DETECTION AND IDENTIFICATION OF STORED-GRAIN INSECTS WITH RF/MICROWAVE AND NEURAL NETWORK TECHNOLOGY

被引：1

作者：

Ding, F. ^{[1
]}

Jones, C. L. ^{[1
]}

Weckler, P. ^{[1
]}

机构：

[1] Oklahoma State Univ, Dept Biosyst & Agr Engn, Stillwater, OK 74078 USA

来源：

TRANSACTIONS OF THE ASABE | 2009年 / 52卷 / 06期

关键词：

Detection; Identification and classification; Neural network; Radio frequency and microwave; Sensing; Stored-grain insects; INDEPENDENT MOISTURE DETERMINATION; MICROWAVE DIELECTRIC-PROPERTIES; NEAR-INFRARED SPECTROSCOPY; MACHINE VISION; WHEAT KERNELS; RF IMPEDANCE; FREQUENCIES; SOYBEANS; PEANUTS; BIOMASS;

D O I：

暂无

中图分类号：

S2 [农业工程];

学科分类号：

0828 ;

摘要：

Eight different species of stored-grain insects were investigated in the radio frequency (RF) and microwave frequency range of 0.3 to 1200 MHz with a free-space device using a vector network analyzer. Detection and identification analysis were performed using neural network techniques. One-, two- and three-waveband sets were optimized in the frequency range to maximize the detection and identification recognition rate. The total recognition rate of identification for the insects was 73%, while the recognition rate of the detection of the empty device was 76% using the frequencies of 180.3, 1020, and 1032 MHz.

引用

页码：2105 / 2114

页数：10

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