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J. Electromagn. Eng. Sci > Volume 24(5); 2024 > Article
Deng, Tan, Yin, Zhou, Li, and Liu: Analysis and Experimental Validation of Electromagnetic Interference of Anti-UAV Equipment on Time Synchronization Devices in Electrical Substations

Abstract

Considering the rapid development of the unmanned aerial vehicle (UAV) industry, it is crucial to prevent UAVs from accidentally entering substations. Installation of anti-UAV equipment is the most effective way to address this issue. However, the influence of electromagnetic interference (EMI) signals emitted by anti-UAV equipment on time synchronization devices (TSDs) used in substations has not been investigated in detail. This paper proposes an EMI evaluation method for the effect of anti-UAV equipment on TSDs. Simulations and Experiments were conducted to validate the proposed method with the results indicating that deceptive anti-UAV equipment (DAE) is more suitable for substations than suppressive anti-UAV equipment (SAE). Moreover, it is established that DAE should be installed 60 m away from TSDs in substations. This recommendation offers valuable guidance for the installation and deployment of anti-UAV equipment in substations in the future.

Introduction

The increasing application of unmanned aerial vehicles (UAVs) has resulted in various accidents over time, with some even causing serious damage. As a result, the development and management of UAVs are becoming increasingly prominent. Simultaneously, countermeasures for the proper management of UAVs have emerged as a global concern [1]. For instance, countries require substations to deploy anti-UAV systems, further proposing that the transmission power and frequency band of anti-UAV equipment should comply with national regulations.
The time synchronization device (TSD) is one of the most basic automatic devices used in substations [2, 3]. Notably, when anti-UAV equipment transmits interference signals, disturbances in the normal reception of satellite signals by the TSD have been observed. Such disturbances affect time accuracy in substations, which impacts the normal operation of automatic devices. Consequently, this may lead to synchronization issues, hindering the accurate identification of transmission line faults. If these fault points within the power system are not addressed in a timely manner, their impact could exacerbate. In more severe cases, such disturbances could paralyze the entire power system. Therefore, to mitigate operational accidents caused by synchronization faults, electromagnetic interference (EMI) evaluation methods for the effect of anti-UAV equipment on the TSD of substations need to be examined in detail.
In terms of EMI from anti-UAV equipment, most existing research has focused on the effectiveness of anti-UAV equipment on UAVs without accounting for the disturbance in surrounding buildings [4, 5]. Currently used anti-UAV technology is already quite mature—it involves defense technologies, such as early warning detection, electrical interference, and direct injury [6, 7]. However, the main utilization of anti-UAV technology is electrical interference technology, which utilizes suppressive anti-UAV equipment (SAE) and deceptive anti-UAV equipment (DAE) to counter UAVs. SAE covers the real signal by transmitting interference signals, while DAE is designed to confuse UAV navigation systems by mimicking their satellite receiving signals. Furthermore, in terms of EMI in substations, most research has focused on the impact of EMI on secondary equipment in substations [810]. At present, no research on the effect of EMI signals emitted by anti-UAV equipment on automatic devices inside substations has been conducted.
The main factor that distinguishes this paper from existing research is the area of focus. Other studies have primarily concentrated on analyzing the impact of interference signals emitted by anti-UAV equipment on UAVs. They also examined the electromagnetic compatibility and EMI coupling mechanism of the equipment in substations. However, this paper focuses on the impact of EMI signals emitted by anti-UAV equipment on TSDs in substations. By examining this aspect, this paper aims to address the gap in the literature related to the impact of anti-UAV equipment on TSD and its potential consequences for substations.
The rest of this paper is organized as follows. Section II addresses two key aspects pertaining to anti-UAV equipment. First, it analyzes the impact of interference signals emitted by anti-UAV equipment on the timing accuracy of TSDs based on the principle of global positioning system (GPS) timing and the generation of interference signals. Second, an EMI evaluation method with multiple indicators for the impact of anti-UAV equipment on TSD is proposed. In Section III, a simulation of a substation is conducted, focusing on the activation of anti-UAV equipment and the examination of the electromagnetic signal power intensity and electric field intensity spatial distribution. The simulation is performed considering different transmission powers of the anti-UAV equipment. Drawing on the simulation results, Section IV focuses on measuring the signal power intensity and electric field intensity spatial distribution of the anti-UAV equipment to validate the effectiveness of the simulation. The measurement also assesses the interference signals that impact satellite quality and timing accuracy. Finally, Section V summarizes the paper.

