电子鼻技术及其在服装领域的应用

电子鼻作为一种由传感器阵列和模式识别系统组成,能够快速检测单一或复杂气体分子的智能设备,它的相关应用研究已在食物仓储、医学诊断、环境监测、农业生产、军事工程等多个领域展开,但该技术在纺织服装行业的应用并不广泛。文章对电子鼻技术的发展原理、传感器阵列、模式识别方法等作一简述,介绍了电子鼻在织物及服装异味检测、气味识别,品质评价以及人体异味监测等最新应用的研究进展,并对其未来发展趋势进行展望。     

电子鼻系统及其在谷物检测中的应用进展

电子鼻技术是近年来迅速发展的气味检测技术之一,可应用于目前以食品安全为背景下的粮食储藏品质评价、农畜产品新鲜度检测和酒类鉴别等研究领域,属于食品工业中无损检测方法。针对国内外电子鼻技术在谷物研究中的应用现状,全文综述了电子鼻的起源、构成、气体传感器阵列和模式识别分析方法等内容,重点介绍从1997年至今,国内外利用电子鼻在谷物检测中的主要研究方向及有关研究结论。最后提出电子鼻的广阔应用前景,希望能为今后的相关研究提供参考依据。     

电子鼻无损检测柑橘成熟度的实验研究

电子鼻技术在水果的无损检测中得到了不断的研究与发展。文中运用电子鼻对柑橘的成熟度进行了无损检测分析,建立了电子鼻响应与成熟度之间的关系,证明了建立在化学传感器和模式识别软件上的电子鼻能够检测区分不同成熟度的柑橘。同时,研究表明电子鼻传感器阵列可以得到进一步的优化,文中也为这种优化提供了一个具体的实例,这为进一步进行电子鼻的检测商业化提供一个依据。     

电子鼻在食品微生物污染快速检测中的应用

世界上大部分的消费食品都受到微生物污染的影响。常用的微生物检测和鉴别方法存在一些缺点,不适用于食品的快速筛查。近年来,电子鼻为包括微生物污染诊断在内的食品品质与安全分析提供了有价值的分析手段。本文介绍了电子鼻的三个组成部分(气体采样单元、气敏传感器阵列、信号处理与模式识别系统),综述了电子鼻对食品中常见的细菌、霉菌、酵母和毒素等四种微生物污染类型的检测,最后对电子鼻的发展趋势和前景进行了展望。     

基于电子鼻技术的烟丝霉变检测

霉变是影响烟丝质量的重要因素之一,研究探索建立基于电子鼻技术的烟丝霉变检测方法。构建的电子鼻系统主要由5只SnO2半导体气敏传感器形成反应阵列,采用BP神经网络(back propagation neural network,BPNN)为主的模式识别方法。从每个传感器响应曲线中提取2个特征值,使用主成分分析和BP神经网络对传感器阵列的所有特征值进行处理。主成分分析结果显示:非霉变烟丝和霉变烟丝存在可区分趋势,但不同霉变程度的烟丝间存在部分重叠。进一步利用BP神经网络对霉变烟丝判别,识别正确率达到90.00%。试验表明,使用电子鼻技术可以客观、有效地区分霉变和非霉变烟丝,为有效控制烟丝质量提供了可靠途径。     

电子鼻及其在食品感官分析中的应用

电子鼻是以模拟人的嗅觉为基本原理,用来对食品中复杂嗅味和挥发性成分进行分析、识别和检测仪器,由气体传感器、信号处理和模式识别系统等组成。介绍了电子鼻的基本组成和原理,综述了电子鼻技术在茶叶、葡萄酒、肉类等食品中的感官评价方面的应用现状与发展趋势。     

电子舌在乳制品质量控制中的应用

电子舌技术是20世纪80年代中期发展起来的一种新型的检测液体味觉特征的手段,它主要由传感器阵列、信号处理和模式识别系统组成。主要介绍了目前国内外电子舌在乳制品中应用现状,重点阐述了电子舌在乳制品质量控制中的研究进展,并对电子舌的发展趋势和前景进行展望。     

