检索结果-内蒙古大学图书馆

Identification and quantification of individual volatile organic compounds in a binary mixture by SAW multisensor array and pattern recognition analysis

引用

MEASUREMENT SCIENCE AND TECHNOLOGY 2002年第6期13卷 846-858页

作者： Penza, M Cassano, G Tortorella, F ENEA CR Brindisi Mat & New Technol Unit I-72100 Brindisi Italy PASTIS CNRSM SCpA I-72100 Brindisi Italy

We have developed a surface acoustic wave (SAW) multisensor array with five acoustic sensing elements configured as two-port resonator 433.92 MHz oscillators and a reference SAW element to recognize different individual components and determine their concentrations in a binary mixture of volatile organic compounds (VOCs) such as methanol and acetone, in the ranges 15-130 and 50-250 ppm, respectively. The SAW sensors have been specifically coated by various sensing thin films such as arachidic acid, carbowax, behenic acid, triethanolamine or acrylated polysiloxane, operating at room temperature. By using the relative frequency change as the output signal of the SAW multisensor array with an artificial neural network (ANN), a recognition system has been realized for the identification and quantification of tested VOCs. The features of the SAW multisensor array exposed to a binary component organic mixture of methanol and acetone have been extracted from the output signals of five SAW sensors by pattern recognition (PARC) techniques, such as principal component analysis (PCA). An organic vapour pattern classifier has been implemented by using a multilayer neural network with a backpropagation learning algorithm. The normalized responses of a reduced set of SAW sensors or selected principal components scores have been used as inputs for a feed-forward multilayer perceptron (MLP), resulting in a 70% correct recognition rate with the normalized responses of the four SAW sensors and in an enhanced 80% correct recognition rate with the first two principal components of the original data consisting of the normalized responses of the four SAW sensors. The prediction of the individual vapour concentrations has been tackled with PCA for features extraction and by using the first two principal components scores as inputs to a feed-forward MLP consisting of a gating network, which decides which of three specific subnets should be used to determine the output concentration: the fi

关键词： SAW chemical sensors multisensor array volatile organic compounds binary mixture pattern recognition principal component analysis artificial neural networks

来源：评论

学校读者我要写书评

暂无评论

Toward a Miniature Wireless Integrated multisensor Microsystem for Industrial and Biomedical Applications

引用

IEEE SENSORS JOURNAL 2002年第6期2卷 628-635页

作者： Tang, Tong Boon Johannessen, Erik A. Wang, Lei Astaras, Alexander Ahmadian, Mansour Murray, Alan F. Cooper, Jonathan M. Beaumont, Steve P. Flynn, Brian W. Cumming, David R. S. Univ Edinburgh Sch Engn & Elect Edinburgh EH9 3JL Midlothian Scotland Univ Glasgow Dept Elect & Elect Engn Glasgow G12 8LT Lanark Scotland Alba Ctr Inst Syst Level Integrat Livingston EH54 7EG Scotland

This paper presents our work toward the integration of a multisensor microsystem with wireless communication, using system-on-chip (SoC) methodology. Four different forms of microelectronic sensors have been fabricated on two separate 5 x 5 mm(2) silicon chips measuring pH, conductivity, dissolved oxygen concentration, and temperature. The sensors are integrated with a sensor fusion chip comprising analog circuitry for sensor operation and signal amplification prior to digital decoding and transmission. The microsystem prototype will be packaged in a miniature capsule, which measures 16 mm x 55 mm including batteries and dissipates 6.3 mW for a minimal life cycle of 12 h.

关键词： Laboratory-on-a-chip (LoC) microsystem multisensor array system-on-chip (SoC) wireless communication

来源：评论

学校读者我要写书评

暂无评论

Estimation of biomass and specific growth rate in a recombinant Escherichia coli batch cultivation process using a chemical multisensor array

引用

JOURNAL OF BIOTECHNOLOGY 1998年第1-2期60卷 55-66页

作者： Bachinger, T Mårtensson, P Mandenius, CF Linkoping Univ Dept Phys & Measurement Technol Appl Phys Lab S-58183 Linkoping Sweden Linkoping Univ Dept Phys & Measurement Technol Swedish Sensor Ctr S-58183 Linkoping Sweden

A chemical multisensor array is used in combination with an artificial neural network to estimate the biomass concentration and specific growth rate in a recombinant Escherichia coli batch cultivation. It is shown that by providing sufficient information to the artificial neural network, an accuracy comparable to that of an established dry weight method can be achieved. The obtained prediction error (1 sigma) of 0.043 g 1(-1) for biomass compares well with the error of the dry weight method in this low biomass concentration range (0.1-3 g 1(-1)). The prediction for the specific growth rate is accurate during important parts of the cell growth (1 sigma = 0.025 h(-1)). The results show that this non-invasive method is potentially useful for estimating biomass and specific growth rate on-line in bioprocesses. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： multisensor array biomass specific growth rate Escherichia coli