Theoretical Illustration

Fig. 1 illustrates the impact of anti-UAV equipment on EMI in substations. When UAVs enter a substation by mistake, anti-UAV equipment transmits interference signals to them. However, these signals also have an impact on the TSD in the substation, which is the primary issue discussed in this paper.

1. GPS Timing Principle

The purpose of GPS timing is to measure the deviation of the TSD clock relative to the GPS time. Time synchronization is achieved by correcting the local clock of the receiver based on clock deviation [11].
The GPS antenna samples and processes GPS signals based on the TSD clock at tu(t) times, resulting in a GPS signal transmission time of t(n)(t). In this context, pseudo-distance is defined as the difference between signal reception time and signal transmission time multiplied by the speed of light c, which can be formulated as follows:
(1)
ρ(t)=c(tu(t)-t(n)(t)).
The purpose of the GPS positioning and timing algorithm is to solve a system of equations involving four unknown quantities: the receiver coordinates (x,y,z) and the difference δtu of the pulse per second (PPS) or the inter-range instrumentation-group-B (IRIG-B) code between the satellite clock and the local clock. This can be represented mathematically as Eq. (2), as noted below:
(2)
{(x(1)-x)2+(y(1)-y)2+(z(1)-z)2+cδtu=ρc(1)(x(2)-x)2+(y(2)-y)2+(z(2)-z)2+cδtu=ρc(2)(x(N)-x)2+(y(N)-y)2+(z(N)-z)2+cδtu=ρc(N).
This indicates that the TSD needs to receive signals from four or more satellites to achieve GPS timing.

2. Interference Principle of Anti-UAV Equipment and the Satellite Quality of TSD

2.1 SAE

Suppressive EMI generates broadband or narrowband active noise signals in the tuning frequency band of a radar to create a strong disturbance environment through spatial radiation. The noise is artificially transmitted to the receiver, increasing its input noise level and jamming-to-signal ratio (Rjs), thereby interfering with normal operation [12]. Notably, Rjs refers to the power ratio of the interference signals at the receiver input end and the communication signal. Therefore, Rjs at the communication receiver input end can be expressed as:
(3)
jsr=PjrPsr=PjGjrGrjPtGtrGrt[dcdj]2,
where Pj is the output power of the interference transmitter, Pt is the output power of the communication transmitter, Gjr is the gain of the interference transmitter antenna, Gtr is the gain of the communication transmitter antenna, Grj is the gain of the SAE antenna, Grt is the gain of the TSD antenna, dc is the distance between the communication transmitter and the TSD, and dj is the distance between the interference transmitter and the TSD.

2.2 DAE

The calculated position of the TSD is susceptible to shifts in the presence of deceptive EMI signals. Notably, such shifts are a result of changes in the code delay of the electromagnetic signal received by the TSD [13]. In Fig. 2, the TSD is placed at point A, and the DAE is positioned at point C. Since the false signal emitted by the anti-UAV equipment has a higher strength than the true GPS signal, the real signal is pulled toward the deception signal, leading to the positioning information displayed on the TSD showing point B.
Based on Fig. 2, the delay between the DAE and the satellite can be represented as follows:
(4)
{t1=(rB1-rC1-rAC)/ct2=(rB2-rC2-rAC)/ct3=(rB3-rC3-rAC)/c,
where rBi (i = 1, 2, 3) represents the distance between the satellite and the deception position, rCi refers to the distance between the satellite and the DAE, and rAC indicates the distance between the DAE and the TSD. On modifying the delay using Eq. (4), the clock bias in the original position determined by the TSD can be transformed, thereby resulting in clock bias in the deceptive position determined by TSD. Consequently, the timing accuracy of the TSD is impacted.

