Fugitive Gas Leak Detection Using Probability Matrices Near Equipment
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Solution Overview
Problem
Existing fugitive gas leak detection systems rely on costly and inaccurate real-time wind data from anemometers, leading to inefficiencies and errors in detecting and quantifying gas emissions, particularly in industrial settings with dense equipment.
Innovation Solution
A probability-based approach using a small number of hazardous area-certified gas sensors positioned close to potential fugitive gas sources, employing time-series data and probability matrices to identify and quantify leaks without anemometers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If anemometers are used to provide real-time wind data for fugitive gas leak detection, then wind information is available for analysis, but the system becomes costly and inaccurate due to equipment limitations in dense industrial settings
Solution Approach 1:
The patent extracts and eliminates the anemometer component from the detection system. Instead of using wind data from external anemometers, the system uses only gas sensor concentration data combined with pre-stored sensor coordinates and probability matrices to identify leak sources, thereby removing the source of measurement errors and cost issues associated with anemometers in dense equipment environments
Solution Approach 2:
The patent creates a virtual representation of wind direction influence through probability matrices that are pre-calculated based on sensor coordinates and potential source locations. This virtual model replaces the physical anemometer, allowing the system to account for wind direction effects without requiring actual wind measurement equipment
2Loss of information
If anemometers are deployed for wind data collection, then wind direction and speed information is obtained, but costs increase significantly
Solution Approach 1:
The patent replaces expensive, maintenance-intensive anemometers with inexpensive gas sensors that have no moving parts and require minimal maintenance. The system uses multiple low-cost sensor units distributed around the facility, each providing concentration data that collectively enables leak source identification without requiring costly wind measurement equipment
Solution Approach 2:
The patent introduces probability matrices as an intermediary computational model that translates gas concentration measurements into leak source identification. These matrices pre-encode the geometric relationships between sensors and potential sources, allowing the system to infer wind direction effects indirectly through mathematical relationships rather than direct physical measurement
3Object-affected harmful factors
If gas sensors are positioned far from potential fugitive gas sources, then safety is improved, but detection accuracy decreases
Solution Approach 1:
The patent divides the monitoring area into multiple zones with several gas sensors positioned at different locations around potential fugitive gas sources. This segmentation allows the system to maintain safe distances from individual sources while collectively achieving high detection accuracy through the coordinated data from multiple sensors and the probability matrix analysis
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
Accurately and timely detects and quantifies fugitive gas emissions, reducing costs and improving detection accuracy by eliminating the need for real-time wind data.
Implementation Method 1
each of the plurality of gas sensors is configured to detect gas concentrations over a time period
Data Source
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AI summary
An illustrative system for probability based fugitive gas leak detection comprises an equipment group including: a potential fugitive gas source; and a plurality of gas sensors positioned at respective locations in proximity to the potential fugitive gas source, wherein each of the plurality of gas sensors is configured to detect gas concentrations over a time period, and a supervisor communicatively coupled to the equipment group, the supervisor being configured to: receive the detected gas concentrations; determine a probability matrix based at least on the coordinates of the gas sensors and coordinates of the potential fugitive gas source; and identify the potential fugitive gas source as an actual fugitive gas source based on the probability matrix and the detected gas concentrations.