Ibrahim Tansel

Professor

Florida International University

United States

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Professor Ibrahim Tansel is a faculty member at Florida International University, United States. His research primarily focuses on the intersection of additive manufacturing, structural health monitoring, and artificial intelligence. Recent publications include works on nondestructive testing of structures, smart assessments of metal components, and deep learning applications for the monitoring of machine tools and manufactured parts.

Articles (14)

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2025

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2025

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2025

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2025

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2024

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2023

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2023

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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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2021

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2020

Collaborators (5)

Dwayne McDaniel

Associate Professor

Florida International University

UNITED STATES

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Ivanka Iordanova

Professor

École de technologie supérieure

CANADA

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shenen chen

Professor

University of North Carolina at Charlotte

UNITED STATES

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John P.T. Mo

Professor

RMIT University

AUSTRALIA

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Mohamed Al-Hussein

Professor

University of Alberta

CANADA

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Ibrahim Tansel

Research Interests

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Contact this professor

About

Articles (14)

Load magnitude and location estimation on additively manufactured circular structures using deep learning

Inspection of Additively Manufactured Structures Using Combined Nondestructive Testing (NDT) and Structural Health Monitoring (SHM) Systems

Intelligent Hybrid SHM-NDT Approach for Structural Assessment of Metal Components

Sensorless tool wear estimation by using the artificial intelligence (AI) tools from the currents of motors generating linear motions

AI-based inspection of the axes of machine tools

Sum Standard Deviation of Frequency – A Context Independent Machine Condition Trend Indicator

Monitoring the misalignment of machine tools with autoencoders after they are trained with transfer learning data

Detection of Anomalies in Additively Manufactured Metal Parts Using CNN and LSTM Networks

Structural Condition Monitoring Using Deep Learning on a Metallic Part Fabricated by Additive Manufacturing

Structural Health Monitoring of Additively Manufactured Parts by Combining Infill Design, Multiple Pulse Width Excitation (MPWE), and Deep Learning

Analysis of Force Sensing Accuracy by Using SHM Methods on Conventionally Manufactured and Additively Manufactured Small Polymer Parts

Implementation of the surface thickness on additively manufactured parts for estimation of the loading location

Wave Propagation and Structural Health Monitoring Application on Parts Fabricated by Additive Manufacturing

Damage detection of 3D printed mold using the surface response to excitation method

Collaborators (5)

Dwayne McDaniel

Ivanka Iordanova

shenen chen

John P.T. Mo

Mohamed Al-Hussein

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