Residual Life Estimation of a Fabricated Humidity Sensor Using AI | Alum-Carbon based humidity sensor: Its Fabrication and Residual Life Prediction using Artificial Intelligence Techniques

Cherry Bhargava (u. a.)

ISBN 10: 6139842999 / ISBN 13: 9786139842995

Published by LAP LAMBERT Academic Publishing, 2018

About this Item

Residual Life Estimation of a Fabricated Humidity Sensor Using AI | Alum-Carbon based humidity sensor: Its Fabrication and Residual Life Prediction using Artificial Intelligence Techniques | Cherry Bhargava (u. a.) | Taschenbuch | 84 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139842995 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 113883115

Bibliographic Details

• Title: Residual Life Estimation of a Fabricated Humidity Sensor Using AI | Alum-Carbon based humidity sensor: Its Fabrication and Residual Life Prediction using Artificial Intelligence Techniques
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2018
• Language: English
• ISBN 10: 6139842999
• ISBN 13: 9786139842995
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 6D millimeters 220 millimeters width by 150 millimeters height by 6 millimeters depth
• Weight: 143 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

From daily life applications to military applications and from toys to satellites, the use of electronic components is in extensive. Due to rapid evolution of electronics device technology towards low cost and high performance, the electronics products become more complex, higher in density and speed, and lighter for easy portability. Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The user can replace faulty component with the accurate one, and system will be saved from complete shutdown. Using low-cost materials, carbon, and potash alum, a new solid composite electrolyte system was fabricated and characterized using various techniques. An Arrhenius behavior was reported when the temperature dependence of conductivity was analyzed. The synthesized solid composite electrolyte exhibited excellent humidity sensing behavior. An expert system was modeled using artificial intelligence techniques and failure of the sensor was predicted using artificial neural networks (ANN), fuzzy logic (FIS) an adaptive neuro-fuzzy inference system (ANFIS).