来源：评论

学校读者我要写书评

暂无评论

Classification of odour samples from multisensor array using new linguistic fuzzy method

引用

ELECTRONICS LETTERS 1998年第23期34卷 2229-2231页

作者： Lazzerini, B Maggiore, A Marcelloni, F Univ Pisa Dipartimento Ingn Informaz I-56126 Pisa Italy

A new method for the fuzzy classification of odour samples that are obtained from an array of conducting polymer sensors is proposed. Linguistic expressions describing the response of both individual sensors and the sensor array to each chemical are derived from a fuzzy model of the sensor data. Experimental results confirming the proposed method are also included.

关键词： gas sensors Chemical variables measurement BAF model multisensor array array signal processing fuzzy set theory conducting polymers linguistic method computational linguistics fuzzy classification odour sample signal classification Signal processing and detection sensor fusion Chemical sensors conducting polymer sensor

来源：评论

学校读者我要写书评

暂无评论

A multisensor array for visualizing continuous state transitions in biopharmaceutical processes using principal component analysis

引用

BIOSENSORS & BIOELECTRONICS 1998年第2期13卷 193-199页

作者： Mandenius, CF Hagman, A Dunas, F Sundgren, H Lundstrom, I Linkoping Univ Appl Phys Lab S-58183 Linkoping Sweden Linkoping Univ Swedish Sensor Ctr S SENCE S-58183 Linkoping Sweden Pharm & UpJohn S-11287 Stockholm Sweden

An array of sensors with varying sensitivities, a so-called multisensor array, has been used for monitoring the growth and production states of biopharmaceutical processes. The sensor array produced continuous and characteristic response patterns from the processes due to the differences of the sensors. By analysing these patterns with the multivariate method principal component analysis, the state as well as the change of state of the bioprocesses could be visualized. The sensors used in the array were well-known semiconductor and optical gas sensors and the array was connected in an on-line set-up to the bioreactor's headspace effluent. The sensor array was applied to the monitoring of two recombinant bioprocesses, the production of human growth hormone in Escherichia coli and human factor VIII in Chinese ovary hamster cells. The sensor array could clearly visualize the characteristic transitions during the main growth or production phases of these two bioprocesses. (C) 1998 Elsevier Science S.A. All rights reserved.

关键词： bioprocess monitoring multisensor array recombinant growth hormone recombinant factor VIII principal component analysis

来源：评论

学校读者我要写书评

暂无评论

A flow injection system based on chalcogenide glass sensors for the determination of heavy metals

引用

ANALYTICA CHIMICA ACTA 2000年第1-2期403卷 273-277页

作者： Mortensen, J Legin, A Ipatov, A Rudnitskaya, A Vlasov, Y Hjuler, K Roskilde Univ Dept Chem & Life Sci DK-4000 Roskilde Denmark St Petersburg State Univ Lab Chem Sensors Pitersburg Russia Dk TEKNIK Energy & Environm Copenhagen Denmark

A flow injection set-up for the determination of Pb(II), Cr(VI), Cu(II), Cd(II) using chalcogenide glass chemical sensors (electrodes) is presented. Seven electrodes are used to determine the four metals and also chloride ions and the signals are analysed using multivariate analysis method, including artificial neural networks. The background solution is 1 M nitric acid. It is divided in two Lines where the first one is mixed with 1.2 M sodium acetate and the other one is 1 M nitric acid. The Hg(II), Cr(VI) and Ag(I) sensors are placed in the acid line while the Pb(II), Tl(I), Cd(II) and Cu(II) electrodes are placed in the buffered line. The detection limit for Pb(II) was about 3 mu M and about 1 mu M for the other metals. In our system chloride can be determined down to about 1 mu M alone and 20 mu M simultaneously with the other species. The average error for the determination of the metals in the range from the detection limit up to about 3 mM was 10-15% for Pb(II), Cr(VI), Cu(II) and Cd(II) and about 30% for Cl-. The parameters for the flow injection system were: flow rate 0.5 ml/min and sample Volume 500 mu l. The peak widths were 100-300 s allowing a theoretical measurement rate of 15 per hour. In practice, sampling rates of about 7-10 times per hour are realistic. The system is developed as a step forward to on-line measurements of exhaust gases from waste incineration plants. (C) 2000 Elsevier Science B.V. All rights reserved.

