基于气体传感器阵列的气味识别系统的研制及应用

发布时间：2018-03-27 09:14

本文选题：气味识别　切入点：气体传感器阵列　出处：《深圳大学》2017年硕士论文

【摘要】：气味识别作为人工智能的研究方向之一,可用作移动机器人的嗅觉感知器,具有非常潜在的应用前景。本文实现了一个基于气体传感器阵列的气味识别系统,该系统还包括信号调理电路,信号获取模块,数据处理软件。本文还阐述了可应用于气味识别的数据的预处理,训练过程和识别方法,并都在数据处理软件中得到了实现。用户可在智能手机上安装该数据处理软件,通过蓝牙接收信号获取模块传来的感知数据,查看传感器的电阻和电压,观看气体传感器的实时响应曲线,训练气味类别,识别未知的气味的类别,记录气体传感器的响应数据并能够回放响应的过程。最后为了尝试验证该系统的识别能力及应用,我们举了几个例子包括日常生活中的各种常见的气味的辨识,苹果成熟度的区分,空气质量状态的判断以及食物新鲜度的评估。结合实验数据进行预处理,气味训练,气味识别,得到处理后的实验结果表明该系统可正确识别不同的气味类别。该系统还可被应用于特定环境(如智能家居和工业生产场所)下的污染气体的全天候监测。该系统具有低成本、便携性、可结合智能手机进行信息处理的特点,使其更具有实用性和通用性。
[Abstract]:As one of the research directions of artificial intelligence, odor recognition can be used as the olfactory sensor of mobile robot, and has a very potential application prospect. In this paper, a scent recognition system based on gas sensor array is implemented. The system also includes signal conditioning circuit, signal acquisition module and data processing software. The user can install the data processing software on the smart phone, obtain the perceptual data from the module through Bluetooth receiving signal, and check the resistance and voltage of the sensor. Watch the real-time response curve of the gas sensor, train the smell category, identify the unknown smell category, record the response data of the gas sensor and be able to play back the response. Finally, to try to verify the recognition ability and application of the system, We gave several examples, including the identification of common odors in everyday life, the differentiation of apple maturity, the assessment of air quality status, and the assessment of food freshness. Smell recognition, The experimental results show that the system can correctly identify different odor categories. The system can also be applied to the all-weather monitoring of polluting gases in specific environments (such as smart homes and industrial production sites). Portability, combined with the characteristics of smart phone information processing, makes it more practical and universal.
【学位授予单位】：深圳大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TP18

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