Sensor Fusion for Incipient Hydrogen Detection Using Deep Learning

As a result of the ongoing fluctuations in the global climate, there has been a persistent increase in the necessity of renewable energy sources.Hydrogen has the potential to play a crucial role as an energy carrier during the transition away from fossil fuels.To ensure safe operations, it becomes imperative to possess a dependable and sensitive system for detecting hydrogen leaks.Nonetheless, relying solely on a singular sensor may prove inadequate for detecting minor alterations or abrupt peaks.Sensor fusion systems, which combine data from several sensors, can improve hydrogen gas detection capabilities.This study proposes a real-time AI-based sensor fusion scheme for multi-sensor hydrogen leak detection that incorporates electromagnetic, ultrasonic, and optical sensors.This ensures a combination of reliability and speed that can't be reached using each of these sensors solely.