AI Vision Monitoring for Machining Danger Zone Intrusion
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Solution Overview
Problem
Existing safety devices for machining operations, such as those using biometric information, are inconvenient and ineffective in preventing accidents when a worker's body part enters the danger zone, as they rely on attached sensors and biometric data rather than visual detection.
Innovation Solution
A device and method that utilize AI-based analysis of video data from machine tools to detect when a worker's hands are in the danger zone, stopping the chuck or cutter motor and triggering an alarm through audio and video signals, without requiring attached sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If biometric information detection sensors are attached to the worker's body to detect safety risks, then the system can monitor worker physiological state, but it causes inconvenience to the worker and cannot prevent accidents when body parts enter the danger zone
Solution Approach 1:
The patent replaces the mechanical/biometric sensor attachment system with an optical vision system. The image acquisition device captures visual data of the worker and machine tool, and the AI model analyzes this visual information to detect danger zone intrusions, eliminating the need for physical sensor attachments on the worker's body.
Solution Approach 2:
The patent creates a virtual copy of the physical workspace through image acquisition. Instead of measuring the worker's physical state directly with sensors, the system captures visual images of the workspace and uses AI to analyze the relationship between the worker's body parts and the danger zone, providing indirect but effective safety monitoring.
2Productivity
If the machine tool operates continuously to maintain productivity, then production efficiency is improved, but the risk of accidents increases when workers are present in the danger zone
Solution Approach 1:
The patent implements a real-time feedback safety system. The image acquisition device continuously monitors the workspace, the AI model analyzes the images to detect worker presence in the danger zone, and the system provides immediate feedback by triggering an alarm and stopping the machine tool when intrusion is detected, enabling continuous operation with enhanced safety.
Solution Approach 2:
The patent performs preliminary safety analysis using AI to predict potential accidents before they occur. By analyzing the spatial relationship between the worker's body parts and the danger zone in real-time images, the system can identify intrusion risks and take preventive action (alarm and stop) before actual contact or damage occurs.
Data Source
AI summary
Proposed is a device and a method for preventing worker safety accidents during machining and, more particularly, a device and a method for preventing worker safety accidents during machining, which can prevent worker safety accidents in advance by stopping an operation of a chuck or cutter and triggering an alarm when a part of a worker's body is present in the danger zone beyond the safety zone judged by an artificial intelligence (AI)-based analysis of work images/videos captured during turning, milling, and other machining using chucks or cutters.