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Carrasco, M., Alvarez, F., Velazquez, R., Concha, J., & Perez-Cotapos, F. (2019). Brush-Holder Integrated Load Sensor Prototype for SAG Grinding Mill Motor. Electronics, 8(11), 14 pp.
Abstract: One of the most widely used electro-mechanical systems in large-scale mining is the electric motor. This device is employed in practically every phase of production. For this reason, it needs to be inspected regularly to maintain maximum operability, thus avoiding unplanned stoppages. In order to identify potential faults, regular check-ups are performed to measure the internal parameters of the components, especially the brushes and brush-holders. Both components must be properly aligned and calibrated to avoid electric arcs to the internal insulation of the motor. Although there is an increasing effort to improve inspection tasks, most inspection procedures are manual, leading to unnecessary costs in inspection time, errors in data entry, and, in extreme cases, measurement errors. This research presents the design, development, and assessment of an integrated measurement prototype for measuring spring tension and other key parameters in brush-holders used in electric motors. It aims to provide the mining industry with a new, fully automatic inspection system that will facilitate maintenance and checking. Our development research was carried out specifically on the brush system of a SAG grinding mill motor. These machines commonly use SIEMENS motors; however, the instrument can be easily adapted to any motor by simply changing the physical dimensions of the prototype.
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Carrasco, M., Alvarez, F., Velazquez, R., Concha, J., & Perez-Cotapos, I. (2018). Inline Force Sensor Development for Electrical Motors for Mining Operations in Chile: A New Inspection Protocol. IEEE Latin Am. Trans., 16(1), 66–74.
Abstract: Electric motors are among the most widely used electro-mechanical systems in the mining industry in Chile. As they are physically present in virtually all phases of the production process, they must be regularly inspected. In order to maintain a maximum level of operability and to avoid the occurrence of catastrophic failures and unscheduled stoppages, regular, planned reviews to measure the internal parameters of their components are performed manually. This part of the process presents serious shortcomings, such as significant inspection times, information input errors and, in some cases, measurement errors resulting from the technical difficulty of physically taking the measurement. This research presents the design, development and evaluation of a new sensor to support the inspection of brush-holder spring tensions as well as the integration of a digital gauge to control other critical dimensions of the brush-holder mounting. Its purpose is to provide the mining industry with a new system and a fully automated inspection protocol to ease maintenance and control tasks, particularly focusing on reducing inspection times. These products are expected to increase the equipment operating life, as well as delivering a maintenance report of the motor's key parameters which directly benefits the Key Performance Indicators (KPI) of mining management
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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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Carrasco, M., Mery, D., Concha, A., Velazquez, R., De Fazio, R., & Visconti, P. (2021). An Efficient Point-Matching Method Based on Multiple Geometrical Hypotheses. Electronics, 10(3), 246.
Abstract: Point matching in multiple images is an open problem in computer vision because of the numerous geometric transformations and photometric conditions that a pixel or point might exhibit in the set of images. Over the last two decades, different techniques have been proposed to address this problem. The most relevant are those that explore the analysis of invariant features. Nonetheless, their main limitation is that invariant analysis all alone cannot reduce false alarms. This paper introduces an efficient point-matching method for two and three views, based on the combined use of two techniques: (1) the correspondence analysis extracted from the similarity of invariant features and (2) the integration of multiple partial solutions obtained from 2D and 3D geometry. The main strength and novelty of this method is the determination of the point-to-point geometric correspondence through the intersection of multiple geometrical hypotheses weighted by the maximum likelihood estimation sample consensus (MLESAC) algorithm. The proposal not only extends the methods based on invariant descriptors but also generalizes the correspondence problem to a perspective projection model in multiple views. The developed method has been evaluated on three types of image sequences: outdoor, indoor, and industrial. Our developed strategy discards most of the wrong matches and achieves remarkable F-scores of 97%, 87%, and 97% for the outdoor, indoor, and industrial sequences, respectively.
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Carrasco, M., Toledo, P. A., Velazquez, R., & Bruno, O. M. (2020). Automatic Stomatal Segmentation Based on Delaunay-Rayleigh Frequency Distance. Plants-Basel, 9(11), 1613.
Abstract: The CO2 and water vapor exchange between leaf and atmosphere are relevant for plant physiology. This process is done through the stomata. These structures are fundamental in the study of plants since their properties are linked to the evolutionary process of the plant, as well as its environmental and phytohormonal conditions. Stomatal detection is a complex task due to the noise and morphology of the microscopic images. Although in recent years segmentation algorithms have been developed that automate this process, they all use techniques that explore chromatic characteristics. This research explores a unique feature in plants, which corresponds to the stomatal spatial distribution within the leaf structure. Unlike segmentation techniques based on deep learning tools, we emphasize the search for an optimal threshold level, so that a high percentage of stomata can be detected, independent of the size and shape of the stomata. This last feature has not been reported in the literature, except for those results of geometric structure formation in the salt formation and other biological formations.
