Gear Cutting Roller Test Correlation via Revolution-Order Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods struggle to efficiently compare rolling test results with gear cutting machine data due to differences in data reference frames, making it difficult to identify correlations between gear deviations and machine errors.
Innovation Solution
Record axis and sensor data during gear machining relative to component revolutions, transforming them into order spectra using FFT, and compare these with rolling test data to directly identify machine deviations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If axis data and sensor data from the gear cutting machine are recorded and compared with rolling test results, then the ability to identify machine errors is improved, but the complexity of data comparison increases due to different reference frames
Solution Approach 1:
The patent segments the data comparison process by transforming both rolling test data and machine data into order spectra, which decompose complex signals into discrete frequency components. This segmentation allows systematic comparison of specific orders between the two data sources, reducing the complexity of analyzing complete time-series data with different reference frames.
Solution Approach 2:
The patent introduces an intermediary transformation process that converts time-domain data into frequency-domain order spectra. This intermediary representation serves as a common language for comparing rolling test results with machine axis and sensor data, enabling correlation identification without direct time-domain comparison.
2Ease of operation
If rolling test data and machine data are compared using time reference, then the comparison process is simplified, but the ability to directly correlate gear deviations with machine errors is reduced
Solution Approach 1:
The patent replaces the mechanical time-reference comparison approach with a frequency-domain order spectrum analysis. Instead of directly comparing time-synced data from different reference frames, the system transforms both datasets into order spectra where correlations can be identified through frequency content matching, substituting mechanical synchronization with spectral analysis.
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 direct correlation of rolling test results with gear cutting machine data, allowing for efficient identification and correction of machine errors, thereby improving gear quality.
Implementation Method 1
machining a gear toothing of a component by means of a gear cutting machine
Implementation Method 2
Rolling test of the geared component using a rolling test bench
Data Source
Figure 1~2
Figure 3~4
Figure 5~6
AI summary
Method comprising the following method steps: machining a gear (17) of a component (16) by means of a gear cutting machine (2), wherein, during the machining of the gear (17), axis data (22, 26) of at least one machine axis (4, 6) of the gear cutting machine (2), such as an axis feed, an axis acceleration, a power consumption of an axis drive, or the like, are recorded and/or wherein, during the machining of the gear (17), sensor data (18) of at least one sensor (10) of the gear cutting machine (2), such as a structure-borne sound sensor, an acceleration sensor, a distance sensor, or the like, are recorded; providing the recorded axis data (22, 26) related to one revolution of the component (16) as revolution-related axis data and/or providing the recorded sensor data (18) related to one revolution of the component (16) as revolution-related sensor data;Rolling test of the toothed component (16) using a rolling test stand (3, 5), wherein measurement data from the rolling test related to one revolution of the component (16) are provided as revolution-related measurement data during the rolling test; comparing the revolution-related axis data (22, 26) and/or the revolution-related sensor data (18) with the revolution-related measurement data from the rolling test in order to determine correlations between gear deviations according to the revolution-related measurement data from the rolling test and machine deviations according to the revolution-related axis data and/or the revolution-related sensor data.