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The recognition of livestock activity is essential to be eligible for subsides, to automatically supervise critical activities and to locate stray animals. In recent decades, research has been carried out into animal detection, but this paper also analyzes the detection of other key elements that can be used to verify the presence of livestock activity in a given terrain: manure piles, feeders, silage balls, silage storage areas, and slurry pits. In recent years, the trend is to apply Convolutional Neuronal Networks (CNN) as they offer significantly better results than those obtained by traditional techniques. To implement a livestock activity detection service, the following object detection algorithms have been evaluated: YOLOv2, YOLOv4, YOLOv5, SSD, and Azure Custom Vision. Since YOLOv5 offers the best results, producing a mean average precision (mAP) of 0.94, this detector is selected for the creation of a livestock activity recognition service. In order to deploy the service in the best infrastructure, the performance/cost ratio of various Azure cloud infrastructures are analyzed and compared with a local solution. The result is an efficient and accurate service that can help to identify the presence of livestock activity in a specified terrain.
Darío Lema; Oscar Pedrayes; Rubén Usamentiaga; Daniel García; Ángela Alonso. Cost-Performance Evaluation of a Recognition Service of Livestock Activity Using Aerial Images. Remote Sensing 2021, 13, 2318 .
AMA StyleDarío Lema, Oscar Pedrayes, Rubén Usamentiaga, Daniel García, Ángela Alonso. Cost-Performance Evaluation of a Recognition Service of Livestock Activity Using Aerial Images. Remote Sensing. 2021; 13 (12):2318.
Chicago/Turabian StyleDarío Lema; Oscar Pedrayes; Rubén Usamentiaga; Daniel García; Ángela Alonso. 2021. "Cost-Performance Evaluation of a Recognition Service of Livestock Activity Using Aerial Images." Remote Sensing 13, no. 12: 2318.
Land use classification using aerial imagery can be complex. Characteristics such as ground sampling distance, resolution, number of bands and the information these bands convey are the keys to its accuracy. Random Forest is the most widely used approach but better and more modern alternatives do exist. In this paper, state-of-the-art methods are evaluated, consisting of semantic segmentation networks such as UNet and DeepLabV3+. In addition, two datasets based on aircraft and satellite imagery are generated as a new state of the art to test land use classification. These datasets, called UOPNOA and UOS2, are publicly available. In this work, the performance of these networks and the two datasets generated are evaluated. This paper demonstrates that ground sampling distance is the most important factor in obtaining good semantic segmentation results, but a suitable number of bands can be as important. This proves that both aircraft and satellite imagery can produce good results, although for different reasons. Finally, cost performance for an inference prototype is evaluated, comparing various Microsoft Azure architectures. The evaluation concludes that using a GPU is unnecessarily costly for deployment. A GPU need only be used for training.
Oscar Pedrayes; Darío Lema; Daniel García; Rubén Usamentiaga; Ángela Alonso. Evaluation of Semantic Segmentation Methods for Land Use with Spectral Imaging Using Sentinel-2 and PNOA Imagery. Remote Sensing 2021, 13, 2292 .
AMA StyleOscar Pedrayes, Darío Lema, Daniel García, Rubén Usamentiaga, Ángela Alonso. Evaluation of Semantic Segmentation Methods for Land Use with Spectral Imaging Using Sentinel-2 and PNOA Imagery. Remote Sensing. 2021; 13 (12):2292.
Chicago/Turabian StyleOscar Pedrayes; Darío Lema; Daniel García; Rubén Usamentiaga; Ángela Alonso. 2021. "Evaluation of Semantic Segmentation Methods for Land Use with Spectral Imaging Using Sentinel-2 and PNOA Imagery." Remote Sensing 13, no. 12: 2292.
Infrared thermography has become a mature and widely accepted technology with applications in many different fields, from medical to industrial
Rubén Usamentiaga; Pablo Venegas. Infrared Imaging and NDT. Applied Sciences 2021, 11, 3024 .
AMA StyleRubén Usamentiaga, Pablo Venegas. Infrared Imaging and NDT. Applied Sciences. 2021; 11 (7):3024.
