Intelligent detection robot for grain purchase and grain classification method

Abstract

The invention discloses an intelligent detection robot for grain purchase and a grain classification method. The intelligent detection robot comprises a first container used for containing raw materials, a first screen, a second screen, a second container and a sample separating and mixing device. A first weighing sensor is arranged at the bottom of the first container; the first screen is communicated with an outlet of the first container; the second screen is communicated with an outlet of the first screen; the second container is communicated with an outlet of the second screen, and a second weighing sensor is arranged at the bottom of the second container; and an inlet of the sample separating and mixing device is communicated with an outlet of the second container, and all outlets are communicated with a machine vision detection device. An inspector does not need to operate an instrument for detection, different detection indexes can be detected, and operation is easy and convenient.

Description

technical field [0001] The invention relates to the field of inspection and detection of grain purchase and circulation, in particular to an intelligent detection robot for grain purchase and a grain classification method. Background technique [0002] The same grain production area has widely different grain quality characteristics due to different cultivators, and different qualities have different rice yields and finished product tastes. Therefore, the raw grain needs to be graded during the grain purchase process. [0003] The quality and grade of raw grain determine the reasonable price of each catty of raw grain. Grain purchase, one end is connected to the farmers who plant the land, and the other end is connected to thousands of households on the dining table, and the next step is the national food security, which is the foundation of all security. The fairness of grain procurement is related to the overall situation. If it is unfair to farmers, it will damage farmer...

AI Technical Summary

Problems solved by technology

[0005] (1) Some inspectors need to operate instruments for testing, but different testing indicators require different testing instruments, and the operation is cumbersome;

[0006] (2) Part of it completely relies on human sensory detection, which greatly increases the subjective randomness of detection;

[0007] (3) The samples for all indicator tests need to be manually operated by personnel, and the samples of different batches, train numbers, and objects are concentrated in the inspection room, which is often confused;

[0008] (4) A few methods that use machine vision and neural networks to detect grain contours, color differences, and textures, including obtaining feature vector information through coordinate conversion or conversion of pixel elements (such as gray value, HSV / RGB value), etc. , on the one hand, it cannot be put into actual production due to the large amount of calculation that requires high computing power (for example, overcomputing); Cannot reduce human factor interference

[0009] To sum up, there are two problems in the procurement testing of grain grading and grading: the long testing time and low efficiency of each sample in the procurement testing, and another more serious problem caused by this problem is that the testing results are not accurate. Determinism, grading fairness is difficult to guarantee

[0010] At present, there is no unmanned intervention intelligent full-index detection equipment for grain purchase

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