LDA优化电子鼻传感器阵列的研究

利用PEN3电子鼻系统对6个糖酸比不同的乳饮料样品进行检测,采用线性判别分析(LDA)对传感器响应值进行分析,确定优化传感器阵列方法,并将各优化结果进行对比,最终确定阵列优化结果,使电子鼻可以用更少的传感器达到更好的分类效果,为电子鼻传感器阵列优化提供了新的思路和方法。     

仿生电子鼻及其在食品工业中的应用研究

电子鼻是一种模拟生物嗅觉工作原理的新颖仿生检测仪器,通常由一定选择性的交叉敏感的电化学传感器阵列、数据处理系统以及适当的模式识别装置所组成,能够检测、分析和鉴别简单、复杂气味和大多数挥发性成分.文章综述和比较生物嗅觉和人工嗅觉的信息处理机制,概述电子鼻的发展历程,着重介绍电子鼻在食品工业中的应用研究进展,并对电子鼻的发展瓶颈及发展前景进行分析.     

电子鼻技术在肉类品质应用中快速分析初探

电子鼻技术是近年发展起来的一种新型仿生嗅觉检测技术,因其具备快速、无损等优点被广泛应用于食品品质检测领域。电子鼻通常包括两部分:硬件部分——多个性能彼此重叠的气体传感器;软件部分——恰当的模式识别技术对采集信号的分析、处理。本文主要综述了近年来国内外电子鼻技术在肉类品质分析中的应用。首先阐述了电子鼻技术工作原理、数据处理方法,随后重点讨论了电子鼻技术在肉类新鲜度评定、肉与肉制品品质区分、肉类有害成分监测、肉类掺假检测等4个方面的应用进展,最后对电子鼻技术目前存在的问题及未来发展趋势进行了简要探讨。     

Array of Different Polyaniline-Based Sensors for Detection of Volatile Compounds in Gummy Candy

Aroma in foodstuff is considered an essential attribute since it is closely related to the consumer acceptance of foodstuffs. Electronic nose (e-nose) system is composed by an array of gas sensor and has emerged as a promising alternative for the aroma volatile compounds recognition. In this study, a lab-made e-nose system comprising of an array of different polyaniline-based sensors has been used for aroma discrimination (apple, strawberry, and grape) in gummy candy. The sensor array was comprised by interdigitated graphite electrodes, using tracing paper substrate and sensitive layer of polyaniline (Pani) obtained by in situ and interfacial synthesis deposited by the in situ adsorption polymerization of aniline and layer-by-layer (LbL) methods. The sensors were characterized in relation to humidity and the Pani-in situ/PSS LbL layer presenting the higher sensitivity, a quite interesting feature for its use as a gas sensor. It has been demonstrated that the lab-made e-nose has been highly efficient in the discrimination of different concentrations of aromas added to gummy candies with excellent sensitivity and a limit of detection in the range of parts-per-billion, so demonstrated the applicability in food matrices.     

The measurement of the responses to different odour intensities of `boar taint' using a sensory panel and an electronic nose

This study explored the possibility of using an electronic nose (e-nose) with a 12-conducting-polymer sensor array combined with pattern recognition routines to discriminate between varying intensities of boar taint. A set of samples in a model system comprising a neutral lipid base containing varying combinations of androstenone and skatole were tested, as were pork fat samples. The e-nose responses for pork fat were calibrated against those given by a trained 10-member sensory panel for abnormal odour of the same samples from a total of 60 Large White cross-bred pigs. The e-nose responses related strongly to those of the sensory panel with a significant (p<0·01) canonical correlation of 0·78. The data set was used to develop a discriminant function for grouping pork samples into three `response classes': normal, doubtful and abnormal. Based on this, the e-nose identified all the abnormal samples correctly. However, 16% of the normal samples were also classified as abnormal. It was concluded that, in general, the electronic nose can discriminate between different levels of boar taint and that although a high specificity of sensors to androstenone and skatole may be desirable it may not be entirely important to the development and configuration of a boar taint sensor array.     

