Portable Gas Leak Detector Using Cross-Correlation Velocity Vectors
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Solution Overview
Problem
Conventional gas leak detection systems are costly, unsuitable for home and vehicle settings, and require pre-installation, making them inefficient for detecting gas leaks in mobile and indoor environments.
Innovation Solution
A portable, wearable gas leak source detector module equipped with gas sensors and a processing unit for mobile devices, capable of identifying gas leaks, flow velocity, and source, utilizing MOX technology sensors and cross-correlation methods to detect gas flows and calculate velocity vectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional automated gas leak detection systems with spatially distributed sensors are used, then detection coverage and reliability are improved, but device complexity and cost increase significantly
Solution Approach 1:
The system divides the detection function into multiple independent sensor units distributed in space, each detecting local gas concentration. This segmentation allows the system to achieve comprehensive coverage without requiring a single complex centralized system, resolving the contradiction between reliability and complexity.
Solution Approach 2:
The patent introduces temporal dimension to the detection system by monitoring gas concentration changes over time at multiple spatial locations. This adds a time dimension to the detection approach, enabling the system to identify leak sources through pattern analysis across space and time, thereby improving reliability without proportionally increasing complexity.
2Device complexity
If portable sensor devices are used for manual leak detection, then device complexity is reduced, but detection speed and automation are worsened
Solution Approach 1:
The system performs preliminary actions by continuously monitoring gas concentration at multiple locations and pre-calculating correlation matrices between sensor readings. When a leak is detected, the pre-computed correlations enable rapid source identification without requiring complex real-time analysis, thus reducing detection time while maintaining portability.
Solution Approach 2:
The detection system uses its own sensor data to automatically identify leak sources through cross-correlation analysis, eliminating the need for external manual intervention. The system serves itself by processing its own measurements to locate leaks, thereby reducing detection time while keeping the device portable and relatively simple.
3Measurement precision
If distributed sensor systems are installed in environments like homes and vehicles, then detection accuracy is improved, but ease of operation and installation are worsened
Solution Approach 1:
The system is designed with universal applicability to various environments including homes, vehicles, and industrial settings. The same core technology of distributed sensors and cross-correlation analysis can be deployed in different locations without requiring environment-specific customization, thereby improving accuracy while maintaining ease of installation and operation.
Solution Approach 2:
The patent uses virtual copies of sensor data through cross-correlation analysis to identify leak sources. Instead of requiring physical tracing or complex installation infrastructure, the system creates computational representations of sensor readings to locate leaks, simplifying installation while maintaining high accuracy for leak source identification.
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
Provides an accurate, low-power, and low-latency gas leak detection system suitable for mobile and indoor environments, enabling effective identification of gas leaks and their sources with minimal setup requirements.
Implementation Method 1
MOX sensors are used to detect gas flows
Implementation Method 2
MOX technology sensors
Implementation Method 3
calculating cross-correlations between pairs of sensor signals received from the plurality of sensors
Data Source
AI summary
A method includes: receiving, from a plurality of sensors, detection signals indicative of fluid flow, the fluid flow having a direction and a speed, the plurality of sensors having respective mutual positions and distances between pairs of sensors in the plurality of sensors; determining, as a function of the detection signals, a first detection sensor in the plurality of sensors detecting the fluid flow prior to other sensors in the plurality of sensors; determining time delays between detection of the fluid flow by a first sensor and by a second sensor in each pair of sensors in the plurality of sensors; and determining a fluid flow velocity vector indicative of the direction and the speed of the fluid flow as a function of the mutual positions and distances between the pairs of sensors in the plurality of sensors and the time delays.