Prospect of Using Artificial Intelligence for Microwave Nondestructive Testing Technique: A Review

Abstract

The development in materials technology has produced stronger, lighter, stiffer, and more durable electrically insulating composites which are replacing metals in many applications. These composites require alternative inspection techniques because the conventional nondestructive testing (NDT) techniques such as thermography, eddy currents, ultrasonic, X-ray and magnetic particles have limitations of inspecting them. Microwave NDT technique employing open-ended rectangular waveguides (OERW) has emerged as a promising approach to detect the defects in both metal and composite materials. Despite its promising results over conventional NDT techniques, OERW microwave NDT technique has shown numerous limitations in terms of poor spatial resolution due to the stand-off distance variations, inspection area irregularities and quantitative estimation in imaging the size of defects. Microwave NDT employing OERW in conjunction with robust artificial intelligence approaches have tremendous potential and viability for evaluating composite structures for the purpose mentioned here. Artificial intelligence techniques with signal processing techniques are highly possible to enhance the efficiency and resolution of microwave NDT technique because the impact of artificial intelligence approaches is proven in various conventional NDT techniques. This paper provides a comprehensive review of NDT techniques as well as the prospect of using artificial intelligence approaches in microwave NDT technique with regards to other conventional NDT techniques. INDEX TERMS Microwave nondestructive testing, open-ended rectangular waveguides, artificial intelligence.

Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm

“…The latest efforts to hybridise microwave NDT and machine learning inspecting complex systems (e.g. GFRP) have tremendous potential to increase the efficiency and reliability of inspection [6]. For example, the unsupervised k-means clustering algorithm as described in the next section is the most suitable technique to process the microwave signal in the time domain due to the simplicity of utilizing less training samples required by SVM and artificial neural network (ANN) techniques.…”

“…Therefore, a predictive inspection method evaluating the integrity of the structure is required to prevent these accidents using nondestructive testing (NDT) and to secure the safety and the health of the pipelines. Methods for evaluating pipeline damage are critical for saving maintenance costs, enhancing the integrity and reliability of the system [6].…”

“…The current inspection routine to remove insulation material to facilitate inspection using a conventional technique such as ultrasonic, followed by re-application of insulation, is a costly and time-consuming process [11]. The microwave NDT system has therefore emerged as a promising solution to the identification and assessment of defects under insulation [6]. The microwave NDT method requires no physical contact with the surface or coupling and is capable of penetrating inside composite-based insulations.…”

Review of microwave techniques used in the manufacture and fault detection of aircraft composites

“…For future research, artificial intelligence, big data and data science can be considered for the processing of the measurement data to achieve enhanced quality checking and fault diagnosis. Some work was done in the microwave detection of cracks in metals (152)(153)(154) , while little has been reported on composite materials. Hence, the potential for intelligent microwave inspection is to be explored.…”

Nondestructive Evaluation of Coatings Delamination Using Microwave Time Domain Reflectometry Technique

“…Moreover, laser ultrasonic simultaneously generates various waves (e.g. shear, longitudinal waves, Rayleigh and Lamb waves) which complicate the signal processing [9]. Besides, a controlled environment remains the main issue for thermography based techniques due to the difficulty of controlling the temperature in the real environment.…”