How Mobile Gas Sensor Trajectories Govern Hydrogen Leak Detection: A Safety Gap in Manual Leak Inspection of Hydrogen System Components
For hydrogen infrastructure safety, this work reveals that current manual leak inspection procedures pose a tangible safety risk due to lack of spatial guidance, and provides actionable routing rules to improve detection reliability.
This study quantifies how sniffer trajectory kinematics affect hydrogen leak detection reliability at small-scale pipes and fittings, showing that conventional linear trajectories frequently miss leaks while geometry-specific routing maintains high safety margins. A reduction-factor model for dynamic signal loss and a proof-of-concept software pipeline for generating validated trajectories are presented.
The integrity of hydrogen infrastructure relies on reliable leak detection, performed almost exclusively via manual tracer gas sniffing in electrolyzer manufacturing. Although mandated by standards, the lack of spatial probe guidance instructions leaves detection reliability entirely to operator execution, further compromised by sensor signal delays. This study quantifies how sniffer trajectory kinematics affect detection reliability at small-scale pipes and fittings, a near-field regime largely neglected by macroscopic dispersion research. Using a robotically guided test bench to eliminate operator variability, static concentration fields and dynamic trajectory passes were acquired across representative geometries under standardized leak rates (5 vol% hydrogen in nitrogen) and varying scanning velocities. Results demonstrate that scanning velocity and spatial probe orientation strongly dictate detectability. Conventional linear trajectories frequently miss leaks under dynamic conditions, causing severe false negatives. Conversely, geometry-specific routing, such as circumferential plunging paths around sealing points, maintains a high safety margin. From these observations, geometry-specific routing rules and a reduction-factor model for dynamic signal loss are derived. The findings reveal that current standard operating procedures pose a tangible safety risk. To operationalize these rules, a proof-of-concept software pipeline is presented, generating validated trajectories directly from 3D models for visualization in assistance systems.