IoT Sensor Monitoring for Hydrogen Refueling Station Safety
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Solution Overview
Problem
The construction of hydrogen refueling stations is hindered by high budget requirements and safety concerns due to the risk of hydrogen gas leakage leading to potential fires or explosions, necessitating effective monitoring systems to ensure safety.
Innovation Solution
A monitoring system utilizing IoT sensors mounted on hydrogen refueling station components to generate sensing data, which is analyzed by a server to calculate risk levels and safety reliability, incorporating weights based on accident frequency and failure impact, enabling remote assessment and alarm generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous monitoring is implemented to ensure safety, then safety reliability is improved, but energy consumption increases
Solution Approach 1:
The IoT sensor operates in periodic cycles, alternating between measurement mode and sleep mode. During measurement mode, the sensor collects data for a preset time; during sleep mode, it consumes minimal energy. This periodic operation maintains safety monitoring capability while significantly reducing overall energy consumption compared to continuous operation.
Solution Approach 2:
The system uses the sensor's own operational cycles to manage its energy consumption. By automatically transitioning between measurement and sleep modes based on its operational needs, the sensor serves its own energy management requirements without external intervention, balancing safety monitoring with energy efficiency.
2Measurement precision
If comprehensive monitoring of all components is implemented, then safety assessment accuracy is improved, but system complexity increases
Solution Approach 1:
The monitoring system is segmented into multiple independent IoT sensors, each mounted on specific components of the hydrogen refueling station. Each sensor independently monitors its designated component, and the analysis server aggregates data from all sensors. This segmentation allows comprehensive monitoring of all components without creating a single complex monolithic system.
Solution Approach 2:
The analysis server performs multiple functions: it receives data from all IoT sensors, calculates risk degrees for each component, determines safety reliability of the entire station, and generates alarms. This multi-functional approach consolidates complexity into a single server rather than requiring separate systems for each monitoring task.
3Measurement precision
If risk assessment with multiple weights is implemented, then safety evaluation accuracy is improved, but computational complexity increases
Solution Approach 1:
The first and second weights (accident frequency weight and failure impact weight) are pre-calculated and stored in the analysis server before actual risk assessment operations. During runtime, the server simply retrieves these pre-computed weights and applies them to the risk scores, avoiding complex computational operations during critical safety assessment moments.
Data Source
AI summary
There are disclosed a monitoring system and method for a hydrogen refueling station and a computing device for executing the same. The monitoring system for a hydrogen refueling station according to one embodiment of the present disclosure includes an Internet of things (IoT) sensor mounted on each of components of the hydrogen refueling station and configured to generate sensing data by measuring preset monitoring elements and an analysis server configured to obtain the sensing data and monitor a state of the hydrogen refueling station based on the obtained sensing data.