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Intelligent Expert System to Optimize the Quartz Crystal Microbalance (QCM) Characterization Test: Intelligent System to Optimize the QCM Characterization Test
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Author(s): Jose Luis Calvo-Rolle (University of A Coruña, Spain), José Luis Casteleiro-Roca (University of A Coruña, Spain), María del Carmen Meizoso-López (University of A Coruña, Spain), Andrés José Piñón-Pazos (University of A Coruña, Spain)and Juan Albino Mendez-Perez (Universidad de La Laguna, Spain)
Copyright: 2017
Pages: 20
Source title:
Handbook of Research on Soft Computing and Nature-Inspired Algorithms
Source Author(s)/Editor(s): Shishir K. Shandilya (Bansal Institute of Research and Technology, India), Smita Shandilya (Sagar Institute of Research Technology and Science, India), Kusum Deep (Indian Institute of Technology Roorkee, India)and Atulya K. Nagar (Liverpool Hope University, UK)
DOI: 10.4018/978-1-5225-2128-0.ch016
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Abstract
This chapter describes an approach to reduce significantly the time in the frequency sweep test of a Quartz Crystal Microbalance (QCM) characterization method based on the resonance principle of passive components. On this test, the spent time was large, because it was necessary carry out a big frequency sweep due to the fact that the resonance frequency was unknown. Moreover, this frequency sweep has great steps and consequently low accuracy. Then, it was necessary to reduce the sweeps and its steps gradually with the aim to increase the accuracy and thereby being able to find the exact frequency. An intelligent expert system was created as a solution to the disadvantage described of the method. This model provides a much smaller frequency range than the initially employed with the original proposal. This frequency range depends of the circuit components of the method. Then, thanks to the new approach of the QCM characterization is achieved better accuracy and the test time is reduced significantly.
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