3. Interference Principle of Anti-UAV Equipment and the Time Accuracy of TSD

The time synchronization system in a power grid sends time synchronization signals to all timing devices in the substation. Notably, systems with high time accuracy requirements must use soft time synchronization involving the PPS or IRIG-B code to ensure time accuracy [14, 15]. Time accuracy is a fundamental measure of time precision.
In Fig. 3(a), |t1t2| represents the time accuracy of the PPS. In Fig. 3(b), |t3t4| shows the time accuracy of the IRIG-B code.
When employing satellite timing for synchronization, it is imperative for the TSD to ensure that the timing accuracies of the PPS and IRIG-B code are lower than 1 μs. Moreover, the time accuracy in a punctual state should be lower than 1 μs/hr [16].

4. EMI Evaluation Method with Multiple Indicators to Investigate the Impact of Anti-UAV Equipment on TSD

The TSD in a substation is composed of three units: a receiving unit, a clock unit, and an output unit. Its main objective is to synchronize with the protection, measurement, and fault-recording devices within the substation, which is accomplished through the outputs of the IRIG-B code and PPS signals [17]. The proposed EMI evaluation method with multiple indicators for TSD is illustrated in Fig. 4. Usually, a TSD lacks EMI detection capabilities. To monitor EMI, an EMI detection module was designed before constructing the receiving unit of the TSD. Furthermore, a time synchronization tester was employed to measure the timing accuracy of the PPS and the IRIG-B code.
Notably, an EMI detection module is capable of detecting both suppressive and deceptive interference signals from received signals. In the absence of interference signals, the radio frequency (RF) switch inside the EMI detection module remains closed. The signals from the BeiDou satellite navigation system (BDS) and GPS antennas are transmitted directly to the TSD, allowing it to operate normally. However, when the antenna receives an interference signal, the RF switch connected to the corresponding disturbed channel is triggered. In such a situation, the EMI detection module utilizes the signal from the other undisturbed antenna to maintain timing. However, if both antennas receive interference signals, the RF switches are simultaneously engaged. Consequently, the TSD is unable to receive satellite signals and enters self-holding mode.
Simultaneously, measurements were carried out using a spectrum analyzer. These measurements assessed the power intensity of the electromagnetic signals received by the antenna at the substation. The spatial distribution of the power intensity and electric field strength of the interference signals emitted by the anti-UAV equipment were also analyzed considering various transmission powers. Subsequently, Rjs was calculated to help determine the range within which the TSD remained unaffected by EMI.
In summary, the proposed EMI evaluation method involving multiple indicators facilitates the assessment of the temporal reliability of the TSD based on three indicators: the Rjs, the number of satellites captured by the GPS and BDS antennas, and the δtu. When Rjs reaches 10, the number of satellites captured by the GPS antenna (NG) becomes either 0 for SAE or equal to the number of false GPS satellites for DAE, or the δtu is lower than 1 μs, it is determined that the received GPS signal has been disturbed. Furthermore, when Rjs reaches 30, the number of satellites captured by the BDS antenna (NB) is less than 4 for the DAE, or the δtu is higher than 1 μs, it is determined that both the received GPS and BDS signals have been disturbed. Moreover, when the δtu progressively enlarges with the passage of time, the TSD is found to be in a punctual state.

Simulation Analysis and Result Discussion

1. Mathematical Model

The majority of anti-UAV equipment employs a method in which interference signals are injected into the receiving antenna. This interference is intended to disrupt the electromagnetic signals received by the TSD.
Considering that the signal undergoes propagation loss in free space, the calculation formula for signal power intensity at different distances can be expressed as follows:
(5)
P2=10lgP1G1G21mW-20lg4πRλ,
where P2 is the power intensity of the detection points at different distances, P1 is the transmission power of the anti-UAV equipment, G1 is the transmission antenna gain, G2 is the receiving antenna gain, λ is the GPS carrier wavelength, and R is the distance between the anti-UAV equipment and the TSD antenna.

