Design, tuning and in-field validation of energy harvesters for railway bridges

Highlights

• A 3D printed energy harvester design and tuning methodology is proposed.

• Tuning process is based on statistical analysis of mechanical energy.

• Harvester performance is assessed for a railway bridge in-service.

• The proposed tuning process increases energy harvested up to 300%.

• Energy harvested in three hours and 18 train passages was 7.65 mJ.

Abstract

Energy harvesters are a promising technology for powering infrastructure condition monitoring systems without batteries. When deployed on railway bridges they are typically tuned to the bridge’s natural frequency, however due to the dominance of train-induced forced vibration of the structure, this results in sub-optimal energy harvesting. As a solution, this paper presents a novel tuning strategy for energy harvesters on railway bridges. The strategy is based on a statistical analysis of the mechanical energy generated in the bridge during train passage and involves four steps: $\left(i\right)$ measurement of bridge response due to train traffic, $\left(ii\right)$ calculation of mechanical energy during train passage, $\left(iii\right)$ statistical characterisation of the energy distribution, and finally, $\left(iv\right)$ calculation of the tuning frequency. A case study is presented to compare the potential of the proposed strategy against tuning based upon the bridge natural frequency. First, an in-service railway bridge is monitored to determine its natural frequency and response to train traffic. Combining the field data with the proposed tuning strategy, the design of energy harvesters for the bridge is optimised. The design of harvesters tuned to natural frequencies is also studied. The underlying harvester type is a cantilever bimorph beam with a mass at the tip and load resistance. Additive manufacturing is used for the substructure, which is formed from PAHT-CF15 (High Temperature Polyamide carbon fibre reinforcement). The harvesters are manufactured and deployed on the bridge subject to live railway traffic. Field results show the devices designed using the new tuning strategy harvest up to 300% more energy. The energy harvested in a time window of three hours (18 train passages) is $7.65\text{mJ}$.