Condition Monitoring System for Light Rail Vehicle and Track

Abstract

Condition monitoring and fault detection systems are becoming increasingly important in rail vehicles maintenance and operation, ensuring safety and reliability improvement. Light rail systems are not the main target for this trend, because of low operational speed and lower safety factors. Nevertheless public transport operators begin to pay a closer attention to the technical state monitoring of vehicle and track, in order to reduce maintenance cost and increase safety and ride comfort for passengers, which is an important challenge for public transport competitiveness in XXI century. The paper describes the main concept of the innovative on-board condition monitoring system for light rail vehicle and track. Functional requirements, assumptions and procedures are described, as well as the on-board data acquisition unit with necessary transducers, which number, function and technical parameters were optimized during the research phase of the project. The prototype of the presented system is now being tested in normal operating conditions.

Monitoring of the technical condition of tracks based on machine learning

“…Suggested methods of dealing with this issue can be found in literature. 16–18 Moreover, measured values can be strongly influenced by the type of track settlement and not just its technical condition. The type of subgrade is of particular importance, as its susceptibility varies much more than in railway lines.…”

A review of key planning and scheduling in the rail industry in Europe and UK

“…This approach, based on the use of radio frequency identification sensors, utilises complex event processing and semantics to evaluate the efficiency of MRO activities. Condition monitoring of rail vehicles is also the subject of the work of Firlik et al 32 who examine light rail systems from this perspective. This paper examines the dynamic adjustment of maintenance needs and track speed limits based on sensor readings from axle boxes.…”

“…Nystrom and Soderholm 63 Dadashi et al 59 Nystrom and Soderholm 63 Jiang et al 79 Selvik and Aven 77 Nash et al 36 Jabri et al 50 Lv et al 57 Data mining Goverde and Meng 15 Kecman and Goverde 17 Kecman and Goverde 17 Kecman and Goverde 17 Autonomous systems Firlik et al 32 Li et al 65 Kuckelberg and Wendler 37 Xun et al 52 Dominguez et al 12 Wackrow and Slamen 13 Expert and decision support systems Dadashi et al 59 Bouillaut et al 61 Filip et al 70 Lai and Wang 73 Saa et al 29 Bouillaut et al 61 Guler 62 Schö bel and Maly 75 Soh et al 78 Zhang 31 Firlik et al 32 Schlake et al 84 Wegele et al 35 Kuckelberg and Wendler 37 Forsgren et al 39 Ho et al 38 Albrecht et al 40 Hu et al 5 Peng et al 80 Palte 30 Beugin et al 34 Kecman and Goverde 17 Filip et al 71 Lai and Wang 73 disruption such as faulty trains and damage within the infrastructure (Briola et al 23 ).…”

Design of a Wireless and Energy Autonomous Sensor Network for Condition Monitoring of Tram Drive Components

“…The obtained measurement data were recorded at a sufficient sampling rate of 4.56 kHz and were successfully transferred from the tram gearbox to the network base station within a radius of 10 m inside the tram despite factors such as reflections, fading and electromagnetic compatibility. A piezoelectric vibration harvester is the power supply for the sensor nodes and it delivers up to 21.22 mW for relevant vibration frequency range between 10 Hz and 30 Hz, thus enabling deployment of autonomous sensor nodes.Designs 2018, 2, 50 2 of 13 tram monitoring are presented in [3][4][5][6]. The power supply and data transmission within the sensor network must be wireless.…”

“…Designs 2018, 2, 50 2 of 13 tram monitoring are presented in [3][4][5][6]. The power supply and data transmission within the sensor network must be wireless.…”