Embedding human annoyance rate models in wireless smart sensors for assessing the influence of subway train-induced ambient vibration

Abstract

The operation of subway trains induces ambient vibrations, which may cause annoyance and other adverse effects on humans, eventually leading to physical, physiological, and psychological problems. In this paper, the human annoyance rate (HAR) models, used to assess the human comfort under the subway train-induced ambient vibrations, were deduced and the calibration curves for 5 typical use circumstances were addressed. An autonomous measurement system, based on the Imote2, wireless smart sensor (WSS) platform, plus the SHM-H, high-sensitivity accelerometer board, was developed for the HAR assessment. The calibration curves were digitized and embedded in the computational core of the WSS unit. Experimental validation was conducted, using the developed system on a large underground reinforced concrete frame structure adjoining the subway station. The ambient acceleration of both basement floors was measured; the embedded computation was implemented and the HAR assessment results were wirelessly transmitted to the central server, all by the WSS unit. The HAR distributions of the testing areas were identified, and the extent to which both basements will be influenced by the close-up subway-train's operation, in term of the 5 typical use circumstances, were quantitatively assessed. The potential of the WSS-based autonomous system for the fast environment impact assessment of the subway train-induced ambient vibration was well demonstrated.