# Review on Rail Damage Detection Technologies for High-Speed Trains
## 3 Non-Destructive Testing Methods for High-Speed Train Rails
### Infrared Thermal Sensing Detection Methods  
Infrared thermal sensor technology is widely used not only in the military field but also in the field of industrial product quality inspection. Infrared thermal sensor technology mainly relies on thermal sensor imaging to obtain thermal images of the detection object; then, based on a series of processing and analysis algorithms developed, it is processed and analyzed to obtain results. Due to the contact operation between the wheel and the rail in high-load and high-speed scenarios, a significant amount of heat is generated on the surface of the rail. The use of infrared thermal bed technology can effectively capture thermal images of the rail surface features, thereby enabling the real-time detection of rail surface defects. At the same time, in the processing of infrared thermal images of railway tracks, there are a series of processing algorithms that can accurately identify and detect surface defects, including damage and defects inside the railway tracks [78]. Infrared thermal sensing detection technology is based on infrared radiation for detection, which is a type of electromagnetic radiation. Infrared radiation is divided into four wavelength bands, as shown in Figure 15: near-infrared (NIR), 0.78-3 um; mid-infrared (MIB), 3-6 um; far infrared (FIR), 6-15 um; and extremely far infrared (XIR), 15-1000 um. Figure 14: Multiple-light-source layout for laser visual detection. With the continuous development of infrared technology, people have increasingly high requirements for the clarity of infrared images, and many new algorithms have been proposed abroad for infrared image processing. In 2011, scholar [PERSON] proposed an adaptive Laplacian filtering algorithm for infrared image enhancement. This algorithm achieves image edge sharpening by minimizing the objective function, improving the clarity and contrast of infrared images [79]. In 2013, American scholar [PERSON] designed an infrared image detection system based on pixel focal plane array which improved the imaging capability of infrared images [80]. In 2015, Malaysian scholar [PERSON] proposed an adaptive contrast enhancement algorithm for infrared image enhancement which improves the visual quality of infrared images by increasing the difference in contrast between the target and the background [81]. In 2016, Indian scholar [PERSON] et al. proposed an infrared image enhancement algorithm based on multimodal image fusion which combines multi-scale decomposition and principal component analysis to improve contrast in infrared images [82]. In 2010, Finnish scholar [PERSON] proposed a manual correction infrared image segmentation algorithm which can analyze and measure the surface area of lesions in human infrared images after segmentation processing and observe their changes over time, which is helpful for clinical diagnosis and treatment [83]. In 2012, American scholar [PERSON] applied infrared image segmentation technology to power equipment detection, extracting the thermal distribution of electrical equipment from segmented images [84]. In 2015, Indian scholar [PERSON] proposed an infrared image segmentation algorithm based on K-means clustering which uses the concepts of fitness and belonging to make the results of image segmentation more applicable [85]. Infrared thermal wave non-destructive testing technology mainly includes three aspects: heating technology, thermal imaging technology, and thermal image processing technology. It can be combined with other detection methods to improve the accuracy of object detection. Compared with traditional non-destructive testing methods such as electromagnetic and eddy current, infrared thermal wave non-destructive testing has the advantages of wide applicability, fast detection speed, large detection area, one-way non-contact detection, and quantitative detection. This article mainly introduces the principle and detection methods of infrared thermal wave non-destructive testing, as well as the application of infrared thermal wave non-destructive testing technology.