Chicago/Turabian StyleRubén Usamentiaga; Pablo Venegas. 2021. "Infrared Imaging and NDT." Applied Sciences 11, no. 7: 3024.
In this paper a surface inspection system for rails is presented. Rails must meet the strict requirements of international quality standards, however there are few commercial surface inspection systems for rails and also, a lack of publications describing the design and configuration of inspection systems in detail. Therefore, manufacturers must develop their own systems or buy one of the few commercial ones available. These systems also need a long, cumbersome and expensive configuration process the manufacturer cannot perform without the assistance of the inspection system provider. The system proposed in this paper needs a set of samples and the requirements of the international standards to carry out an automatic configuration process avoiding the cost of manual configuration. The system uses four profilometers to acquire the surface of the rail. The acquired data is compared to a mathematical model of the rail to generate differential topographic images of the surface of the rail. Then a computer vision algorithm is used to detect defects based on the tolerances established in the international quality standards. The system has been tested and validated using a set of rails and a rail pattern from ArcelorMittal, with better results than the other two systems installed in a factory.
Francisco J. Delacalle; Daniel F. Garcia; Ruben Usamentiaga. Rail Surface Inspection System Using Differential Topographic Images. IEEE Transactions on Industry Applications 2021, 57, 2994 -3003.
AMA StyleFrancisco J. Delacalle, Daniel F. Garcia, Ruben Usamentiaga. Rail Surface Inspection System Using Differential Topographic Images. IEEE Transactions on Industry Applications. 2021; 57 (3):2994-3003.
Chicago/Turabian StyleFrancisco J. Delacalle; Daniel F. Garcia; Ruben Usamentiaga. 2021. "Rail Surface Inspection System Using Differential Topographic Images." IEEE Transactions on Industry Applications 57, no. 3: 2994-3003.
Dimensional quality control is a key issue in product manufacturing, particularly in long products such as rails or beams. To this end, international standards define precise methods to test if the dimensions are within the established tolerances, indicating whether they meet the required specification. The standards describe these methods using gauges that technicians can use to manually verify the dimensions of the product. In some cases, these methods provide different results from automated procedures, as they are based on different principles. To eliminate these discrepancies, this work proposes a novel automated method that emulates manual testing using virtual gauges. The proposed approach is based on an iterative procedure that aligns virtual gauges with the measured product shape, preventing one shape from penetrating another. This is achieved by assigning different weights to point correspondences according to their position. The result perfectly emulates the manual procedure, substituting the long and tedious manual procedure with a fast and robust automated alternative. Moreover, the proposed method can be applied to any dimensions with any type of gauge. Extensive tests with synthetic and manufactured rails corroborate the success of this approach.
Ruben Usamentiaga; Daniel F. Garcia; Francisco J. Delacalle. Automated Virtual Gauges for Dimensional Quality Control. IEEE Transactions on Industry Applications 2021, 57, 2983 -2993.
AMA StyleRuben Usamentiaga, Daniel F. Garcia, Francisco J. Delacalle. Automated Virtual Gauges for Dimensional Quality Control. IEEE Transactions on Industry Applications. 2021; 57 (3):2983-2993.
Chicago/Turabian StyleRuben Usamentiaga; Daniel F. Garcia; Francisco J. Delacalle. 2021. "Automated Virtual Gauges for Dimensional Quality Control." IEEE Transactions on Industry Applications 57, no. 3: 2983-2993.
Infrared thermography is a widely used technology that has been successfully applied to many and varied applications. These applications include the use as a non-destructive testing tool to assess the integrity state of materials. The current level of development of this application is high and its effectiveness is widely verified. There are application protocols and methodologies that have demonstrated a high capacity to extract relevant information from the captured thermal signals and guarantee the detection of anomalies in the inspected materials. However, there is still room for improvement in certain aspects, such as the increase of the detection capacity and the definition of a detailed characterization procedure of indications, that must be investigated further to reduce uncertainties and optimize this technology. In this work, an innovative thermographic data analysis methodology is proposed that extracts a greater amount of information from the recorded sequences by applying advanced processing techniques to the results. The extracted information is synthesized into three channels that may be represented through real color images and processed by quaternion algebra techniques to improve the detection level and facilitate the classification of defects. To validate the proposed methodology, synthetic data and actual experimental sequences have been analyzed. Seven different definitions of signal-to-noise ratio (SNR) have been used to assess the increment in the detection capacity, and a generalized application procedure has been proposed to extend their use to color images. The results verify the capacity of this methodology, showing significant increments in the SNR compared to conventional processing techniques in thermographic NDT.
