Aircraft Engine Neuromorphic Sensing for Event-Driven Data Acquisition
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Solution Overview
Problem
Conventional synchronous sensors in aircraft engines generate large volumes of data at high frequencies, posing challenges in efficient analysis and storage, particularly on aircraft with limited data processing and storage capabilities.
Innovation Solution
Implementing neuromorphic sensors that asynchronously report changes in data characteristics, allowing the data acquisition system to activate additional sensors only when anomalies are detected, reducing unnecessary data collection and processing during nominal operating conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional synchronous sensors are used to monitor engine status, then comprehensive data coverage is achieved, but data storage requirements and processing complexity increase significantly
Solution Approach 1:
The patent extracts only the essential information (changes in data characteristics) from the continuous data stream, reporting only when anomalies or changes occur rather than transmitting all raw data points. This selective extraction reduces data volume while maintaining anomaly detection capability.
Solution Approach 2:
The system performs partial monitoring by focusing resources on detecting changes rather than continuously processing all parameters at full resolution. Neuromorphic sensors activate only when necessary, performing exactly enough monitoring to detect anomalies without excessive data collection.
2Reliability
If synchronous sensors report data at predetermined intervals, then continuous monitoring is maintained, but unnecessary data is generated during nominal operating conditions
Solution Approach 1:
Instead of continuous synchronous reporting, the system uses event-driven periodic action where neuromorphic sensors report only when changes occur. This transforms continuous monitoring into on-demand periodic reporting, reducing processing energy during nominal conditions while maintaining fault detection timeliness.
Solution Approach 2:
The neuromorphic sensors autonomously determine when reporting is necessary based on detected changes in data characteristics. The system serves itself by automatically activating reporting only when anomalies are detected, eliminating the need for external control signals and reducing unnecessary processing.
3Reliability
If all sensors are activated continuously, then complete data acquisition is ensured, but device complexity and data management burden increase
Solution Approach 1:
The sensor activation scheme transitions from static continuous operation to dynamic on-demand activation. Sensors are activated only when neuromorphic sensors detect changes requiring monitoring, adapting the system's monitoring intensity to actual engine conditions and reducing management complexity.
Data Source
AI summary
Embodiments of the present disclosure generally relate to aircraft engines and, more particularly to data acquisition for aircraft engines using neuromorphic sensors. In some embodiments, an event associated with the aircraft engine may be identified based on a change in a data characteristic measured from a neuromorphic sensor and, in response to identifying the event associated with the aircraft engine, at least one other sensor coupled to the aircraft engine may be activated. Other embodiments may be disclosed or claimed.