Tool Wear Detection Using Spindle Loading Rate and Fuzzy Logic
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Solution Overview
Problem
Current methods for detecting tool wear in CNC machining processes are inefficient, requiring additional sensors and providing only binary wear status indicators, which can lead to premature tool replacement and increased production costs, while lacking real-time monitoring and detailed wear level determination.
Innovation Solution
A detection method and device that utilizes a fuzzy logic unit to calculate an estimated cutting force by comparing loading rates during cutting procedures with different parameter sets, allowing for precise wear level classification and real-time monitoring without additional sensors, and adjusts the cutting locus based on wear levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional sensors (laser transceivers, accelerometers, etc.) are installed to directly measure cutter status, then measurement precision of tool wear is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The system uses the machine tool's own existing sensors (spindle loading rate sensors) to detect tool wear, eliminating the need for additional dedicated sensors. The control device processes data from these existing sensors to determine tool status, making the system self-sufficient without external additions.
Solution Approach 2:
The existing spindle loading rate sensors, originally designed for monitoring machine load, are repurposed to also detect tool wear conditions. This multi-functional use of existing sensors eliminates the need for separate tool monitoring sensors, reducing system complexity while maintaining detection capability.
2Productivity
If additional sensors are installed near the tool for real-time monitoring, then productivity through continuous monitoring is improved, but ease of operation deteriorates due to frequent sensor damage from cut-off chips and cutting fluids requiring repair and replacement
Solution Approach 1:
The system utilizes sensors already integrated into the machine tool structure, positioned away from the direct cutting zone. These existing sensors are not exposed to cut-off chips and cutting fluids, eliminating the need for frequent maintenance while maintaining continuous monitoring capability.
Solution Approach 2:
The system uses the spindle loading rate as an intermediary parameter to indirectly detect tool wear conditions. Instead of placing sensors directly near the tool where they would be damaged, the system measures the effect of tool wear on spindle loading, providing remote, maintenance-free monitoring.
3Ease of operation
If binary wear status indicators (Normal/Worn) are used to simplify detection, then ease of operation is improved, but loss of information occurs because detailed wear level determination is unavailable leading to premature tool replacement
Solution Approach 1:
The tool wear detection is divided into multiple wear levels (first wear level, second wear level, third wear level) rather than a single binary status. This segmentation allows the system to provide detailed wear progression information while maintaining simple visual indication through different display colors or codes, balancing simplicity with information richness.
Solution Approach 2:
The system provides continuous feedback on tool wear progression through multiple defined wear levels, allowing operators to monitor the gradual deterioration of tool condition. This feedback mechanism enables timely intervention at appropriate wear stages, preventing both premature replacement and unexpected tool failure.
4Reliability
If tool replacement is performed based on conservative estimates to ensure quality, then reliability of product quality is improved, but productivity decreases due to unnecessary premature replacements increasing equipment expenditure
Solution Approach 1:
The tool replacement strategy transitions from static, conservative time-based replacement to dynamic condition-based replacement. The system continuously monitors actual tool wear levels and triggers replacement only when necessary, adapting the replacement timing to actual tool condition rather than predetermined schedules, thereby optimizing both quality and productivity.
Solution Approach 2:
The system changes the monitoring parameter from binary wear status to multi-level wear progression detection. By detecting intermediate wear levels and tracking their progression, the system can determine the optimal replacement timing based on actual tool degradation, preventing both premature replacement and quality degradation from excessive wear.
Data Source
AI summary
A detection device, detection method, and compensation method for tool wear, applied to a machine tool including a spindle connected to a tool. A first parameter set including a first cutting depth having a zero cutting depth is set, and the machine tool performs a cutting procedure with the first parameter set to record a first loading rate of the spindle. A second parameter set including a second cutting depth having a non-zero cutting depth is set, and the machine tool performs the cutting procedure with the second parameter set to record a second loading rate of the spindle. A processing device calculates an estimated cutting force according to the loading rates and a machine performance database. A fuzzy logic unit outputs a wear level according to a tool wear database and the estimated cutting force. The machine tool adjusts a cutting locus according to the wear level.