Table of contents
Scenario introduction-Metallurgical industry application background
Fully automatic cold rolling production line and early warning application
Billet OCR intelligent recognition
Long material tracking application scenarios
Safety production application scenarios
Scrap mixed material inspection
Product Features of Scrap Mixed Material Inspection
Intelligent grading of scrap steel briquettes
Case Advantages - Introduction to Commercial Implementation Cases
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The industrial defect detection system based on AI image recognition is a system that uses artificial intelligence technology and image processing algorithms to automatically detect defects in industrial products. It can monitor the quality of products in real time during the production process, improving production efficiency and product quality.
Today I would like to share with you a self-developed product, a defect detection system based on AI recognition and applied to industrial scenarios.
Traditional scrap quality assessment mainly relies on visual inspection by staff and lacks intelligent mechanized equipment testing, which is prone to quality objections and economic disputes. In addition, due to the wide variety of impurities in scrap steel, it is extremely difficult to identify them through AI. To this end, we have completely self-developed an automatic scrap grading system to empower the AI strategic upgrade of traditional industries.
Market background analysis
Scenario introduction-Metallurgical industry application background
The working principle of this system is to obtain images of products through cameras or other image acquisition devices, and then use AI image recognition algorithms to analyze and process the images to identify defects in the products. AI image recognition algorithms can learn and identify different types of defects, such as cracks, damage, foreign objects, etc., by training models.
During the implementation of the system, a training data set needs to be established first, including different types of defect images and normal images. The data set is then trained using machine learning algorithms to generate a model that can accurately identify defects. After training is completed, the model is deployed into the system and defect detection can begin.
Fully automatic cold rolling production line and early warning application
Billet OCR intelligent recognition
When a product enters the detection area through the sensor, the camera automatically takes an image of the product and transmits it to the system for analysis. The system will preprocess the image, such as denoising, smoothing, etc., and then use the trained model to recognize the image. If a defect is identified in the product, the system will issue an alarm in time and record the location and type information of the defect to facilitate subsequent processing and analysis.
System advantages
Next, we introduce the advantages of the product:
1. Automation: By using AI image recognition algorithms, the system can automatically detect product defects without manual intervention, improving production efficiency and product quality.
2. High accuracy: AI image recognition algorithm can learn and identify different types of defects, has high accuracy and stability, and can effectively detect defects in products.
3. Real-time monitoring: The system can monitor and detect products in real time, discover and deal with defects in time, avoid defective products from entering the market, and ensure product quality.
4. Data analysis: The system can record and analyze the location and type information of defects to help companies conduct quality control and production optimization, and improve product quality and production efficiency.
Customer case
Appearance defect detection
Customer case
Long material tracking application scenarios
Thin steel materials are bundled every 200 pieces. In the semi-automatic era, manual intervention is required and the cost is high. Nowadays, with the introduction of AI machine vision, automatic counting and bundling can be achieved completely unmanned. We have accumulated case experience in the steel, coal mining, and electric power industries and welcome cooperation and consultation!
Safety production application scenarios
Scrap mixed material inspection
Product Features of Scrap Mixed Material Inspection
Intelligent grading of scrap steel briquettes
Case Advantages - Introduction to Commercial Implementation Cases
Leading edge description
The industrial defect detection system based on AI image recognition is an advanced technology application that can help companies realize automated defect detection and improve product quality and production efficiency. With the continuous development and advancement of artificial intelligence technology, this system will play an increasingly important role in industrial production.
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