MID-INFRARED (MIR) OCT-based inspection in industry

TL;DR

This study explores the use of mid-infrared OCT systems combined with AI algorithms for non-destructive, sub-surface inspection of industrial materials like composites and ceramics, highlighting potential and limitations.

Contribution

It evaluates MIR OCT's effectiveness for detecting subsurface irregularities and assesses AI-based anomaly detection methods in industrial inspection.

Findings

MIR OCT can penetrate materials to reveal subsurface features.

AI algorithms show promise in identifying anomalies.

Limitations depend on material type and system parameters.

Abstract

This paper aims to evaluate mid-infrared (MIR) Optical Coherence Tomography (OCT) systems as a tool to penetrate different materials and detect sub-surface irregularities. This is useful for monitoring production processes, allowing Non-Destructive Inspection Techniques of great value to the industry. In this exploratory study, several acquisitions are made on composite and ceramics to know the capabilities of the system. In addition, it is assessed which preprocessing and AI-enhanced vision algorithms can be anomaly-detection methodologies capable of detecting abnormal zones in the analyzed objects. Limitations and criteria for the selection of optimal parameters will be discussed, as well as strengths and weaknesses will be highlighted.