Research Of Low Power Line Carrier Communication Detection Based On Virtual Instrument

With the development of information and networks technology, the utilization of low power line network communications has been paid more and more attention. However, detection for low Power Line Carrier (PLC) communications has been mentioned a little according to power system standard, in which the draft did not form a comprehensive and systematic criterion. At the same time, there is no integrated detection system for detection of low PLC communications, for the installation difficulties and poor equipment compatible in engineering. This article analyzed the detection of low PLC communication, based on theoretical research of the channel characteristics.With the virtual instrument technology as the development platform, NI PCI 6251 DAQ card as acquisition device, this article designed a low PLC communication detection system. Since the channel is time variable, the characteristics of the uncertain channel constitute fuzzy evaluation factors. On this basis, this paper proposed a T-S fuzzy neural network evaluation model to assess the quality of carrier communication. The model input is the channel performance index, which is from channel detection. Learning of the model is according to operational success rate as model expectation, which is used for training the membership parameters and weighting factors. Since the traditional fuzzy C means clustering algorithm exist some issues, this paper proposed LBG algorithm to train the membership parameters in learning algorithm.Simulation and test results show that, this detection system based on Virtual Instrument technology is capable of measuring low PLC communications. The model evaluation results can reflect the real state of the PLC channel.