Pablo Venegas; Rubén Usamentiaga; Juan Perán; Idurre Sáez De Ocáriz. Quaternion Processing Techniques for Color Synthesized NDT Thermography. Applied Sciences 2021, 11, 790 .
AMA StylePablo Venegas, Rubén Usamentiaga, Juan Perán, Idurre Sáez De Ocáriz. Quaternion Processing Techniques for Color Synthesized NDT Thermography. Applied Sciences. 2021; 11 (2):790.
Chicago/Turabian StylePablo Venegas; Rubén Usamentiaga; Juan Perán; Idurre Sáez De Ocáriz. 2021. "Quaternion Processing Techniques for Color Synthesized NDT Thermography." Applied Sciences 11, no. 2: 790.
Solar energy is mostly harnessed in arid areas where a high concentration of atmospheric dust represents a major environmental degradation factor. Gravitationally settled particles and other solid particles on the surface of the photovoltaic panels or thermal collectors greatly reduce the absorbed solar energy. Therefore, frequent cleaning schedules are required, consuming high quantities of water in regions where water precipitation is rare. The efficiency of this cleaning maintenance is greatly improved when methods to estimate the degree of cleanness are introduced. This work focuses on the need for better detecting the degradation created by dust deposition, considering experimental data based on different air pollutants, and analyzing the resulting thermal and visible signatures under different operating environments. Experiments are performed using six different types of pollutants applied to the surface of parabolic trough collectors while varying the pollutant density. The resulting reflectivity in the visible and infrared spectrum is calculated and compared. Results indicate that the pollutants can be distinguished, although the reflectivity greatly depends on the combination of the particle size of the pollutant and the applied amount, with greater impact from pollutants with small particles.
Rubén Usamentiaga; Alberto Fernández; Juan Luis Carús. Evaluation of Dust Deposition on Parabolic Trough Collectors in the Visible and Infrared Spectrum. Sensors 2020, 20, 6249 .
AMA StyleRubén Usamentiaga, Alberto Fernández, Juan Luis Carús. Evaluation of Dust Deposition on Parabolic Trough Collectors in the Visible and Infrared Spectrum. Sensors. 2020; 20 (21):6249.
Chicago/Turabian StyleRubén Usamentiaga; Alberto Fernández; Juan Luis Carús. 2020. "Evaluation of Dust Deposition on Parabolic Trough Collectors in the Visible and Infrared Spectrum." Sensors 20, no. 21: 6249.
Camera calibration requires three steps: estimation of correspondences between world and image coordinates, computation of a linear solution, and nonlinear optimization using the linear estimate as a starting point. The resulting accuracy depends mostly on the first and final steps. However, the nonlinear optimization method can achieve an accurate result only when given an initial estimate close to the global solution. Therefore, obtaining a good linear estimation is crucial for the performance of the camera calibration procedure. This work proposes a robust method to estimate a linear solution for the calibration of line-scan cameras, resulting in individual intrinsic and extrinsic parameters by using only a single line scan. The calculated parameters can then be used by nonlinear optimization methods to finely adjust the estimation of all the line-scan camera parameters, including distortions. The proposed procedure does not impose restrictions on particular orientations, and always generates a well-conditioned problem that can be solved analytically with no optimization required. Extensive experiments are performed to verify the robustness and accuracy of the proposed method. The comparative results demonstrate that the proposed method provides excellent performance.
Ruben Usamentiaga; Daniel Garcia; Francisco Delacalle. Line-scan camera calibration: a robust linear approach. Applied Optics 2020, 59, 9443 -9453.
