The quality inspector for red rice in the processing plant developed and produced by our company is connected to the red rice processing production line, and to the red rice lifting and conveying pipeline. The red rice is regularly extracted from the conveying pipeline and the quality of the red rice is analyzed. Analyze the budding grains, heterogeneous buds, grass seeds, worm-eaten grains, Gibberellin grains, damaged grains, black germs, impurities, etc. of red rice for testing and analysis, guiding the improvement of red rice quality, and generating statistical reports from time to time to improve products Security and traceability.

Inspection principle

When it is detected that the quality of the red rice sampled is not good, the operators of the production line can adjust the parameters of the red rice sorting machine on the production line in time to ensure the quality of the red rice produced. The red rice that has been inspected can be automatically sent back to the red rice processing line through the pipeline, and the grains are returned to the warehouse without wasting a grain of grain.

Combine traditional machine vision methods and artificial intelligence algorithms to analyze red rice. First, use traditional vision methods to segment the red rice grains in the video frame, and then use artificial intelligence algorithms to identify the attributes of the segmented red rice grains to determine whether they exist Insect-eaten, sprouting, mildew and other problems. At the same time, two high-resolution cameras were used to photograph the front and back of the red rice, and the properties of the two sides were analyzed. Through the registration algorithm, the front and back of the red rice are registered one by one, and their respective attributes are combined to obtain the attributes of a complete red rice grain.

Examples of segmentation diagrams are as follows:

Product Description

The equipment uses the latest AI vision detection technology and is equipped with 3 high-resolution cameras to analyze the attributes of the front and back sides of glutinous rice. Through the registration algorithm, the front and back sides of the glutinous rice are registered one by one, and their respective attributes are combined to obtain a synthesis. The properties of a whole piece of glutinous rice; use deep neural network to segment the sticky glutinous rice at instance level to easily deal with the sticking situation of glutinous rice; at the same time, open the cloud platform to remotely train samples of different customers to meet customer customized classification standards.

This machine replaces manual work, can work 7*24 hours, detect the quality of glutinous rice with high precision, detect broken rice, chalky grains, imperfect grains, and moisture in the glutinous rice in time, and find whether there are mildew, worms, impurities and other problems. It can be used for daily sampling inspection before and after glutinous rice production.

The glutinous rice quality detector can be connected to upstream and downstream production equipment according to the specific production needs of customers on site. The parts in contact with the equipment and samples are made of medical-grade materials, which are safe and hygienic, intelligent in design, simple to operate, and convenient to maintain.

Machining process