Dual-Filter Fire Imaging for High-Resolution Detection
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Solution Overview
Problem
Existing fire detection systems, particularly optical outdoor systems, are expensive, complex, and often have low spatial resolution, requiring significant data processing and sweeping of imaging equipment, with thermal cameras being power-hungry and inefficient.
Innovation Solution
A fire detection system utilizing a camera with dual filters, each with distinct center frequencies (770 nm and 810 nm), a focusing system, and a controller to compare images captured through these filters to determine the presence of a fire, enhancing resolution and reducing atmospheric noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high resolution spectrometry is used for fire detection, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The optical spectrum is segmented into multiple discrete wavelength bands using bandpass filters (e.g., 400-700nm visible light, 700-1400nm short-wave infrared, 1400-3000nm mid-wave infrared, 3000-14000nm long-wave infrared). Instead of using a complex high-resolution spectrometer that continuously scans the entire spectrum, the system divides the spectrum into separate bands and detects each band independently using simpler camera sensors, thereby reducing device complexity while maintaining measurement precision for fire detection
Solution Approach 2:
The invention extracts only the critical wavelength bands relevant to fire detection (visible light, short-wave infrared, mid-wave infrared, and long-wave infrared bands) from the entire electromagnetic spectrum. By using bandpass filters to isolate these specific bands and discarding irrelevant spectral regions, the system achieves accurate fire detection without the complexity of analyzing the complete spectrum, thus resolving the contradiction between measurement precision and device complexity
2Reliability
If thermal cameras (LWIR systems) are used for fire detection, then detection capability is improved, but power consumption increases and spatial resolution deteriorates
Solution Approach 1:
The infrared detection range is segmented into two distinct bands: short-wave infrared (700-1400nm) and long-wave infrared (3000-14000nm). Each band is detected by separate camera systems with appropriate focal plane arrays. This segmentation allows the system to capture both the thermal radiation (LWIR) for reliable fire detection and the shorter wavelength radiation (SWIR) that carries spatial detail information, thereby maintaining detection capability while improving spatial resolution and reducing power consumption compared to using only LWIR systems
3Adaptability or versatility
If sweeping of imaging equipment is performed to collect light across spectrum, then measurement coverage is improved, but productivity decreases due to time-consuming data collection and stitching
Solution Approach 1:
The system uses periodic modulation of narrowband filters (e.g., acousto-optic modulators or electro-optic modulators) to sequentially pass different wavelength bands to the detector. This periodic filtering allows the system to collect data from multiple spectral bands in rapid succession without physically sweeping the imaging equipment, thereby achieving broad spectral coverage while maintaining high detection speed and avoiding the time-consuming stitching process
Solution Approach 2:
The system pre-configures multiple bandpass filters covering different spectral regions (visible, SWIR, MWIR, LWIR) in advance, so that when fire detection is needed, the appropriate filters are already in position or can be quickly switched to. This preliminary preparation eliminates the need for real-time spectral scanning and stitching, enabling rapid multi-spectral fire detection while maintaining comprehensive spectral coverage
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 higher resolution and automated fire detection, improving accuracy and reducing common-mode noise, while being cost-effective and efficient, enabling fire estimation and guiding firefighting efforts.
Implementation Method 1
a first filter having a first center frequency and first passband and a second filter having a second center frequency and second passband
Implementation Method 2
at least one focusing element such as a lens, mirror, or other focusing element in the at least one optical path
Data Source
AI summary
A fire detection system is provided. The system includes camera(s), focusing elements such as lenses or mirrors, and filters. The camera(s) collect images, some through at least a first filter of the filters, and some through at least a second filter of the filters. By comparing the images, fires may be detected. For instance, the filters may be selected so that one filter selects for light at a frequency associated with emissions from fires and so that another filter selects for light at another frequency. By comparing images collected through the different filters, a presence or absence of a fire may be determined.