Smart Inventory System for Expiry Date Tracking
Volume-7 | Issue-2

Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2

Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2

Survey: Unconventional Categories of Chatbots that make use of Machine Learning Techniques
Volume-5 | Issue-3

AI based Identification of Students Dress Code in Schools and Universities
Volume-6 | Issue-1

Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4

PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3

Getis-Ord (Gi*) based Farmer Suicide Hotspot Detection
Volume-4 | Issue-2

Ground-breaking Theory of Knowledge Representation Practices for Information Sharing in IT Organization
Volume-4 | Issue-3

Is Internet becoming a Major Contributor for Global warming - The Online Carbon Footprint
Volume-2 | Issue-4

AUTOMATION USING IOT IN GREENHOUSE ENVIRONMENT
Volume-1 | Issue-1

Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4

Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2

Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2

VIRTUAL REALITY GAMING TECHNOLOGY FOR MENTAL STIMULATION AND THERAPY
Volume-1 | Issue-1

Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain
Volume-3 | Issue-3

Analysis of Natural Language Processing in the FinTech Models of Mid-21st Century
Volume-4 | Issue-3

PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3

Image Augmentation based on GAN deep learning approach with Textual Content Descriptors
Volume-3 | Issue-3

Comparative Analysis for Personality Prediction by Digital Footprints in Social Media
Volume-3 | Issue-2

Home / Archives / Volume-2 / Issue-4 / Article-1

Volume - 2 | Issue - 4 | december 2020

Tungsten DiSulphide FBG Sensor for Temperature Monitoring in Float Glass Manufacturing
Pages: 191-200
DOI
10.36548/jitdw.2020.4.001
Published
30 September, 2020
Abstract

In this paper, a temperature monitoring system for glass manufacturing process is proposed by using Fibre Bragg Grating (FBG) approach. This system can be done by using OptiSystem simulation. FBG was used as it allows a reflects a wavelength of light that shifts according to variations in temperature. Generally, FBG sensors can be easily installed, it has higher accuracy, longer stability, small in size, immunity to electromagnetic interference (EMI) and the ability to measure ultra-high and speed events. The results indicated that wavelength shifting is depended on thermal expansion coefficient and thermo-optic coefficient of materials, from simulation results it was seen that, Tungsten DiSulfide(WS2) has a better sensitivity than Silica, Poly Methyl Methacrylate(PMMA) and Lead Sulfide(PbS).

Keywords

Fibre Bragg Grating sensor temperature monitoring glass industry material comparison temperature sensitivity

×

Currently, subscription is the only source of revenue. The subscription resource covers the operating expenses such as web presence, online version, pre-press preparations, and staff wages.

To access the full PDF, please complete the payment process.

Subscription Details

Category Fee
Article Access Charge
15 USD
Open Access Fee Nil
Annual Subscription Fee
200 USD
After payment,
please send an email to irojournals.contact@gmail.com / journals@iroglobal.com requesting article access.
Subscription form: click here