AMA StyleRuben Usamentiaga, Daniel Garcia, Francisco Delacalle. Line-scan camera calibration: a robust linear approach. Applied Optics. 2020; 59 (30):9443-9453.
Chicago/Turabian StyleRuben Usamentiaga; Daniel Garcia; Francisco Delacalle. 2020. "Line-scan camera calibration: a robust linear approach." Applied Optics 59, no. 30: 9443-9453.
The efficiency and profitability of photovoltaic (PV) plants are highly controlled by their operation and maintenance (O&M) procedures. Today, the effective diagnosis of any possible fault of PV plants remains a technical and economic challenge, especially when dealing with large-scale PV plants. Currently, PV plant monitoring is carried out by either electrical performance measurements or image processing. The first approach presents limited fault detection ability, it is costly and time-consuming, and it is incapable of fast identification of the physical location of the fault. In the second approach, Infrared Thermography (IRT) imaging has been used for the characterization of PV module failures, but their setup and processing are rather complex and an experienced technician is required. The use of Unmanned Aerial Vehicles (UAVs) for IRT imaging of PV plants for health status monitoring of PV modules has been identified as a cost-effective approach that offers 10–-15 fold lower inspection times than conventional techniques. However, previous works have not performed a comprehensive approach in the context of automated UAV inspection using IRT. This work provides a fully automated approach for the: (a) detection, (b) classification, and (c) geopositioning of the thermal defects in the PV modules. The system has been tested on a real PV plant in Spain. The obtained results indicate that an autonomous solution can be implemented for a full characterization of the thermal defects.
Alberto Fernández; Rubén Usamentiaga; Pedro De Arquer; Miguel Ángel Fernández; D. Fernández; Juan Luis Carús; Manés Fernández. Robust Detection, Classification and Localization of Defects in Large Photovoltaic Plants Based on Unmanned Aerial Vehicles and Infrared Thermography. Applied Sciences 2020, 10, 5948 .
AMA StyleAlberto Fernández, Rubén Usamentiaga, Pedro De Arquer, Miguel Ángel Fernández, D. Fernández, Juan Luis Carús, Manés Fernández. Robust Detection, Classification and Localization of Defects in Large Photovoltaic Plants Based on Unmanned Aerial Vehicles and Infrared Thermography. Applied Sciences. 2020; 10 (17):5948.
Chicago/Turabian StyleAlberto Fernández; Rubén Usamentiaga; Pedro De Arquer; Miguel Ángel Fernández; D. Fernández; Juan Luis Carús; Manés Fernández. 2020. "Robust Detection, Classification and Localization of Defects in Large Photovoltaic Plants Based on Unmanned Aerial Vehicles and Infrared Thermography." Applied Sciences 10, no. 17: 5948.
Intelligent automation, including robotics, is one of the current trends in the manufacturing industry in the context of “Industry 4.0”, where cyber-physical systems control the production at automated or semi-automated factories. Robots are perfect substitutes for a skilled workforce for some repeatable, general, and strategically-important tasks. However, this transformation is not always feasible and immediate, since certain technologies do not provide the required degree of flexibility. The introduction of collaborative robots in the industry permits the combination of the advantages of manual and automated production. In some processes, it is necessary to incorporate robots from different manufacturers, thus the design of these multi-robot systems is crucial to guarantee the maximum quality and efficiency. In this context, this paper presents a novel methodology for process automation design, enhanced implementation, and real-time monitoring in operation based on creating a digital twin of the manufacturing process with an immersive virtual reality interface to be used as a virtual testbed before the physical implementation. Moreover, it can be efficiently used for operator training, real-time monitoring, and feasibility studies of future optimizations. It has been validated in a use case which provides a solution for an assembly manufacturing process.
Luis Pérez; Silvia Rodríguez-Jiménez; Nuria Rodríguez; Rubén Usamentiaga; Daniel F. García. Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning. Applied Sciences 2020, 10, 3633 .
