Aircraft Engine Thermal Neuromorphic Sensing for Event-Driven Data Capture
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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, especially on aircraft with limited resources, and often collect unnecessary data during nominal operating conditions.
Innovation Solution
Implementing a thermal neuromorphic sensor system that asynchronously reports changes in thermal data characteristics, activating additional sensors only when anomalies are detected, thereby reducing data analysis and storage needs during normal operation and efficiently focusing resources on potential fault conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If synchronous sensors are used to continuously monitor engine parameters, then measurement precision and reliability are improved, but data processing complexity and storage requirements increase significantly
Solution Approach 1:
The patent extracts only the essential information (temperature changes indicating anomalies) from the continuous sensor data stream. Instead of processing all synchronous data, the system isolates and processes only the relevant thermal events that indicate potential engine faults, thereby reducing data processing complexity while maintaining anomaly detection reliability
Solution Approach 2:
The system dynamically adjusts its monitoring approach by switching between continuous monitoring mode and event-triggered mode. During normal operation, only thermal anomalies trigger full data collection and processing, while during nominal conditions, the system remains in a low-power state with minimal processing requirements
2Measurement precision
If synchronous sensors collect data at high frequencies, then measurement precision is improved, but data storage requirements increase significantly
Solution Approach 1:
The patent extracts only the critical thermal events from the continuous temperature data stream. By using thermal neuromorphic sensors, the system extracts only the temperature changes that exceed predefined thresholds or represent significant deviations from normal operation, thereby maintaining measurement precision for anomaly detection while dramatically reducing the volume of data requiring storage
Solution Approach 2:
The system discards redundant temperature data collected during nominal engine operation and recovers only the essential anomaly information. Normal temperature fluctuations are filtered out and not stored, while significant thermal events are captured and stored for analysis, effectively reducing storage requirements while preserving critical diagnostic information
3Loss of information
If continuous data collection is performed during nominal operation, then complete operational data is obtained, but unnecessary data processing and storage resources are consumed
Solution Approach 1:
Instead of continuous data collection and processing, the system employs periodic sampling triggered by thermal events. The thermal neuromorphic sensors periodically activate full data collection only when temperature anomalies occur, while during nominal operation between events, the system enters a low-power state with minimal processing activity, thereby reducing energy consumption while maintaining operational data completeness through event-driven sampling
Solution Approach 2:
The thermal neuromorphic sensors autonomously determine when data collection is necessary by self-monitoring temperature conditions. The system serves itself by automatically activating full monitoring modes only when thermal anomalies are detected, without requiring continuous external control or processing resources, thereby reducing overall energy consumption while ensuring complete data capture during critical events
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
This approach minimizes data processing and storage requirements during nominal conditions, allowing for rapid and efficient anomaly detection and diagnosis, and reduces unnecessary data collection, enhancing real-time fault identification and alerting capabilities.
Implementation Method 1
a thermal neuromorphic sensor coupled to an aircraft engine... receive first data from the thermal neuromorphic sensor, the first data including a thermal data characteristic associated with the aircraft engine
Data Source
AI summary
Embodiments of the present disclosure generally relate to aircraft engines and, more particularly to data acquisition for aircraft engines using thermal neuromorphic sensors. In some embodiments, an event associated with the aircraft engine may be identified based on a change in a thermal data characteristic measured from a thermal neuromorphic sensor. In response to identifying the event associated with the aircraft engine, one or more other sensors coupled to the aircraft engine may be activated and data received from the activated sensors stored in memory. Other embodiments may be disclosed or claimed.