Research Projects
Here are some projects I've been working during the years, they include technologies such as advanced sensing, machine learning, imaging, computer vision, signal and image processing in different contexts.
1. Industrial glass deffect detection (stand by)
The project aims to develope image analysis models capable of detect deffects in industrial manufactured glass samples, in this previous work, a dataset of different types of glass deffects and artifacts were collected in a laboratory setup (left image). The final goal is to implement a computer vision system for online sorting of industrial size flat glass plates.
Previous results: Image processing and deep learning models to classify glass samples with defects.
2. Spectral sensing and signal analysis for high temperature processes
The project aimed to characterize and model the combustion process of copper/iron sulfide minerals and copper concentrates using spectral analysis techniques and machine learning algorithms. Through laboratory experiments, spectral patterns were identified to determine combustion states, and signal processing and machine learning methods facilitated temperature estimation from combustion spectra. Additionally, the project involved the development of a prototype industrial monitoring system (currently being tested internationally). These efforts contribute to advancing scientific and technological capabilities in high-temperature industrial monitoring and the characterization of pure species during combustion through optoelectronic technology and advanced data analysis techniques. See Articles 1-8 in the list below for more details.
3. Hyperspectral image reconstruction
This thesis introduces two new Multispectral Imaging Systems with application to combustion processes. The first combines a liquid crystal tunable filter with a monochrome camera but has limited use for fast-moving objects. The second system, using spectral reconstruction techniques with color image acquisition, achieved fast high-resolution spectral imaging. It was effective in flame sensing, producing accurate radiation profiles and temperature maps for different flames. Overall, both systems offer promising applications in combustion research.
Results:
PhD_Thesis_pdf (ESP version).
PhD_Thesis_pdf (ENG version, draft with images still to be translated).
Articles 9-13 in the list below.
Publications
Metallurgical and Materials Transactions B, 2023, “Development and Application of an Optoelectronic Sensor for Flame Monitoring of a Copper Concentrate Flash Bruner” (In peer review).
Metallurgical and Materials Transactions B-Process Metallurgy and Materials Processing Science, DOI: 10.1007/s11663-022-02657-5, 2022. “Radiometric temperature measurement of copper concentrates in flash smelting conditions simulated at laboratory scale coupled with a macroscopic chemical reaction model and automated mineralogical characterization”, W. Díaz, G. Reyes, C. Toro, R. Li, E. Balladares, R. Parra.
Processes, Special issue: Advanced Process Monitoring for Industry 4.0, DOI: 10.3390/pr9020188, vol. 9, no. 2, 2021, “Copper oxide spectral emission detection in chalcopyrite and copper concentrate combustion”, G. Reyes, W. Díaz, C. Toro, E. Balladares, S. Torres, R. Parra. [pdf]
Sensors, Special issue: Advanced Sensors and Signal Processing of Sensor Data, Recent Advances and Applications, DOI: 10.3390/s20051284, vol. 20, no. 5, 2020, “On the detection of spectral emissions of iron oxides in combustion experiments of pyrite concentrates”, C. Toro, S. Torres, V. Parra, R. Fuentes, R. Castillo, W. Díaz, G. Reyes, E. Balladares, R. Parra. [pdf]
Metals, DOI: 10.1109/ACCESS.2019.2925734, vol. 9, no. 9, 2019, “Spectral characterization of copper and iron sulfide combustion: a multivariate data analysis approach for mineral identification on the blend”, W. Díaz, C. Toro, E. Balladares, V. Parra, P. Coelho, G. Reyes, R. Parra. [pdf]
18th IFAC (International Federation of Automatic Control) Conference, Stellenbosch, South Africa, Aug. 28-30, vol. 52, 2019. “Automatic near-infrared hyperspectral image analysis of copper concentrates”, P. Coelho, C. Sandoval, J. Alvarez, I. Sanhueza, C. Godoy, S. Torres, C. Toro, D. Sbarbaro. [pdf]
IEEE Access, DOI: 10.1109/ACCESS.2019.2925734, June 2019, “Estimation of spectral emissivity and S/Cu ratio from emissions of copper concentrates at the flash smelting process”. Authors: M. Marin, C. Toro, L. Arias, E. Balladares.
Sensors, DOI: 10.3390/s18072009, Vol 18 Issue 7- June 2018, “Flash Smelting Copper Concentrates Spectral Emission Measurements”. Authors: L. Arias, S. Torres, C. Toro, E. Balladares, R. Parra, C. Loeza, C. Villagrán and P. Coelho. [pdf]
J. of Food Engineering, DOI: 10.1016/j.jfoodeng.2016.03.005, Vol 181, 84-91, 2016, "A machine vision system for automatic detection of parasites Edotea magellanica in shell-off cooked clam Mulina edulis". Authors: P. Coelho, S. Torres, W. Ramirez, P. Gutierrez, C. Toro, J. Soto, D. Sbarbaro, J. Pezoa.
IEEE Latinoamericana, Vol 13 Issue 8 - August 2015, “1CCD and 3CCD Color Cameras Performance Comparison Applied to Hyperspectral Image Reconstruction”. Authors: C. Toro, P. Meza, L. Arias. [pdf]
Applied Optics, Vol. 53 No. 28, 6351-6361, 2014, “Flame spectra-temperature estimation based on a color imaging camera and a spectral reconstruction technique”. Authors: C. Toro, L. Arias, S. Torres, D. Sbarbaro. [pdf]
Proc. SPIE 8693, Smart Sensor Phenomena, Technology, Networks, and Systems Integration, Ap. 11, 2013, “Time-resolved luminescence measurements on upconversion phosphors for electron beam sterilization monitoring”. Authors: M. Reitzig, T. Härtling, M. Winkler, P. Powers, S. Darenko, C. Toro, O. Röder, J. Opitz.
16th Iberoamerican Congress, CIARP, Pucón, Chile, Nov. 15-18, 2011, “Infrared Focal Plane Array Imaging System Characterization by Means of Blackbody Radiator”, Lecture Notes in Computer Science 7042, 2011. Authors: F. Parra, C. Toro, P. Meza, S. Torres.