2. Boundary Condition Settings

The distribution of electromagnetic signals inside the substation on activating the anti-UAV equipment is illustrated in Fig. 5. To conduct the analysis, a near-field calculation area was established within the primary equipment area of the substation. The purpose of selecting this calculation area was to examine electromagnetic signal distribution. The calculation area encompassed a range of 60 m, with the anti-UAV equipment stationed at the center. The surface antenna and line antenna were divided using a finite element algorithm. Subsequently, the electromagnetic field generated by the anti-UAV equipment in space was calculated according to Eq. (5). The purpose of this simulation was to study the EMI generated by anti-UAV equipment during operation. Additionally, the simulation utilized omnidirectional antennas to replace the anti-UAV equipment for transmitting the interference signals. In this simulation, it was crucial to account for both the GPS antenna in the TSD and the transmission signal frequency of the DAE, which operated at 1,575.42 MHz. Notably, the SAE had a maximum transmission power of 10 W, while the DAE had a maximum transmission power of 10 mW. Therefore, the simulation focused on setting the frequency to 1,575.42 MHz and manipulating the power levels, specifically at 10 W, 5 mW, and 10 mW.

3. Simulation and Calculation Results

Fig. 6(a) illustrates the near-field distribution of the electromagnetic signals emitted by the primary equipment of the substation. The measurements were recorded at a height of 0 m and at a power intensity of 10 W for the anti-UAV equipment.
Fig. 6(b) shows the calculated distribution values of different signal power intensities for the anti-UAV equipment in free space. Specifically, both the x-axis and the z-axis are set to 0 m. It is observed that the interference signals generated by the anti-UAV equipment in free space present an exponential decay trend.

Experimentation

1. Experimental Equipment Parameters

The anti-UAV equipment used in this experiment complied with national standards. The DAE employed an omnidirectional antenna with a maximum transmission power of 10 mW, which was capable of generating 10 channels of deceptive GPS interference signals. Meanwhile, the SAE utilized a directional antenna with a maximum transmission power of 10 W. The handheld spectrum analyzer had an average noise floor of −155 dBm. Furthermore, the equipment comprised a high-precision directional detection antenna with a frequency range of 1 MHz to 9.4 GHz that enabled accurate electromagnetic environment detection with a measurement accuracy of 1 dB. The EMI detection module incorporated a satellite safety isolation device capable of the real-time detection of interference signals within the received signals. In the presence of interference signals, the EMI detection module isolated the signals and issued an alert. The GPS and BDS antennas had a minimum reception power of −135 dBm and −127.6 dBm, respectively. Moreover, the GPS and BDS antennas could receive signals from up to 12 and 11 satellites, respectively. The time synchronization testers (YZ-9900 and YZ-9910) possessed the highest level of performance in terms of electromagnetic compatibility, thus serving as high-precision and highly stable timing references.

2. Experimental Environment Settings

GPS and BDS antennas are typically installed on the rooftop of the main control room. In this study, anti-UAV equipment were deployed at different locations within the substation to measure its impact on the TSD at various distances.
The detection mechanism presented in Fig. 7 aims to assess the received satellite count and timing accuracy under the influence of EMI. The experiment involved the use of SAE (10 W) and DAE (5 mW and 10 mW) at different distances. The anti-UAV equipment simultaneously applied disturbance to both the GPS and BDS antennas. Notably, measurements were conducted between 14:00 and 16:00 each day. At each measurement point, a 10-minute interference signal was introduced after the TSD achieved clock synchronization by receiving authentic GPS and BDS signals. The interference signal was applied for a duration of 10 minutes.
To assess the impact of the anti-UAV equipment on TSD, two key parameters were observed. First, the satellite count was monitored to determine the presence of any interference. Second, the time accuracies of the PPS and IRIG-B code were measured using the time synchronization testers. Simultaneously, the spectrum analyzer was employed to measure the power intensity of the background signal at the 220 kV substation. Additionally, the signal power intensity and spatial distribution of the anti-UAV equipment at different transmission powers were measured.

