Condiments Container Visual Inspection System With AI Intelligent Conveyor Line

Condiments Container Visual Inspection System with AI Intelligent Conveyor Line

Inspection standards

Inspection principle

After the product is formed, it will pass through the front-end guiding mechanism to ensure that all the bottles are in the same direction. After passing through the conveying line in a stable and orderly manner, it will be sent to the inspection station inside our inspection machine for sequential inspection.

After being processed by image processing software and AI detection algorithm, it will be judged Good products and defective products, detected defective products are automatically eliminated online, and the counting function can be realized after the finished product is detected. After product detection, it is transported by the export conveyor line for transition
Go to the backend for the next step of the packaging process.

Vision solutions

Our company's design scheme adopts 14 sets of high-pixel area array industrial cameras and high-performance strobe light sources to conduct comprehensive inspections on the appearance defects of bottle products. The design inspection speed of the entire set of inspection equipment is 60 pieces/minute, and the equipment can realize It operates 7*24 hours a day, and unqualified products can be automatically eliminated online.

Advantages of ai algorithm

• Accuracy of results: Compared with traditional vision algorithms, the stability of deep learning algorithms is greatly improved, and it can adapt to general disturbances in the environment and background. At the same time, the accuracy of the algorithm is also higher than that of traditional vision algorithms;
• Algorithm versatility: For different defects, only a small number of defect samples need to be collected. After sufficient training, different defect samples can be automatically identified. The algorithm adopted is a unified algorithm framework;
• Development timeliness: Since there is no need to develop algorithms for different defects, the entire development cycle is greatly shortened, and general visual defect projects only need 2-3 hours to go online for testing;
• Environmental reliability: Due to the guarantee of GPU computing power, the entire system can work in a high-temperature environment for a long time with sufficient computing power margin.