Defect Characteristics and Online Detection Techniques During Manufacturing of FRPs Using Automated Fiber Placement: A Review

Advances in structural analysis and process monitoring of thermoplastic composite pipes

Thermoplastic composite pipes (TCP) in comparison to other pipes have proven beneficial features due to its flexibility which includes being fit for purpose, lightweight and no corrosion. However, during the manufacturing of TCP which involves the consolidation process, certain defects may be induced in it because of certain parameters, and this can affect the performance of the pipe in the long run as the induced defects might lead to in-service defects. Current techniques used in the industry are facing challenges with on-the-spot detection in a continuous manufacturing system. In TCP manufacturing process, the pipe is regularly monitored. When a defect is noticed, the whole process stops, and the appropriate action is taken. However, shutting down the process is costly; hence it is vital to decrease the downtime during manufacturing to the barest minimum. The solutions include optimizing the process for reduction in the manufacturing defects amount and thoroughly understanding the effect of parameters which causes certain defect types in the pipe. This review covers the current state-of-the-art and challenges associated with characterizing the identified manufacturing induced defects in TCP. It discusses and describes all effective consolidation monitoring strategies for early detection of these defects during manufacturing through the application of suitable sensing technology that is compatible with the TCP. It can be deduced that there is a correlation between manufacturing process to the performance of the final part and selection of characterization technique as well as optimizing process parameters.

Research on Void Dynamics during In Situ Consolidation of CF/High-Performance Thermoplastic Composite

Automated fiber placement (AFP) in situ consolidation of continuous CF/high-performance thermoplastic composite is the key technology for efficient and low-cost manufacturing of large thermoplastic composites. However, the void in the in situ composite is difficult to eliminate because of the high pressure and the short consolidation time; the void content percentage consequently is the important defect that determines the performance of the thermoplastic composite parts. In this paper, based on the two-dimensional Newtonian fluid extrusion flow model, the void dynamics model and boundary conditions were established. The changes of the void content percentage were predicted by the cyclic iteration method. It was found that the void content percentage increased gradually along the direction of the layers’ thickness. With the increasing of the laying speed, the void content percentage increased gradually. With the increasing of the pressure of the roller, the void content percentage gradually decreased. When the AFP speed was 11 m/min and the pressure of the compaction roller reached 2000 N, the void content percentage of the layers fell below 2%. It was verified by the AFP test that the measured results of the layers’ thickness were in good agreement with the predicted results of the model, and the test results of the void content percentage were basically equivalent to the predicted results at different AFP speeds, which indicates that the kinetic model established in this paper is representative to predict the void content percentage. According to the metallographic observation, it was also found that the repeated pressure of the roller was helpful to reduce the void content percentage.

Quality Control Approach for the Detection of Internal Lower Density Areas in Composite Disks in Industrial Conditions Based on a Combination of NDT Techniques

Voids in polymer matrix composites are one of the most common manufacturing defects, which may influence the mechanical properties and structural behavior of the final parts made of composites by various manufacturing methods. Therefore, numerous non-destructive testing (NDT) techniques were developed and applied for quality control and in-service testing of such structures. In this paper, the authors analyzed various alternatives to the reference technique, X-ray computed tomography (XCT) NDT, which is used for industrial testing of composite disks having defects in the form of the lower density areas. Different candidates, namely: vibration-based testing, infrared thermography, vibro-thermography, as well as ultrasonic testing were analyzed in terms of their sensitivity and technical feasibility. The quality of the results, the complexity of the testing procedure, time and labor consumption, and the cost of the equipment were analyzed and compared with the reference technique. Based on the conducted research the authors finally proposed a hybrid approach to quality control, using a combination of two NDT techniques-infrared thermography (for initial scanning and detection of near-surface defects) and ultrasonic testing (for a more detailed analysis of products that pass the first testing procedure). It allowed for replacing the costly XCT diagnostics with a much cheaper, but almost equally effective, alternative.

Enhanced Defect Detection in Carbon Fiber Reinforced Polymer Composites via Generative Kernel Principal Component Thermography

Increasing machine learning methods are being applied to infrared non-destructive assessment for internal defects assessment of composite materials. However, most of them extract only linear features, which is not in accord with the nonlinear characteristics of infrared data. Moreover, limited infrared images tend to restrict the data analysis capabilities of machine learning methods. In this work, a novel generative kernel principal component thermography (GKPCT) method is proposed for defect detection of carbon fiber reinforced polymer (CFRP) composites. Specifically, the spectral normalization generative adversarial network is proposed to augment the thermograms for model construction. Sequentially, the KPCT method is used by feature mapping of all thermogram data using kernel principal component analysis, which allows for differentiation of defects and background in the dimensionality-reduced data. Additionally, a defect-background separation metric is designed to help the performance evaluation of data analysis methods. Experimental results on CFRP demonstrate the feasibility and advantages of the proposed GKPCT method.

Influence Mechanism and Optimization Analysis of Technological Parameters for the Composite Prepreg Tape Winding Process

Composite prepreg tape winding technology has proven to be an effective method for manufacturing revolving body composite structures in aerospace field. Process parameters including heating temperature, tape tension and roller pressure have an important impact on the winding products’ mechanical property such as tensile strength. The aim of this study is to investigate the influence mechanism and optimization analysis of parameters for the composite prepreg tape winding process. Firstly, the sensitivity analysis for single parameter had be employed to reveal the influence mechanism of each winding parameter change on tensile strength. Secondly, iso-surfaces analysis for parameter range had be applied to describe the distribution law of parameter with continuous distribution characteristics. Then the coupling analysis for process parameters was carried out employing response surface methodology. The analysis results showed that tape tension has the most significant effect on the winding products’ tensile strength. And the outstanding parameter combination with the heating temperature of 72 °C, tape tension of 307 N and roller pressure of 1263 N was provided by response surface design software via desirability function method. The validation experiments showed that the optimal parameter combination has a positive guiding significance for improving the quality of winding products.