## 1 Introduction  
EMI (Electromagnetic Interference) prediction and analysis of onboard sensitive equipment on high-speed trains is a primary requirement to ensure the safe operation of trains. It is also the main basis for the EMC (Electromagnetic Compatibility) design and EMI protection of the entire high-speed railway. Wireless communication systems are critical systems to ensure the timely transmission of train control information and the safe operation of trains. Thus, EMI research for wireless communication transmission systems has become an important issue. Generally, some wireless communication antennas are placed on the roof of the train close to the pantograph. Therefore, pantograph arcing disturbance has become the main electromagnetic disturbance source in its electromagnetic environment [1, 2]. Based on previous research, the main power spectrum range of pantograph arcing is from a few hundred Hz to a few GHz [3]. It interferes with antenna reception and may cause communication anomalies. Much research has studied the impact of pantograph arcing on wireless communication transmission systems, especially the transmission quality of the GSM-R (Global System for Mobile Communications for Railway) signal. For example, the impact of pantograph arcing on the GSM-R wireless communication system caused by the train passing through a neutral section is studied by electromagnetic simulation software in [4]. Ref. [5] studied the interval time of pantograph arcing and analyzed the BER (Bit Error Rate) of the wireless GSM-R signal due to the interval time of arcing. However, as a second-generationmobile communication technology, GSM-R fails to meet the large data communication requirements of video surveillance, video conferencing, passenger service, and other high bandwidth applications on high-speed railways. Compared with GSM-R, LTE-R has the advantages of more flexible bandwidth, higher transmission rates and spectral efficiency, as well as good service agility, strong service carrying capacity, and good security in high-speed mobile services [6]. Therefore, the evolution of high-speed railway communications from the existing GSM-R to LTE-R has become an inevitable trend of practical demand and technology development [7; 8]. In fact, LTE supports TDD (Time Division Duplex) used in China and FDD (Frequency Division Duplex) used in Europe [9]. It will be a trend for LTE to replace GSM in railway applications. The interference of pantograph arcing on LTE-R TDD signal quality in the 400 MHz frequency band is studied in [10]. In [11], the time-domain and frequency-domain characteristics of pantograph arcing are modeled, and a measurement system is established in the laboratory to evaluate the impact of interference on the downlink throughput of the LTE-R system. However, there is little mention of the real-time analysis of the interference to LTE-R roof antennas via pantograph arcing and the real-time dynamic signals coupled to the antenna ports. In a previous article published by the author's laboratory, a fast prediction model based on machine learning is established to analyze the coupling coefficient between pantograph arcing and the GSM-R roof antenna [12]. Nevertheless, this research is entirely based on simulation results. Long simulation times and large storage spaces are required to obtain large amounts of simulation data. In order to obtain more practical engineering requirements, based on previous studies, the prediction and analysis methods proposed in this paper use a small amount of simulation data. The proposed method overcomes the problem of difficult measurements for the interference at the roof antenna port. It enables rapid identification of pantograph arcing characteristics and prediction of interference coupling problems on the LTE-R roof antenna. When machine learning algorithms are used to solve electromagnetic problems, the number of repeated measurements or electromagnetic simulations will be greatly reduced.