Fire Detector Time Series Analysis for Early Detection
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Solution Overview
Problem
Conventional fire detectors often detect fires late due to reliance on slow increases in measured variables and are prone to interference, lacking robustness and the ability to distinguish between fire types or sources.
Innovation Solution
A method utilizing time series analysis of measurement signals from multiple sensor devices, including light, temperature, and CO detection, to detect early signs of fires by analyzing fluctuations, noise, and scatter, allowing for more precise and error-free detection through detrending and correlation analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional fire detectors rely on slow increase in measured values and threshold exceedance, then the detection method is simple, but fires are detected at a late stage
Solution Approach 1:
The patent applies preliminary action by performing time series analysis on measurement signals to detect early signs of fires before they reach threshold levels. The system analyzes fluctuations, noise, and scatter in the measurement signal over time to identify incipient fire stages, enabling early detection without waiting for slow increases in measured values to exceed thresholds.
2Reliability
If conventional fire detectors use simple threshold-based detection, then the device complexity is low, but the detectors are prone to interference and lack robustness
Solution Approach 1:
The patent implements feedback by continuously analyzing the time series characteristics of measurement signals and using this information to improve detection reliability. The system monitors fluctuations, noise, and scatter over time, comparing them against learned patterns to distinguish true fire signals from interference, thereby enhancing robustness through continuous adaptive feedback.
Solution Approach 2:
The patent applies parameter changes by analyzing multiple characteristics of the measurement signal including fluctuations, noise, and scatter over time. Instead of relying on a single threshold parameter, the system evaluates temporal patterns and statistical properties of the signal, transforming the detection approach from simple threshold comparison to multi-parameter time series analysis.
3Adaptability or versatility
If conventional fire detectors use single sensor detection, then the device complexity is low, but the ability to distinguish between fire types and sources is limited
Solution Approach 1:
The patent applies universality by using a single sensor device that performs multiple functions through time series analysis. The same sensor signal is analyzed for various fire types and sources by examining different temporal patterns, fluctuations, and noise characteristics, enabling the system to distinguish between different fire scenarios without requiring multiple specialized sensors.
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
Enables early detection of fires by identifying minor changes in the fire development process, reducing false alarms, and distinguishing between fire types, while improving robustness against interference.
Implementation Method 1
Light is only detected by the light sensor when particles (e.g. smoke or dust) enter the optical path between the light source and light sensor and scatter the light from the light source onto the light sensor
Data Source
Figure 1a~1b
Figure 2a~2b
Figure 2c~2d
AI summary
Method for fire detection using a fire detector 1, wherein the fire detector 1 comprises a sensor device for acquiring a measured quantity and for outputting a measurement signal S, wherein the measurement signal S has noise and/or dispersion, wherein the method comprises the following steps: - Acquiring the measurement signal S of the sensor device for an evaluation time interval, - Performing a time series analysis for the measurement signal S in the evaluation time interval, - Determining a fire event based on the time series analysis.