Bearing Scratch Size Estimation From Vibration Frequency Analysis
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Solution Overview
Problem
Conventional diagnosis methods for bearing mechanisms in production machines cannot accurately determine the deterioration degree, specifically the size of scratches, which hinders timely maintenance and countermeasure decisions.
Innovation Solution
A diagnosis apparatus and method that acquire vibration data from bearing mechanisms, perform frequency analysis, extract feature amounts, and estimate scratch size based on predetermined relationships, allowing for the diagnosis of scratch presence and size on both outer and inner rings without interrupting production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If periodic inspection with manual oil sampling is performed to measure iron powder concentration, then bearing deterioration can be detected, but production must be interrupted and manual labor is required
Solution Approach 1:
The patent replaces manual mechanical inspection (opening lids, sampling oil, laboratory analysis) with an automated vibration sensing system. Accelerometers mounted on the decelerator housing capture vibration signals, which are then processed through frequency analysis to detect bearing deterioration, eliminating the need for production interruption and manual labor while maintaining detection capability
Solution Approach 2:
The system enables the bearing mechanism to diagnose its own condition through vibration analysis. The acquisition unit continuously collects vibration data, the extraction unit processes this data to identify deterioration patterns, and the system automatically determines when maintenance is needed, allowing the equipment to monitor itself without external intervention during operation
2Productivity
If automated vibration-based diagnosis is implemented, then production continuity is maintained, but the ability to quantify deterioration degree is insufficient
Solution Approach 1:
The patent transforms vibration signal parameters (frequency, amplitude, spectral characteristics) into meaningful deterioration indicators. By analyzing specific frequency components corresponding to bearing defect frequencies and tracking their evolution over time, the system quantifies the progression of bearing degradation, providing actionable information about deterioration degree while maintaining continuous operation
Solution Approach 2:
The system establishes a feedback loop where vibration data is continuously acquired, analyzed, and used to update the bearing condition assessment. The extraction unit compares current vibration patterns against baseline data and deterioration models, providing ongoing feedback about the bearing's health status and predicting remaining useful life, enabling proactive maintenance decisions
3Loss of time
If detailed bearing inspection is performed to determine scratch size, then maintenance timing can be optimized, but complex manual procedures are required
Solution Approach 1:
The patent extracts specific diagnostic information (bearing deterioration degree, estimated scratch size) from complex vibration signals through frequency domain analysis. By focusing on particular frequency components and their modulation patterns, the system isolates the relevant deterioration indicators from the overall vibration spectrum, providing quantified maintenance guidance without requiring complex manual disassembly or inspection procedures
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 accurate diagnosis of bearing mechanism degradation, facilitating timely maintenance decisions and reducing manual inspection hours by determining the deterioration degree and specific countermeasures.
Implementation Method 1
an acquisition unit that acquires data relating to vibrations corresponding to a rotation of a bearing mechanism including rolling elements between an outer ring and an inner ring
Implementation Method 2
an extraction unit that extracts a feature amount from a result of performing a frequency analysis on the data acquired by the acquisition unit
Data Source
AI summary
Degradation degree of a bearing mechanism is diagnosed. A diagnosis apparatus includes: an acquisition unit that acquires measurement data relating to vibrations corresponding to a rotation of a bearing mechanism including rolling elements between an outer ring and an inner ring; an extraction unit that extracts a feature amount from a result of performing a frequency analysis on the measurement data; an estimation unit that estimates a size of a scratch generated on the outer ring or the inner ring based on a predetermined relationship between a change of the feature amount and a size of a scratch generated on the outer ring or the inner ring, and based on the feature amount extracted by the extraction unit; and an output unit that outputs an estimation result of the estimation unit.