[Intelligent Manufacturing Technology] 3.Machine Vision Application Technology-Online Course-CATECP

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[Intelligent Manufacturing Technology] 3.Machine Vision Application Technology

Lesson Code: TCEN2025H009

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Academic Hours

6.00hours

Publish Date

Jul 2025

Lecturer

1. Lecturers YANG YuGuangxi Technological College of Machinery and Electricity

General Introduction

This course is an interdisciplinary course that integrates knowledge from optics, electronics, computer science, and control engineering. Its core positioning can be summarized as “technology empowerment, application-oriented, and innovation-driven.”

The course aims to cultivate interdisciplinary talents equipped with the capabilities to design, develop, deploy, and maintain industrial vision systems.

This Course is for

# Helping trainees become familiar with the fundamental principles of industrial vision and the setup of typical vision systems.
# Enabling trainees to master the methods and procedures for applying machine vision in practical industrial scenarios.
# Laying a solid foundation for further study in comprehensive courses related to Electrical Automation Technology.

Learning Materials

1. Corresponding PPT
2. Online Course Video
3. Simulation Question Banks

Recognized By

Benefits of Learning

# Being able to complete the installation, debugging, and signal configuration of machine vision systems and follow industrial robot safety operation standards.
# Knowing how to apply image processing techniques such as image filtering, enhancement, segmentation, and feature extraction.
# Being capable of performing automatic detection and analysis of target objects.
# Being able to execute automated identification of target objects.
# Capable of recognizing defects such as cracks, scratches, stains, and dimensional deviations on target objects.

Courses Videos

Course Introduction_1.mp4play 1.1 Task 1 Fundamentals of Machine Vision_1.mp4play 1.2 Task 2 Types and Performance Parameters of Industrial Cameras_1.mp4play 1.3 Task 3 Types and Performance Parameters of Industrial Lenses_1.mp4play 1.4 Task 4 Types and Performance Parameters of Industrial Light Sources_1.mp4play 1.5.1 Task 5 Introduction to the Machine Vision Experimental Teaching Platform_1.mp4play 1.5.2 Experiment 1 Hardware Installation_1.mp4play 2.1.1 Task 1 Application of MV Viewer Software (Camera Driver Software)_1.mp4play 2.1.2 Experiment 1 Use of MV Viewer Software_1.mp4play 2.2.1 Task 2 Application of KImage Software_1.mp4play 2.2.2 Experiment 2 Use of KImage Software_1.mp4play 2.3.1 Task 3 Principles of Soybean Counting_1.mp4play 2.3.2 Experiment 3 Soybean Counting_1.mp4play 3.1.1 Task 1 Principles of XY Calibration_1.mp4play 3.1.2 Experiment 1 XY Calibration_1.mp4play 3.2.1 Task 2 Gears Measurement_1.mp4play 3.2.2 Experiment 2 Measurement of Glue Trajectories_1.mp4play 3.3.1 Task 3 Principles of Mechanical Parts Measurement_1.mp4play 3.3.2 Experiment 3 Mechanical Parts Measurement_1.mp4play 4.1.1 Task 1 Basic Principles of Defect Detection_1.mp4play 4.2.1 Experiment 2 Print Inspection_1.mp4play 5.1.1 Task 1 Principle of Color Recognition_1.mp4play 5.1.2 Experiment 1 Color Recognition_1.mp4play 5.2.1 Task 2 Principles of QR Code and Barcode Recognition_1.mp4play 5.2.2 Experiment 2 QR Code and Barcode Recognition_1.mp4play 5.2.3 Experiment 3 Liquid Test Tube Recognition_1.mp4play 6.1.1 Task 1 Principle of PCB Image Stitching_1.mp4play 6.1.2 Experiment 1 PCB Image Stitching_1.mp4play 7.1.1 Task 1 Principles of N-Point Calibration_1.mp4play 7.1.2 Experiment 1 N-Point Calibration_1.mp4play 7.2.1 Task 2 Principles of Tangram Recognition and Puzzle Assembly_1.mp4play 7.2.2 Experiment 2 Tangram Sorting and Puzzle Assembly_1.mp4play

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