Engine Monitoring With Adaptive Sampling and Look-Back Capture
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Solution Overview
Problem
Current engine monitoring units (EMUs) are not configured for intelligent and continuous engine monitoring, leading to inefficient data logging and insights for maintenance crews, and face challenges in managing the data size-to-relevance trade-off due to the voluminous nature of internal engine data.
Innovation Solution
A variable-rate monitoring system that adjusts recording speeds based on event occurrence, allowing for high-frequency capture during transients and events while reducing recording speed during steady-state operations, with dynamically adjustable thresholds to maintain file size constraints, and a look-back feature for retroactive high-speed data capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-frequency data recording is implemented to capture all engine events and transients, then measurement precision and reliability are improved, but data volume increases significantly causing storage and transmission challenges
Solution Approach 1:
The system dynamically adjusts the recording frequency based on engine operating conditions. During steady-state operations, recording occurs at a lower frequency to reduce data volume. When transients or events are detected, the system automatically increases recording frequency to capture detailed information, thus resolving the contradiction between measurement precision and data volume.
Solution Approach 2:
The patent changes the recording parameter (sampling frequency) based on engine state. By monitoring engine parameters and detecting transitions between steady-state and transient conditions, the system adjusts the data recording rate accordingly, maintaining measurement precision when needed while minimizing data volume during normal operations.
2Loss of information
If continuous high-rate data logging is performed to capture all engine operations, then complete operational insights are obtained, but maintenance burden and transmission costs increase
Solution Approach 1:
The system extracts and prioritizes critical information by identifying significant events and transients in engine operation. Instead of logging all data at high rate, it selectively captures detailed information only when events occur, removing unnecessary data during steady-state operations. This reduces maintenance burden while preserving essential operational insights.
Solution Approach 2:
The patent applies partial action by recording data at high frequency only when necessary (during events and transients) rather than continuously. During normal steady-state operations, recording occurs at a reduced rate, providing sufficient operational insights while significantly reducing the maintenance and transmission burden associated with processing all possible data.
3Quantity of substance
If engineers manually decide what data to store and what to not store, then data storage capacity is optimized, but intelligent and continuous monitoring capability is lost
Solution Approach 1:
The system implements automated feedback mechanisms that continuously monitor engine parameters and automatically adjust recording strategies. When the system detects events or transients, it automatically increases recording frequency without manual intervention. This maintains intelligent and continuous monitoring capability while optimizing data storage capacity through automated decision-making about what data to capture.
Data Source
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AI summary
There is provided a system for monitoring an engine. The system includes a processor. A memory including instructions that, when executed by the processor, cause the processor to perform certain operations. The operations may include receiving a first data set and a second data set. The first data set being sampled at a first rate and the second data set being sampled at a second rate, where the first and second rate are different. The operations further include determining, based on a number of occurrences in either the first data set or the second set, whether an event that has occurred in the engine has occurred a predetermined number of times. The operations further include recording the first data set as an output in response to the number of occurrences exceeding the predetermined number of times, and in the contrary recording the second data set as the output. The operations may include computing a ratio of a fast recording process to a slow recording process and adjusting an output file size according the ratio. Another feature may be a look back subsystem that backfills an interval of pre-event fast recordings when an event is detected. The system can self-adjust thresholds to maintain file size constraints during unusually active or eventful flights.