电子鼻技术及在乳制品中的应用研究进展

介绍了电子鼻的基本组成及工作原理；并从电子鼻系统的角度叙述了传感器技术和模式识别技术的发展现状及趋势；综述了电子鼻在乳制品识别中的应用。主要包括不同保质期的牛奶的识别，以及不同产地不同风味奶酪的鉴别，细菌检测和生产过程监控；最后展望了电子鼻在乳制品中的应用前景及其存在的问题。     

电子舌在食品感官品评中的应用

电子舌是以人类味觉感受机理为基础研究开发的一种新型现代化分析检测仪器,通过传感器阵列代替生物味觉味蕾细胞感测检测对象,经系统的模式识别方法得到结果.本文介绍电子舌技术的结构特点及目前研究现状,并综述电子舌在初级农产品分级,茶、酒、饮料等食品感官品质鉴别方面的研究进展.     

光纤彩色读图系统

研制出用光导纤维作传感器的数字式彩色读图系统.光纤传感器检测图案的彩色信息转换成数字信号并传递给彼处理机进行处理.整个系境由MCS-51单片机控制.     

电子舌在食品加工在线检测中的应用研究

电子舌模拟人的味觉器官，是一种分析、识别液体“味道”的新型检测手段。主要由传感器阵列和模式识别系统组成。介绍了电子舌的结构和工作原理，并重点介绍了电子舌在乳品、饮料等食品加工在线检测中的应用。     

A Gaussian-based kernel Fisher discriminant analysis for electronic nose data and applications in spirit and vinegar classification

Fisher discriminant analysis (FDA) is a very useful pattern recognition technique widely used in electronic nose system (e-nose). However, due to its linear characteristic, the classification problems of multi-class and high-dimensional e-nose data cannot be handled effectively. Therefore, a Gaussian-based kernel FDA (KFDA) method is proposed to solve multi-class and high-dimensional classification problems of complex samples such as food classification using e-nose. The key point of the method is how to determine the Gaussian kernel parameter. Firstly, according to distance discriminant analysis viewpoint, a desired kernel matrix adapted to Gaussian kernel function can be given successfully. Secondly, an evaluation function based on Euclidean distance is established for measuring the degree of approximation between actual kernel matrix containing an unknown Gaussian kernel parameter and the desired kernel matrix so as to get an optimal solution of the parameter, and then the actual kernel matrix can be definitely determined. Finally, the principal component analysis (PCA) for the actual kernel matrix is carried out. Meanwhile, FDA for the principal component matrix generated by PCA is also implemented in succession, and the KFDA is completed. Six kinds of Chinese spirit and six kinds of Chinese vinegar samples as two classification applications were respectively carried out accurately with the KFDA method; and the KFDA method is tested to be very simple and effective. The KFDA method may be promising for complex samples classification dataset of e-nose.     

Intelligent clothing for automated recognition of human physical activities in free-living environment

This paper presents an intelligent clothing framework for human daily activity recognition using a single waist-worn tri-axial accelerometer sensor coupled with a robust pattern recognition system. The activity recognition algorithm is realized to distinguish six different physical activities through three major steps: acceleration signal collection/pre-processing, wavelet-based principle component analysis, and a support vector machine classifier. The proposed activity recognition method has been experimentally validated through two batches of trials with an overall mean classification accuracy of 95.25 and 94.87%, respectively. These results suggest that the intelligent clothing is not only able to learn the activity patterns but also capable of generalizing new data from both known and unknown subjects. This enables the proposed intelligent clothing to be applied in a comfortable and in situ assessment of human physical activities, which would open up new market segments to the textile industry.     

电子舌技术在饮料识别中的应用

电子舌技术是一种分析、识别液体味道的新型检测手段,在饮料识别中的应用日益广泛。介绍了电子舌技术的基本原理,综述了电子舌在饮料识别中的应用,展望了电子舌技术在饮料识别中的发展趋势和应用前景,并指出了电子舌技术在实现过程中所需要解决的问题。     

地理标志大米的仿生电子鼻分类识别

为了对地理标志大米进行原产地保护,采用PEN3电子鼻,分析样品质量、项空空间及静置时间等试验参数对电子鼻传感器响应值影响,结合主成分分析(PCA)和线性判别分析(LDA)方法对3个不同地理标志大米进行识别研究。结果表明:选取50 g样品,以50 mL顶空空间、静置1 h测得的电子鼻响应值最佳;PCA法可以区分不同地域的大米,也可以区分不同品种大米,LDA法也可以区分不同地域的大米,但不能区分不同品种的大米。运用电子鼻可以将地理标志大米进行较好的区分,为电子鼻技术应用于大米产地溯源提供理论基础。