Machine Tool Chip Detection Using Mesh-Based Image Segmentation
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Solution Overview
Problem
Existing chip detection methods struggle to accurately and efficiently detect chips produced during machine tool processing due to variations in chip shape, color, size, and environmental conditions, leading to complex image processing requirements and high computational costs.
Innovation Solution
A chip detection apparatus that divides the target area image into mesh images of a predetermined size and uses a chip information determiner to determine chip presence and ease of cleaning for each mesh image, employing a machine learning algorithm to improve detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing is performed on the entire image to detect all chips, then comprehensive chip detection is achieved, but the calculation amount and time required become enormous
Solution Approach 1:
The entire image is divided into multiple mesh images of a predetermined size. The chip information determiner processes each mesh image separately using a preset determination parameter, rather than processing the entire image at once. This segmentation approach reduces the computational burden and processing time while maintaining detection accuracy for each chip location.
2Measurement precision
If image processing is performed on the entire image to detect all chips, then comprehensive chip detection is achieved, but the computational complexity increases significantly
Solution Approach 1:
By dividing the image into mesh images and processing them independently with preset determination parameters, the system simplifies the overall processing complexity. Each mesh image is evaluated separately, avoiding the need for complex global image analysis while maintaining comprehensive chip detection capability.
3Adaptability or versatility
If traditional image processing methods are used to detect chips with various shapes, colors, and sizes, then all chip types can be detected, but detection accuracy decreases due to environmental variations
Solution Approach 1:
The system uses a determination parameter that is preset for determining chip information in each mesh image. This parameter-based approach allows the system to adapt to various chip types (different shapes, colors, sizes) and environmental conditions (illuminance, coolant presence) by evaluating whether chip information is present in each mesh image, rather than relying on fixed image processing thresholds that fail under varying conditions.
Data Source
AI summary
To easily and accurately detect chips produced when processing a work by a machine tool, there is provided a chip detection apparatus for detecting chips produced when processing a work by a machine tool. The chip detection apparatus includes a mesh divider that performs processing of dividing, into a plurality of mesh images in a predetermined mesh size, at least part of an area image obtained by capturing a target area where the chips are to be detected, and a chip information determiner that determines chip information concerning the chips for each of the mesh images using a determination parameter preset for determining the chip information.