An intelligent detection system for wood quality based on industrial big data image analysis

Abstract

The invention discloses an intelligent wood quality detection system based on industrial big data image analysis, including an image acquisition module, an image processing module, a wood grain area detection module, a wood grain area analysis module, a weight detection module, a weight analysis module, and a gas detection module , a gas analysis module, an analysis server, a display terminal and a storage database; the present invention analyzes the types of wood through the image acquisition module and the image processing module, and at the same time through the wood grain area detection module and the wood grain area analysis module combined with the analysis server to comprehensively analyze each The strength grade of the wood, and the relevant personnel will mark the corresponding strength grade of each wood, and at the same time detect the weight of each wood and the concentration of decaying gas leaked, calculate the comprehensive quality influence coefficient of each wood, and compare and judge whether the quality of each wood is qualified , to display the number of unqualified wood, and carry out waste treatment, thus ensuring the quality of wood.

Description

technical field [0001] The invention relates to the field of industrial wood quality detection, and relates to an intelligent wood quality detection system based on industrial big data image analysis. Background technique [0002] There is a large demand for wood in my country, and wood grain area, decay and moisture content will affect the quality of wood, and then affect the use of wood. In order to effectively use wood resources, it is necessary to test the quality of wood to maximize economic benefits. [0003] However, there are some deficiencies in the existing wood quality detection technology. The traditional wood quality detection mainly relies on manual visual inspection to judge the type of wood by visually observing the color of the wood. However, the manual detection standards are different, resulting in misjudgment of the type. The increase will affect the quality of the wood. The strength of the wood cannot be accurately judged through manual experience, and t...

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Problems solved by technology

[0003] However, there are some deficiencies in the existing wood quality detection technology. The traditional wood quality detection mainly relies on manual visual inspection to judge the type of wood by visually observing the color of the wood. However, the manual detection standards are different, resulting in misjudgment of the type. The increase will affect the quality of the wood. The strength of the wood cannot be accurately judged through manual experience, and the dryness of the wood cannot be detected. The volume of the wet wood will become smaller after losing water, resulting in cracking and warping of the wood, resulting in economic property losses and The concentration of decaying gas emitted by wood is detected by artificial smell, which is not only labor-intensive, it is easy to cause physical fatigue for a long time, and affects the detection accuracy, and the efficiency of manual detection is still very low. In order to solve the above problems, an industrial large-scale Wood quality intelligent detection system based on data image analysis

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