Measurements of Human Perception of Train Vibration

Environmental protection encompasses various aspects, ranging from well-known concerns like air and water pollution to landscape preservation. One often-overlooked facet of pollution is the mitigation of vibrations, a matter addressed not only by Polish legislation but also by EU directives. Human perception of vibrations constitutes a crucial subjective parameter in evaluating the level of vibration pollution, and is influenced by factors such as age, gender, and individual height. Buildings are predominantly exposed to vibration excitation from external sources, including industrial machinery (e.g., vibration road rollers, pile driving) and transport-related sources such as roads, railways, subways, or trams. Vibrations transmitted from the ground to a building can impact its structural integrity, but more commonly, they result in discomfort for occupants. Particularly, unexpected vibrations from transport-related sources can be bothersome. This study aimed to check whether there is a correlation between the type of train and the speed of travel near a representative residential building of brick construction. This study used actual in situ measurements of the horizontal components and the vertical component of vibrations in the building. Analyses of the measured vibration components were carried out to assess the impact of vibrations on people staying in the building and passively receiving these vibrations. Procedures described in the Polish standard concerning measurements and method of analysis were used. The analyses used the value of the vibration impact index on people (WODL). This study used linear and nonlinear regression analyses to obtain information on whether there is a relationship between the type of train, its speed, and the value of the WODL index. The results of the analyses indicate a relationship between the speed of the train and the value of the WODL index, but it should be emphasized that some events deviate from the developed regression model. Adopting a multiple regression model that takes into account the speed of the train and its type gives better results. Our findings should provide valuable information for designers and managers involved in the planning and operation of train transport systems.