Bearing Maintenance Timing via Dimensionless Vibration Analysis
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Solution Overview
Problem
Existing methods for determining the time to repair a bearing are inaccurate due to environmental factors like load, speed, and temperature, leading to increased repair costs and reduced service life.
Innovation Solution
A method that involves obtaining vibration signals, calculating dimensionless criteria such as NIE, J-Divergence, Kurtosis, and mixed dimensionless criterion C to predict bearing damage and determine the optimal time for repair, thereby improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vibration peak threshold method is used to determine bearing repair time, then the monitoring process is simple, but the repair time determination is inaccurate due to environmental factors
Solution Approach 1:
The patent transforms the vibration signal from raw amplitude data into dimensionless parameters (NIE, Kurtosis, J-Divergence) that normalize the signal characteristics. This parameter transformation eliminates the influence of environmental factors such as load, speed, and temperature variations, enabling accurate bearing condition assessment across different operating conditions while maintaining computational simplicity.
Solution Approach 2:
The patent replaces the conventional mechanical threshold-based monitoring approach with an information-theoretic analysis method. By using NIE (Normalized Information Entropy), Kurtosis, and J-Divergence calculations, the system substitutes simple peak detection with a more robust mathematical framework that accounts for the statistical distribution of vibration signals, thereby improving measurement precision without significantly increasing operational complexity.
2Duration of action of stationary object
If the repair time is determined too early based on conventional methods, then the bearing service life is reduced, but the reliability of the monitoring system is compromised
Solution Approach 1:
The patent establishes a feedback mechanism by continuously calculating dimensionless parameters from vibration signals and comparing them against reference values. The NIE, Kurtosis, and J-Divergence values provide real-time feedback on bearing condition, allowing the system to dynamically adjust repair timing decisions. This feedback loop ensures that repairs are scheduled based on actual bearing degradation rather than fixed thresholds, improving both service life and reliability.
Solution Approach 2:
The patent enables preliminary assessment of bearing condition by calculating dimensionless parameters that indicate early signs of degradation. By detecting changes in NIE, Kurtosis, and J-Divergence before catastrophic failure occurs, the system allows for planned maintenance actions that extend service life while maintaining reliability through proactive rather than reactive monitoring.
Data Source
AI summary
Provided in the present invention is a bearing maintenance timing acquisition method: first, acquiring vibration signals of a bearing under different loads; then, respectively acquiring dimensionless parameters according to the vibration signal of each load; thus, acquiring predicted damage condition distribution data of the bearing under different loads according to the dimensionless parameters; and finally, obtaining accurate maintenance timing based on the predicted damage condition distribution data under different loads, so as to prolong the service life of the bearing while reducing maintenance costs.