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Quality Detection of Damaged Bean Kernels by Acoustic Signal Analysis Method
Author: WuXiaoChen
Tutor: LiuJieHui
School: Nanjing University
Course: Electronics and Communication Engineering
Keywords: Moisture content Impaired Acoustic signal analysis Characteristic quantities
CLC: O429
Type: Master's thesis
Year: 2011
Downloads: 18
Quote: 0
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Abstract
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Food security has been subject to the threat of several different ways , such as infestation rupture . Meanwhile , the moisture content of the basic indicators of the evaluation of food quality . Currently, there are a number of methods can be used to detect the moisture content of the food particles or damaged condition , but these methods or slow or labor-intensive or too costly and not widely applicable , the purpose of this paper is to study and explore a use of food particles impact sound to determine food quality acoustic methods . This selection of soybean , for example, using the microphone collected the soybeans particles issued impact sounds fall from height on the polished stainless steel block , based on matlab filtering the sound signal preprocessing , extraction time domain fitting parameters of the acoustic signal , the sound intensity , spectral energy , spectral peaks characteristic value to describe the signal . The method of application of multiple linear regression , binomial regression and neural network to conduct a comprehensive analysis . The results showed that: a strong correlation exists between the fitting parameters of the acoustic signal , the intensity , spectral energy and spectral peak feature value and the moisture content of the soybean particles or the degree of injury . Using these characteristics can be more accurate determination of the rate and extent of the damage of the water content of the soybean particles .
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CLC: > Mathematical sciences and chemical > Physics > Acoustics > Applied Acoustics
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