# A Method for Detecting Surface Defects in Railhead by Magnetic Flux Leakage
## 2 Related Works  
Researchers conducted in-depth research on the MFL detection technology, including the effect of excitation form and size on the MFL signal, the influence of lift-off on the defect signal, the distribution pattern and strength of the \(x,y,\) and \(z\) components of the defects MFL signals [10], and the MFL signal processing and defect signal extraction under different detection conditions [11]. A variety of sensor probe structures have been proposed.  
The establishment process and influence factors of MFL testing are studied [12]. Some magnetization systems are designed to establish the saturation field quickly and improve magnetic field homogeneity, so the accuracy of detection can be improved [13; 14].  
[PERSON] proposes a method using a sensor probe consisting of a semicircular yoke with induction coils at each end and a gradiometer with two anisotropic magnetic resistance sensors for detecting the components perpendicular to the steel surface [15]. [PERSON] studies the influence of sensor lift-off on the magnetic field distribution, which affects the detection capability of various damages and proposes a quantitative approach based on the Pulsed MFL method [16].  
The method creatively utilizes a ferromagnetic one to guide more magnetic flux to leak out. To find small defects in the rail surface, a ferrite is added to an LMF sensor to reduce the reluctance to increase the magnetic intensity above the defects [17]. [PERSON] proposes a high-sensitivity MFL method based on a magnetic induction head [18]. A magnetic core with an open gap is applied to guide leaked magnetic flux into a detection magnetic circuit, where an induction coil is placed to detect the change of the magnetic flux. A coil sensor is designed to detect metallic area loss based using the MFL method. A magnetic sensor prototype was fabricated using the optimum parameters obtained by a numerical parametric study [19]. To cover the whole workpiece or to get more sufficient data, sensor arrays can be used [20]. Researchers carefully set the position of the sensors in the probe and the relative position between the sensors [21; 22].  
[PERSON] and others proposed a new MFL method for pipeline inspection [23]. A signal differential module is introduced to reduce the noise rising from the probe vibration. Defects can only be determined when a certain threshold is reached. However, the leakage magnetic field of a defect is affected by many factors such as lift-off, velocity, remanence, and others interference. Therefore, the appropriate threshold is difficult to set.  
Through these studies, researchers have accumulated some experience to detect the surface defect in railroad by MFL, such as velocity effect and hysteresis effect. Although artificial defects can already be identified in the laboratory, there is still a lot of work to do in the practical application of rail surface defect detection. The existing method of defect identification based on the absolute value of the MFL signal is usually applied to the specific lift-off, speed, and other fixed conditions. The MFL signal of the same defect changes significantly with the change of speed or lift-off. During the actual detection, the speed and lift-off are usually varying. These bring many difficulties to determine whether a defect is present.  
In this paper, a method is proposed to determine whether there is a surface defect in the railroad by using the relative value of multiple sensors signals rather than the absolute value of only one sensor signal. This method reduces the interference of velocity,lift-off, and so on, and improves the reliability of detection results and the accuracy of identifying defects.