UAV Optical Gas Sensor With Pressure Control for Methane Mapping
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Solution Overview
Problem
Current gas detection technologies are inadequate for accurately and efficiently monitoring methane and other greenhouse gas concentrations, particularly in inaccessible or risky environments, due to limitations in sensitivity, adaptability to temperature and pressure changes, and operational power constraints.
Innovation Solution
A system comprising a gas sensor mounted on an unmanned aerial vehicle (UAV) with optical cells, a processor, and a gas handling system that modifies temperature and pressure, enabling detection of methane and other gases while adjusting sampling rates based on flight speed and turbulence, and generating maps of atmospheric greenhouse gas concentrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If gas detection is performed in inaccessible or risky environments, then detection coverage and safety are improved, but system complexity and operational difficulty increase
Solution Approach 1:
The patent employs an aerial vehicle as an intermediary carrier to transport the gas detection system to inaccessible or risky environments. This mediator enables the detection system to operate in hazardous areas without exposing personnel to danger, while the aerial vehicle handles navigation and positioning functions, allowing the detection system to focus on gas analysis.
Solution Approach 2:
The detection system integrates multiple functions into a single platform: gas sampling, gas analysis, spatial positioning, and data mapping. By combining these functions on the aerial vehicle, the system achieves multi-functionality that improves operational efficiency and reduces the need for separate specialized equipment for each function.
2Loss of time
If real-time gas detection is implemented, then response time and monitoring capability are improved, but data processing load and system resource consumption increase
Solution Approach 1:
The system performs gas detection at periodic intervals during aerial vehicle flight, rather than requiring continuous analysis. This periodic sampling approach enables real-time monitoring capability while reducing the computational load and power consumption associated with continuous data processing, as the system only needs to analyze gas samples at discrete time points.
3Measurement precision
If spatial distribution mapping is generated, then analysis precision and environmental understanding are improved, but computational requirements and data processing time increase
Solution Approach 1:
The system automatically performs spatial distribution mapping by integrating gas concentration measurements with aerial vehicle position data from GPS and other positioning systems. This self-service capability eliminates the need for manual data processing and mapping operations, achieving high measurement precision while reducing processing time through automated algorithms that continuously update the spatial distribution maps in real-time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides lightweight, high-sensitivity, and resilient gas concentration measurements across varying environmental conditions, enabling effective monitoring of methane and other greenhouse gases in previously inaccessible areas with improved spatial distribution and power efficiency.
Implementation Method 1
one or more optical cells of the gas sensor... detect gas from the one or more optical cells
Data Source
AI summary
Systems, devices, and methods for a gas sensor comprising one or more optical cells; a processor having addressable memory, the processor configured to: detect gas from the one or more optical cells of the gas sensor, where the detected gas is one or more of: methane, carbon dioxide, hydrogen sulfide, water, ammonia, sulfur oxides, and nitrogen; record data corresponding to the detected gas, where the recorded data comprises at least one of: an ambient temperature from a temperature sensor, an ambient pressure from a pressure sensor, an aerial vehicle telemetry, and an aerial vehicle location from a global positioning system (GPS); and generate a map of atmospheric greenhouse gas concentration on a map based on the detected gas and the recorded data.