Condition-Based Monitoring and Maintenance System for Tunnel Booster Fans
Tunnels are an important part of transportation. Keeping the ventilation and air quality in a tunnel standardized greatly serves a purpose for safe work as well as failure to cause any accumulation or harmful gases. A conventional maintenance philosophy is highly based on scheduled inspection and reactive repairs, which in turn resulted in inefficiencies, operational expenditure, and some regrettable failures. Thus, in respect to these contingencies, the present paper purports Condition-Based Monitoring and Maintenance System for Tunnel Booster Fans through acquiring real-time data and IoT automation. The specific system used ESP32 as the brain interfacing major sensors like DHT11 temperature and humidity sensor, MQ smoke sensor, and voltage sensor. The sensors can keep track of an environment’s condition and the fan’s electrical health continuously. The system employs a 5V relay in order to control fan, automatic buzzer for alarm notification and Wi-Fi in order to connect for remote monitoring. The mobile application provides operators with an interface to the real-time data monitoring and control the fan. Improvement on reliability and efficiency is made in tunnel ventilation systems, while the downtime and maintenance cost are reduced. Conditions that have undergone several tests validated the system. These experimental results indeed prove that abnormalities have been detected quickly, bringing improvement in safety and operational performance. Condition-based monitoring offers a much more proactive and feasible, and comparatively low-cost approach to this problem than traditional strategies for maintenance. This paper deals with hardware and software implementations, system architecture, and experimental results that make it for intelligent monitoring of a tunnel booster fan feasible. The solution may accommodate different ventilations in the industry, thus providing scalable and flexible solutions for improved safety and efficiency of tunnels.
Authors
- S. Nithish
- S Mohanraj
- Pachagounder Sakthivel (ORCID: https://orcid.org/0000-0002-9436-8070)
- C. Pradeep
- K G Ramprasath
Institutions
- M. Kumarasamy College of Engineering
Publication Details
- Published
- 2025-05-07
- DOI
- https://doi.org/10.1109/rmkmate64874.2025.11042669
- Citations
- 1
- Primary Topic
- Advanced Sensor and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 1.21