AMA StyleLuis Pérez, Silvia Rodríguez-Jiménez, Nuria Rodríguez, Rubén Usamentiaga, Daniel F. García. Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning. Applied Sciences. 2020; 10 (10):3633.
Chicago/Turabian StyleLuis Pérez; Silvia Rodríguez-Jiménez; Nuria Rodríguez; Rubén Usamentiaga; Daniel F. García. 2020. "Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning." Applied Sciences 10, no. 10: 3633.
Current industrial products must meet quality requirements defined by international standards. Most commercial surface inspection systems give qualitative detections after a long, cumbersome and very expensive configuration process made by the seller company. In this paper, a new surface defect detection method is proposed based on 3D laser reconstruction. The method compares the long products, scan by scan, with their desired shape and produces differential topographic images of the surface at very high speeds. This work proposes a novel method where the values of the pixels in the images have a direct translation to real-world dimensions, which enables a detection based on the tolerances defined by international standards. These images are processed using computer vision techniques to detect defects and filter erroneous detections using both statistical distributions and a multilayer perceptron. Moreover, a systematic configuration procedure is proposed that is repeatable and can be performed by the manufacturer. The method has been tested using train track rails, which reports better results than two photometric systems including one commercial system, in both defect detection and erroneous detection rate. The method has been validated using a surface inspection rail pattern showing excellent performance.
F.J. Delacalle Herrero; Daniel F. García; Rubén Usamentiaga. Surface Defect System for Long Product Manufacturing Using Differential Topographic Images. Sensors 2020, 20, 2142 .
AMA StyleF.J. Delacalle Herrero, Daniel F. García, Rubén Usamentiaga. Surface Defect System for Long Product Manufacturing Using Differential Topographic Images. Sensors. 2020; 20 (7):2142.
Chicago/Turabian StyleF.J. Delacalle Herrero; Daniel F. García; Rubén Usamentiaga. 2020. "Surface Defect System for Long Product Manufacturing Using Differential Topographic Images." Sensors 20, no. 7: 2142.
Infrared thermography is nowadays used in a wide range of applications. In the steel industry, infrared thermography is mostly used for temperature measurement, which is required for process and quality control. In this work, a high-speed temperature monitoring system for steel strips is proposed. The proposed system is based on infrared line-scanners, which are the most suitable devices for temperature monitoring of moving objects. Accurate temperature measurement is critical for this type of application. Therefore, a rigorous methodology to apply quantitative thermography is presented. In addition, this work proposes accurate temperature and spatial calibrations, including a geometrical model, calibration targets and an optimization procedure. The proposed calibrations open up the possibility of detecting regions of interest in the resulting thermograms, determining the position with accuracy while avoiding distortions. The proposed system is applied to a real industrial application: temperature monitoring in cold rolling. Tests show excellent performance, producing accurate results that provide detailed information about the temperature of very long steel strips.
Ruben Usamentiaga; Daniel F. Garcia; Jesus Maria Perez; Garcia Daniel. High-Speed Temperature Monitoring for Steel Strips Using Infrared Line Scanners. IEEE Transactions on Industry Applications 2020, 56, 3261 -3271.
AMA StyleRuben Usamentiaga, Daniel F. Garcia, Jesus Maria Perez, Garcia Daniel. High-Speed Temperature Monitoring for Steel Strips Using Infrared Line Scanners. IEEE Transactions on Industry Applications. 2020; 56 (3):3261-3271.
Chicago/Turabian StyleRuben Usamentiaga; Daniel F. Garcia; Jesus Maria Perez; Garcia Daniel. 2020. "High-Speed Temperature Monitoring for Steel Strips Using Infrared Line Scanners." IEEE Transactions on Industry Applications 56, no. 3: 3261-3271.