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de Fazio, R., Giannoccaro, N. I., Carrasco, M., Velazquez, R., & Visconti, P. (2021). Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey. Front. Inf. Technol. Electron. Eng., 22(11), 1413–1442.
Abstract: Until a safe and effective vaccine to fight the SARS-CoV-2 virus is developed and available for the global population, preventive measures, such as wearable tracking and monitoring systems supported by Internet of Things (IoT) infrastructures, are valuable tools for containing the pandemic. In this review paper we analyze innovative wearable systems for limiting the virus spread, early detection of the first symptoms of the coronavirus disease COVID-19 infection, and remote monitoring of the health conditions of infected patients during the quarantine. The attention is focused on systems allowing quick user screening through ready-to-use hardware and software components. Such sensor-based systems monitor the principal vital signs, detect symptoms related to COVID-19 early, and alert patients and medical staff. Novel wearable devices for complying with social distancing rules and limiting interpersonal contagion (such as smart masks) are investigated and analyzed. In addition, an overview of implantable devices for monitoring the effects of COVID-19 on the cardiovascular system is presented. Then we report an overview of tracing strategies and technologies for containing the COVID-19 pandemic based on IoT technologies, wearable devices, and cloud computing. In detail, we demonstrate the potential of radio frequency based signal technology, including Bluetooth Low Energy (BLE), Wi-Fi, and radio frequency identification (RFID), often combined with Apps and cloud technology. Finally, critical analysis and comparisons of the different discussed solutions are presented, highlighting their potential and providing new insights for developing innovative tools for facing future pandemics.
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Tachiquin, R., Velazquez, R., Del-Valle-Soto, C., Gutierrez, C. A., Carrasco, M., De Fazio, R., et al. (2021). Wearable Urban Mobility Assistive Device for Visually Impaired Pedestrians Using a Smartphone and a Tactile-Foot Interface.21(16), 5274.
Abstract: This paper reports on the progress of a wearable assistive technology (AT) device designed to enhance the independent, safe, and efficient mobility of blind and visually impaired pedestrians in outdoor environments. Such device exploits the smartphone's positioning and computing capabilities to locate and guide users along urban settings. The necessary navigation instructions to reach a destination are encoded as vibrating patterns which are conveyed to the user via a foot-placed tactile interface. To determine the performance of the proposed AT device, two user experiments were conducted. The first one requested a group of 20 voluntary normally sighted subjects to recognize the feedback provided by the tactile-foot interface. The results showed recognition rates over 93%. The second experiment involved two blind voluntary subjects which were assisted to find target destinations along public urban pathways. Results show that the subjects successfully accomplished the task and suggest that blind and visually impaired pedestrians might find the AT device and its concept approach useful, friendly, fast to master, and easy to use.
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Varona, J., De Fazio, R., Velazquez, R., Giannoccaro, N. I., Carrasco, M., & Visconti, P. (2020). MEMS-based Micro-scale Wind Turbines as Energy Harvesters of the Convective Airflows in Microelectronic Circuits. Int. J. Renew. Energy. Res., 10(3), 1213–1225.
Abstract: As an alternative to conventional batteries and other energy scavenging techniques, this paper introduces the idea of using micro-turbines to extract energy from wind forces at the microscale level and to supply power to battery-less microsystems. Fundamental research efforts on the design, fabrication, and test of micro-turbines with blade lengths of just 160 μm are presented in this paper along with analytical models and preliminary experimental results. The proof-of-concept prototypes presented herein were fabricated using a standard polysilicon surface micro-machining silicon technology (PolyMUMPs) and could effectively transform the kinetic energy of the available wind into a torque that might drive an electric generator or directly power supply a micro-mechanical system. Since conventional batteries do not scale-down well to the microscale, wind micro-turbines have the potential for becoming a practical alternative power source for microsystems, as well as for extending the operating range of devices running on batteries.
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Velazquez, R., Pissaloux, E., Rodrigo, P., Carrasco, M., Giannoccaro, N. I., & Lay-Ekuakille, A. (2018). An Outdoor Navigation System for Blind Pedestrians Using GPS and Tactile-Foot Feedback. Appl. Sci.-Basel, 8(4), 15 pp.
Abstract: This paper presents a novel, wearable navigation system for visually impaired and blind pedestrians that combines a global positioning system (GPS) for user outdoor localization and tactile-foot stimulation for information presentation. Real-time GPS data provided by a smartphone are processed by dedicated navigation software to determine the directions to a destination. Navigational directions are then encoded as vibrations and conveyed to the user via a tactile display that inserts into the shoe. The experimental results showed that users were capable of recognizing with high accuracy the tactile feedback provided to their feet. The preliminary tests conducted in outdoor locations involved two blind users who were guided along 380-420 m predetermined pathways, while sharing the space with other pedestrians and facing typical urban obstacles. The subjects successfully reached the target destinations. The results suggest that the proposed system enhances independent, safe navigation of blind pedestrians and show the potential of tactile-foot stimulation in assistive devices.
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