# Research on Wheel Flat Recognition Based on Wayside Wheel-Rail Force
## 5 Field Test and Discussion
The algorithm processes the spatially ordered discrete wheel-rail forces generated by the same wheel, utilizing the wheel passage sequence and proximity switch signals, as illustrated in Figure 18b. From Figure 18b, it is evident that when a wheel passes through the detection area, the responses of each force-measuring channel occur in a precise spatiotemporal sequence with consistent time intervals. The top data from all test channels exhibit smooth characteristics, free of any impact-induced anomalies or signal burrs. The wheel-rail force profile obtained through the concatenation method is presented in Figure 19. The data reveals that the fluctuations in the wheel-rail force remain within the normal operational range, devoid of significant burrs or wheel-rail impact signatures. This observation strongly suggests that the wheel is in excellent condition, free from surface defects such as wheel flats; it serves as excellent comparative data for the faulty wheel data. With a wheel-rail force magnitude of approximately 120 kN, it can be deduced that the vehicle is operating under a full-load condition, corresponding to a payload of around 76 t.  
Figure 20 illustrates an abnormal wheel-rail force signal detected by the No. 2 left-side wheel-rail vertical force channel in an empty car line, with the channel positioned on the right side relative to the incoming vehicle direction. A magnified view of the wheel-rail impact reveals that the abnormal force signature originates from wheel tread damage. Retrieve all the wheel data of this wheel from all channels and connect them in the time domain; the continuous wheel-rail force results can be obtained, as shown in Figure 21.  
Figure 19: Connected wheel–rail force of a normal wheel in spatial order. Figure 18: A train’s whole wheel–rail forces collected in a single test channel (**a**). The discrete wheel–rail force obtained by a single wheel passing through the whole system (**b**). The vehicle speed during this test was 59.89 km/h, with a maximum wheel-rail impact force of 46.1 kN. The average wheel-rail force of 25 kN confirms an empty-load condition. Leveraging the wheel flat mapping relationships and linear interpolation method established in Section 4 for heavy-haul trains, the calculated flat length for this wheel is approximately 4.2 mm. Figure 22 displays the wheel-rail force signal of an abnormal train experiencing a wheel-rail impact. The vehicle was operating under fully loaded conditions, with the wheel generating an impact equivalent of 1.397 and a maximum impact force of approximately 170 kN--prompting the system to trigger a warning signal. Tracking records indicate the train number was 28,940, the vehicle number 0018149, and the vehicle type C80, with a  
Figure 21: Connected wheel–rail force of the wheel with the wheel flat. Figure 20: Abnormal wheel–rail impact force detected by wheel–rail force detection system. Substituting the impact parameters into the mapping relationship established in Section 4, the calculated wheel flat length is 7.3 mm. Cross-referencing with the TPDS (Truck Performance Detection System) alarm data on the same route (Figure 23) reveals consistent alarm timing and impact characteristics. The vehicle number, train number, and vehicle type all match perfectly between the two systems, validating the reliability of TODS' detection results. The wayside detection system has been in field tests for 10 days (from 17 October to 27 October 2022), continuously monitoring passing vehicles with extensive data acquisition. In total, it has detected 465 trains comprising 56,265 vehicles, 225,060 wheelsets, and  
Figure 23: TPDS fault alarm data comparison (to ensure the authenticity of the data, the text has retained the Chinese description). Figure 22: Measured data of wheel–rail impact force for abnormal wheels. 450,120 wheels, with the C80 vehicle type constituting the majority. During this period, the system captured 20 wheel-rail impact events, including 4 from downstream trains and 16 from upstream trains.