基于電子鼻的發(fā)酵過程狀態(tài)監(jiān)控研究

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摘要 固態(tài)發(fā)酵技術在我國有著悠久的歷史。然而由于缺少成熟的過程檢測技術，傳統(tǒng)的固態(tài)發(fā)酵技術發(fā)酵過程難以自動化控制，生產質量難以保證。近年來，開始研究使用電子鼻來代替人的嗅覺器官，以達到對固態(tài)發(fā)酵過程中產生氣體的檢測。
本研究以實現(xiàn)固態(tài)發(fā)酵過程檢測為目的，以研究蛋白飼料固態(tài)發(fā)酵過程為對象，開展基于電子鼻技術的固態(tài)發(fā)酵過程檢測應用研究。重點探討了基于電子鼻技術的固態(tài)發(fā)酵過程狀態(tài)模式識別方法。具體工作如下：首先對所提取的電子鼻信號進行主元分析法處理并提取主元變量，然后使用支持向量機結合主元變量建立固態(tài)發(fā)酵過程狀態(tài)的識別模型。
本研究為固態(tài)發(fā)酵過程檢測提供了一條新途徑，該研究成果可以為固態(tài)發(fā)酵過程監(jiān)控儀器裝備的研發(fā)提供基礎。

關鍵詞: 固態(tài)發(fā)酵，電子鼻，過程檢測，PCA，SVM

Monitoring fermentation process using electronic nose
Abstract The technology of solid-state fermentation enjoys a long history in China. The traditional solid-state fermentation process is very difficult to control, as there is no mature technology to the process detection during the fermentation. With the development of biosensor technology, electronic nose is more and more frequently used to replace olfactory organs.

In order to improve the efficiency of process detection and control of solid‒state fermentation (SSF), this work attempted to the feasibility and method of the measurement of process parameters of SSF of protein feed by use of electronic nose.In addition, the pattern recognition of process state of SSF was also focused on by use of electronic nose in this work. The main research points are summarized as follows. With the help of chemometrics analysis,the electronic nose technique was attempted in this work. The feature vectors were extracted by use of PCA, and the number of PCs were optimized by a five‒fold cross‒validation in model calibration. Then,SVM respectively was used to calibrate identification models in order to eva luate the influences of different linear and non‒linear classification algorithms on the classification performance.

This study provides a new idea for the process detection and control of SSF. The results in this work can provide research foundation for developing instruments and equipment for the monitoring of SSF process.

Keywords: solid‒state fermentation; electronic nose; process detection; PCA; SVM目 錄
第一章 緒論 1
1.1課題背景與意義 1
1.1.1研究背景 1
1.1.2研究意義 2
1.2基于電子鼻技術的發(fā)酵過程檢測研究綜述 3
1.2.1電子鼻概述 3
1.2.2電子鼻技術的發(fā)展 4
1.2.3電子鼻技術在各領域中的應用 5
1.2.4電子鼻技術在發(fā)酵過程中的應用 5
1.3本章小結 7
第二章 蛋白飼料固態(tài)發(fā)酵實驗和數據采集 8
2.1材料與方法 8
2.1.1 試驗主要儀器設備 8
2.1.2 試驗材料 8
2.1.3 發(fā)酵試驗 8
2.2電子鼻信號采集 9
2.2.1電子鼻系統(tǒng) 9
2.2.2電子系統(tǒng)鼻數據采集 12
2.3本章小結 12
第三章 基于電子鼻技術的固態(tài)發(fā)酵過程狀態(tài)識別研究 13
3.1電子鼻信號預處理 13
3.2電子鼻信號特征提取 15
3.2.1主成分分析法原理 15
3.2.2主成分分析法的計算步驟 17
3.2.3主成分分析的結果 18
3.3識別模型建立及結果分析 20
3.3.1支持向量機的概述 20
3.3.2 基于支持向量機的固態(tài)發(fā)酵過程狀態(tài)模式識別 21
3.3.3基于支持向量機的固態(tài)發(fā)酵過程狀態(tài)模型結果分析 23
3.4 本章小結 24
第四章 結論與展望 25
4.1主要結論 26
4.2研究展望 26
致 謝 27
參考文獻 29