🤖 AI Summary
This study addresses the limitations of manual hydrogen leak detection, which suffers from unstandardized probe trajectories, operator dependency, and sensor signal latency, resulting in low detection rates and significant safety risks. The authors develop a robot-guided gas sensing testbed integrating standardized leak sources (5% H₂/N₂), 3D geometric modeling, and dynamic concentration field measurements to systematically investigate the impact of scanning speed and probe orientation on detection performance in near-field environments. They reveal, for the first time, the critical role of trajectory dynamics in detecting small-scale pipeline leaks and propose a geometry-adapted scanning strategy alongside a dynamic signal attenuation correction model. Experiments demonstrate that geometry-specific trajectories encircling seal points substantially enhance detection reliability compared to conventional linear paths. A prototype software tool capable of automatically generating and validating 3D inspection trajectories is also developed, establishing a new paradigm for safe and effective hydrogen leak detection.
📝 Abstract
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.