Data Acquisition System for Preventive Maintenance of Equipment in the Urban Tunnels

Abstract

Urban Tunnel construction for supporting the Under-ground Transit Solutions (UTS) namely Metros and Subways in highly densely populated locations involves huge power requirements. This power requirement is normally met by the power supplied by the power agencies for the over the ground requirements. However, in the cases of underground work at the drilling site or de-watering sites we need to use the smaller portable generator sets. These generator sets generate a lot of harmful gases and CO2 and in-cases of over loading lead to short circuits and also fire. In the cases of prolonged tunneling times these generators remain inside the tunnel and are not serviced on time leading to gen-sets often going out of order leading to loss of work and may also cause accidents. Regular maintenance enhances the lifespan of the generators. This paper takes the approach to provide a solution to the preventive generator maintenance problems which would take care of reliability issues. In the proposed design we monitor the vital parameters of the gen-sets like fuel levels, temperatures, loads (current and voltage), running time, last servicing time, average fuel consumption, last serviced dates, battery voltages, Air filter life etc. This information is then collected by an on-board Data Acquisition System (DAS) which is then passed on to Cloud via a Wi-Fi connection. Once this information is made available on the cloud, we can apply the Machine Learning Algorithms to predict the failure rates of the generators and calculate the RUL - Remaining Useful Life.