Wood quality intelligent detection system based on industrial big data image analysis

Abstract

The invention discloses a wood quality intelligent detection system based on industrial big data image analysis. The wood quality intelligent detection system comprises an image acquisition module, animage processing module, a wood grain area detection module, a wood grain area analysis module, a weight detection module, a weight analysis module, a gas detection module, a gas analysis module, ananalysis server, a display terminal and a storage database. According to the invention, the image acquisition module and the image processing module are used for analyzing the types of woods; meanwhile, the wood grain area detection module and the wood grain area analysis module are combined with the analysis server to comprehensively analyze the strength grade of each piece of wood; correspondingstrength grade marking is carried out on each piece of wood through related personnel; meanwhile, the weight of each piece of wood and the concentration value of leaked rotten gas are detected, the comprehensive quality influence coefficient of each piece of wood is calculated, whether the quality of each piece of wood is qualified or not is judged through comparison, the number of unqualified wood is displayed, waste treatment is conducted, and therefore the quality of the wood is guaranteed.

Description

technical field [0001] The invention relates to the field of industrial wood quality detection, and relates to a wood quality intelligent 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 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 ...

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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 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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