Feed Axis Abnormality Diagnosis Using Encoder Frequency Analysis
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Solution Overview
Problem
Existing methods for diagnosing abnormalities in feed axis devices of machine tools, such as ball screws, often require additional sensors, leading to increased costs and failure risks due to the complexity of full-closed loop systems and semi-closed loop methods.
Innovation Solution
A method and device that perform abnormality diagnosis using a minimum configuration by controlling the feed axis device to operate in a predetermined pattern, detecting physical quantity signals, and performing frequency analysis to compare changes in frequencies with bending vibration modes, allowing for diagnosis without additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional sensors are added to detect vibration and rotational speed for abnormality diagnosis, then diagnostic capability is improved, but device complexity and cost increase
Solution Approach 1:
The system uses the existing rotary encoder that is already installed for position detection to simultaneously perform abnormality diagnosis. The rotary encoder serves dual purposes: position feedback for control and vibration detection for diagnostics, eliminating the need for separate diagnostic sensors.
Solution Approach 2:
The rotary encoder is made multi-functional by using it both for position detection in the control system and for vibration analysis in the diagnostic system. This allows one component to serve multiple functions, reducing overall system complexity.
2Measurement precision
If a full-closed loop method with displacement sensor is used for diagnosis, then measurement accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The system performs positioning accuracy measurement and abnormality diagnosis using only the existing rotary encoder and control unit, without requiring additional displacement sensors or full-closed loop configuration. The control unit leverages existing position detection data for diagnostic purposes.
3Adaptability or versatility
If more components are added to the minimum configuration for controlling the feed axis device, then diagnostic functionality is improved, but reliability decreases due to increased failure risk
Solution Approach 1:
The system achieves diagnostic functionality using only the components already present in the minimum configuration for controlling the feed axis device (motor, rotary encoder, and control unit). No additional components are added, thus maintaining high reliability while providing diagnostic capabilities.
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 low-cost and low-risk abnormality diagnosis for feed axis devices by eliminating the need for extra components, thereby reducing the risk of increased failure and maintaining diagnostic accuracy.
Implementation Method 1
a method that detects and diagnoses vibration of the ball screw, the support bearing, and a linear guide by a vibration sensor
Implementation Method 2
identifies which component that constitutes a ball screw has an abnormality by detecting a vibration and a rotational speed of the ball screw to perform a frequency analysis
Data Source
AI summary
An abnormality diagnostic method for a feed axis device that diagnoses an abnormality of the feed axis device including a screw shaft and a nut, the feed axis device being incorporated in mechanical equipment, the abnormality diagnostic method includes controlling an operation of the feed axis device such that the screw shaft operates in a predetermined operating pattern, detecting a physical quantity signal generated from the feed axis device, and performing an abnormality diagnosis for the feed axis device based on the physical quantity signal detected by the detecting in accordance with a predetermined abnormality diagnosis algorithm. The performing includes performing a frequency analysis on the physical quantity signal to extract respective frequencies corresponding to a plurality of operating positions in the operating pattern and performing the abnormality diagnosis based on change of the frequencies corresponding to the respective operating positions.