3. Detection and Analysis of EMI Signals Power Intensity in Anti-UAV Equipment

Fig. 8 depicts the frequency spectrum of the GPS antenna at the 220 kV substation when the anti-UAV equipment is not triggered. Based on the measurement results, it is observed that the power intensity of the background GPS signal frequency band (1,575.42 MHz) is only −76.7 dBm.
The measured values of GPS interference signal power intensity at each measurement point are shown in Fig. 9(a). Compared with the calculated value of 10 W signal power intensity in Fig. 6(b), the trend is the same as the actual measurement value. Due to the presence of background noise, the attenuation trend of measured values is smoother compared to calculated values. Therefore, the power intensity of the interference signal calculated by Eq. (5) is effective.
The measured values of the power intensity of the GPS interference signal at each measurement point are shown in Fig. 9(a). In contrast to the calculated value at the 10 W signal power intensity in Fig. 6(b), the trend in Fig. 9(a) is similar to the actual measurement value. Notably, due to the presence of background noise, the attenuation trend of the measured values is observed to be smoother than that of the calculated values.
Moreover, the experimental measurements show a maximum and minimum value of −15 dBm and −53 dBm, respectively. These results indicate that the simulated measurements align closely with the experimental measurement data, with the relative error not exceeding 10%. This comparison further highlights the reliability and accuracy of the simulation in reproducing signal power intensity.
Fig. 9(b) shows that the spatial electric field intensity reaches 5.2 V/m after the SAE is triggered, with its electromagnetic field radiation being considerably lower than the 10 V/m specified in the standard [18]. Therefore, the EMI generated by the main body of the TSD is found to be relatively small.
The power strength of the GPS deception signal in the DAE is a key factor involved in successfully deceiving the GPS antenna. Fig. 10(a) presents a comparison of the measured values of the deception interference signal at different power intensities, showing a trend similar to the simulated values. The close agreement further validates the effectiveness of the simulation model in calculating signal power intensity. Therefore, Eq. (5) can be applied to the power intensity attenuation of deceptive interference signals transmitted by the DAE.
Furthermore, Fig. 10(b) indicates that the space electric field intensity reached 52 mV/m. As a result, the disturbance caused to the TSD by the anti-UAV equipment is considered minimal.
When the SAE was activated at a power of 10 W, the GPS signal power intensity measured at a distance of 100 m was −57 dBm. Subsequently, by applying Eq. (3), the Rjs was calculated as 9.66. Meanwhile, the GPS signal power intensity measured at a distance of 10 m was −38 dBm, with the Rjs being 86.10. Therefore, it is evident that SAE causes significant EMI with regard to GPS signals within the range of the 220 kV substation. Meanwhile, when the DAE was activated with a power of 10 mW, the GPS signal power intensity measured at a distance of 60 m was −61.9 dBm, with the Rjs being 5.50. In contrast, the GPS signal power intensity measured at a distance of 10 m was −48 dBm, with the Rjs being 27.23. Based on these findings, it is evident that the high-frequency background EMI produced by DAE in substations is primarily concentrated in the mobile communication frequency band. Additionally, it is observed that this interference has a minimal impact on GPS signals. Therefore, DAE is considered more suitable for preventing the accidental entry of UAVs in substations than SAE.

4. Influence and Analysis of EMI Signals on Satellite Quality

Upon activating the SAE in the 220 kV substation, the NG gradually decreased to 0. As the distance between the SAE and the receiving antenna approached, the number of received satellites started changing at a faster rate. Meanwhile, the alarm signal lights of the EMI detection module displayed a red light. Consequently, the GPS suppressive interference signals hindered the reception of satellite signals by the antenna of the TSD.
Fig. 11 and Table 1 show the impact of the DAE, indicating that the quality of the GPS and BDS signals deteriorates as the distance decreases. This is because when the RF front-end of GPS and BDS antennas encounter EMI, it becomes challenging to simultaneously capture and track multiple satellite signals for a certain period. Consequently, there is a decline in positioning and timing accuracy.
Fig. 11 shows that EMI signals emitted by the SAE at the 1.5 GHz frequency point influence the GPS and BDS antennas within the 220 kV substation. Additionally, when the GPS antenna is 60 m away from the DAE, the EMI detection module fails to detect the deceptive interference signal. However, at a distance of 50 m from the DAE, the GPS antenna captures the 10-channel deception satellite signal, regardless of whether the DAE emits a power of 5 mW or 10 mW. Therefore, it was determined that the DAE is able to disrupt the GPS antenna of the TSD.
Furthermore, when the power intensity is too strong, the signals tend to saturate the BDS antenna’s RF. Consequently, the quality of the BDS signal reception declines severely, posing a risk of weakening the overall performance of the antenna. In particular, when the transmission power is 5 mW and the BDS antenna is located 1 m away from the DAE, the NB is found to be 0 in Fig. 11(a). This indicates that the satellites captured by the BDS antenna do not comply with the timing calculation conditions of Eq. (2). Furthermore, the BDS module of the TSD is observed to be out of step. Furthermore, when the transmission power is 10 mW and the BDS antenna is located within 7 m, the NB is found to be 2, resulting in a disorder in the BDS module.

