Active Video Smoke Detection Using Shadow Analysis
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Solution Overview
Problem
Active video smoke detection systems face challenges such as false alarms and reduced sensitivity due to encroaching objects, alignment difficulties, and environmental robustness issues, particularly in large, varied environments with fluctuating light levels.
Innovation Solution
The system incorporates a primary light source and image sensor to detect particles based on scattered radiation, with additional features like shadow detection, fault notification, and alignment methods using reflectors and steerable light sources to improve robustness and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a laser beam is directed across an air volume for smoke detection, then particle detection capability is improved, but false alarms occur due to encroaching objects blocking the beam
Solution Approach 1:
A secondary light source is introduced as an intermediary element to illuminate the beam path and enable shadow detection. This additional light source allows the system to distinguish between smoke particles and encroaching objects by detecting shadows cast on the beam, thereby reducing false alarms while maintaining particle detection capability
Solution Approach 2:
The system implements feedback through shadow detection mechanisms that monitor the beam path for obstructions. When shadows are detected indicating encroaching objects, the system can differentiate these from smoke particles and adjust its detection algorithms accordingly, preventing false alarms while maintaining accurate particle detection
2Measurement precision
If system components are accurately aligned across extended distance, then detection accuracy is improved, but alignment maintenance becomes difficult in varied environments
Solution Approach 1:
The system incorporates self-aligning features where the secondary light source and detection mechanisms automatically adjust to maintain optimal alignment across the beam path. This self-service capability reduces the need for manual realignment in varied environments while maintaining detection accuracy
Solution Approach 2:
The alignment system is made dynamic through adjustable components that can adapt to environmental changes. The secondary light source and detection apparatus can be repositioned or reoriented to compensate for shifts in the primary beam path, maintaining accurate detection without requiring complete realignment
3Area of stationary object
If the system operates in large areas with fluctuating light levels, then coverage area is improved, but environmental robustness deteriorates due to background light interference
Solution Approach 1:
The system applies local quality by using the secondary light source to specifically illuminate only the beam path region of interest. This localized illumination creates a controlled detection zone that is less susceptible to background light interference from the surrounding environment, maintaining reliability across large areas with varying light conditions
Solution Approach 2:
The system changes detection parameters dynamically based on ambient light conditions. By adjusting the intensity and timing of the secondary light source and modifying detection thresholds according to background light levels, the system maintains environmental robustness while operating across large areas with fluctuating illumination
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
Enhances the sensitivity, usability, and robustness of active video smoke detection systems by reducing false alarms and maintaining accurate detection in diverse environments with fluctuating light conditions.
Implementation Method 1
at least one illumination means (also called a primary light source) for directing a beam of radiation through at least part of the air volume being monitored
Implementation Method 2
The captured images are analysed to detect the presence of smoke by determining the level of scattered EM radiation captured in the images
Data Source
AI summary
A particle detection system (100), such as an active video smoke detection system, includes at least one illumination means (102) for directing a beam (106) of radiation through at least part of the air volume being monitored (110), an image sensor (104) is positioned to capture images of at least part of a beam (106) from illumination means (102); and means to analyse (107) the captured images to detect the presence of particles within the volume. At least 29 different aspects are described for improving the sensitivity, usability, and robustness of particle detection. These include, for example, configuring illumination means (102) to create a curtain of light or a rapidly-scanned beam across the air volume (110), and configuring a reflector to steer or change direction of a beam reflected from illumination means (102).