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Apple sugar degree detection device and detection method based on multispectral machine learning

A machine learning and detection device technology, applied in machine learning, measuring devices, color/spectral characteristic measurement, etc., can solve the problems of complex operation, difficult carrying, high cost, etc., and achieve simple processing, fast detection and high accuracy Effect

Pending Publication Date: 2022-01-04
TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the above-mentioned problems existing in the prior art, and provide an apple sugar detection device and detection method based on multi-spectral machine learning, which is convenient to solve the problems of complicated operation, difficult carrying and high cost of existing fruit quality non-destructive detection technology

Method used

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  • Apple sugar degree detection device and detection method based on multispectral machine learning
  • Apple sugar degree detection device and detection method based on multispectral machine learning
  • Apple sugar degree detection device and detection method based on multispectral machine learning

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Embodiment 1

[0060] Refer to the accompanying drawings in the manual figure 1 , an apple sugar detection device based on multispectral machine learning, including an acrylic black box 1, a main control circuit board 2, a multispectral sensor 3 and a mobile power supply 4;

[0061] The acrylic black box 1 includes a black box body 101, a black box door 102 and a storage base 103. The black box door 102 is installed on the front side of the black box body 101. When the black box door 102 is closed, it can seal the light path environment and isolate the interference of external light. function, the storage base 103 is fixedly installed at the bottom of the inner cavity of the black box 101, and plays the role of supporting the detection of apples, and the storage base 103 is blackened to avoid affecting the detection spectrum;

[0062] The main control circuit board 2 is installed on the right side of the black box 101, the multispectral sensor 3 is placed in the storage base 103, and is in a...

Embodiment 2

[0068] This embodiment is a further description of Embodiment 1. The light source uses AS7341 multi-spectral sensor chip, and the supplementary light source uses two white bright LEDs. The peak wavelengths of the LEDs are 415nm, 445nm, 480nm, 510nm, 550nm, 590nm, 630nm, 680nm ; The bandwidth is 20nm, the circuit diagram is as follows Figure 5 shown.

Embodiment 3

[0070] This embodiment is a further description of the second embodiment, and the reflection spectrum signals of 8 but not limited to 8 band channels are collected by the multi-spectral sensor 3 .

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Abstract

The invention discloses an apple sugar degree detection device and detection method based on multispectral machine learning. The apple sugar degree detection device comprises an acrylic black box, a main control circuit board, a multispectral sensor and a mobile power supply; the acrylic black box comprises a black box body, a black box door and a storage base, the black box door is installed on the front side face of the black box body, and the storage base is fixedly installed at the bottom of an inner cavity of the black box body; the main control circuit board is installed on the right side face of the black box body, the multispectral sensor is arranged in the storage base and is in an embedded state, the mobile power supply is installed on the top face of the black box body, and the main control circuit board is electrically connected with the mobile power supply and the multispectral sensor. The problems that an existing fruit quality nondestructive testing technology is complex in operation, difficult to carry and high in cost are solved.

Description

technical field [0001] The invention relates to the technical field of fruit detection, in particular to an apple sugar content detection device and detection method based on multispectral machine learning. Background technique [0002] The fruit industry is an important industry in my country's national economic life, and the quality of fruit is directly related to personal life. At present, my country's fruit industry has problems such as low yield per mu, low ratio of export volume to total output, low export price, and low rate of post-harvest commercialization. The key lies in the lack of practicability of existing fruit quality detection technologies. [0003] At present, the non-destructive detection technology of fruit quality mainly uses near-infrared detection technology. Existing near-infrared detection technology analyzes the quality information of fruits based on near-infrared spectroscopy, which requires the use of spectrometer equipment, and spectrometer equi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/25G01N21/41G01N21/47G06N20/00
CPCG01N21/25G01N21/4133G01N21/4738G06N20/00
Inventor 郭古青马成聪李传亮邱选兵
Owner TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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