摘要
浪涌保护器(SPD)广泛应用于铁路通信信号系统中,可实现对被防护电路瞬时过电压、过电流的钳制和泄放。由于浪涌保护器在使用过程中存在劣化问题,因此开展浪涌保护器寿命自监测系统研究非常必要。该系统由传感器、微控制器、显示和通信等多种功能模块构成,可实现对雷电流和脱扣状态监测,以及CAN通信和NFC通信接口等应用;通过计算劣化核,进而计算寿命值,构建SPD寿命模型;展示了SPD状态显示及报警发布的流程。在SPD中引入雷电流测量机制,基于历次雷电流冲击数据构建的寿命模型,相比于单纯依赖是否脱扣作为寿命判别条件更科学、更准确;相比于使用漏电流进行寿命表征,更具有广泛的适用性。实际应用中的SPD适配了该系统后,可明确感知SPD的状态和寿命值,从而降低劳动强度,提升SPD雷电防护的可靠性。
Surge Protection Device(SPD)is widely used in railway communication and signal systems for clamping and releasing instantaneous overvoltage and overcurrent in the protected circuit.Because of the deterioration of SPD in use,it is necessary to study a self-monitoring system for the life span of SPD.The system consists of various functional modules such as sensor,microcontroller,and display and communication modules that enable the monitoring of lightning currents and the tripping state,and applications of CAN communication and NFC communication interfaces.By calculating the deterioration kernel,the life span value was determined,and an SPD life span model was established,in which the process of displaying SPD status and issuing alarms was also described.By introducing a lightning current measurement mechanism in the SPD and constructing a life span model based on historical lightning current impact data,the system can deliver more scientific and accurate results compared to relying solely on tripping as a life span determination condition and has a wider range of applications compared to the method of life span characterization based on leakage current.By adopting the system in practical SPD applications,it becomes possible to perceive the status and life span value of the SPD clearly,thus reducing labor intensity and enhancing the reliability of lightning protection provided by SPD.
作者
靳邵云
肖桐
王州龙
徐金鹏
JIN Shaoyun;XIAO Tong;WANG Zhoulong;XU Jinpeng
出处
《铁道通信信号》
2024年第3期13-18,共6页
Railway Signalling & Communication
基金
中国国家铁路集团有限公司科研专项(J2022G006)
中国铁道科学研究院集团有限公司通信信号研究所科研项目(2021HT14)。
关键词
浪涌保护器
雷电电流采集
脱扣状态监测
劣化
寿命模型
自监测系统
Surge Protection Device(SPD)
Lightning current collecting
Tripping state monitoring
Deterioration
Life span model
Self-monitoring system
