The high-precision coffee bean defect analyzer developed and produced by our company can be used in coffee beanprocessing plants, coffee beanstorage, laboratories, and quality inspection centers. It can detect sprout, moldy, heat-damaged kernels (natural, dried), imperfect kernels, disease spots, worm-eaten kernels, broken kernels, impurities, etc. of coffee bean, and form online statistical reports to improve products Safety and traceability can also guide the improvement of quality.

Combine traditional machine vision methods and artificial intelligence algorithms to analyze coffee bean. First, use traditional vision methods to segment the coffee bean kernels in the video frame, and then use artificial intelligence algorithms to identify the attributes of the segmented coffee bean kernels to determine whether there are insects. Moth, sprouting, mildew and other problems. At the same time, two high-resolution cameras were used to photograph the front and back sides of the coffee bean, and the attributes of the two sides were analyzed. Through the registration algorithm, the front and back coffee bean are registered one by one, and their respective attributes are combined to obtain the attributes of a complete coffee bean.

Equipment advantages:

1. High accuracy, artificial intelligence AI detection, the error is controlled within 0.01%;

2. High efficiency, 2 minutes to complete the test, one is equivalent to 3 manual workers;

3. Intelligent, three-dimensional, easy to operate, you can use it in 3 minutes;

4. Femto-visible, high-precision camera omni-directional detection 0.04mm recognition accuracy;

Key technology

1. Automatic binarization: Use deep neural network to segment the foreground and background of the image. Compared with the traditional binarization method, it can be applied to a variety of lighting conditions, and the coffee bean edge segmentation is smoother, fast and robust High advantages.

2. Adhesion coffee bean segmentation algorithm: The method based on connected domains cannot segment the adhesion coffee bean. The deep neural network is used to segment the adhesion coffee bean at an instance level, which can reach a speed of 1000fps and can process the adhesion coffee bean in real time.

3. Coffee bean attribute recognition algorithm: adopts a lightweight neural network and integrates a semi-supervised learning method. The model can be iteratively optimized only by marking a small amount of data. It has the advantages of high accuracy, fast speed, and convenient deployment.

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.