In the rail traffic industry, the utilisation of inexpensive real-time sensors and the industrial internet of things for proactive asset management is a relatively new concept with great potential. As railways are one of the longest-lasting infrastructure assets, even marginal efficiency and cost gains have a significant impact on the life-cycle cost. This paper shows how wireless three-dimensional acceleration sensor technology can be applied to monitor track condition. The data collection was carried out in October 2016 on a railway line operated by Finnish Railways. In the test, a sensor was attached to a train unit and the acceleration of the train on a track segment was repeatedly measured at variable speeds. The collected data set was enhanced using map-matching and Bayesian filtering in order to improve the Global Positioning System location accuracy of the data. The filtered acceleration signals were analysed, and detected anomalies were compared against known parameters such as bridges and switches. The results of the testing support the feasibility of the concept. Finally, the implications of the concept regarding proactive asset management of track networks and statistical process control-based monitoring of tracks’ condition are discussed.
This paper presents a software-based modular and hierarchical building energy management system (BEMS) to control the power consumption in sensor-equipped buildings. In addition, the need of this type of solution is also highlighted by presenting the worldwide trends of thermal energy end use in buildings and peak power problems. Buildings are critical component of smart grid environments and bottom-up BEMS solutions are need of the hour to optimize the consumption and to provide consumption side flexibility. This system is able to aggregate the controls of the all-controllable resources in building to realize its flexible power capacity. This system provides a solution for consumer to aggregate the controls of ‘behind-the-meter’ small loads in short response and provide ‘deep’ demand-side flexibility. This system is capable of discovery, status check, control and management of networked loads. The main novelty of this solution is that it can handle the heterogeneity of the installed hardware system along with time bound changes in the load device network and its scalability; resulting in low maintenance requirements after deployment. The control execution latency (including data logging) of this BEMS system for an external control signal is less than one second per connected load. In addition, the system is capable of overriding the external control signal in order to maintain consumer coziness within the comfort temperature thresholds. This system provides a way forward in future for the estimation of the energy stored in the buildings in the form of heat/temperature and use buildings as temporary batteries when electricity supply is constrained or abundant.
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