Surface metrology in automated quality inspection is a field, among many others, affected by noise and thus requiring filtering. In surface metrology, filtering is required to remove undesired information from data in order to extract surface features and relevant properties necessary for quality control. Moreover, filtering requires immediate results, while the product is being manufactured. This way, quick correcting actions can be directly applied to solve possible manufacturing issues. This work proposes different strategies to filter height maps in real-time acquired using laser profilers, the most widely used inspection method in industrial applications. Different models to apply the filtering operations are considered, particularly assessing different alternatives to store previous samples in memory, which are required for data filtering. FIFO, double FIFO, circular and double circular buffers are evaluated. Furthermore, CPU parallelism, SIMD instructions and cache-line friendly data structures are analyzed. The proposed methods are extremely efficient, capable of filtering laser profiles at extremely high acquisition rates. The proposed methods are designed for real-time surface metrology, but they are very likely to find potential applications in different areas. The filters are compared in terms of accuracy and speed, including other well-known filters such as the spline filter. Tests analyze execution time, including cache efficiency and filtering accuracy. Results with synthetic data and real data obtained from steel strips show excellent performance, providing accurate results at very high speeds.
R. Usamentiaga. Real-time filtering on parallel SIMD architectures for automated quality inspection. Journal of Real-Time Image Processing 2020, 18, 127 -141.
AMA StyleR. Usamentiaga. Real-time filtering on parallel SIMD architectures for automated quality inspection. Journal of Real-Time Image Processing. 2020; 18 (1):127-141.
Chicago/Turabian StyleR. Usamentiaga. 2020. "Real-time filtering on parallel SIMD architectures for automated quality inspection." Journal of Real-Time Image Processing 18, no. 1: 127-141.
This paper analyzes the application of an innovative method for thermographic NDT data processing to inspections on real aeronautical components. The results provided by this method are related to thermal diffusivity values obtained by projecting the characteristics of a 3D thermal diffusion model onto one of the coordinate planes. In previous studies, laboratory experiments demonstrated that this method produces a higher increase in the signal-to-noise ratio (SNR) compared to conventional processing algorithms and it also provides a novel way of representing detected defects identifying the area affected by the lateral thermal diffusion effect.
P. Venegas; J. Perán; R. Usamentiaga; I. Sáez De Ocáriz. NDT inspection of aeronautical components by projected thermal diffusivity analysis. Quantitative InfraRed Thermography Journal 2019, 18, 34 -49.
AMA StyleP. Venegas, J. Perán, R. Usamentiaga, I. Sáez De Ocáriz. NDT inspection of aeronautical components by projected thermal diffusivity analysis. Quantitative InfraRed Thermography Journal. 2019; 18 (1):34-49.
Chicago/Turabian StyleP. Venegas; J. Perán; R. Usamentiaga; I. Sáez De Ocáriz. 2019. "NDT inspection of aeronautical components by projected thermal diffusivity analysis." Quantitative InfraRed Thermography Journal 18, no. 1: 34-49.
Calibration, registration, reconstruction and measurement are the fundamental tasks required for the inspection of dimensions in long steel products. Calibration is performed offline. The rest of the tasks are performed repeatedly while the long steel product is moved under 3D reconstruction sensors. This work proposes robust methods for the reconstruction of long steel products. In addition, measurement procedures for some representative dimensions are presented. Three different reconstruction procedures are proposed: reconstruction based on geometric primitives in the model of the product, reconstruction based on local fitting and reconstruction based on piecewise linear approximation. Tests on synthetic on real data indicate excellent performance in terms of computational costs and measurement accuracy. Conclusions also provide recommendations for the application of the proposed reconstruction procedures depending on whether a model is available or not, and the type of features that need to be calculated for the long steel products.
Ruben Usamentiaga; Daniel F. Garcia; Francisco Javier Delacalle Herrero. Geometric Reconstruction and Measurement of Long Steel Products Using 3-D Sensors in Real Time. IEEE Transactions on Industry Applications 2019, 55, 5476 -5486.
AMA StyleRuben Usamentiaga, Daniel F. Garcia, Francisco Javier Delacalle Herrero. Geometric Reconstruction and Measurement of Long Steel Products Using 3-D Sensors in Real Time. IEEE Transactions on Industry Applications. 2019; 55 (5):5476-5486.
