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Design of Multi-spot Sensor Array Detector for Toxic Gas Based on Spectral Analysis

机译:基于光谱分析的有毒气体多点传感器阵列检测仪设计

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According to the requirement of single-component toxic gases recognition and trace concentration measurement, a novel gas-sensitive sensor array is developed, which chooses metallic porphyrin as sensitive material. Moreover, the multi-spot sensor array detector is designed based on the absorption spectrum measurement and multi-spot measurement. This paper focuses on the structural design of the system and the establishment of the spectral analysis method. The model of after-spectrophotometric structure is adopted by the detector. The entire hardware platform is implemented based on S3C44B0 & uC/OS-II embedded system. In addition, this paper puts forward a recognition model, which combines Principal Component Analysis (PCA) with BP Artificial Neural Networks (BPANN), and an algorithm for trace concentration measurement, based on visible light absorption spectrum analysis. The experimental results show that the correct rate of prediction for 50 unknown samples is 98%, and the maximum relative measuring error is 3%.
机译:根据单组分有毒气体识别和痕量浓度测量的要求,研制了一种新型的气敏传感器阵列,该传感器阵列采用金属卟啉作为敏感材料。此外,基于吸收光谱测量和多点测量设计了多点传感器阵列检测器。本文着重于系统的结构设计和光谱分析方法的建立。检测器采用分光光度结构模型。整个硬件平台是基于S3C44B0和uC / OS-II嵌入式系统实现的。此外,本文提出了一种识别模型,该模型结合了主成分分析(PCA)和BP人工神经网络(BPANN),以及一种基于可见光吸收光谱分析的痕量浓度测量算法。实验结果表明,对50个未知样品的预测正确率为98%,最大相对测量误差为3%。

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