5. Influence and Analysis of EMI Signals on Time Accuracy

During the experiment, the TSD immediately fell into a punctual state after the SAE was activated. Moreover, as the punctuality duration increased, the time accuracy exceeded the threshold required by the substation equipment. This poses a threat to the normal operation of the substation automatic devices.
Fig. 12(a) depicts the time accuracy of the PPS and IRIG-B code when P1 = 5 mW. When the distance between the antennas and the DAE exceeds 2 m, the timing of the TSD relies on the BDS antenna, with a stable time accuracy ranging from 50 to 100 ns. However, when the distance is within 2 m of the DAE, the BDS antenna is strongly disturbed and fails to capture the satellite signals. As a result, the TSD falls out of step and maintains a punctual state.
Fig. 12(b) illustrates the time accuracy of the PPS and IRIGB code when P1 = 10 mW. At a distance of more than 10 m, the GPS antenna is cutoff. Furthermore, the TSD serves as a timing source, relying on the BDS antenna. In this case, the stable PPS time accuracy ranges between 50 and 100 ns. Similarly, the time accuracy of the IRIG-B code exhibits stability within the range of 100 to 250 ns. The time accuracy is lower than 1 μs, thus meeting the timing accuracy threshold. However, when the distance is within 10 m of the DAE, the TSD falls out of step, and the device transitions into a punctual state. As the δtu gradually enlarges with the passage of time, it eventually paralyzes power systems in extreme cases.

Conclusion

This paper proposes an EMI evaluation method involving multiple indicators to assess the impact of anti-UAV equipment on TSDs in substations. The following guidance is provided for the installation and deployment of anti-UAV equipment in substations in the future:
  • 1) Since the TSD is a double modular redundancy of the GPS and BDS, it is only when the GPS and BDS antennas are disturbed simultaneously that the TSD attains a punctual state. After the duration of the punctual state exceeds 1 hour, the time accuracy will exceed the threshold of 1 μs, posing a severe threat to automatic devices in substations.

  • 2) An EMI evaluation method involving multiple indicators is proposed to judge whether the TSD is disturbed. When Rjs reaches 10, NG becomes 0 for SAE or becomes equal to the number of false GPS satellites for DAE, or δtu is lower than 1 μs, it is determined that the received GPS signal has been disturbed. Furthermore, when Rjs reaches 30, NB is less than 4 for DAE, or δtu is higher than 1 μs, it is determined that the received GPS and BDS signals have been disturbed.

  • 3) Based on the results obtained from the EMI evaluation method, the simulation, and the experiment, DAE is found to be more suitable for installation in substations. Specifically, the installation distance between the DAE and the TSD directly determines the degree of disturbance. When the DAE is installed more than 60 m away from the TSD, the influence of the EMI on the device is negligible. However, at a distance of 10–60 m, the received GPS signal is influenced by the DAE. In particular, when the DAE is located within 10 m of the TSD, the received GPS and BDS signals both experience disturbances, which are responsible for the TSD being in a punctual state.

Acknowledgments

This work was supported by the Science and Technology Funded Project of China Southern Power Grid Co., Ltd. (No. 0006200000086753) and the Project Supported by the National Natural Science Foundation of China (No. 51977083).

