Twisted Pair Cable Fault Diagnosis via Random Forest Machine Learning

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.

Transient Response of Twisted Wire Pairs IIIuminated by HEMP

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.

Eavesdropping the display image from conducted emission on network cable of a PC

The display image of a PC can be reconstructed by using the conducted emission on the PC＇s network cable. The relevant signals which be used to reconstruct the original image are coupling from the radiation of the switching of red, green, blue （RGB） signals in PC. These pertinent signals are partly contained in the frequency region higher than 30 MHz in the conducted emission. From these findings, the near-field coupling principle from PC to the network cable is analyzed firstly. And then, a multi-conductor transmission model for the RGB signals which transmit in the network cable is proposed. In addition, the maximum safe distance is estimated by using this model. In order to check the validity of the estimating distance, the eavesdropping experiment is carried out to reconstruct the original display image. The results demonstrate that the blurred display image can be retrieved at the place of 29.5 m.