Cutter-Tip Vibration Mapping for Faster Machining Defect Analysis
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Solution Overview
Problem
Current methods for identifying machining defects, such as those caused by cutter-tip vibration, are inefficient and rely heavily on technician experience, leading to delayed problem resolution and reduced production efficiency.
Innovation Solution
A method involving obtaining motion and vibration acceleration data, performing time-frequency analysis, normalizing the data, and synchronizing it with motion data to create an amplitude color map, which intuitively identifies defects caused by cutter-tip vibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If technicians use experience-based trial-and-error approach to identify defect causes, then they can leverage their expertise, but the defect identification is delayed and production efficiency is reduced
Solution Approach 1:
The patent replaces the mechanical trial-and-error approach with an automated data processing system that collects vibration data, performs FFT analysis, and generates amplitude distribution maps. This substitution of manual mechanical diagnosis with automated computational analysis simultaneously improves identification accuracy and reduces resolution time.
Solution Approach 2:
The patent introduces vibration data and amplitude distribution maps as intermediary elements between the defect and the technician. Instead of direct trial-and-error diagnosis, the system uses vibration signals and their spectral analysis as mediators to objectively identify defect causes, improving both accuracy and speed.
2Productivity
If automated data processing methods are used to identify machining defects, then defect identification speed is improved, but the system complexity increases
Solution Approach 1:
The patent creates a multi-functional system that simultaneously collects vibration data, performs FFT analysis, generates amplitude distribution maps, and identifies defect causes. By consolidating multiple functions into one integrated system, the patent improves defect identification speed while managing system complexity through functional integration rather than separate components.
Solution Approach 2:
The system performs self-diagnosis by automatically processing vibration data and generating defect identification results without requiring complex external analysis tools or multiple separate systems. The automated FFT analysis and amplitude map generation enable the system to serve itself, improving productivity while keeping the device architecture relatively simple.
Data Source
AI summary
A method for facilitating analysis of causes of machining defects is provided. The method is carried out by a computer system. The method includes the step of obtaining motion data and vibration acceleration data about the tip of a cutter mounted on a machine tool. The method further includes the step of obtaining time-frequency information about the vibration acceleration data by performing a time-frequency analysis on the vibration acceleration data. The method further includes the step of obtaining vibration-displacement data by normalizing the time-frequency information. The method further includes the step of obtaining amplitude-distribution data about the tip by synchronizing the motion data and the vibration-displacement data.