关键词： flow injection chalcogenide glass sensors multisensor array gas emission control

来源：评论

学校读者我要写书评

暂无评论

Searching for process information in the aroma of cell cultures

引用

TRENDS IN BIOTECHNOLOGY 2000年第12期18卷 494-500页

作者： Bachinger, T Mandenius, CF Linkoping Univ Swedish Senor S-58183 Linkoping Sweden Linkoping Univ Div Biotechnol S-58183 Linkoping Sweden

Aroma emissions from living cells can provide valuable information about the metabolic and physiological condition of those cells. Electronic noses are chemical gas-sensor arrays that use artificial neural network models to evaluate aromas. They can interpret the complex aroma information emitted from cultures of bacteria, yeast cells and animal cells. Potential applications for electronic noses range from medical diagnosis to industrial bioprocessing.

关键词： electronic nose bioreactor monitoring bioprocess monitoring artificial nose multisensor array

来源：评论

学校读者我要写书评

暂无评论

Sensor fusion with on‐line gas emission multisensor arrays and standard process measuring devices in baker's yeast manufacturing process

引用

Biotechnology and Bioengineering 2000年第2期55卷

作者： C.‐F. Mandenius T. Eklöv I. Lundström Laboratory of Applied Physics and Swedish Sensor Centre Department of Physics and Measurement Technology Linköping University S‐581 83 Linköping Sweden telephone: 46 (13) 288967 fax: 46 (13) 288969

The use of a multisensor array for measuring the emission from a production‐scale baker's yeast manufacturing process is reported. The sensor array, containing 14 different gas‐sensitive semiconductor devices and an infrared gas sensor, was used to monitor the gas emission from a yeast culture bioreactor during fed‐batch operation. The signal pattern from the sensors was evaluated in relation to two key process variables, the cell mass and the ethanol concentrations. Fusion with the on‐line sensor signals for reactor weight and aeration rate made it possible to estimate cell mass and ethanol concentration using computation with backpropagating artificial neural nets. Identification of process states with the same fusion of sensor signals was realized using principal component analysis. © 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 55 : 427–438, 1997.

关键词： multisensor array baker's yeast sensor fusion

来源：评论

学校读者我要写书评

暂无评论

Sensor fusion with on-line gas emission multisensor arrays and standard process measuring devices in baker's yeast manufacturing process

引用

BIOTECHNOLOGY AND BIOENGINEERING 1997年第2期55卷 427-438页

作者： Mandenius, CF Eklov, T Lundstrom, I LINKOPING UNIV DEPT PHYS & MEASUREMENT TECHNOLSWEDISH SENSOR CTRS-58183 LINKOPINGSWEDEN

The use of a multisensor array for measuring the emission from a production-scale baker's yeast manufacturing process is reported. The sensor array, containing 14 different gas-sensitive semiconductor devices and an infrared gas sensor, was used to monitor the gas emission from a yeast culture bioreactor during fed-batch operation. The signal pattern from the sensors was evaluated in relation to two key process variables, the cell mass and the ethanol concentrations. Fusion with the on-line sensor signals for reactor weight and aeration rate made it possible to estimate cell mass and ethanol concentration using computation with backpropagating artificial neural nets. identification of process states with the same fusion of sensor signals was realized using principal component analysis. (C) 1997 John Wiley & Sons, Inc.

关键词： multisensor array baker's yeast sensor fusion

来源：评论

学校读者我要写书评

暂无评论

Adaptive resonance theory based neural network for supervised chemical pattern recognition (FuzzyARTMAP) .2. Classification of post-consumer plastics by remote NIR spectroscopy using an InGaAs diode array

引用

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 1996年第2期32卷 165-176页

作者： Wienke, D vandenBroek, W Buydens, L HuthFehre, T Feldhoff, R Kantimm, T Cammann, K INST CHEM & BIOCHEM SENSOR RES MUNSTER D-48149 MUNSTERGERMANY

The supervised working FuzzyARTMAP pattern recognition algorithm has been applied to automated identification of post-consumer plastics by near-infrared spectroscopy (NIRS). Experimentally, a remote operating parallel multisensor device, based on a rapid InGaAs diode array detector combined with new collimation optics, has been used. The laboratory setup allows on-line identification of more than 100 spectra per second. Internal parameter settings of FuzzyARTMAP were varied to explore their influence on the classifier's behavior. Discrimination results obtained were better than those from an optimized multilayer feedforward backpropagation artificial neural network (MLF-BP) and significantly better than those provided by the partial least squares method (PLS2). Additional advantages of FuzzyARTMAP compared to these two classifiers are a significantly higher speed of calibration, the chemical interpretability of network weight coefficients and a built-in detector against extrapolations.

关键词： artificial neural networks adaptive resonance theory (ART) fuzzy set theory pattern recognition plastics recycling near-infrared spectroscopy multisensor array

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：