Malcolm McGugan

Technical University of Denmark

Denmark

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Articles (13)

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2026

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2025

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2025

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2024

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2024

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2024

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2024

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2023

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2023

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2022

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2022

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2021

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2020

Collaborators (11)

Henrik Madsen

Technical University of Denmark

DENMARK

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Süleyman Cem Yeniceli

Technical University of Denmark

DENMARK

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Bent F. Sørensen

Technical University of Denmark

DENMARK

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Hans-Henrik Benzon

Technical University of Denmark

DENMARK

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Seyed Sina Samareh-Mousavi

Technical University of Denmark

DENMARK

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Peter Berring

Technical University of Denmark

DENMARK

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Xiao Chen

Technical University of Denmark

DENMARK

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Steffen Rasmussen

Technical University of Denmark

DENMARK

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Sergei Semenov

Technical University of Denmark

DENMARK

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Nicolai Frost-Jensen Johansen

Technical University of Denmark

DENMARK

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Kim Branner

Technical University of Denmark

DENMARK

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Malcolm McGugan

Research Interests

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Articles (13)

Design and testing of an element test specimen for fatigue delamination crack growth initiating at a ply drop

Acoustic emission data analytics on delamination growth in a wind turbine blade under full-scale cyclic testing

Use of Fourier-based frequency-wavenumber domain filtering of simulated elastic waves for damage detection in fiber/polymer composites

Artificial intelligence-based blade identification in operational wind turbines through similarity analysis aided drone inspection

Compression–compression fatigue damage of wrinkled carbon/glass hybrid composite laminates

Analysis of damage localization based on acoustic emission data from test of wind turbine blades

Monitoring fatigue delamination growth in a wind turbine blade using passive thermography and acoustic emission

A full-scale wind turbine blade monitoring campaign: detection of damage initiation and progression using medium-frequency active vibrations

Feasibility study on a full-scale wind turbine blade monitoring campaign: Comparing performance and robustness of features extracted from medium-frequency active vibrations

Structural health monitoring of 52-meter wind turbine blade: Detection of damage propagation during fatigue testing

Control of damage‐sensitive features for early failure prediction of wind turbine blades

Fatigue testing of a 14.3 m composite blade embedded with artificial defects – damage growth and structural health monitoring

Damage mechanism based approach to the structural health monitoring of wind turbine blades

Collaborators (11)

Henrik Madsen

Süleyman Cem Yeniceli

Bent F. Sørensen

Hans-Henrik Benzon

Seyed Sina Samareh-Mousavi

Peter Berring

Xiao Chen

Steffen Rasmussen

Sergei Semenov

Nicolai Frost-Jensen Johansen

Kim Branner

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