NON-INVASIVE BASED INFRARED THERMOGRAPHY APPROACH FOR FIELD ASSESSMENT OF SURFACE EROSION IN TAILING DAMS

In recent years, non-destructive testing (NDT) has emerged as an efficient tool for evaluating the performance, quality, and integrity of existing structures.This study investigates novel non-destructive techniques, specifically Infrared Thermography (IRT), to detect surface erosion in real-life tailing dams.The tailing dams considered in the study are designed to store coal combustion byproducts in a slurry form, consisting of bottom ash and fly ash.IRT offers a quick and non-invasive monitoring technique to detect, identify, and describe potential anomalies in dykes impacting the integrity of these critical structures.This study captured the thermal images using a FLIR C5 thermal infrared camera during field reconnaissance of an existing starter dyke of a tailing dam located in Northern India.Analysis of these images is facilitated by different software, such as FLIR tools and ResearchIR, enabling the identification of localized temperature variations, which are indicative of potentially affected areas.This study demonstrates the efficiency of IRT in delivering real-time insights into dam conditions, enabling prompt maintenance and action to reduce potential risks.The findings emphasize IRT's ability to monitor and manage dam infrastructure proactively, ultimately improving safety and resilience in tailing management systems.

Authors

Publication Details

Journal
International Journal of Geomate
Published
2025-08-29
DOI
https://doi.org/10.21660/2025.132.g14386
Primary Topic
Tailings Management and Properties
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

NON-INVASIVE BASED INFRARED THERMOGRAPHY APPROACH FOR FIELD ASSESSMENT OF SURFACE EROSION IN TAILING DAMS

Vaishnavi Bherde
International Journal of Geomate
Tailings Management and Properties
article

NON-INVASIVE BASED INFRARED THERMOGRAPHY APPROACH FOR FIELD ASSESSMENT OF SURFACE EROSION IN TAILING DAMS

Vaishnavi Bherde
article en

Abstract

In recent years, non-destructive testing (NDT) has emerged as an efficient tool for evaluating the performance, quality, and integrity of existing structures.This study investigates novel non-destructive techniques, specifically Infrared Thermography (IRT), to detect surface erosion in real-life tailing dams.The tailing dams considered in the study are designed to store coal combustion byproducts in a slurry form, consisting of bottom ash and fly ash.IRT offers a quick and non-invasive monitoring technique to detect, identify, and describe potential anomalies in dykes impacting the integrity of these critical structures.This study captured the thermal images using a FLIR C5 thermal infrared camera during field reconnaissance of an existing starter dyke of a tailing dam located in Northern India.Analysis of these images is facilitated by different software, such as FLIR tools and ResearchIR, enabling the identification of localized temperature variations, which are indicative of potentially affected areas.This study demonstrates the efficiency of IRT in delivering real-time insights into dam conditions, enabling prompt maintenance and action to reduce potential risks.The findings emphasize IRT's ability to monitor and manage dam infrastructure proactively, ultimately improving safety and resilience in tailing management systems.

International Journal of GeomateVol. 29(132)
Department of Science and Technology, Ministry of Science and Technology, India
Climate action
Openalex Percentile: Top 76%
Tailings Management and Properties
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.