Developing a Low-Cost Thermal Camera for Industrial Predictive Maintenance Applications View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019

AUTHORS

Alda Xhafa , Pere Tuset-Peiró , Xavier Vilajosana

ABSTRACT

This paper presents the development and evaluation of a low-cost thermal camera based on off-the-shelf components that can be used to predict failures of industrial machines. On the sensing side the system is based on a LWIR thermal camera (FLiR Lepton), whereas for the data acquisition it uses an ARM Cortex-M4F micro-controller (Texas Instruments MSP432) running FreeRTOS. For the data communications the system uses a Wi-Fi transceiver with an embedded IPV4 stack (Texas Instruments CC3100), which provides seamless integration with the Cloud back-end (Amazon AWS) used to retrieve, store and process the thermal images. The paper also presents the calibration method used to obtain the relation between the camera raw output and the actual object temperature, as well the measurements that have been conducted to determine the overall energy consumption of the system. More... »

PAGES

182-193

Book

TITLE

Advances in Network-Based Information Systems

ISBN

978-3-319-98529-9
978-3-319-98530-5

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-98530-5_16

DOI

http://dx.doi.org/10.1007/978-3-319-98530-5_16

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106365298


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