Honey parameter detection method based on deep learning and system thereof

Abstract

The invention discloses a honey parameter detection method based on deep learning and a system thereof, which belong to the field of honey parameter detection based on deep learning. The method comprises the following steps: 1) honey according with production requirements can be placed on a conveyor belt, a detection apparatus is turned on for detection learning to obtain a sample data; 2) other honey is successively placed on the conveyor belt for detection to obtain the honey parameter; 3) whether the honey parameter belongs to a sample data scope is determined, if a LED light source displays green light, the process goes to a step 4; if negative, the LED light source displays red light, the process goes to a step 5); 4) the honey parameter is printed by printing equipment, and a label for qualification is pasted by a manipulator; and 5) the honey parameter is printed by printing equipment, and a label for disqualification is pasted by the manipulator. The honey parameter detection method solves the problems that adulteration is generated by merchants due lacking of detection parameter setting, and the consumers cannot conveniently know the product parameter, and can achieve theeffect of visual check of parameter by consumers and production with quality and amount guaranteeing by merchants.

Description

technical field [0001] The invention relates to the field of honey parameter detection based on deep learning, in particular to a method and system for detecting honey parameters based on deep learning. Background technique [0002] With the further improvement of transparency in all walks of life, food quality problems are frequently exposed by the media, making food safety the most common concern of people. Various food safety problems emerge in endlessly, but people's diet is cast a shadow, so food inspection has become an indispensable and important part of food safety; honey is collected by bees from the flowers of flowering plants The honey made from nectar in the hive, honey is a supersaturated solution of sugar, crystallization will occur at low temperature, the crystallization is glucose, and the part that does not crystallize is mainly fructose. Due to the difference of bee species, nectar source and environment, the chemical composition of honey is very different...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is: the present invention provides a honey parameter detection method and system based on deep learning, which solves the existing problem of adulteration in production due to the lack of detection parameter devices and the inability of consumers to know product parameters conveniently

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