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DATA ACQUISITION AND DATA PROCESSING CHALLENGES IN HEAVY METAL MEASUREMENTS

José Miguel Dias Pereira, Ricardo Manuel Nunes Salgado

Abstract


Water quality is a key factor to preserve human life quality, as well as, environmental and biological ecosystems. This paper highlights specific issues related with the acquisition and data processing of heavy metal measurement systems. Between the main challenges related with this kind of measurements, such as the ones related with the very low signal amplitudes to be measured, since very low concentrations, in the order of tens of p.p.b., of some heavy metals, can be very dangerous for human life and for ecosystems sustainability. Additional challenges, that are associated with online heavy metals measurements, are related with the capability to obtain accurate results using a low number of measurement points. Thus, the main goal of this paper is a comparison of different data processing algorithms that can be used to improve heavy metal measurement accuracy when a segmented voltammetric voltage scan is performed with a low number of measurement points. Regarding data processing of the measurement data, B-Spline, Gaussian and artificial neural network based techniques are compared with traditional least mean square techniques based on polynomial curve fitting. The performance of each technique is evaluated in terms of the required number of measurement points, for a given root mean square deviation between curve fitted and experimental data. A brief comparison of the different techniques, in terms of insensitivity to errors caused by measurement data outliers, is also presented.

Keywords


Heavy metals; curve fitting methods; measurement data outliers; measurement accuracy; sensitivity and celerity.

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References


European Environment Agency, Water EU policies, available on line http://www.eea.europa.eu/themes/water/intro, accessed November 2015.

US Environmental Protection Agency (EPA), Regulatory Information, available online on http://www2.epa.gov/regulatory-information-topic/, accessed November 2015.

O. Malm et al., Mercury and Methylmercury in Fish and Human Hair from the Tapajós River Basin-Brazil, Science of the Total Environment, (175) 2, (1995), pp. 141-150.

S. Yurish, M. Gomes, Smart Sensors and MEMS in Mathematics, Physics and Chemistry, Kluwer Academic Plublishers, 2003, 181 p.

M. Gomes, A. Duarte, J. Oliveira, Comparison of two methods for coating piezoelectrical crystals, Anal. Chim. Acta, (300) (1995), pp. 329-334.

O. Postolache, J. M. Dias Pereira, P. S. Girão, Water Quality Monitoring and Associated Distributed Measurement Systems: An Overview in Series: “Water Quality and Assessment”, Society for Instrumentation, Systems, and Automation Society, In-Tech Publishing, Rijeka, Croatia, 2012, pp. 25-64.

M. Dias Pereira, O. Postolache, P. S. Girão, Heavy Metals Measurement: A Suitable Solution to Improve Online Measurement Celerity, Instrumentation Science & Technology, (40) 4, (2012), pp. 355-371.

Zou Xiaoyong, Mo Jinyuan, Spline wavelet overlapped peaks analysis, Science Bulletin, (44) 10 (1999), pp. 901-904.

M. A. Tarighat, Analytical Methods: Orthogonal Projection Approach and Continuous Wavelet Transform-feed Forward Neural Networks for Simultaneous Spectrophotometric Determination of some Heavy Metals in Diet Samples, Food Chemistry, (192) (2016), pp. 548-556.

A. Scozzari, N. Acito, G. Corsini, Signal Analysis of Voltammetric Data Series for Water Quality Tests and Classification, in Proceedings of the Instrumentation and Measurement Technology Conference, Pisa, Italy (May, 2005), Vol. 1, pp. 89-92.

K. Kano, T. Konse and T. Kubota, The Curve Fitting Analysis of D.C. and A.C. Voltammograms of a Two-step Surface-redox Reaction. The Application to the Surface-redox System of Adriamycin Adsorbed on a Pyrolytic Graphite Electrode, Bull. Chem. Soc. of Japan, (58) 7 (1985), pp. 1879-1885.

B. D. Fleming, N. L. Barlow, J. Zhang, A.M. Bond, F.A. Armstrong, Application of power spectra patterns in Fourier transform square wave voltammetry to evaluate electrode kinetics of surface-confined proteins, Anal Chem. 1, (78) 9 (2006), pp. 2948-2956.

Zheng Xiaoping, Mo Jinyuan and Cai Peixiang, Spline wavelet in the resolution of overlapping voltammetric peaks, Journal of Science in China (Series B): Chemistry, Publisher Science China Press, co-published with Springer, (42) 2 (1999), pp. 145-152.

W. Huanga, T. L. E. Hendersonb, A. M. Bondc, and K. B. Oldhamd, Curve fitting to resolve overlapping voltammetric peaks: model and examples, Analytica Chimica Acta, (304) 1 (1995), pp. 1-15.

D. A. Skoog, F. J. Holler, T. A. Nieman, Principles of Instrumental Analysis, 5th edition, Sauders College publishing, Orlando, Florida, Chap. 25, 1998, pp. 639-670.

J. Zhuang, L. Zhang, W. Lu, D. Shen, R. Zhu, D. Pan, Determination of trace copper in water samples by anodic stripping voltammetry at gold microelectrode, Int. J. Electrochem. Sci., (6) (2011), pp. 4690-4699.

J. M. Friedrich, C. Ponce-de-León, G. W. Reade, F. C. Walsh, Reticulated vitreous carbon as an electrode material, J. Electroanal Chem., (561) (2004), pp. 203-217.

R. L. McCreery, K. K. Kline, Laboratory Techniques in Electroanalytical Chemistry, 2nd Edition, P. T. Kissinger and W. R. Heineman eds., Dekker, New York, 1995, Chap. 4 and 10.

Analog Devices, Application Note AN-283, Sigma-Delta ADCs and DACs, available online on http://www.analog.com/, accessed July 2015.

J. M. Dias Pereira, P. S. Girão, O. Postolache, Adaptive Analog-to-Digital Conversion Using Self-Dithering in Data Acquisition Systems, in Proceedings of the 11th IEEE International Conference on Electronics, Circuits and Systems, (ICECS’2004), Tel Aviv, Israel, (December 2004), Vol. 1, pp. 627-630.

M. Unser, A. Aldroubi, M. Eden, B-Spline Signal Processing: Part I-Theory, IEEE Transactions on Signal Processing, (41) 2 (1993), pp. 821-833.

S. A. Dyer, J. S. Dyer, Cubic-Spline Interpolation: Part 1, IEEE Instrumentation Measurement Magazine, (4) 1 (2001), pp. 44-46.

L. Yingwei, N. Sundararajan, P. Saratchandran, Performance evaluation of a sequential minimal radial basis function (RBF) neural network learning algorithm, IEEE Transactions on Neural Networks, (9) 2 (1998), pp. 308-318.

S. Haykin, Neural Networks – A Comprehensive Foundations, 2nd edition, Prentice Hall, NJ, USA, 1999, 842 p.

J. R. Taylor, An Introduction to Error Analysis, 2nd edition, University Science Books, Sausalito, California, USA, 1997, 327 p.

J. A. Nelder, R. Mead, A Simplex Method for Function Minimization, Computer Journal, (7) 4 (1965), pp. 308-313.

F. M. Silva, L. B. Almeida, Speeding up Back-propagation, in: Advanced Neural Computers, R. Eckmiller edition, North Holland, 1990, pp. 151-160.


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