Machine Tool Self-Diagnosis Using Impulsive Axis Excitation
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Solution Overview
Problem
Traditional diagnostic methods for machine tools, such as modal analysis, face challenges in repeatability and compatibility with normal operations, requiring dedicated calibration steps that result in machine-tool downtime and are sensitive to external environmental conditions.
Innovation Solution
A method and system for diagnosing machine tool operation that allows for self-excitation during normal operations, using a control module to generate impulsive variations in kinematic quantities, enabling analysis of impulsive responses for fault detection and providing homogeneous samples for neural networks, thus improving repeatability and independence from external conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If external excitation elements (hammer or shaker) are used for modal analysis, then diagnostic capability is improved, but repeatability deteriorates due to sensitivity to external conditions and operator variability
Solution Approach 1:
The machine tool system performs self-diagnosis by using its own operational data and control systems to generate excitation signals and measure responses, eliminating the need for external excitation elements. The control module generates impulsive variations in kinematic quantities during normal operation, and sensors capture the system's own response, enabling repeatable diagnostics without external operators or tools
Solution Approach 2:
The patent replaces mechanical excitation methods (hammer impacts, shaker vibrations) with electronic/control-based excitation. The control module generates impulsive variations in kinematic quantities through the machine tool's own control system, substituting external mechanical excitation with internal electronic control signals that are more repeatable and programmable
2Measurement precision
If traditional modal analysis with external excitation is used, then fault detection capability is improved, but machine-tool downtime increases due to dedicated calibration steps
Solution Approach 1:
The diagnostic system operates continuously during normal machine tool operations without requiring dedicated calibration steps or downtime. The control module generates impulsive excitation signals and sensors capture responses while the machine tool is running, enabling fault detection to occur continuously alongside productive operations rather than requiring separate maintenance intervals
Solution Approach 2:
The system performs diagnostic measurements during normal operations before faults develop or worsen, enabling early detection. By continuously monitoring during productive use rather than waiting for scheduled maintenance, the system can identify issues preliminarily while the machine is still functioning normally, preventing future downtime
3Measurement precision
If external excitation sources are used for diagnosis, then diagnostic accuracy is improved, but device complexity increases due to additional external components
Solution Approach 1:
The patent merges the diagnostic function with the machine tool's existing control and operational systems. The control module that normally operates the machine tool also generates diagnostic excitation signals, and existing sensors used for operation monitoring also capture diagnostic responses, combining production and diagnostic functions into a single integrated system without adding separate external excitation devices
Solution Approach 2:
The control module and sensors serve multiple functions: they control and monitor normal machine tool operations while simultaneously generating and measuring diagnostic signals. This multi-functionality eliminates the need for dedicated external excitation sources and separate diagnostic equipment, reducing overall system complexity while maintaining diagnostic accuracy
Data Source
AI summary
A method (1000) of diagnosis of operation of a machine tool (10, 100) that includes one or more axes (X, Y, Z) moved by one or more actuators (101, 102, 104) and at least one sensor (30) coupled to the machine tool (10, 100), the method (1000) comprising operations of: generating (1200) a programming sequence of movement of the axes (X, Y, Z) of the machine tool (10, 100); controlling (1210) the movement of the axes (X, Y, Z) of the machine tool (10, 100) according to the programming sequence; receiving (1220) a read-out signal (S) of the at least one sensor (30) coupled to the machine tool (10, 100); and processing (1230) the read-out signal (S) of the at least one sensor (30) coupled to the machine tool (10, 100). The programming sequence comprises instructions that are such as to apply (T) at least one single impulsive variation of a kinematic quantity that regards one or more actuators (101, 102, 104). The operation (1230) of processing the read-out signal (S) comprises processing a response of the machine tool (10, 100) to at least one single impulsive variation. The operation (1230) of processing the read-out signal (S) comprises artificial-neural-network processing (206) via one or more artificial neural networks (206, 2060) configured for analysing operating profiles in particular, one or more signals indicative of the status of the machine tool (W) in the read-out signal (S).