Automatic Extraction of Material Defect Size by Infrared Image Sequence

Abstract

A typical pulsed thermography procedure results in a sequence of infrared images that reflects the evolution of temperature over time. Many features of defects, such as shape, position, and size, are derived from single image by image processing. Hence, determining the key frame from the sequence is an important problem to be solved first. A maximum standard deviation of the sensitive region method was proposed, which can identify a reasonable image frame automatically from an infrared image sequence; then, a stratagem of image composition was applied for enhancing the detection of deep defects in the key frame. Blob analysis had been adopted to acquire general information of defects such as their distributions and total number of defects. A region of interest of the defect was automatically located by its key frame combined with blob analysis. The defect information was obtained through image segmentation techniques. To obtain a robustness of results, a method of two steps of detection was proposed. The specimen of polyvinyl chloride with two artificial defects at different depths as an example was used to demonstrate how to operate the proposed method for an accurate result. At last, the proposed method was successfully adopted to examine the damage of carbon fiber-reinforced polymer. A comparative study between the proposed method and several state-of-the-art ones shows that the former is accurate and reliable and may provide a more useful and reliable tool for quality assurance in the industrial and manufacturing sectors.

Feature Concatenation based Multilayered Sparse Tensor for Debond Detection Optical Thermography

“…The analysis is presented to characterize the defect depth with regard to specimen thickness and defect size. In [22], the authors propose an automated defect detection method in thermal sequences using important frame selection, feature extraction, and image segmentation to detect the defect size. In [23], the authors propose a Levenberg-Marquardt algorithm to remove the uneven heating noise in thermal sequences.…”

Application of Pulsed Thermography and Post-processing Techniques for CFRP Industrial Components

“…Pulsed thermography (PT) represents a no-contact and full-field ND technique, widely used for the industrial controls of large composite surfaces due to wide detection area, fast and relatively simple detection [11,12]. In recent years, the enhancement of visual image modality, combined with fast and robust temperature processing strategy has significantly grown for a multi-functionality of Infrared thermography for specific industrial applications, characterized by difficult to inspection components or as requirement of faster inspection [13][14][15][16]. Therefore, the image-processing methods and their continuous improvement make the thermographic inspection even more suitable alternative to popular ND controls, as ultrasonic testing, for different production environments [12,16].…”

“…Therefore, the image-processing methods and their continuous improvement make the thermographic inspection even more suitable alternative to popular ND controls, as ultrasonic testing, for different production environments [12,16]. In literature, different algorithms were proposed to enhance defect detection in terms of dimension, depth and shape [15,17,18].…”

Infrared Imaging and NDT

“…Another research work on pulsed thermography is presented in [10]. This work deals with a different problem: the determination of the size of defects from the resulting inspection using active thermography.…”