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Published on: January 16, 2020
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Nondestructive material characterization and component identification in sheet metal processing with electromagnetic
Bernd Wolter1, Benjamin Straß2, Kevin Jacob2
1Fraunhofer Institute for Nondestructive Testing IZFP, 66123, Saarbrücken, Germany. bernd.wolter@izfp.fraunhofer.de.
Scientific Reports
|March 16, 2024
Summary
Micromagnetic Multiparametric Microstructure and stress Analyser (3MA) and eddy current (EC) methods enable non-destructive evaluation of sheet metals. These techniques characterize material properties, predict formability, and offer marker-free traceability in manufacturing.
Area of Science:
- Materials Science
- Non-Destructive Evaluation (NDE)
- Electromagnetism
Background:
- Sheet metal components require robust identification and material property characterization for quality control.
- Existing non-destructive evaluation (NDE) methods face challenges in accurately assessing microstructure and stress.
- Predicting sheet metal formability and ensuring traceability in processing are critical manufacturing concerns.
Purpose of the Study:
- To present electromagnetic NDE methods for identifying sheet metal components and characterizing their material properties.
- To investigate the application of Micromagnetic Multiparametric Microstructure and stress Analyser (3MA) for pre-process testing and formability prediction.
- To develop a marker-free traceability method for sheet metal processing using spatially resolved eddy current (EC) imaging.
Main Methods:
- Utilized Micromagnetic Multiparametric Microstructure and stress Analyser (3MA), combining multiple micromagnetic NDE techniques.
- Investigated the influence of probe speed and distance for in-line 3MA application.
- Employed a spatially resolved eddy current (EC) method to generate intrinsic material microstructure images.
- Developed a machine learning (ML)-based system for specimen identification using robust features from EC fingerprint images.
Main Results:
- 3MA enables quantitative analysis of microstructure, mechanical properties, and stress states in ferromagnetic materials.
- 3MA information can predict sheet metal formability, particularly in cold forming applications.
- Intrinsic fingerprint images generated by EC methods remain recognizable after plastic deformation and surface coating.
- A marker-free traceability method was successfully developed using EC imaging and ML for robust specimen identification.
Conclusions:
- Electromagnetic NDE methods, including 3MA and EC, offer powerful tools for sheet metal evaluation.
- 3MA provides valuable insights for pre-process testing, enhancing formability prediction.
- EC-based intrinsic fingerprinting enables reliable, marker-free traceability throughout sheet metal processing.
