Aircraft Cargo Smoke Detection Using Particle and Gas Sensor Networks

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Solution Overview

Problem

Aircraft cargo compartment smoke detection systems experience high false alarm rates due to particulates, and existing multi-sensor systems are bulky and impractical for wide-body aircraft, leading to potential delays in detecting fires in uncovered areas.

Innovation Solution

A smoke detection system comprising a first set of particle sensors and a second set of gas sensors, including nano-technology gas sensors, with a processor that uses radial basis functions to process data and generate alert signals when both particle and gas thresholds are exceeded, effectively reducing false alarms and covering gaps between sensor packages.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If multi-sensor smoke detector packages are used to reduce false alarms, then detection reliability is improved, but device weight and volume increase making them impractical for wide-body aircraft

Engineering Contradiction:
Improvedetection reliabilityVSAvoidsensor package weight
Core Design Contradiction:
ReliabilityVSWeight of stationary object

Solution Approach 1:

The system divides the detection function into separate sensor types distributed throughout the cargo bay. Instead of using few bulky multi-sensor packages, the patent employs multiple individual sensors (particle sensors and gas sensors) spaced throughout the space, with each sensor performing a specific detection function. This segmentation reduces the weight and size of individual sensor units while maintaining or improving overall detection coverage.

Inventive Principle:
Principle #1Segmentation

2Reliability

If multi-sensor smoke detector packages are distributed on cargo bay ceiling, then detection coverage is improved, but large open spaces create white spaces that delay fire detection

Engineering Contradiction:
Improvedetection coverageVSAvoidfire detection time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The cargo bay is divided into multiple detection zones with individual particle sensors and gas sensors positioned throughout. This segmentation allows for finer spatial resolution and ensures that no large white spaces exist between sensor coverage areas. Each sensor monitors its local zone, and the networked system provides comprehensive coverage of the entire cargo bay.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system transitions from relying solely on particle detection (single dimension) to combining particle detection with gas detection (adding another dimension). By monitoring both particulate matter and combustion gases simultaneously, the system detects fires earlier and more reliably, eliminating blind spots that would exist with particle sensors alone.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

3Device complexity

If particle sensors are used alone, then device complexity is reduced, but false alarm rate increases due to particulates such as mist, dust, and condensation

Engineering Contradiction:
Improvesensor system complexityVSAvoidfalse alarm rate
Core Design Contradiction:
Device complexityVSReliability

Solution Approach 1:

The system merges particle sensing technology with gas sensing technology into an integrated detection network. Particle sensors detect combustion particulates while gas sensors detect combustion gases. By combining these different sensing modalities, the system achieves high detection reliability with low false alarm rates, as the sensors cross-validate each other's readings to confirm actual fire conditions.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The networked sensor system implements feedback mechanisms where each sensor's readings are continuously monitored and compared against thresholds. When particle sensors detect elevated particulate levels, the system queries gas sensor data to verify whether combustion gases are also present. This feedback loop eliminates false alarms caused by non-combustion particulates like dust or condensation while maintaining sensitivity to actual fires.

Inventive Principle:
Principle #23Feedback

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 significantly reduces false alarm rates and provides quicker detection of smoke and fire events by using lightweight, nanotechnology-based gas sensors to supplement particle sensors, ensuring more comprehensive coverage of aircraft cargo bays.

Implementation Method 1

a first set of sensors positioned within a cargo compartment and configured to sense at least particles in the cargo compartment

Methodology Applied
Scientific EffectLight scattering: Scattering

Implementation Method 2

a second set of sensors positioned within the cargo compartment and configured to sense at least one gas in the cargo compartment

Methodology Applied
Scientific EffectGas concentration detection:

Data Source

PatentEP2897114B1Smoke detector and gas sensor network system and method
Publication Date: 2018.10.10 THE BOEING CO
  • EP2897114B1 patent drawingFigure 1~2
  • EP2897114B1 patent drawingFigure 3
  • EP2897114B1 patent drawingFigure 4

AI summary

A system and method for detecting smoke in a compartment that includes a first set of sensors 110, a second set of sensors 120 and a processor 220. Each sensor in the first set is configured to sense particles 110. Each sensor in the second set is configured to sense at least one gas 120. The processor 220 is configured to receive first input data from the first set of sensors 110 and second input data from the second set of sensors 120, to compare the second input data with a noise level when the first input data indicates that particles are present in the compartment, and to generate an alert signal when the second input data exceeds the noise level. The processor 220 preferably calculates a rate of change of the second data and compares the second input data with the noise level only when the rate of change of the second data exceeds a third threshold.