Chicago/Turabian StyleRuben Usamentiaga; Daniel F. Garcia; Francisco Javier Delacalle Herrero. 2019. "Geometric Reconstruction and Measurement of Long Steel Products Using 3-D Sensors in Real Time." IEEE Transactions on Industry Applications 55, no. 5: 5476-5486.
Profile measuring is a key data acquisition process in the rail manufacturing industry. In rail rolling mills, profile measurement systems inspect the shape of the rail profiles to assess their dimensional quality. This assessment can be used in order to provide feedback for shape control devices in upstream manufacturing, and also to check whether the products are compliant with rail standards and client requirements. This paper deals with designing autonomic computing capabilities, specifically self-awareness, to a rail profile measurement system based on laser range finding, and then evaluating their suitability for the following tasks: i) automatically detect changes in both the working environment and the operating conditions; and ii) warn process computers and operators of the rail rolling mill when working conditions indicate that the accuracy of the inspection system has fallen below a given threshold.
Alvaro Fernandez Millara; Julio Molleda; Ruben Usamentiaga; Daniel F. Garcia; Garcia Daniel. Profile Measurement of Rails in a Rolling Mill: Implementing and Evaluating Autonomic Computing Capabilities. IEEE Transactions on Industry Applications 2019, 55, 5466 -5475.
AMA StyleAlvaro Fernandez Millara, Julio Molleda, Ruben Usamentiaga, Daniel F. Garcia, Garcia Daniel. Profile Measurement of Rails in a Rolling Mill: Implementing and Evaluating Autonomic Computing Capabilities. IEEE Transactions on Industry Applications. 2019; 55 (5):5466-5475.
Chicago/Turabian StyleAlvaro Fernandez Millara; Julio Molleda; Ruben Usamentiaga; Daniel F. Garcia; Garcia Daniel. 2019. "Profile Measurement of Rails in a Rolling Mill: Implementing and Evaluating Autonomic Computing Capabilities." IEEE Transactions on Industry Applications 55, no. 5: 5466-5475.
Nowadays, we are involved in the fourth industrial revolution, commonly referred to as “Industry 4.0,” where cyber-physical systems and intelligent automation, including robotics, are the keys. Traditionally, the use of robots has been limited by safety and, in addition, some manufacturing tasks are too complex to be fully automated. Thus, human-robot collaborative applications, where robots are not isolated, are necessary in order to increase the productivity ensuring the safety of the operators with new perception systems for the robot and new interaction interfaces for the human. Moreover, virtual reality has been extended to the industry in the last years, but most of its applications are not related to robots. In this context, this paper works on the synergies between virtual reality and robotics, presenting the use of commercial gaming technologies to create a totally immersive environment based on virtual reality. This environment includes an interface connected to the robot controller, where the necessary mathematical models have been implemented for the control of the virtual robot. The proposed system can be used for training, simulation, and what is more innovative, for robot controlling in an integrated, non-expensive and unique application. Results show that the immersive experience increments the efficiency of the training and simulation processes, offering a cost-effective solution.
Luis Pérez; Eduardo Diez; Rubén Usamentiaga; Daniel F. García. Industrial robot control and operator training using virtual reality interfaces. Computers in Industry 2019, 109, 114 -120.
AMA StyleLuis Pérez, Eduardo Diez, Rubén Usamentiaga, Daniel F. García. Industrial robot control and operator training using virtual reality interfaces. Computers in Industry. 2019; 109 ():114-120.
Chicago/Turabian StyleLuis Pérez; Eduardo Diez; Rubén Usamentiaga; Daniel F. García. 2019. "Industrial robot control and operator training using virtual reality interfaces." Computers in Industry 109, no. : 114-120.
The current manufacturing industries need efficient quality control systems to ensure their products are free of defects. In most cases, surface inspection is carried out by automatic systems that process 2D images which lack measurable information such as the height or depth of the surface defects. An alternative technology for surface inspection is laser scanning. Using this technique, a 3D representation of a product can be generated and therefore, defects can be easily measured. This paper proposes a real-time algorithm to generate differential topographic images of the surface of a product using laser scanning. The images generated by the proposed method are a flattened representation of the surface of the product which compare it to a perfect-shaped product. In these images, the volumetric defects can be easily segmented and measured using computer vision techniques to fulfill the requirements of the international standards of quality. The proposed algorithm is tested on 500,000 profiles meeting the constraints of real time.
