Recent status

The quality inspection of glutinous rice is an important business node for grain processing and grain storage enterprises. The accuracy of the inspection results is directly related to the economic interests and reputation of the enterprise. At present, the moldy and imperfect grains in the quality inspection of glutinous rice are all manually inspected, recorded and counted based on artificial senses by personnel. The existence speed is slow, the accuracy rate is low, the missed detection rate and the false detection rate are high, and long-term work fatigue. At the same time, there is a lot of uncertainty, and there are risks such as collusion among personnel. The efficiency of quality inspection is also difficult to meet the requirements of automated operations. It needs to be solved in a smarter and more efficient way.

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.

Core technology

1.Automatic binarization: use deep neural network to segment the foreground and background of the image, smoothly segment the grain edge, and accurately locate the grain to be analyzed.

2.Adhesion material segmentation algorithm: deep neural network segments the adhering grains to form independent and complete grains, which are analyzed and classified.

3.Multi-attribute recognition: It adopts a lightweight neural network and integrates a semi-supervised multi-attribute learning method. The user can label a small number of samples of the grain to be analyzed, and then the data model can be updated to perform fast and high-precision analysis of the grain.

After-sale service

The company has a complete technical service team and rapid response mechanism, and has dedicated service specialists for each customer, who can receive technical consultation and fault reports from customers at any time. And to ensure rapid response to customer emergencies, to ensure that customers receive satisfactory service.During the epidemic or due to special reasons, when after-sales engineers are unable to reach the site, the service center can remotely adjust customer equipment for troubleshooting and technical consultation.

After the equipment arrives at the customer site, the after-sales engineer arrives in time to carry out equipment installation, commissioning, and operation training. The product quality of the whole machine is traceable, and the quality warranty period is 1 year from the date of acceptance. In the event of non-human faults during the warranty period, after-sales engineers will quickly arrive at the site or provide remote guidance for free maintenance.