The prospect of growth of a railway system impacts both the network size and its occupation. Due to the overloaded infrastructure, it is necessary to increase reliability by adopting fast maintenance services to reach economic and security conditions. In this context, one major problem is the excessive friction caused by the wheels. This contingency may cause ruptures with severe consequences. While eddy’s current approaches are adequate to detect superficial damages in metal structures, there are still open challenges concerning automatic identification of rail defects. Herein, we propose an embedded system for online detection and location of rails defects based on eddy current. Moreover, we propose a new method to interpret eddy current signals by analyzing their wavelet transforms through a convolutional neural network. With this approach, the embedded system locates and classifies different types of anomalies, enabling an optimization of the railway maintenance plan. Field tests were performed, in which the rail anomalies were grouped in three classes: squids, weld and joints. The results showed a classification efficiency of ~98%, surpassing the most commonly used methods found in the literature.

We present the status of the Angra Neutrino Experiment, aimed at developing an antineutrino detector for monitoring nuclear reactor activity. The detector comprises a 1.42 m3 Gadolinium-Water Cerenkov target, surrounded by 50 cm of water shielding, placed inside a commercial container about 30 m from the reactor core, at the Angra II nuclear power plant, Brazil. The 4 GW thermal power of the Angra II reactor will provide a few thousand antineutrino interactions per day. The main challenge of the experiment is to overcome the very high cosmic ray induced background at sea level. The present text describes the construction status and simulations results

Railway track circuit failures can cause significant train delays and economic losses. A crucial point of the railway operation system is the corrective maintenance process. During this operation, the railway lines have the circulation of trains interrupted in the respective sector, where traffic restoration occurs only after completing the maintenance process. Depending on the cause and length of the track circuit, identifying and solving the problem may take a long time. A tool that assists in track circuit fault detection during an inspection adds agility and efficiency in its restoration and cost reduction. This paper presents a new method, based on frequency domain reflectometry, to diagnose and locate false occupancy failures of track circuits. Initially, simulations are performed considering simplified track circuit approximations to demonstrate the operation of the proposed method, where the fault position is estimated by identifying the null points and through non-linear regression on signal amplitude response. A field test is then carried out in a track circuit approximately 1500 m long to validate the proposed method. The results show that the proposed method can identify and estimate the fault location due to a short circuit between rails with high accuracy.

This work addresses the subject of preventive maintenance of railroads which has a considerable impact on the cost and safety of railway companies by proposing a new technique to detect concentrated regions of low impedance between rails along railway lines from a railroad inspection vehicle. Its methodology is based on the standing waves theory applied to transmission lines. Simulation and field measurements have been carried out in order to understand and validate such technique, and a compact measurement system has been designed and implemented producing field-testing results that clearly indicate its feasibility and effectiveness.

This document presents a performance assessment of digital filters applied to the signal arriving to the acquisition system of the Neutrinos-Angra Detector which is equipped with the PMT model R5912 by Hamamatsu. It is shown that the signal-to-noise ratio of the front-end output signal generated by single photoelectrons can be well enhanced, improving the detection efficiency for events of this kind. Some of the proposed filters will be designed to work as estimator of the peak amplitude value of the signal of interest. The considered filters will be described and the achieved results presented.