Carrasco, M., Araya-Letelier, G., Velazquez, R., & Visconti, P. (2021). Image-Based Automated Width Measurement of Surface Cracking. Sensors, 21(22), 7534.
Abstract: The detection of cracks is an important monitoring task in civil engineering infrastructure devoted to ensuring durability, structural safety, and integrity. It has been traditionally performed by visual inspection, and the measurement of crack width has been manually obtained with a crack-width comparator gauge (CWCG). Unfortunately, this technique is time-consuming, suffers from subjective judgement, and is error-prone due to the difficulty of ensuring a correct spatial measurement as the CWCG may not be correctly positioned in accordance with the crack orientation. Although algorithms for automatic crack detection have been developed, most of them have specifically focused on solving the segmentation problem through Deep Learning techniques failing to address the underlying problem: crack width evaluation, which is critical for the assessment of civil structures. This paper proposes a novel automated method for surface cracking width measurement based on digital image processing techniques. Our proposal consists of three stages: anisotropic smoothing, segmentation, and stabilized central points by k-means adjustment and allows the characterization of both crack width and curvature-related orientation. The method is validated by assessing the surface cracking of fiber-reinforced earthen construction materials. The preliminary results show that the proposal is robust, efficient, and highly accurate at estimating crack width in digital images. The method effectively discards false cracks and detects real ones as small as 0.15 mm width regardless of the lighting conditions.
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Cho, A. D., Carrasco, R. A., & Ruz, G. A. (2022). A RUL Estimation System from Clustered Run-to-Failure Degradation Signals. Sensors, 22(14), 5323.
Abstract: The prognostics and health management disciplines provide an efficient solution to improve a system's durability, taking advantage of its lifespan in functionality before a failure appears. Prognostics are performed to estimate the system or subsystem's remaining useful life (RUL). This estimation can be used as a supply in decision-making within maintenance plans and procedures. This work focuses on prognostics by developing a recurrent neural network and a forecasting method called Prophet to measure the performance quality in RUL estimation. We apply this approach to degradation signals, which do not need to be monotonical. Finally, we test our system using data from new generation telescopes in real-world applications.
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Garces, H. O., Fuentes, A., Reszka, P., & Carvajal, G. (2018). Analysis of Soot Propensity in Combustion Processes Using Optical Sensors and Video Magnification. Sensors, 18(5), 18 pp.
Abstract: Industrial combustion processes are an important source of particulate matter, causing significant pollution problems that affect human health, and are a major contributor to global warming. The most common method for analyzing the soot emission propensity in flames is the Smoke Point Height (SPH) analysis, which relates the fuel flow rate to a critical flame height at which soot particles begin to leave the reactive zone through the tip of the flame. The SPH and is marked by morphological changes on the flame tip. SPH analysis is normally done through flame observations with the naked eye, leading to high bias. Other techniques are more accurate, but are not practical to implement in industrial settings, such as the Line Of Sight Attenuation (LOSA), which obtains soot volume fractions within the flame from the attenuation of a laser beam. We propose the use of Video Magnification techniques to detect the flame morphological changes and thus determine the SPH minimizing observation bias. We have applied for the first time Eulerian Video Magnification (EVM) and Phase-based Video Magnification (PVM) on an ethylene laminar diffusion flame. The results were compared with LOSA measurements, and indicate that EVM is the most accurate method for SPH determination.
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Moffat, R., Parra, P., & Carrasco, M. (2020). Monitoring a 28.5 m High Anchored Pile Wall in Gravel Using Various Methods. Sensors, 20(1), 14 pp.
