Multi-Sensor Fire Detection with Fuzzy Inference
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Solution Overview
Problem
Conventional fire detection systems, including smoke and temperature sensors, often fail to provide early and accurate detection, especially for slow smoldering fires and are prone to false alarms from nuisance sources, leading to inadequate fire detection in various fire types.
Innovation Solution
An automated fire detection system combining sensors such as temperature, infrared, smoke, and gas sensors, utilizing fuzzy inference and neural network-based classification to analyze sensor readings and differentiate between actual fires and nuisance sources, allowing for quick and accurate detection of fire types and sizes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional smoke detectors (photoelectric or ionization type) are used, then fire detection is provided, but false alarms occur due to detection of steam, aerosol spray, and smoke from nuisance sources
Solution Approach 1:
The patent combines multiple sensor types (photoelectric smoke detector, ionization smoke detector, and temperature sensor) into a single fire detection system. This multi-sensor approach allows the system to cross-validate readings and differentiate between actual fire conditions and nuisance sources, thereby reducing false alarms while maintaining high detection accuracy
Solution Approach 2:
The fire detection system is designed to perform multiple detection functions simultaneously - detecting smoke particles, measuring temperature, and analyzing combustion byproducts. This multi-functional capability enables the system to identify various fire types (smoldering, fast-flame, cooking fires) and distinguish them from non-fire sources, improving reliability while reducing false alarms
2Loss of time
If photoelectric smoke sensor is used, then slow smoldering fire detection is improved, but fast open-flame fire detection is inadequate
Solution Approach 1:
The patent merges photoelectric smoke detectors (effective for smoldering fires) with ionization smoke detectors (effective for fast-flame fires) and temperature sensors. This combination ensures that each fire type is detected by the sensor type best suited for it, eliminating the detection weaknesses of individual sensor types
3Measurement precision
If ionization smoke sensor is used, then fast open-flame fire detection is improved, but slow smoldering fire detection is inadequate
Solution Approach 1:
The system combines ionization smoke detectors with photoelectric smoke detectors and temperature sensors, creating a complementary multi-sensor network where each sensor type compensates for the weaknesses of the others, ensuring both fast-flame and smoldering fires are detected with high accuracy and speed
4Reliability
If temperature sensors with rate of rise detection are used, then fire detection is provided, but detection is delayed
Solution Approach 1:
The patent integrates temperature sensors with smoke detection capabilities (both photoelectric and ionization). This allows the system to detect the presence of smoke particles immediately upon fire ignition, rather than waiting for temperature rise, thereby eliminating detection delay while maintaining reliable fire detection through multi-parameter monitoring
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 reduces false alarms and provides early detection of various fire types by accurately analyzing sensor data, enabling timely alerts and responses, even when some sensors fail, and operates with or without CO sensors, enhancing overall fire detection efficiency.
Implementation Method 1
When smoke enters the chamber, the light from the LED is scattered, causing some of the light from the LED source to be sensed by the detector
Implementation Method 2
When smoke enters the chamber, the radiation from the chamber ionizes the smoke particles, causing the chamber to conduct electric current
Implementation Method 3
combining sensors such as temperature, infrared, smoke, and gas sensors
Data Source
AI summary
A method and system are provided, which provides reliable fire detection. In one implementation, the automated system includes a combination of sensors configured to measure various factors associated with a hazard, such as a fire or gas leakage, and generate sensor readings. Factors measured can include smoke, carbon monoxide and heat. The system further includes a detection device that is configured to determine whether a hazard or fire exists by performing a fuzzy analysis of sensor readings. The fuzzy analysis includes categorizing respective sensor readings into fuzzy sets, and determining whether the hazard exists based on a combination of the categorizations. In addition the size and direction of a fire can be determined from multiple sensors.