Machine Tool Controller Automatic Abnormality Diagnosis
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Solution Overview
Problem
Current machine tool controllers require significant time and effort for operators to identify abnormality factors, as they need to manually examine data and input symptoms, and lack automatic analysis capabilities, leading to inefficient troubleshooting.
Innovation Solution
A machine tool controller equipped with a power supply monitoring unit, abnormality detecting unit, and abnormality diagnosing unit that automatically selects and diagnoses abnormality factors, displaying and storing the results, allowing for automatic identification and recovery of abnormalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual examination of stored data is performed to identify abnormality factors, then the controller can detect abnormalities, but the time required for identification increases significantly
Solution Approach 1:
The controller performs self-diagnosis by automatically analyzing stored data and identifying abnormality factors without requiring manual examination. The abnormality diagnosing unit autonomously processes the stored measurements and determination results to determine the cause of abnormalities, enabling the system to serve itself in the diagnosis process.
Solution Approach 2:
The patent replaces the manual mechanical process of examining data with an automated electronic diagnosis system. The abnormality diagnosing unit electronically processes stored data and generates diagnosis results, substituting the operator's manual analysis with an automated computational system.
2Measurement precision
If separate abnormality diagnosis devices are provided, then detailed abnormality analysis is possible, but the complexity of the system increases
Solution Approach 1:
The patent combines the abnormality diagnosis function with the existing controller by adding a diagnosis program to the control unit. This integration merges the diagnosis capability into the controller's existing data processing and control functions, eliminating the need for separate external diagnosis devices while maintaining comprehensive analysis capability.
Solution Approach 2:
The controller is designed to perform multiple functions including both control operations and abnormality diagnosis. The control unit executes both control programs and diagnosis programs, and the storage unit stores both control data and measurement data, making the controller a universal device that handles both operational control and diagnostic analysis.
3Loss of information
If operators manually input symptoms to diagnosis devices, then specific abnormality information can be obtained, but the effort and time required increase
Solution Approach 1:
The system performs preliminary data collection and storage during normal operation, continuously storing measurements from various sensors and determination results in the storage unit. When an abnormality occurs, this pre-stored data is immediately available for automatic analysis, eliminating the need for operators to manually input symptoms at the time of diagnosis.
Solution Approach 2:
The controller continuously monitors system parameters and provides feedback by storing determination results and measurements. This feedback mechanism ensures that accurate abnormality information is automatically captured and made available for diagnosis, eliminating the need for manual symptom input while maintaining high information accuracy.
Data Source
AI summary
A machine tool controller capable of identifying the factors of a warning easily is provided. A controller of a machine tool includes a power supply monitoring unit, a power supply abnormality detecting unit, and an abnormality diagnosis unit. The power supply monitoring unit acquires measurements indicating an operating state of a machine tool and/or a peripheral device (for example, an AC power supply or a motor) of the machine tool. The power supply abnormality detecting unit detects an abnormality in the operating state of the machine tool and/or the peripheral device and outputs a signal indicating the abnormality and the measurements obtained when the abnormality was detected. The abnormality diagnosis unit automatically selects a measurement related to the abnormality among the measurements and automatically diagnoses factors of the abnormality.