[关键词]
[摘要]
为实现香油精的快速检测,研制了一套能够实时、准确地进行香油精检测的系统。该系统主要由数据采集部分和数据处理部分组成。数据采集部分采用了气体传感器阵列和上位机结合的方式,数据处理部分用Matlab训练了一个3层BP神经网络。在实验过程中,配制了8个不同比例的香油精样本,用标准样本进行了神经网络的训练,测试样本进行了验证。该系统为香油精的快速检测方法的研究提供了依据,据有一定的实用价值。
[Key word]
[Abstract]
For the rapid detection of sesame oil flavoring, a real-time and accurate detection of sesame oil flavoring system was developed. The system mainly consists of the data acquisition part and data processing components. The data acquisition part included gas sensor and the host computer; data processing part include a three-layer BP neural network which was trained in Matlab. During the experiment, 8 samples of sesame oil flavoring with different proportions and the standard samples were prepared for the neural network training. The test samples were verified. The system provided a basis method for the rapid detection of sesame oil flavoring.
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