【摘要】 声表面波(SAW)传感器阵列具有体积小、功耗低、反应灵敏等优点,在食品检测、环境治理、气体鉴别等领域有广泛的应用前景。结合声表面波传感器阵列的原理及特点,建立和优化了声表面波传感器阵列的数学模型,并对数据进行预处理、主成分分析(PCA)以及BP神经网络分析处理,实现了对气体的鉴别分类,取得了好的实验结果。更多还原

【Abstract】 With the advantages of small size,low power consumption and sensitive response,surface acoustic wave(SAW) sensor array is widely applied in the fields of food testing,environmental governance and gas detection.The mathematical model of the SAW sensor array is presented and optimized according to its principles and characteristics.And the system data preprocessing,principal component analysis(PCA) and the analysis on BP neural network are achieved to make a good identification and classification on gases.更多还原