Robotic Railway Multi-Sensing and Profiling Unit Based on Artificial Intelligence and Data Fusion.

Marius Minea,Cătălin Marian Dumitrescu,Mihai Dima

doi:10.3390/s21206876

Marius Minea, Cătălin Marian Dumitrescu + Show 1 more

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https://doi.org/10.3390/s21206876

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Abstract

This article presents the research and results of field tests and simulations regarding an autonomous/robotic railway vehicle, designed to collect multiple information on safety and functional parameters of a surface railway and/or subway section, based on data fusion and machine learning. The maintenance of complex railways, or subway networks with long operating times is a difficult process and intensive resources consuming. The proposed solution delivers human operators in the fault management service and operations from the time-consuming task of railway inspection and measurements, by integrating several sensors and collecting most relevant information on railway, associated automation equipment and infrastructure on a single intelligent platform. The robotic cart integrates autonomy, remote sensing, artificial intelligence, and ability to detect even infrastructural anomalies. Moreover, via a future process of complex statistical filtering of data, it is foreseen that the solution might be configured to offer second-order information about infrastructure changes, such as land sliding, water flooding, or similar modifications. Results of simulations and field tests show the ability of the platform to integrate several fault management operations in a single process, useful in increasing railway capacity and resilience.

Highlights

The present evolution of intelligent transport systems and policies in this field points towards the reduction of environmental emissions, use of green and/or renewable energies, and increasing the efficiency of processes
To construct the principal component analysis (PCA) T2 Q model, the input matrix was divided into a training set, and a test set in an odd-even manner, for enabling the possibility to carry out ultrasonic investigations of metal parts with different geometries and sizes
To make reliable the detection of geometrical defects in the mechanical structure of rails, in this article we proposed a method based on the feature manipulation algorithm with

Summary

Introduction

The present evolution of intelligent transport systems and policies in this field points towards the reduction of environmental emissions, use of green and/or renewable energies, and increasing the efficiency of processes. The document recommends several directions in which the railway transport system should go: (i) interoperability—meaning all high-speed railway automation systems and infrastructures should be compatible, (ii) social harmonization—harmonization of the minimal qualification requirements for workers engaged in interoperable activities, (iii) reducing environmental emissions, especially noise in this case. In this context, it can be noticed that the pressure on the interoperable workers will be greater and the associated necessary knowledge on equipment, infrastructure and operations need to be of a higher level.

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