Autonomous Optical Inspection of Large Scale Freeform Surfaces

Rasmus Ahrenkiel Lyngby*

*Corresponding author for this work

Research output: Book/ReportPh.D. thesis

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Abstract

It is estimated that 80% of wind turbine blade failures can be back-tracked to defects which were introduced during production. Blades that are nonconforming to the intended design of their outer geometry are likely to underperform concerning aerodynamic lift, and can, therefore, cause their turbines to have a lower than nominal power output. Furthermore, small, usually discrete, surface aberrations can lead to turbulence in the boundary ow around the blade. This turbulence reduces the lift even more and can lead to surface erosion, which potentially can cause blade failure within a few years after installment. Consequently, geometric quality inspection in the production is vital to the performance and expected lifetime of a blade, and thus also to the business cases of the blade manufactures, owners, and operators.
This thesis studies how the geometric inspection of blades can be automated, through the development and construction of a novel autonomous robotic scanner system. The studied scanner modality is optically based and relies on a structured light camera-projector system, which samples point clouds from the blade's surface. Experiments demonstrate the system's capabilities in measuring the outermost 20 meters of 55 meter long blades. The Modular Freeform Gauge approach is used to study the scanner system's metrological performance. Additionally, the thesis considers the interaction between light and materials, with the purpose of selecting the optimal parameters, such as the coding strategy, for the structured light scanner.
Original languageEnglish
Place of PublicationKgs. Lyngby, Denmark
PublisherTechnical University of Denmark
Number of pages253
Publication statusPublished - 2019
SeriesDTU Compute PHD-2018
Volume486
ISSN0909-3192

Cite this

Lyngby, R. A. (2019). Autonomous Optical Inspection of Large Scale Freeform Surfaces. Kgs. Lyngby, Denmark: Technical University of Denmark. DTU Compute PHD-2018, Vol.. 486
Lyngby, Rasmus Ahrenkiel. / Autonomous Optical Inspection of Large Scale Freeform Surfaces. Kgs. Lyngby, Denmark : Technical University of Denmark, 2019. 253 p. (DTU Compute PHD-2018, Vol. 486).
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title = "Autonomous Optical Inspection of Large Scale Freeform Surfaces",
abstract = "It is estimated that 80{\%} of wind turbine blade failures can be back-tracked to defects which were introduced during production. Blades that are nonconforming to the intended design of their outer geometry are likely to underperform concerning aerodynamic lift, and can, therefore, cause their turbines to have a lower than nominal power output. Furthermore, small, usually discrete, surface aberrations can lead to turbulence in the boundary ow around the blade. This turbulence reduces the lift even more and can lead to surface erosion, which potentially can cause blade failure within a few years after installment. Consequently, geometric quality inspection in the production is vital to the performance and expected lifetime of a blade, and thus also to the business cases of the blade manufactures, owners, and operators.This thesis studies how the geometric inspection of blades can be automated, through the development and construction of a novel autonomous robotic scanner system. The studied scanner modality is optically based and relies on a structured light camera-projector system, which samples point clouds from the blade's surface. Experiments demonstrate the system's capabilities in measuring the outermost 20 meters of 55 meter long blades. The Modular Freeform Gauge approach is used to study the scanner system's metrological performance. Additionally, the thesis considers the interaction between light and materials, with the purpose of selecting the optimal parameters, such as the coding strategy, for the structured light scanner.",
author = "Lyngby, {Rasmus Ahrenkiel}",
year = "2019",
language = "English",
publisher = "Technical University of Denmark",

}

Lyngby, RA 2019, Autonomous Optical Inspection of Large Scale Freeform Surfaces. DTU Compute PHD-2018, vol. 486, Technical University of Denmark, Kgs. Lyngby, Denmark.

Autonomous Optical Inspection of Large Scale Freeform Surfaces. / Lyngby, Rasmus Ahrenkiel.

Kgs. Lyngby, Denmark : Technical University of Denmark, 2019. 253 p. (DTU Compute PHD-2018, Vol. 486).

Research output: Book/ReportPh.D. thesis

TY - BOOK

T1 - Autonomous Optical Inspection of Large Scale Freeform Surfaces

AU - Lyngby, Rasmus Ahrenkiel

PY - 2019

Y1 - 2019

N2 - It is estimated that 80% of wind turbine blade failures can be back-tracked to defects which were introduced during production. Blades that are nonconforming to the intended design of their outer geometry are likely to underperform concerning aerodynamic lift, and can, therefore, cause their turbines to have a lower than nominal power output. Furthermore, small, usually discrete, surface aberrations can lead to turbulence in the boundary ow around the blade. This turbulence reduces the lift even more and can lead to surface erosion, which potentially can cause blade failure within a few years after installment. Consequently, geometric quality inspection in the production is vital to the performance and expected lifetime of a blade, and thus also to the business cases of the blade manufactures, owners, and operators.This thesis studies how the geometric inspection of blades can be automated, through the development and construction of a novel autonomous robotic scanner system. The studied scanner modality is optically based and relies on a structured light camera-projector system, which samples point clouds from the blade's surface. Experiments demonstrate the system's capabilities in measuring the outermost 20 meters of 55 meter long blades. The Modular Freeform Gauge approach is used to study the scanner system's metrological performance. Additionally, the thesis considers the interaction between light and materials, with the purpose of selecting the optimal parameters, such as the coding strategy, for the structured light scanner.

AB - It is estimated that 80% of wind turbine blade failures can be back-tracked to defects which were introduced during production. Blades that are nonconforming to the intended design of their outer geometry are likely to underperform concerning aerodynamic lift, and can, therefore, cause their turbines to have a lower than nominal power output. Furthermore, small, usually discrete, surface aberrations can lead to turbulence in the boundary ow around the blade. This turbulence reduces the lift even more and can lead to surface erosion, which potentially can cause blade failure within a few years after installment. Consequently, geometric quality inspection in the production is vital to the performance and expected lifetime of a blade, and thus also to the business cases of the blade manufactures, owners, and operators.This thesis studies how the geometric inspection of blades can be automated, through the development and construction of a novel autonomous robotic scanner system. The studied scanner modality is optically based and relies on a structured light camera-projector system, which samples point clouds from the blade's surface. Experiments demonstrate the system's capabilities in measuring the outermost 20 meters of 55 meter long blades. The Modular Freeform Gauge approach is used to study the scanner system's metrological performance. Additionally, the thesis considers the interaction between light and materials, with the purpose of selecting the optimal parameters, such as the coding strategy, for the structured light scanner.

M3 - Ph.D. thesis

BT - Autonomous Optical Inspection of Large Scale Freeform Surfaces

PB - Technical University of Denmark

CY - Kgs. Lyngby, Denmark

ER -

Lyngby RA. Autonomous Optical Inspection of Large Scale Freeform Surfaces. Kgs. Lyngby, Denmark: Technical University of Denmark, 2019. 253 p. (DTU Compute PHD-2018, Vol. 486).