Multi-Sensor Flame Detection for False Positive Suppression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing flame detection methods in ignition systems suffer from accuracy issues due to interference from water vapor, dirt, and ambient noise, leading to false positives and unreliable flame detection, which can result in safety hazards.
Innovation Solution
A sensor device comprising a carbon dioxide sensor, fuel sensor, and electrostatic charge variation sensor, which detects flame presence through carbon dioxide concentration, fuel combustion emissions, and electrostatic charge variations, using narrow-band optical filters to enhance detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If optical detection using infrared sensors is used for flame detection, then flame detection capability is provided, but detection accuracy deteriorates due to interference from water vapor, dirt, and ambient radiation
Solution Approach 1:
The patent divides the detection task into multiple independent sensor channels: an infrared sensor for thermal detection, a UV sensor for chemical radical detection, and an acoustic sensor for combustion noise detection. Each sensor targets different physical/chemical aspects of combustion, so interference affecting one sensor does not necessarily affect the others, thereby maintaining overall detection accuracy despite individual sensor limitations
Solution Approach 2:
The patent combines multiple sensing modalities (infrared, ultraviolet, acoustic) into a unified flame detection system. By merging these different detection approaches, the system compensates for the weaknesses of individual sensors - for example, the UV sensor can detect flames even when infrared detection is compromised by water vapor or dirt accumulation on optical filters
2Reliability
If infrared optical filters are used to detect carbon dioxide radiation, then flame detection is enabled, but false positives increase due to radiation from other heat sources
Solution Approach 1:
The patent segments the detection spectrum into multiple wavelength regions using different sensors: infrared for thermal radiation, UV for chemical emission, and acoustic for mechanical vibration. This segmentation allows the system to distinguish flame-specific multi-wavelength radiation patterns from single-wavelength radiation of other heat sources, reducing false positives
Solution Approach 2:
The system uses feedback from multiple sensor channels to verify flame presence. The control unit processes signals from infrared, UV, and acoustic sensors simultaneously, requiring consistent detection across multiple modalities before confirming flame presence. This cross-validation feedback mechanism significantly reduces false positives caused by ambient radiation from non-flame heat sources
3Reliability
If acoustic analysis through microphone is used for spark generator monitoring, then spark detection capability is provided, but accuracy deteriorates due to ambient acoustic noise
Solution Approach 1:
The patent segments the acoustic detection task by using a dedicated acoustic sensor positioned near the spark generator to capture high-frequency spark sounds, while the control unit applies frequency filtering to isolate spark-related acoustic signatures from ambient noise. This segmentation in frequency domain allows accurate spark detection despite background acoustic interference
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 sensor device provides reliable and accurate flame detection, preventing fuel supply when no flame is present, thereby preventing uncontrolled combustion and reducing the risk of fires and explosions.
Implementation Method 1
a carbon dioxide sensor (20) configured to detect a concentration of carbon dioxide in the air
Implementation Method 2
a fuel sensor (30) configured to detect the presence of fuel combustion
Implementation Method 3
an electrostatic charge variation sensor (40) including a first and a second electrode (40a, 40b) spaced from each other and configured to detect respective electrostatic charge variations generated by the flame (12)
Implementation Method 4
using narrow-band optical filters to enhance detection accuracy
Data Source
Figure 1
Figure 2~3
Figure 4~5
AI summary
Sensor device (10) for detecting a flame (12), comprising: a carbon dioxide sensor (20) for detecting a CO2 concentration; a fuel sensor (30) for detecting the combustion of a fuel; an electrostatic charge variation sensor (40) for detecting electrostatic charge variations generated by the flame (12); and a control unit (50). The control unit (50) is configured to: acquire a carbon dioxide signal (SA) indicative of the concentration of carbon dioxide, a fuel signal (Sc) indicative of the fuel combustion, and an electrostatic charge variation signal (SQ) indicative of a difference between the electrostatic charge variations detected by a first (40a) and a second (40b) electrode of the electrostatic charge variation sensor (40); determine a quantized signal (SQ') based on the electrostatic charge variation signal (SQ); determine an aggregate datum (IA) based on the carbon dioxide signal (SA), the fuel signal (Sc) and the electrostatic charge variation signal (SQ); and generate, based on the aggregate datum (IA), a flame signal (SF) indicative of the presence or absence of the flame.