Protea Ltd

Crewe, United Kingdom

Protea Ltd

Crewe, United Kingdom
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Ziyatdinov A.,Polytechnic University of Catalonia | Ziyatdinov A.,CIBER ISCIII | Marco S.,CIBER ISCIII | Marco S.,Institute for Bioengineering of Catalonia IBEC | And 7 more authors.
Sensors and Actuators, B: Chemical | Year: 2010

A new drift compensation method based on common principal component analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a principal component analysis (PCA) of a reference gas. The proposed new method - employing no specific reference gas, but information from all gases - has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7 months including three gases at different concentrations for an array of 17 polymeric sensors. © 2009 Elsevier B.V. All rights reserved.

Ziyatdinov A.,Polytechnic University of Catalonia | Ziyatdinov A.,CIBER ISCIII | Fernandez Diaz E.,Institute for Bioengineering of Catalonia IBEC | Chaudry A.,Protea Ltd | And 6 more authors.
Sensors and Actuators, B: Chemical | Year: 2013

This manuscript introduces a software tool that allows for the design of synthetic experiments in machine olfaction. The proposed software package includes both, a virtual sensor array that reproduces the diversity and response of a polymer array and tools for data generation. The synthetic array of sensors allows for the generation of chemosensor data with a variety of characteristics: unlimited number of sensors, support of multicomponent gas mixtures and full parametric control of the noise in the system. The artificial sensor array is inspired from a reference database of seventeen polymeric sensors with concentration profiles for three analytes. The main features in the sensor data, like sensitivity, diversity, drift and sensor noise, are captured by a set of models under simplified assumptions. The generator of sensor signals can be used in applications related to test and benchmarking of signal processing methods, neuromorphic simulations in machine olfaction and educational tools. The software is implemented in R language and can be freely accessed at:

Coleman M.D.,National Physical Laboratory United Kingdom | Render S.,National Physical Laboratory United Kingdom | Dimopoulos C.,National Physical Laboratory United Kingdom | Lilley A.,National Physical Laboratory United Kingdom | And 4 more authors.
Journal of the Air and Waste Management Association | Year: 2015

We compare the performance of an alternative method based on portable Fourier-transform infrared (FTIR) spectroscopy described in TGN M22, “Measuring Stack Gas Emissions Using FTIR Instruments,” to the Standard Reference Methods (SRMs) for CO (EN 15058), NOx (EN 14792), SO2 (EN 14791), HCl (EN 1911), and H2O (EN 14790). Testing was carried out using a Stack Simulator facility generating complex gas matrices of the measurands across concentration ranges of 0–75 mg m−3 and 0–100 mg m−3 CO, 0–200 mg m−3 and 0–300 mg m−3 NO, 0–75 mg m−3 and 0–200 mg m−3 SO2, 0–15 mg m−3 and 0–60 mg m−3 HCl, and 0–14 vol% H2O. The former values are the required monitoring range for each measurand as described in the European Union (EU) Industrial Emissions Directive (2010/75/EU) for waste incineration processes, and the latter are supplementary ranges representative of emissions from some large combustion plant processes. Test data were treated in accordance with CEN/TS 14793, and it was found that equivalency test criteria could be met across all concentration ranges with the exception of the NO supplementary range. The results demonstrated in principle where TGN M22/FTIR could be used in place of the existing SRMs to provide, as required under the Industrial Emissions Directive, annual validation/calibration of automated measuring systems (AMSs being permanently installed on industrial stacks to provide continuous monitoring of emissions to air). These data take a step toward the wider regulatory acceptance of portable FTIR providing the advantages of real-time calibration and quantification of all measurands on a single technique. Implications: Portable FTIR offers significant advantages for the calibration (as is required by the EU’s Industrial Emissions Directive, 2010/75/EU) of process plant operators instrumentation installed for continuous monitoring of emissions to air. All key gaseous emission species regulated under the directive can be calibrated using a single technique, and the real-time calibration data allows issues with plant instrumentation to be identified sooner, reducing the amount of time where unreliable emissions data might be reported from the plant. This work takes an important step toward the regulatory acceptance of portable FTIR for the validation/calibration of in situ emissions monitoring systems. © 2015 Crown copyright.

Padilla M.,University of Barcelona | Padilla M.,Institute Of Bioenginyeria Of Catalonia Ibec | Perera A.,University of Barcelona | Perera A.,Institute Of Bioenginyeria Of Catalonia Ibec | And 6 more authors.
Chemometrics and Intelligent Laboratory Systems | Year: 2010

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period. © 2009 Elsevier B.V. All rights reserved.

Agency: European Commission | Branch: FP7 | Program: JTI-CP-FCH | Phase: SP1-JTI-FCH.2013.1.5 | Award Amount: 3.91M | Year: 2014

In HyCoRA project, a strategy for cost reduction for hydrogen fuel quality assurance QA is developed and executed. For developing this strategy, hydrogen quality risk assessment is used to define the needs for hydrogen impurity gas analysis, system level PEMFC contaminant research as well as needs for purification needs in hydrogen production, especially produced by steam methane reforming (SMR). The use of qualitative and quantitative risk assessment enables identification of critical needs for gas analysis development and guides the research work on those issues, which require most attention. The development of quantitative risk model enables implementation of data from other parallel activities in USA, Japan and Korea. The measurement campaigns in hydrogen refuelling stations, as well as in SMR production units, provide quantitative data, which can be used for identification of canary species, when analysed with help of quantitative risk assessment. Essential part of the HyCoRA project is hydrogen contaminant research in PEMFC system level. The research is performed in down-scaled automotive fuel cell systems, which can replicate all the features of full-scale automotive fuel cell systems, including the change of gases in the anode and cathode during the start-stop cycling. The contaminants and levels to be studied are, excluding obvious carbon monoxide, determined using risk assessment with help of automotive advisory board. The main objective of HyCoRA project is to provide information to lower reduce cost of hydrogen fuel QA. However, it will also provide recommendations for revision of existing ISO 14687-2:2012 standard for hydrogen fuel in automotive applications.

Agency: GTR | Branch: Innovate UK | Program: | Phase: Smart - Proof of Concept | Award Amount: 87.11K | Year: 2015

Protea Ltd. has been at the forefront of the use of Fourier Transform Infrared (FTIR) spectrometry for the measurement of industrial pollutants for 20 years. One major advantage of FTIR spectroscopy is that it can give detailed qualitative and quantitative chemical information for a wide range of gases. As a detection and analysis tool it is very powerful, but its analytical capability in real time is limited. It is either in the hands of a trained operator (a spectroscopist) who can study IR spectra and apply the correct calibration routine in the software for the gas matrix observed or is automated to the detection of a specific gas for a specific industrial emission. This adds significant extra cost to the ownership and operation of the equipment. This means that FTIR technology is often viewed as a difficult or skilled technique requiring expertise. Full automation of the process would remove the time and skill required for the pre-programming of a system for expected gases and the post-collection analysis routines. Therefore the aim of this Project “AIR-IQ” is to prove the concept for real time dynamic qualification and quantification using IR and advances in software algorithms, and to deliver this in a portable light weighted gas analyser. This would be an industry first, and would result in a gas analyser that can be switched on in factory or field and give qualitative feedback as to what gases are present in a sample, before then automatically applying the correct quantification analysis to report direct concentration values. Industrial users will for the first time be able to see, in real-time, what gaseous species are present in their process or emission gas streams. Furthermore, the analyser’s readings will be able to be reported to legislative bodies, such as in reporting emission limit values for which a plant would have permitted levels. Protea’s technology will therefore contribute to the UK’s goal of reducing harmful gas emissions.

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