摘要
小麦硬度是评价小麦品质的一项重要指标。对小麦籽粒碰撞发声装置发出的声信号进行频域分析研究,结合使用小波变换与离散余弦变换算法对小麦声音信号进行分析处理,利用小波变换的多分辨率特性及离散余弦变换的能量压缩和解相关能力,提取一些有用的特征参数,分别采用一元和多元线性回归的方法构建不同小麦硬度的声学检测模型。研究结果表明:建立的回归模型的线性相关系数r2可达到0.957。
wheat hardness is an important index for wheat quality evaluation.In this paper,the wheat grain collision objects produce audio test signal analysis,combined with wavelet transform and discrete cosine transform algorithm for wheat audio test signal processing,using the multiresolution feature of wavelet transform and discrete cosine transform energy compression and related ability,extract useful characteristic parameters of linear regression analysis method is adopted to establish the regression model based on these feature parameters.Experiments show that the built model of the linear correlation coefficient can reach 0.957 3.
出处
《农机化研究》
北大核心
2014年第6期10-13,69,共5页
Journal of Agricultural Mechanization Research
基金
"十二五"国家科技支撑计划项目(2013BAD17B04)
关键词
小麦硬度
超声信号
小波变换
离散余弦变换
特征提取
线性回归
wheat hardness
ultrasonic signal
wavelet transform
discrete cosine transform
feature extraction
the linear regression