Fig. 1
Schematic diagram of the impact of anti-UAV equipment on EMI in substations.
jees-2024-5-r-255f1.jpg
Fig. 2
Principle behind DAE interfering with TSD antenna.
jees-2024-5-r-255f2.jpg
Fig. 3
Time accuracy of the TSD: (a) PPP and (b) IRIG-B code.
jees-2024-5-r-255f3.jpg
Fig. 4
The proposed EMI evaluation method with multiple indicators for TSD.
jees-2024-5-r-255f4.jpg
Fig. 5
Substation simulation model.
jees-2024-5-r-255f5.jpg
Fig. 6
Diagram of the simulation and calculation results: (a) near-field distribution diagram of power intensity in substation and (b) calculated values of different signal power intensities.
jees-2024-5-r-255f6.jpg
Fig. 7
Schematic diagram of EMI detection.
jees-2024-5-r-255f7.jpg
Fig. 8
Scanning frequency spectrum of the GPS antenna at the 220 kV substation.
jees-2024-5-r-255f8.jpg
Fig. 9
Measured value of (a) the signal power intensity of SAE and (b) the electromagnetic signal strength for SAE.
jees-2024-5-r-255f9.jpg
Fig. 10
Measured value of (a) the signal power intensity of DAE and (b) signal electric field intensity of DAE.
jees-2024-5-r-255f10.jpg
Fig. 11
Changes in the number of GPS/BDS satellites at difference distances: (a) 5 m/W and (b) 10 m/W.
jees-2024-5-r-255f11.jpg
Fig. 12
Time accuracy disturbance situation of the TSD: (a) 5 m/W and (b) 10 m/W.
jees-2024-5-r-255f12.jpg
Table 1
Changes in alarm signal lights of the EMI detection module
Distance

5 m 10 m 50 m 60 m
5 mW
 GPS Solid red light Solid red light Normal Normal
 BDS Flashing red light Normal Normal Normal
10 mW
 GPS Solid red light Solid red light Flashing red light Normal
 BDS Flashing red light Normal Normal Normal

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Biography

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Honglei Deng, received his B.Eng. degree in electrical engineering from Harbin Institute of Technology, Weihai, in 1995, and his M.Eng degree in engineering from Wuhan University in 2002. In 2005, he completed his Ph.D. in engineering from the Institute of Electrical Engineering, Chinese Academy of Sciences. Currently, he is an associate professor at the School of Electric Power Engineering, South China University of Technology, Guangzhou, China. His research interests include the online monitoring of power equipment and AC/DC hybrid distribution networks.

Biography

jees-2024-5-r-255i2.jpg
Junyang Tan, received his B.Eng. degree in electrical engineering from Hunan University in Changsha, China, in 2021. He is currently working toward his M.Eng. degree in electrical engineering. His research interests include high-frequency electromagnetic interference.

Biography

jees-2024-5-r-255i3.jpg
Yanyang Yin, received his B.Eng. degree in electrical engineering from Jinan University, Guangzhou, China, in 2021. He is currently working toward his M.Eng. degree in electrical engineering. His research interests include high-frequency electromagnetic interference.

Biography

jees-2024-5-r-255i4.jpg
Wenqing Zhou, received his B.Eng. degree in electrical engineering from South China Agricultural University in 2018, and his M.Eng. degree in engineering from South China University of Technology in Guangzhou, China, in 2021. He is currently pursuing a Ph.D. degree at the South China University of Technology. His research interests include the online monitoring of power equipment and smart grid technology and applications.

Biography

jees-2024-5-r-255i5.jpg
Wenxiang Li, received his B.Eng. degree in engineering management in 2000 and his M.Eng. degree in electrical automation from North China Electric Power University in 2008. He is currently a senior engineer. His research interests include power system and grid security protection.

Biography

jees-2024-5-r-255i6.jpg
Gang Liu, received his B.Eng., M.Eng., and Ph.D. degrees in electrical engineering from Xi’an Jiaotong University, Xi’an, China, in 1991, 1994, and 1998, respectively. Currently, he is a professor at the School of Electric Power Engineering, South China University of Technology, Guangzhou, China. His research interests include current carrying capacity assessment and fault diagnosis of electrical equipment and lightning protection of transmission lines.
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