Defect measurement in CFRP drilling based on digital image processing

Abstract

Carbon Fiber Reinforced polymers (CFRPs) are critical kind of materials in many industries due to their superior mechanical and physical properties. However, the pivotal mechanical process of CFRPs is considered to be drilling, which easily leads to CFRPs defects including burr and delamination. Although substantial CFRPs defect inspection methods have been suggested, the user-friendly measurement of CFRPs defects and fast measurement speed are still challenging. To this end, a digital-image-processingbased method for identifying and measuring the drilling-induced defects in CFRPs specimens is proposed. By comparing with the manually measured results, it shows that the proposed method can accurately (the maximal relative errors are separately 5.76% and 3.42% for burr factor and delamination factor) and quickly (4 s per micrograph) recognize and measure CFRPs defects. Moreover, the method has no requirement for adjusting any parameters manually and shows strong robustness to the interference from the bright noise. Based on above, the method is anticipated to provide a meaningful reference for recognizing and measuring CFRPs defects in large quantities.

Experimental Analysis and Application of a Multivariable Regression Technique to Define the Optimal Drilling Conditions for Carbon Fiber Reinforced Polymer (CFRP) Composites

“…This can be explained if it is taken into consideration that the cutting speed increases the temperature on the cutting zone, which can in turn soften the epoxy resin, i.e., the matrix of the composite material. This behavior has been found by other authors [ 19 ], although these authors found a lower influence of the cutting speed than that obtained herein, as they worked with a cutting speed range narrower than that under investigation here.…”

“…This can be explained if it is taken into consideration that the cutting speed increases the temperature on the cutting zone, which can in turn soften the epoxy resin, i.e., the matrix of the composite material. This behavior has been found by other authors [19], although these authors found a lower The measured forces in the tests are depicted in Figure 10. It is observed that, among the input parameters, the feed rate and the tool geometry heavily influence the thrust force that appears in the machining process.…”

“…Since internal delamination detection is not available, the delamination evaluation on the sheet faces is the most common procedure in industrial practice. Recently, some research has demonstrated that digital image processing techniques allow the delaminated area from visible two-dimensional defects to be determined with good accuracy [ 19 ]. For their part, Lukács et al [ 20 ] have developed a novel image treatment algorithm that recognizes changes induced by the drilling process by comparing initial and post-drilled images and by applying image differencing.…”