F. J. Delacalle; Daniel García; Rubén Usamentiaga. Generation of differential topographic images for surface inspection of long products. Journal of Real-Time Image Processing 2019, 17, 967 -980.
AMA StyleF. J. Delacalle, Daniel García, Rubén Usamentiaga. Generation of differential topographic images for surface inspection of long products. Journal of Real-Time Image Processing. 2019; 17 (4):967-980.
Chicago/Turabian StyleF. J. Delacalle; Daniel García; Rubén Usamentiaga. 2019. "Generation of differential topographic images for surface inspection of long products." Journal of Real-Time Image Processing 17, no. 4: 967-980.
Accurate camera calibration is a challenging task required for 3D reconstruction sensors. In structured light sensors based on laser line projection, it is necessary to determine the position and orientation of the camera relative to the laser plane. The standard approach based on laser plane fitting requires a difficult setup, particularly in multi-camera configurations. This work proposes a calibration method based on a calibration plate with protruding cylinders. The projection of the laser line on the calibration plate produces a set of partial contours of ellipses, resulting from the projection of the cross section of the cylinders. These contours are used to calculate the position and orientation of the camera accurately. The proposed procedure is divided in two steps: a coarse calibration based on a robust estimator, which provides a rough approximation, and a fine calibration that iteratively optimizes the solution. The result is an accurate and robust procedure that can be applied to multiple cameras simultaneously on devices with limited computational power. Extended tests are used to validate the procedure with test pieces. Results indicate the calibration can be performed in 30 ms, producing a calibration error of only 0.027 mm.
R. Usamentiaga; D.F. Garcia. Multi-camera calibration for accurate geometric measurements in industrial environments. Measurement 2018, 134, 345 -358.
AMA StyleR. Usamentiaga, D.F. Garcia. Multi-camera calibration for accurate geometric measurements in industrial environments. Measurement. 2018; 134 ():345-358.
Chicago/Turabian StyleR. Usamentiaga; D.F. Garcia. 2018. "Multi-camera calibration for accurate geometric measurements in industrial environments." Measurement 134, no. : 345-358.
Large corporations require smart interconnected cyber-physical systems that can interact and cooperate to reach common goals. The design of complex monitoring and fault detection systems based on this approach, usually referred to as Industrial Internet of Things, creates interconnected physical systems that generate value by providing more efficient manufacturing opportunities. However, this approach also creates important challenges, as the large number of sensors and devices provokes difficulties for configuration, application deployment and service generation. This work presents solutions for this advanced automation model, proposing an architecture for temperature monitoring and fault detection in electrical substations using infrared thermography. In this work, systematic methods to apply flexible configurations and deployments are presented, including robust procedures to measure and monitor the temperature of electrical components. Architectural abstractions are also identified for this particular scenario. The proposed methodology and architecture proposed is validated in a real-life case study in a large industrial organization.
Ruben Usamentiaga; Miguel Angel Fernandez; Alberto Fernandez Villan; Juan Luis Carus. Temperature Monitoring for Electrical Substations Using Infrared Thermography: Architecture for Industrial Internet of Things. IEEE Transactions on Industrial Informatics 2018, 14, 5667 -5677.
AMA StyleRuben Usamentiaga, Miguel Angel Fernandez, Alberto Fernandez Villan, Juan Luis Carus. Temperature Monitoring for Electrical Substations Using Infrared Thermography: Architecture for Industrial Internet of Things. IEEE Transactions on Industrial Informatics. 2018; 14 (12):5667-5677.
Chicago/Turabian StyleRuben Usamentiaga; Miguel Angel Fernandez; Alberto Fernandez Villan; Juan Luis Carus. 2018. "Temperature Monitoring for Electrical Substations Using Infrared Thermography: Architecture for Industrial Internet of Things." IEEE Transactions on Industrial Informatics 14, no. 12: 5667-5677.