# A Method for Detecting Surface Defects in Railhead by Magnetic Flux Leakage
## 4 Experimental Results and Analysis
### Physical Experiment Results and Analysis
#### 4.2.2 Experiment of the Different Spacings of the Sensors  
The detection object is artificial defects, as shown in Figure 10. The distance between auxiliary sensors 1 and 2 to the main sensor is 3.4 mm and the distance between auxiliary sensors 3 and 4 to the main sensor is 2.2 mm. The direction of detection is from left to right. A wire is tied to the rail, which will change the lift-off of the handcart to simulate the vibration interference in the actual process. During detection, when no vibration is encountered, the lift-off of the sensor is fixed at 1 mm, and when the handcart wheel rolls over the wire, the lift-off will fluctuate within 1-2 mm.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Component** & **Model** & **Properties** \\ \hline Sensor & SL-106C & Output voltage of the hall sensor is dozens of millivolts \\ \hline Amplifier & AD620 & Magnification is 100 \\ \hline DAQ card & ADLINK DAQ2208 & Sampling frequency of each channel is set to 10 kHz \\ \hline \hline \end{tabular}
\end{table}
Table 1: Specifications of the experimental system.  
Figure 9: Experimental system.  
Firstly, the \(x\)-components of the sensors are tested. The distance of the main sensor to auxiliary sensors 1 and 2 is set to 3.4 mm, 6.5 mm, and 10 mm, respectively. The detection results are shown in Figure 11.  
Figure 11: _Cont._  
Figure 10: A rail with an artificial defect.  
The sensitivities of the three sensors are different, so the maximum amplitude of each signal is different. According to Figure 11a-c, as shown in the red region, the phase difference of the three signals is obvious when the sensors pass through the defect, and the difference increases with the increase of the sensor distance. In the yellow region, there is vibration interference, the amplitudes of the three signals are different, but the phases are basically the same. For only one sensor signal, the signal changes caused by vibration and defect are similar, which brings great difficulty to defect detection. The relative value of the sensors signals of a defect is different from those of a vibration. When the signal amplitude of the main sensor is the largest, the outputs of the two auxiliary sensors are smaller than that of the main sensor. There is no such phenomenon at the vibration position.  
Secondly, the \(z\)-component of the sensors are tested. The distance of the main sensor to auxiliary sensors 3 and 4 is set to 2.2 mm, 4 mm, and 6 mm, respectively. The detection results are shown in Figure 12.  
Figure 11: \(x\)-component results with different distance.  
Figure 12: \(Cont.\)  
According to Figure 12, when the sensors pass through the defect, the phase difference of the three signals increases with the increase of the sensor distance, as shown in the red region. If there is a vibration interference, the phases of the three signals are basically the same, as shown in the yellow region.  
From the experimental results in \(x\) and \(z\) directions, it can be obtained that the RMS value can eliminate the influence of most system noises. At the same time, the signals at defects and vibration interference signals will be retained. Next, the phase relationship of multiple signals can be used to determine further whether it is a defect. This method can reduce the workload and misjudgment rate.