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Application of fanless industrial computers in robot visual defect detection
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Application of fanless industrial computers in robot visual defect detection

2024-10-14
Table of Contents

1. Product technical advantages

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AIR-300 is an embedded fanless industrial computer equipped with Intel Xeon E3 and Core 6/7 generation processors, with 32G DDR4 memory, and its processing performance is comparable to that of a desktop computer.

2. Application requirements for visual defect detection

Robot vision systems require high precision and stability in defect detection. The identification of differences between similar parts and accurate judgment of defect types are the key to improving manufacturing quality. This requires the system to be able to capture high-definition images from different perspectives and use pre-trained deep learning models for reasoning analysis.

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3. Specific application solutions

AIR-300 can support the installation of NVIDIA high-end independent graphics cards through the PCI Express expansion slot. The graphics card is responsible for capturing image data from multiple perspectives. Combined with deep learning models, AIR-300 can implement edge reasoning, that is, instant processing of data at the location where the data is generated, thereby identifying defects in real time.

4. System implementation steps

1. Data preparation: Collect a large number of part images containing various defects, annotate the defect types, and build a training data set.

2. Model training: Use a deep learning framework to train the model so that it can learn to identify and classify various defects.

3. System integration: Deploy the trained model on AIR-300 and integrate it with the graphics card and image capture device to form a complete defect detection system.

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4. On-site debugging: debug the system in a real industrial environment, optimize model parameters, and ensure that the detection accuracy and speed meet actual needs.

5. Production monitoring: After the system is put into production, continuously monitor the detection effect and regularly update the model to adapt to new defect types.

5. System advantages

1. High precision: The application of deep learning technology has greatly improved the accuracy of defect detection.

2. High efficiency: high-performance processor and memory configuration ensure high efficiency of image processing and data analysis.

3. Flexibility: The system is easy to expand and upgrade, and can adapt to the needs of different production lines.

4. Stability: fanless heat dissipation design, can run stably in harsh industrial environments.

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