Applying the fault diagnosis techniques to twisted pair copper cable is beneficial to improve the stability and reliability of internet access in Digital Subscriber Line(DSL)Access Network System.The network performan...Applying the fault diagnosis techniques to twisted pair copper cable is beneficial to improve the stability and reliability of internet access in Digital Subscriber Line(DSL)Access Network System.The network performance depends on the occurrence of cable fault along the copper cable.Currently,most of the telecommunication providers monitor the network performance degradation hence troubleshoot the present of the fault by using commercial test gear on-site,which may be resolved using data analytics and machine learning algorithm.This paper presents a fault diagnosis method for twisted pair cable fault detection based on knowledge-based and data-driven machine learning methods.The DSL Access Network is emulated in the laboratory to accommodate VDSL2 Technology with various types of cable fault along the cable distance between 100 m to 1200 m.Firstly,the line operation parameters and loop line testing parameters are collected and used to analyze.Secondly,the feature transformation,a knowledge-based method,is utilized to pre-process the fault data.Then,the random forests algorithms(RFs),a data-driven method,are adopted to train the fault diagnosis classifier and regression algorithm with the processed fault data.Finally,the proposed fault diagnosis method is used to detect and locate the cable fault in the DSL Access Network System.The results show that the cable fault detection has an accuracy of more than 97%,with less minimum absolute error in cable fault localization of less than 11%.The proposed algorithm may assist the telecommunication service provider to initiate automated cable faults identification and troubleshooting in the DSL Access Network System.展开更多
In this paper,the time domain characters of the response of twisted wire pairs(TWPs) excited by the high-altitude electromagnetic pulse (HEMP) have been proposed.The finite different time domain transmission line mode...In this paper,the time domain characters of the response of twisted wire pairs(TWPs) excited by the high-altitude electromagnetic pulse (HEMP) have been proposed.The finite different time domain transmission line model (FDTD-TLM) method,which we have proposed previously,is used to calculate the terminal response of TWP.It shows that the time domain response includes two stages:The transient stage and damped stage.The transient stage is the key point of the coupling and protecting research.The influence factors of the transient stage have been analyzed.In the end,we obtain the changes of the induced voltage when the incident wave parameters and TWP parameters change.展开更多
建立精确的线缆参数模型对于分析测量数据传输过程中的损耗特性,实现测量数据的高速、远距离可靠传输具有重要意义。在建立百米普通双绞线缆参数模型的基础上,通过最小二乘法估计出线缆的损耗特性。矢量网络分析仪对线缆的测试结果表明,...建立精确的线缆参数模型对于分析测量数据传输过程中的损耗特性,实现测量数据的高速、远距离可靠传输具有重要意义。在建立百米普通双绞线缆参数模型的基础上,通过最小二乘法估计出线缆的损耗特性。矢量网络分析仪对线缆的测试结果表明,在10~200 MHz的频率范围内,实测曲线与估计曲线的误差小于0.5 d B,估计出的参数模型表征的衰减特性与实测结果具有良好的一致性。该模型为研究低电压差分信号(low voltage differential signaling,LVDS)信号通过双绞线进行高速、远距离、可靠传输提供了理论依据。展开更多
基金The authors received the funding from Smart Challenge Fund(SR0218I100)GPPS Grant VOT H404,from Ministry of Science,Technology and Innovation Malaysia,and Research Management Centre(RMC)of Universiti Tun Hussein Onn Malaysia(UTHM)。
文摘Applying the fault diagnosis techniques to twisted pair copper cable is beneficial to improve the stability and reliability of internet access in Digital Subscriber Line(DSL)Access Network System.The network performance depends on the occurrence of cable fault along the copper cable.Currently,most of the telecommunication providers monitor the network performance degradation hence troubleshoot the present of the fault by using commercial test gear on-site,which may be resolved using data analytics and machine learning algorithm.This paper presents a fault diagnosis method for twisted pair cable fault detection based on knowledge-based and data-driven machine learning methods.The DSL Access Network is emulated in the laboratory to accommodate VDSL2 Technology with various types of cable fault along the cable distance between 100 m to 1200 m.Firstly,the line operation parameters and loop line testing parameters are collected and used to analyze.Secondly,the feature transformation,a knowledge-based method,is utilized to pre-process the fault data.Then,the random forests algorithms(RFs),a data-driven method,are adopted to train the fault diagnosis classifier and regression algorithm with the processed fault data.Finally,the proposed fault diagnosis method is used to detect and locate the cable fault in the DSL Access Network System.The results show that the cable fault detection has an accuracy of more than 97%,with less minimum absolute error in cable fault localization of less than 11%.The proposed algorithm may assist the telecommunication service provider to initiate automated cable faults identification and troubleshooting in the DSL Access Network System.
基金National Natural Science Foundation of China under Grant No.61671116。
文摘In this paper,the time domain characters of the response of twisted wire pairs(TWPs) excited by the high-altitude electromagnetic pulse (HEMP) have been proposed.The finite different time domain transmission line model (FDTD-TLM) method,which we have proposed previously,is used to calculate the terminal response of TWP.It shows that the time domain response includes two stages:The transient stage and damped stage.The transient stage is the key point of the coupling and protecting research.The influence factors of the transient stage have been analyzed.In the end,we obtain the changes of the induced voltage when the incident wave parameters and TWP parameters change.
文摘建立精确的线缆参数模型对于分析测量数据传输过程中的损耗特性,实现测量数据的高速、远距离可靠传输具有重要意义。在建立百米普通双绞线缆参数模型的基础上,通过最小二乘法估计出线缆的损耗特性。矢量网络分析仪对线缆的测试结果表明,在10~200 MHz的频率范围内,实测曲线与估计曲线的误差小于0.5 d B,估计出的参数模型表征的衰减特性与实测结果具有良好的一致性。该模型为研究低电压差分信号(low voltage differential signaling,LVDS)信号通过双绞线进行高速、远距离、可靠传输提供了理论依据。
