Assessing damage to wind turbine blades to support autonomous inspection

Andy Gibson; Sarinova Simandjuntak; Emily Jane Dunkason; Hanly Simon Bingari; Alexander   Fraess-Ehrfeld

doi:10.1117/12.2644972

Assessing damage to wind turbine blades to support autonomous inspection

Andy Gibson^*
, Sarinova Simandjuntak
, Emily Jane Dunkason
, Hanly Simon Bingari
, Alexander Fraess-Ehrfeld

^*Corresponding author for this work

AIRBORNE ROBOTICS Limited

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We describe results from experiments investigating how hyperspectral data might be incorporated into autonomous inspections for offshore turbines, part of Dr SUIT– (Drone Swarm for Unmanned Inspection of Wind Turbines), a collaboration funded by InnovateUK (UKRI). Imagery and point measurements were captured of small turbine blades subjected to damage by abrasion, impact and UV exposure. The technique appears effective at classifying abrasion damage to a degree comparable with conventional inspection schemes. Impact damage could be classified as ‘lower’ or ‘higher’ energies. The blades designed resilience to UV meant that little change was detected in those tests.

Original language	English
Title of host publication	Proceedings SPIE Photonex 2022
Subtitle of host publication	Hyperspectral Imaging and Applications II
Editors	Nick J. Barnett, Aoife A. Gowen, Haida Liang
Publisher	Society of Photographic Instrumentation Engineers
ISBN (Electronic)	9781510657496
ISBN (Print)	9781510657489
DOIs	https://doi.org/10.1117/12.2644972
Publication status	Published - 12 Jan 2023
Event	SPIE Photonex 2022 - Birmingham, United Kingdom Duration: 7 Dec 2022 → 8 Dec 2022

Publication series

Name	Proceedings of SPIE
Volume	12338
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	SPIE Photonex 2022
Country/Territory	United Kingdom
City	Birmingham
Period	7/12/22 → 8/12/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1117/12.2644972Licence: Unspecified

Cite this

Gibson, A., Simandjuntak, S., Dunkason, E. J., Bingari, H. S., & Fraess-Ehrfeld, A. (2023). Assessing damage to wind turbine blades to support autonomous inspection. In N. J. Barnett, A. A. Gowen, & H. Liang (Eds.), Proceedings SPIE Photonex 2022: Hyperspectral Imaging and Applications II Article 123380A (Proceedings of SPIE; Vol. 12338). Society of Photographic Instrumentation Engineers. https://doi.org/10.1117/12.2644972

@inproceedings{334901fd93874aa5a765931562e1cac4,

title = "Assessing damage to wind turbine blades to support autonomous inspection",

abstract = "We describe results from experiments investigating how hyperspectral data might be incorporated into autonomous inspections for offshore turbines, part of Dr SUIT– (Drone Swarm for Unmanned Inspection of Wind Turbines), a collaboration funded by InnovateUK (UKRI). Imagery and point measurements were captured of small turbine blades subjected to damage by abrasion, impact and UV exposure. The technique appears effective at classifying abrasion damage to a degree comparable with conventional inspection schemes. Impact damage could be classified as {\textquoteleft}lower{\textquoteright} or {\textquoteleft}higher{\textquoteright} energies. The blades designed resilience to UV meant that little change was detected in those tests.",

author = "Andy Gibson and Sarinova Simandjuntak and Dunkason, \{Emily Jane\} and Bingari, \{Hanly Simon\} and Alexander Fraess-Ehrfeld",

note = "Conference paper so no acceptance date needed; SPIE Photonex 2022 ; Conference date: 07-12-2022 Through 08-12-2022",

year = "2023",

month = jan,

day = "12",

doi = "10.1117/12.2644972",

language = "English",

isbn = "9781510657489",

series = "Proceedings of SPIE",

publisher = "Society of Photographic Instrumentation Engineers",

editor = "Barnett, \{Nick J. \} and Gowen, \{Aoife A.\} and Liang, \{Haida \}",

booktitle = "Proceedings SPIE Photonex 2022",

address = "United States",

}

Gibson, A, Simandjuntak, S, Dunkason, EJ, Bingari, HS & Fraess-Ehrfeld, A 2023, Assessing damage to wind turbine blades to support autonomous inspection. in NJ Barnett, AA Gowen & H Liang (eds), Proceedings SPIE Photonex 2022: Hyperspectral Imaging and Applications II., 123380A, Proceedings of SPIE, vol. 12338, Society of Photographic Instrumentation Engineers, SPIE Photonex 2022, Birmingham, United Kingdom, 7/12/22. https://doi.org/10.1117/12.2644972

Assessing damage to wind turbine blades to support autonomous inspection. / Gibson, Andy; Simandjuntak, Sarinova; Dunkason, Emily Jane et al.
Proceedings SPIE Photonex 2022: Hyperspectral Imaging and Applications II. ed. / Nick J. Barnett; Aoife A. Gowen; Haida Liang. Society of Photographic Instrumentation Engineers, 2023. 123380A (Proceedings of SPIE; Vol. 12338).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Gibson, Andy

AU - Simandjuntak, Sarinova

AU - Dunkason, Emily Jane

AU - Bingari, Hanly Simon

AU - Fraess-Ehrfeld, Alexander

N1 - Conference paper so no acceptance date needed

PY - 2023/1/12

Y1 - 2023/1/12

N2 - We describe results from experiments investigating how hyperspectral data might be incorporated into autonomous inspections for offshore turbines, part of Dr SUIT– (Drone Swarm for Unmanned Inspection of Wind Turbines), a collaboration funded by InnovateUK (UKRI). Imagery and point measurements were captured of small turbine blades subjected to damage by abrasion, impact and UV exposure. The technique appears effective at classifying abrasion damage to a degree comparable with conventional inspection schemes. Impact damage could be classified as ‘lower’ or ‘higher’ energies. The blades designed resilience to UV meant that little change was detected in those tests.

AB - We describe results from experiments investigating how hyperspectral data might be incorporated into autonomous inspections for offshore turbines, part of Dr SUIT– (Drone Swarm for Unmanned Inspection of Wind Turbines), a collaboration funded by InnovateUK (UKRI). Imagery and point measurements were captured of small turbine blades subjected to damage by abrasion, impact and UV exposure. The technique appears effective at classifying abrasion damage to a degree comparable with conventional inspection schemes. Impact damage could be classified as ‘lower’ or ‘higher’ energies. The blades designed resilience to UV meant that little change was detected in those tests.

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DO - 10.1117/12.2644972

M3 - Conference contribution

SN - 9781510657489

T3 - Proceedings of SPIE

BT - Proceedings SPIE Photonex 2022

A2 - Barnett, Nick J.

A2 - Gowen, Aoife A.

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Y2 - 7 December 2022 through 8 December 2022

ER -

Gibson A, Simandjuntak S, Dunkason EJ, Bingari HS, Fraess-Ehrfeld A. Assessing damage to wind turbine blades to support autonomous inspection. In Barnett NJ, Gowen AA, Liang H, editors, Proceedings SPIE Photonex 2022: Hyperspectral Imaging and Applications II. Society of Photographic Instrumentation Engineers. 2023. 123380A. (Proceedings of SPIE). doi: 10.1117/12.2644972

Assessing damage to wind turbine blades to support autonomous inspection

Abstract

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Conference

UN SDGs

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