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Residual life estimation of fabricated humidity sensors using different artificial intelligence techniques

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Background: a humidity sensor is used to sense and measure the relative humidity of air. A new composite system has been fabricated using environmental pollutants such as carbon black and low-cost zinc oxide, and it acts as a humidity sensor. Residual life of the sensor is calculated and an expert system is modelled. For properties and nature confirmation, characterization is performed, and a sensing material is fabricated. Methodology: characterization is performed on the fabricated material. Complex impedance spectroscopy (CIS), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM) are all used to confirm the surface roughness, its composite nature as well as the morphology of the composite. The residual lifetime of the fabricated humidity sensor is calculated by means of accelerated life testing. An intelligent model is designed using artificial intelligence techniques, including the artificial neural network (ANN), fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS). Results: maximum conductivity obtained is 6.4£10−3 S/cm when zinc oxide is doped with 80% of carbon black. Conclusion: the solid composite obtained possesses good humidity-sensing capability in the range of 30–95%. ANFIS exhibits the maximum prediction accuracy, with an error rate of just 1.1%.
Rocznik
Strony
147--154
Opis fizyczny
Bibliogr. 36 poz., rys., tab., wykr.
Twórcy
autor
  • Department of ECE, Lovely Professional University, Phagwara, Punjab 144411, India
autor
  • CSS Corp., Chennai, Tamilnadu, 600058, India
autor
  • Department of PS, Lovely Professional University, Phagwara, Punjab 144411, India
Bibliografia
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Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-484c5c4c-bb89-42cb-8bf4-9d9f7d3b2c77
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