Bearing Preload Measurement Using Outer Ring Vibration Modes
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Solution Overview
Problem
Current methods for determining bearing preload are invasive, time-consuming, and lack repeatability, making it challenging to integrate them into production cycles effectively, and they fail to directly measure internal preload which affects key performance metrics like friction, life, stiffness, and NVH.
Innovation Solution
A system and method using vibration measurement by rotating the bearing's inner ring to create vibrational noise on the outer ring, which is measured and analyzed using FFT and peak detection algorithms to determine eigen-frequencies and correlate them with ideally referenced data to calculate the preload, allowing for non-invasive and efficient preload determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the spacer insertion method is used to measure preload, then the measurement can be performed, but the process becomes invasive and time-consuming
Solution Approach 1:
The patent applies mechanical vibration by rotating the bearing at predetermined speeds to generate vibrational signals from the outer ring. These vibrations are then analyzed through FFT to determine eigen-frequencies, which are correlated with preload values. This non-invasive vibration-based approach eliminates the need for physical spacer insertion while enabling rapid measurement within production cycle times.
Solution Approach 2:
The patent replaces the mechanical spacer insertion method with a vibration analysis system. Instead of physically inserting spacers to measure preload, the system uses sensors to detect vibrational signals and processes them through FFT algorithms to determine preload values, thereby eliminating the invasive mechanical process.
2Productivity
If the stiffness measurement method with axial loads is used, then the measurement is faster, but the equipment lacks repeatability and speed for production integration
Solution Approach 1:
The patent implements feedback by comparing the measured eigen-frequencies against a pre-established correlation model that relates frequencies to preload values. The system continuously adjusts and refines measurements by referencing this correlation, ensuring repeatable and reliable results that can be consistently integrated into production environments.
Solution Approach 2:
The patent applies preliminary action by pre-establishing the correlation between eigen-frequencies and preload values through calibration measurements taken at various known preload levels. This pre-computed correlation data is stored and used during actual production measurements, enabling rapid and repeatable preload determination without requiring complex real-time calculations.
3Measurement precision
If direct preload measurement is attempted, then the internal preload can be determined, but the measurement process becomes complex and difficult to implement
Solution Approach 1:
The patent extracts the essential information needed for preload measurement by isolating the outer ring's eigen-frequencies from the complex vibrational signals. Through FFT analysis, the system extracts specific frequency components that are directly correlated with preload, simplifying the measurement process while maintaining accuracy in determining internal preload.
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 and efficient determination of bearing preload, improving production cycle integration and quality control by providing a direct measurement of internal preload, enhancing stiffness and NVH performance without the need for invasive methods.
Implementation Method 1
measuring the noise or vibration data emanating from the outer ring of the bearing
Implementation Method 2
The computer workstation having a software analysis package, the software analysis package performing a numerical Fast Fourier Transform (FFT) of the data to transform it into a Frequency Domain
Implementation Method 3
The software analysis package employing a peak detection algorithm to determine the peaks of the amplitude data in the frequency domain, wherein the peaks are various modes of the outer ring
Data Source
AI summary
A method of determining bearing preload by vibration measurement including mounting the bearing on a vibration tester, the outer ring clamped preventing rotation, mounting a sensor proximate the outer ring to measure vibration, the bearing inner ring rotated to excavate eigen-frequencies, the measured vibration data transmitted from the sensor to a computer workstation, the computer workstation performs a numerical FFT transforming data to Frequency Domain, spectral data from the FFT analyzed with the computer workstation, a peak detection algorithm determines the peaks that are the various modes of the outer ring, the modes are sorted and main modes identified, numerical relationship is obtained for each mode between the resonance and preload, the mode relationships are compared to one or more references, a match between the numerical relationships for each mode and the ideally referenced graph modes indicates a correct preload is determined. Also, a system for carrying out the method.