## 2 Methods and Materials
### Non-Destructive Testing (NDT) Techniques

Table 1: _Cont._sensitivity to surface imperfections, allowing for more precise detection of surface-breaking defects than other methods like ultrasonic and radiographic testing. MPI is ideal for scenarios where identifying even minor surface defects is critical to maintaining structural integrity and safety. However, the technique is limited to ferromagnetic materials--such as iron, nickel, cobalt, and certain alloys--because only these materials can be effectively magnetised to create the magnetic fields needed for the inspection. As a result, MPI cannot be used on non-ferromagnetic materials like aluminium, copper, or austenitic stainless steel, which restricts its use to specific types of materials. [PERSON] et al. [43] conducted a study to examine the performance of four non-destructive testing (NDT) methods in detecting structural defects in an in-service aircraft's landing gear components and engines. The study involved a certified maintenance engineer who used and compared visual testing, ultrasonic inspection, radiography, and magnetic particle inspection to assess each method's accuracy, reliability, and sensitivity. Focusing on the magnetic particle technique, the author outlined the methodology of magnetic particle testing, as illustrated in Figure 4a. Suppose there is a defect, such as a crack, a leakage field is created, which attracts magnetic particles and produces a distinct cluster as an indication. Figure 4b is a representative example of a flux leakage from surface and near-surface discontinuities. For near-surface defects, the accumulation of particles is less pronounced, leading to a weaker and less defined indication. The results of this study indicated that the most effective inspection technique was visual inspection using a borescope system, which could detect defects ranging from 1.6 mm to 2.5 mm. In contrast, Magnetic Particle Inspection (MPI) was more sensitive to detecting larger defects, between 4.0 mm and 12.6 mm, located on or just below the surface of ferrous material specimens. Penetrant [37; 38; 39] testing is an easy-to-use, highly sensitive inspection method that is particularly effective at detecting surface-opening defects. While the technique is simple to use and effectively identifies surface anomalies, it is restricted to detecting only those defects that are exposed on the surface, lacking the ability to detect subsurface or near-surface defects. [PERSON] et al. [45] aimed to develop an automated penetrant inspection system using a commercial UAV equipped with a wide-field-of-view camera and an ultraviolet torch to inspect wing panels by flying pre-defined trajectories. Traditional manual penetrant flow inspections are typically time-consuming, taking 1 to 4 h, depending on the object's size. This study introduced an automated, cost-effective, and time-efficient solution for real-time image processing. The proposed non-destructive inspection system detected defects of various sizes, ranging from 2.54 mm to 12.7 mm. The findings indicated that post-processing could enhance reliability, though it would add approximately 2 min to the process. Additionally, further development of the computer vision algorithms was needed to improve the automatic classification and size estimation of defects. Figure 4: (a) Magnetic Particle Inspection testing method [43]; (b) Magnetic Particle Inspection working principle of MPI [44]. Eddy Current [37; 38; 39] is a non-invasive inspection technology based on conductivity, designed to detect surface and near-surface defects. It is highly automated and time-efficient, making it a capable choice for certain applications. A great advantage of this method is that it does not require a couplant between the inspection system and the object. Nevertheless, it is restricted to conductive materials and may sometimes provide inconsistent results, leading to potential confusion. The most common type of defect that Eddy Current can effectively detect is a crack. In 2024, [PERSON] et al.