Versatile image processing technique for fuel science: A review

Soosai, Michael Rahul; Joshya, Yonas Camy; Kumar, R. Mohan; Moorthy, I. Ganesh; Sankar, Karthikumar; Lan, Nguyễn Thúy; Pugazhendhi, Arivalagan

doi:10.1016/j.scitotenv.2021.146469

Cited by 13 publications

(4 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the study, the average flight distance of a conveyed bundle of fuel was also determined. In addition, a thorough review of versatile image processing techniques in fuel science is drawn up …”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Plenoptic Camera-Based Measurement System for the Investigation into Flight and Combustion Behavior of Refuse-Derived Fuel Particles

et al. 2023

View full text Add to dashboard Cite

In the past several decades, refuse-derived fuels (RDFs) have been widely applied in industrial combustion processes, for instance, in cement production. Since RDF is composed of various waste fractions with complex shapes, its flight and combustion behaviors can be relatively complicated. In this paper, we present a novel plenoptic camera-based spatial measurement system that uses image processing approaches to determine the dwell time, the space-sliced velocity in the depth direction, and the ignition time of various applied RDF fractions based on the obtained images. The image processing approach follows the concept of tracking-by-detection and includes a novel combined detection method, a 2.5D multiple particle tracking algorithm, and a postprocessing framework to tackle the issues in the initial tracking results. The thereby obtained complete spatial fuel trajectories enable the analysis of the flight behaviors elaborated in the paper. The acquired particles' properties (duration, velocity, and ignition time) reversely prove the availability and applicability of the developed measurement system. The adequacy and accuracy of the proposed novel measurement system are validated by the experiments of detecting and tracking burning and nonburning fuel particles in a rotary kiln. This new measurement system and the provided experimental results can benefit a better understanding of the RDF's combustion for future research.

show abstract

Section: Introductionmentioning

confidence: 99%

“…In addition, a thorough review of versatile image processing techniques in fuel science is drawn up. 10 …”

Section: Introductionmentioning

confidence: 99%

A Novel Plenoptic Camera-Based Measurement System for the Investigation into Flight and Combustion Behavior of Refuse-Derived Fuel Particles

et al. 2023

View full text Add to dashboard Cite

show abstract

“…The main process involves digitization of the image (11,12) which can be graphically represented by Figure 1. Such favorable characteristics of image processing led researchers to realize its potential for providing valuable microstructural information in the process of improving performance and efficiency of clean energy systems (13)(14)(15).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Automatic Microstructural Analysis of Energy Dispersive Spectroscopy (EDS) Maps via a Python-Based Data Processing Framework

Batool¹,

Godoy²,

Birnbach³

et al. 2021

ECS Trans.

View full text Add to dashboard Cite

Computer-aided data acquisition, analysis and interpretation have been employed in various research areas generating useful information. Among these, image processing is most often implemented for post-processing of material characterization data. However, to tackle ambiguity of multi-component materials analysis, spectral data analysis can be used instead. The current study introduces a unique Python-based data processing method for indepth analysis of energy dispersive spectroscopy (EDS) elemental maps to analyze agglomerate size distribution, average area of each component and their overlap. The framework developed in this study is applied to examine interaction of Cerium (Ce) and Palladium (Pd) particles in membrane electrode assembly (MEA) of Anion-Exchange Membrane Fuel Cell (AEMFC) and investigate if this approach can be utilized to predict the fuel cell's electrochemical behavior. The study concludes that the developed framework is a promising method for automatic data extraction and can be beneficial for use in a variety of clean energy applications.

show abstract

“…1. 15,16 However, although computer-based automated image processing has its challenges, it is far superior and has unarguably overshadowed manual image processing techniques in recent decades.…”

mentioning

confidence: 99%

Evaluation of Semi-Automatic Compositional and Microstructural Analysis of Energy Dispersive Spectroscopy (EDS) Maps via a Python-Based Image and Data Processing Framework for Fuel Cell Applications

Batool¹,

Godoy²,

Birnbach³

et al. 2023

J. Electrochem. Soc.

View full text Add to dashboard Cite

Computer-aided data acquisition, analysis, and interpretation are rapidly gaining traction in numerous facets of research. One of the subsets of this field, image processing, is most often implemented for post-processing material microstructural characterization data to understand better and predict materials' features, properties, and behaviors at multiple scales. However, to tackle the ambiguity of multi-component materials analysis, spectral data can be used in combination with image processing. The current study introduces a novel Python-based image and data processing method for in-depth analysis of energy dispersive spectroscopy (EDS) elemental maps to analyze multi-component agglomerate size distribution, the average area of each component, and their overlap. The framework developed in this study is applied to examine the interaction of cerium oxide and palladium particles in the membrane electrode assembly of an anion-exchange membrane fuel cell and to investigate if this approach can be correlated to the cell performance. The study also performs a sensitivity analysis of several parameters and their effect on the computed results. The developed framework is a promising method for semi-automatic data processing and can be further advanced towards a fully automatic analysis of similar data types in the field of clean energy materials and broader.

show abstract

Versatile image processing technique for fuel science: A review

Cited by 13 publications

References 41 publications

A Novel Plenoptic Camera-Based Measurement System for the Investigation into Flight and Combustion Behavior of Refuse-Derived Fuel Particles

A Novel Plenoptic Camera-Based Measurement System for the Investigation into Flight and Combustion Behavior of Refuse-Derived Fuel Particles

Evaluation of Automatic Microstructural Analysis of Energy Dispersive Spectroscopy (EDS) Maps via a Python-Based Data Processing Framework

Evaluation of Semi-Automatic Compositional and Microstructural Analysis of Energy Dispersive Spectroscopy (EDS) Maps via a Python-Based Image and Data Processing Framework for Fuel Cell Applications

Contact Info

Product

Resources

About