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.

Asymmetric Patch Element Reflectarray with Dual Linear and Dual Circular Polarization

A reflectarray antenna consisting of asymmetrical patch elements is proposed,which is capable of producing dual linear and dual circular polarized operation at 26GHz frequency.The main purpose of this design is to support four different polarizations using the same patch element.The proposed reflectarray has a single layer configuration with a linearly polarized feed and circular ring slots in the ground plane.Asymmetric patch element is designed from a square patch element by tilting its one vertical side to some optimized inclination.A wide reflection phase range of 600°is obtained with the asymmetric patch element during unit cell measurements.A 332 element circular aperture reflectarray is designed with the proposed configuration and experimentally validated with a linearly polarized prime feed configuration.Two different orientations of mirror and non-mirror asymmetric patch elements on the surface of reflectarray are analyzed.Dual linear polarization is obtained with the mirror orientation of the asymmetric patch elements on the surface of reflectarray.Alternatively,asymmetric patch elements without mirror orientation are demonstrated to produce dual circular polarization with the same linearly polarized feed.A maximum measured gain of 24.4 dB and 26.1 dB is achieved for dual linear and dual circular polarization,respectively.Their respective measured efficiencies are 28%and 41.3%,which are supported by amaximum−3 dB gain bandwidth of 13.8%and 11.5%.The circular polarization operation of the reflectarray is also supported by a 6 dB axial ratio bandwidth of 9.2%.The proposed asymmetric patch reflectarray antenna with polarization diversity,wide bandwidth and high gain is suitable to be used in many high frequency applications of 5G communication.

Detection of Low Sugar Concentration Solution Using Frequency Selective Surface (FSS)

Sugar is important in daily food intake since it is used as food preservative and sweetener.Therefore,is important to analyze the influence of sugar on the spectroscopic properties of the sample.Terahertz spectroscopy is proven to be useful and an efficient method for sugar detection as well as for future food quality industry.However,the lack of detection sensitivity in Terahertz Spectroscopy has prevented it from being used in a widespread spectroscopic analysis technology.In this paper,Frequency Selective Surface(FSS)using the Terahertz Spectroscopy Time Domain Spectrum(THz-TDS)which operates at terahertz frequency range has been demonstrated for application of sugar detection.The FSS is designed with a circle slot structure and has been optimized in line with the molecular resonance of glucose and fructose at different level concentration at 1.98 THz and 1.80 THz,respectively.Transmission magnitude of glucose and sucrose is inversely proportional with the level of sugar concentrations.The realization of the FSS structure is using electron beam lithography and wet etching technique.Results show that the FSS performance for glucose and sucrose reveal fair shifts in measured transmission magnitude from its original in CST by approximately 30%.The use of fabricated FSS with circle structure indicates that the concentration can be improved averagely at 25%for glucose and 13%for sucrose.Thus,it shows that the FSS circle structure combined with THz-TDS has the potential to become an alternative method for food sensing technology in the future.