Rolling Element Bearing Residual Life Estimation via Vibration Pattern Analysis
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Solution Overview
Problem
Conventional methods for detecting spall initiation in rolling element bearings of gas turbine engines cannot accurately predict the progression of failure and the remaining useful life, as they do not differentiate between the stages of spall progression effectively.
Innovation Solution
A system and method that assesses changes in vibratory responses and patterns to determine the stage of spall progression by comparing the vibratory patterns to a reference, using a ratio of imbalance response to impulse response, allowing for accurate estimation of residual useful life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional oil debris monitoring systems are used to detect spall initiation, then the presence of particles can be detected, but the system cannot predict the progression stage or remaining useful life of the bearing
Solution Approach 1:
The failure progression is segmented into multiple distinct stages (Stage 1: Spall Initiation, Stage 2: Early Spall Progression, Stage 3: Advanced Spall Progression, Stage 4: Impending Failure). Each stage is characterized by specific vibratory pattern features, allowing the system to not only detect spall initiation but also track progression through each stage to predict remaining useful life.
Solution Approach 2:
The system dynamically transitions from static particle detection to continuous vibratory monitoring that adapts to changing bearing conditions. The vibratory patterns are analyzed in real-time to detect transitions between failure stages, enabling dynamic assessment of bearing health and progression tracking.
2Reliability
If particle detection methods are used, then spall initiation can be identified, but the progression rate and time to failure cannot be determined
Solution Approach 1:
The system performs preliminary detection of spall initiation and identifies the specific stage of progression before actual failure occurs. By detecting characteristic vibratory patterns at each stage, the system provides advance warning and prediction of time to failure, allowing maintenance to be scheduled before catastrophic failure.
Solution Approach 2:
The system continuously monitors vibratory patterns and provides feedback on the current failure stage and progression rate. This feedback mechanism allows for real-time assessment of bearing condition and prediction of remaining useful life, enabling proactive maintenance decisions.
3Ease of operation
If simple particle detection is used, then the system is easy to operate, but it cannot differentiate between stages of spall progression
Solution Approach 1:
Vibratory pattern analysis serves as an intermediary between simple particle detection and complex failure prediction. The system uses vibration sensors and spectral analysis algorithms to translate raw vibratory signals into meaningful failure stage classifications, bridging the gap between simple monitoring and sophisticated prediction while maintaining ease of operation.
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
Enables precise tracking of rolling element bearing failure stages and prediction of impending failure, providing a health score-based assessment of the remaining useful life.
Implementation Method 1
A vibration sensor detects a vibratory response of the rolling element bearing and the rotor bearing system
Data Source
Figure 1A~2
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AI summary
Estimating residual useful life of a rolling element bearing (12) in an operating gas turbine engine (16) is provided. A processor (400) receives a vibration signal from a vibration sensor. The vibration signal includes a vibratory response of the rolling element bearing (12). Processor (400) detects a vibratory pattern of the rolling element bearing (12) from the vibration signal and compares the vibratory pattern to a reference vibratory pattern. Processor (400) identifies a failure propagation stage (21,22,23,24) in which the vibratory pattern matches the reference vibratory pattern. Processor (400) correlates the failure propagation stage (21,22,23,24) to the residual useful life remaining in the rolling element bearing (12) and generates an output signal representing the residual useful life remaining in the rolling element bearing (12).