Aircraft Cabin Sensor Mapping for Targeted Maintenance Inspection
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Solution Overview
Problem
Existing aircraft typically have limited sensor installations inside the cabin, making it time-consuming and costly to obtain comprehensive datasets of interior parameters during flight, which hinders efficient maintenance scheduling and passenger experience optimization.
Innovation Solution
A real-time ad hoc network sensor system comprising fixed and mobile sensors, with mobile devices like tablets and smartphones, that create a vehicle data-signature-map by mapping sensor outputs to a computer model of the aircraft, allowing for efficient data collection and analysis without the need for extensive additional sensor installations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If hundreds of new sensors are installed throughout the aircraft interior, then comprehensive datasets of interior parameters can be obtained, but the time-consuming certification process and installation complexity increase significantly
Solution Approach 1:
The patent uses mobile devices (smartphones, tablets, laptops) carried by passengers as temporary sensor nodes. These devices copy the sensing functionality needed for interior parameter measurement, eliminating the need for permanent sensor installations. The mobile devices' existing sensors (accelerometers, gyroscopes, microphones, cameras) are leveraged to collect data that would otherwise require dedicated aircraft sensors.
Solution Approach 2:
The mobile devices serve multiple functions: they act as sensors for interior parameter measurement, provide wireless communication nodes for data transmission, and serve as positioning references. This multi-functionality reduces the need for specialized equipment and simplifies the overall system architecture.
2Reliability
If additional sensors are installed in the aircraft interior, then more interior parameters can be monitored, but the certification process becomes more time-consuming and costly
Solution Approach 1:
Passengers use their own mobile devices, which already contain certified sensors, to perform the measurement function. The devices self-organize into a sensor network without requiring aircraft-specific certification. The system leverages the existing certification of consumer mobile devices rather than requiring new certification processes.
Solution Approach 2:
The mobile devices act as intermediaries between passengers and the aircraft maintenance system. They collect interior parameter data, process it locally, and transmit it to ground systems, eliminating the need for direct integration with aircraft systems and the associated certification requirements.
3Productivity
If a limited suite of sensors is installed during the build process, then installation time is reduced, but insufficient data is obtained for comprehensive maintenance scheduling and passenger experience optimization
Solution Approach 1:
The sensor network is segmented into multiple independent mobile devices distributed throughout the aircraft interior. Each device independently collects and processes data for its local area, then contributes to the overall dataset. This segmentation allows comprehensive coverage without requiring a single complex centralized sensor system.
Solution Approach 2:
The sensor network is dynamic rather than static - mobile devices move throughout the aircraft interior during flights, automatically adjusting their measurement positions and coverage areas. This dynamic deployment provides comprehensive spatial and temporal data coverage that fixed sensors cannot achieve.
4Ease of manufacture
If mobile devices are used as sensors, then sensor installation cost is reduced, but data mapping and synchronization complexity increases
Solution Approach 1:
The system uses feedback from mobile device sensors (accelerometers, gyroscopes, GPS) to continuously track device position and orientation. This feedback information is used to dynamically map sensor readings to the appropriate locations in the aircraft interior model, automatically handling the complexity of data spatial mapping.
Solution Approach 2:
The system transforms raw sensor data from mobile devices into standardized parameters by applying coordinate transformations and temporal synchronization. The mobile device's motion parameters (position, velocity, orientation) are used to adjust and align the sensor data with the aircraft's reference frame, simplifying the integration process.
Data Source
AI summary
An example method of performing maintenance on an aircraft includes receiving a vehicle data-signature-map of an interior of an aircraft for at least one parameter of the aircraft, and the vehicle data-signature-map is based on sensor outputs received from sensors of mobile devices positioned at locations in the interior of the aircraft. The method also includes comparing the vehicle data-signature-map with a previous vehicle data-signature-map, based on differences of the vehicle data-signature-map as compared to the previous vehicle data-signature-map making a determination for maintenance, and generating and outputting a recommendation for inspection of an identified portion of the aircraft based on the distribution of the at least one parameter in the vehicle data-signature-map for the identified portion of the aircraft being substantially different than the distribution of the at least one parameter in the vehicle data-signature-map for other portions of the aircraft to assist with the maintenance of the aircraft.