Open AccessChestnuts quality online detection technology based on acoustics
Author(s) -
He Wang,
Aiyun Wei,
Wuyi Ming,
Haojie Jia,
Zhijun Chen,
Ziqiang Wu
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/768/7/072083
Subject(s) - matlab , computer science , software , process (computing) , quality (philosophy) , acoustics , artificial intelligence , data mining , philosophy , physics , epistemology , programming language , operating system
In order to overcome the influence of various uncertain factors on the quality of chestnuts in the process of manual detection, an online detection method based on acoustics was proposed. In this paper, a multilevel inspection platform for chestnut surface defects based on acoustics is constructed to realize real-time acquisition and measurement of chestnut surface defects. Through acoustic detection, the sound collected from the feature area is converted into a time-frequency map, and image processing was performed using matlab software. At the same time, in the return air detection, the chestnuts with wormholes will produce a return air, which was used as the secondary detection of the chestnuts. This study provides a useful reference for chestnuts quality testing and improves the objectivity and accuracy of chestnuts quality testing.