU - Veljkovic, Milan

N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2023

Y1 - 2023

N2 - The performance of the Acoustic Emission (AE) technique is significantly dependent on the sensors attached to the structural surface. Although conventional commercially AE sensors, like R15a and WSa sensors, have been extensively employed in monitoring many different structures, they are unavailable in restricted-assess areas. In contrast, thin PZT sensors are small, inexpensive and lightweight. These thin PZT sensors have a great potential for passive sensing to detect AE signals. However, their utility in AE monitoring is limited due to their low signal-to-noise ratio and information incompleteness because of their simple construction. This work discusses the issues and possible solutions with regards to the specific selection and application of thin PZT sensors for passive sensing. The compatibility of different thin PZT sensors and conventional bulky sensors is investigated using pencil break lead (PBL) tests. The comparison between the recorded signals is carried out in both the time domain and frequency domain for these sensors. To improve the reliability and performance of the thin PZT sensors, a methodology employing multiple thin PZT sensors of different sizes is proposed based on machine learning techniques and sensor data fusion.

AB - The performance of the Acoustic Emission (AE) technique is significantly dependent on the sensors attached to the structural surface. Although conventional commercially AE sensors, like R15a and WSa sensors, have been extensively employed in monitoring many different structures, they are unavailable in restricted-assess areas. In contrast, thin PZT sensors are small, inexpensive and lightweight. These thin PZT sensors have a great potential for passive sensing to detect AE signals. However, their utility in AE monitoring is limited due to their low signal-to-noise ratio and information incompleteness because of their simple construction. This work discusses the issues and possible solutions with regards to the specific selection and application of thin PZT sensors for passive sensing. The compatibility of different thin PZT sensors and conventional bulky sensors is investigated using pencil break lead (PBL) tests. The comparison between the recorded signals is carried out in both the time domain and frequency domain for these sensors. To improve the reliability and performance of the thin PZT sensors, a methodology employing multiple thin PZT sensors of different sizes is proposed based on machine learning techniques and sensor data fusion.

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ER -

Acoustic Emission-Based Detection in Restricted-Access Areas Using Multiple PZT Disc Sensors

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Keywords

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