Damage prediction device and program
The damage prediction device analyzes spindle current and vibration data to predict rotary tool damage using regression equations, addressing inaccuracies in existing methods by accounting for varying operating states and operations.
Patent Information
- Application Number
- JP2024209227
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2024-12-02
- Publication Date
- 2026-06-12
AI Technical Summary
Existing damage prediction methods for rotary tools fail to accurately predict tool damage when the operating state changes, such as during operations other than machining or variations in machining intervals, due to power consumption fluctuations from movements and non-machining operations.
A damage prediction device that acquires and analyzes time-series data of spindle current and vibration measurements during forward rotation machining periods, calculates statistical values, and uses regression equations to predict tool damage by assessing deviations from established relationships, considering air-cut operations and non-processing periods.
Enables accurate prediction of rotary tool damage even when the operating state changes, improving the reliability of tool life assessment.
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Abstract
Citation Information
Patent Citations
Method and device for determining life of rotary tool
JP6864394B1