Quantifying uncertainty in railway noise measurement

Even though the railway is very safe and environmentally friendly mode of transport, it also gives rise to immense noise problems. Over the past several decades, the overall railway noise level has been compounded by increasing in railway transport traffic in the world. At this stage, conducting effective noise measurement and making a reliable control come to exist as critical operations. When a noise measurement is performed, a reliable uncertainty evaluation on the measurement accuracy should be considered by the evaluators. This study focuses on the measurement uncertainties dealing with noise measurements recorded in the railway transport. Together with the effects of the systematic uncertainty sources such as equipment, calibration, environment and operator uncertainties as well as the amount of the random uncertainties, the uncertainties resourced from the angular dependency (measurement position) were quantified based on measurement uncertainty analysis framework. The calculations revealed that the main effective uncertainty components are repeatability uncertainty arising from the data variability and the position uncertainty arising from the angular dependency. Based on the position of the equipment (critical angle) and corresponding uncertainty, a trade trade-off analysis between the amount of the combined uncertainty and the distance has also been made for determining the optimum instrument position. The results showed that providing practical and correct measurement records together with created uncertainties have a remarkable amount of importance in noise measurement. (C) 2019 Elsevier Ltd. All rights reserved.