小波分析在活蛹缫丝单根蚕丝颣节检测中的应用

Application of Wavelet Analysis in Detection of Single Silk's Coarse Points During Live Cocoon Reeling

小波分析是应用数学和工程学科领域发展的一项新技术,广泛应用于信号处理。针对家蚕新品种选育中活蛹缫丝单根蚕丝颣节信号出现的特征,采用小波分析方法对其进行有效检测。检测原理是:将单根蚕丝信号进行小波分解,利用小波域阈值滤波方法抑制噪声信号提高检测效率及抗干扰能力,利用小波在奇异性检测上的优势找出单根蚕丝检测信号中的突变点,再根据相对应的时域信号进行颣节信号检测。针对小波分析在信号分析和信号消噪处理中的应用建立了matlab仿真模型,将基于小波分析的传感器安装在ZHJ-20智能型活蛹缫丝机上,使单根蚕丝颣节的检测速度较传统人工肉眼检测方法提高2倍以上,检测数据误差值小于企业标准中的误差值。建立的用于活蛹缫丝单根蚕丝颣节检测的小波分析方法,具有数据处理速度快,检测结果准确的特点。

Wavelet analysis is a new technology developed from applied mathematics and engineering discipline and has been widely used in signal processing. An effective detection method by using wavelet analysis was established based on the characteristics of single silk＇s coarse point signal during live cocoon reeling which is commonly used in breeding of new silkworm varieties. The principle of this detection method was as follows, to decompose the single silk＇s signal by wavelet analysis; to suppress the noise signal by threshold filtering method to improve the detecting efficiency and anti-jamming ability; to find mutation points in the single silk signal by making use of singularity detection in the wavelet analysis; and to detect the coarse point according to correspondent time-domain signal, Matlab simulation model was constructed based on the application of wavelet analysis in signal analysis and signal de-noising processing. Using ZHJ-20 intelligent live cocoon reeling machine with the sensor based on the theory of wavelet analysis, the detecting rate of coarse points was 2 times to that of traditional method, and the error value of detecting data was lower than that of the enterprise standard. The established detecting method has the features of high speed data processing and accurate detection.