Abstract: Horizontal displacements of a multiple-anchor pile wall in a 28.5 m deep excavation using the top-down construction method have been monitored using optical fiber (Brillouin optical time-domain reflectometry (BOTDR)), strain gauges, inclinometers, and a topographic survey. This work presents a comparison between these different techniques to measure horizontal displacements in the pile at several stages of the soil excavation process. It was observed that displacements can be separated into two components: Rigid body motion and pile flexural deformation. Measurements using optical fiber and inclinometers are considered the most adequate and easy to install. A numerical model allows us to evaluate the influence of earth pressure on the estimated horizontal displacements. It is shown that using soil pressure on the wall given by p = 0.65Ka gamma h, on a simplified modeled wall, provides a close deduction of horizontal displacements compared to observed values on the field.
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Peters, A. A., Vargas, F. J., Garrido, C., Andrade, C., & Villenas, F. (2021). PL-TOON: A Low-Cost Experimental Platform for Teaching and Research on Decentralized Cooperative Control. Sensors, 21(6), 2072.
Abstract: In this paper, we present the development of a low-cost multi-agent system experimental platform for teaching, and research purposes. The platform consists of train-like autonomous agents equipped with local speed estimation, distance sensing to their nearest predecessor, and wireless communications with other agents and a central coordinator. The individual agents can be used for simple PID experiments in a classroom or laboratory setting, while a collection of agents are capable of performing decentralized platooning with cooperative adaptive cruise control in a variety of settings, the latter being the main goal of the platform. The agents are built from low cost components and programmed with open source software, enabling teaching experiences and experimental work with a larger number of agents that would otherwise be possible with other existing solutions. Additionally, we illustrate with experimental results some of the teaching activities that the platform is capable of performing.
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Pina, S., Candia-Onfray, C., Hassan, N., Jara-Ulloa, P., Contreras, D., & Salazar, R. (2021). Glassy Carbon Electrode Modified with C/Au Nanostructured Materials for Simultaneous Determination of Hydroquinone and Catechol in Water Matrices. Chemosensors, 9(5), 88.
Abstract: The simultaneous determination of hydroquinone and catechol was conducted in aqueous and real samples by means of differential pulse voltammetry (DPV) using a glassy carbon electrode modified with Gold Nanoparticles (AuNP) and functionalized multiwalled carbon nanotubes by drop coating. A good response was obtained in the simultaneous determination of both isomers through standard addition to samples prepared with analytical grade water and multivariate calibration by partial least squares (PLS) in winery wastewater fortified with HQ and CT from 4.0 to 150.00 mu M. A sensitivity of 0.154 mu A mu M-1 and 0.107 mu A mu M-1, and detection limits of 4.3 and 3.9 mu M were found for hydroquinone and catechol, respectively. We verified the reliability of the developed method by simultaneously screening analytes in spiked tap water and industrial wastewater, achieving recoveries over 80%. In addition, this paper demonstrates the applicability of chemometric tools for the simultaneous quantification of both isomers in real matrices, obtaining prediction errors of lower than 10% in fortified wastewater.
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Villacres, J., Arevalo-Ramirez, T., Fuentes, A., Reszka, P., & Cheein, F. A. (2019). Foliar Moisture Content from the Spectral Signature for Wildfire Risk Assessments in Valparaiso-Chile. Sensors, 19(24), 17 pp.
Abstract: Fuel moisture content (FMC) proved to be one of the most relevant parameters for controlling fire behavior and risk, particularly at the wildland-urban interface (WUI). Data relating FMC to spectral indexes for different species are an important requirement identified by the wildfire safety community. In Valparaiso, the WUI is mainly composed of Eucalyptus Globulus and Pinus Radiata-commonly found in Mediterranean WUI areas-which represent the 97.51% of the forests plantation inventory. In this work we study the spectral signature of these species under different levels of FMC. In particular, we analyze the behavior of the spectral reflectance per each species at five dehydration stages, obtaining eighteen spectral indexes related to water content and, for Eucalyptus Globulus, the area of each leave-associated with the water content-is also computed. As the main outcome of this research, we provide a validated linear regression model associated with each spectral index and the fuel moisture content and moisture loss, per each species studied.
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