Novel Adaptive Peak Detection Method for Track Circuits Based on Encoded Transmissions

Track detection systems based on ultrasonic guided waves (UGWs) for continuous welded rails have achieved a rapid development in recent years. Though these systems can work properly in normal track conditions, UGW signals cannot penetrate the gap caused by a track breakage. To overcome this issue, a novel track circuit system based on a previous UGW system has been proposed in this paper. The 63-bit Kasami codes have been applied to the transmission scheme. The auto- and cross-correlation properties from Kasami codes have allowed the transmission detection at the receiver end, even under adverse conditions, such as noise or high attenuation. Furthermore, in previous track circuits, the correct detection and identification of the corresponding transmissions at the receivers had become a key aspect for the suitable and reliable operation of such type of systems. In this way, in addition to describing a novel track circuit, this paper focuses on the proposal of a novel adaptive peak detection algorithm to discriminate the main lobes in the auto-correlation functions at the receiver, thus making possible to correctly determine the track status in future works. This algorithm is mainly based on the discrete wavelet transform, on a moving average filter, as well as on the Hilbert Transform. Through the usage of a simulation model for the proposed track circuit as well as some outdoor experimental tests, the accuracy and the stability of the adaptive peak detection algorithm for the novel track circuit have been verified.