Early fault detection in cable television networks (the case of the reverse pilot)

In this work, we present a model based method for reliably detecting reverse pilot faults within cable amplifier networks. This method has the advantage over traditional fixed bound fault detection techniques in that it is able to compensate for changes in the environmental conditions and, hence, reduce the occurrence of false alarms. Cable television distribution networks are used to distribute cable signals from a centrally located injection site (head-end), to subscribers' homes. Typically cable amplifier plants are two way asymmetrical communication networks. The downstream path, from the head-end to the subscribers' homes, is used mainly for delivering cable television services. Traditionally, the upstream path has been used to transmit the status data from the trunk amplifiers to the head-end. More recently it is used to provide a data path from the subscribers to the head-end for use in interactive services. Hence the ability to detect the occurrence of faults in the reverse path is quite important. We have implemented a general approach based on using a back propagation neural network to model the dynamics of the reverse pilot of cable television amplifiers. This technique was able to provide good temporal localization of the start of fault conditions and a clear indication of the presence of the fault through its occurrence.