DESDEMONA Achievements

DESDEMONA achievements constitute a series of steps beyond the status of knowledge at the EU funded project starting on 1st June 2018, in the development of novel design methods, systems, procedure and technical solution, to integrate sensing and automation technologies for the purpose of self-inspection and self-monitoring of steel structures. The obtained results will lead to an increment of the service life of existing and new steel civil and industrial infrastructure and to a decrease in the cost associated to inspections, improving human activities performed in difficult conditions, safety and workers’ potential by the use of advanced tools. The research succeeded to expand new high-quality standard and practices for steel structure inspection and maintenance through the interrelated development of the following actions: i) steel structure geometry and condition virtualization through data fusion of image processing, thermography and vibration measurements; ii) developing of procedure for steel defect detection by robotic and automatic systems such as Cable-Driven Parallel Manipulators (CDPM), Unmanned Aerial Vehicles (UAV), Wall Climbing Drone (WCD), Cable Climbing Robot (CCR) and Wheeled Robot (WR) iii) embedding sensor systems to revalorize and transform steel elements and structures into self-diagnostic (smart) elements and materials even through nanotechnologies, iv) realizing an experimental lab-based apparatus and a series of case studies inspected by intelligent and robotic systems. The project outcomes are determining an impact on the reduction of the cost of steel structures inspection and maintenance and on the increase of user safety and comfort in industrial and civil environment

Flexible joint robotic manipulator: Modeling and design of robust control law

This paper presents modeling and sophisticated control of a single Degree Of Freedom (DOF) flexible robotic arm. The derived model is based on Euler-Lagrange approach while the first and second order (super twisting) Sliding Mode Control (SMC) is proposed as a non-linear control strategy. The control laws are subjected to various test inputs including step and sinusoids to demonstrate their tracking efficiency by observing transient and steady state behaviours. Both orders of SMC are then compared to characterize the control performance in terms of robustness, handling external disturbances and chattering. Results dictate that the super twisting SMC is more accurate and robust against the external noise and chattering phenomena compared to the first order SMC

Virtual Prototyping of a Flexure-based RCC Device for Automated Assembly

The actual use of Industrial Robots (IR) for assembly systems requires the exertion of suitable strategies allowing to overcome shortcomings about IR poor precision and repeatability. In this paper, the practical issues that emerge during common \ue2\u80\u9cpeg-in-hole\ue2\u80\u9d assembly procedures are discussed. In particular, the use of passive Remote Center of Compliance (RCC) devices, capable of compensating the IR non-optimal performance in terms of repeatability, is investigated. The focus of the paper is the design and simulation of a flexure-based RCC that allows the prevention of jamming, due to possible positioning inaccuracies during peg insertion. The proposed RCC architecture comprises a set of flexural hinges, whose behavior is simulated via a CAE tool that provides built-in functions for modelling the motion of compliant members. For given friction coefficients of the contact surfaces, these numerical simulations allow to determine the maximum lateral and angular misalignments effectively manageable by the RCC device

Robotic friction stir welding—Seam-tracking control, force control and process supervision

Purpose – This study aims to enable robotic friction stir welding (FSW) in practice. The use of robots has hitherto been limited, because of the large contact forces necessary for FSW. These forces are detrimental for the position accuracy of the robot. In this context, it is not sufficient to rely on the robot’s internal sensors for positioning. This paper describes and evaluates a new method for overcoming this issue.Design/methodology/approach – A closed-loop robot control system for seam-tracking control and force control, running and recording data in real-time operation, was developed. The complete system was experimentally verified. External position measurements were obtained from a laser seam tracker and deviations from the seam were compensated for, using feedback of the measurements to a position controller.Findings – The proposed system was shown to be working well in overcoming position error. The system is flexible and reconfigurable for batch and short production runs. The welds were free of defects and had beneficial mechanical properties.Research limitations/implications – In the experiments, the laser seam tracker was used both for control feedback and for performance evaluation. For evaluation, it would be better to use yet another external sensor for position measurements, providing ground truth.Practical implications – These results imply that robotic FSW is practically realizable, with the accuracy requirements fulfilled.Originality/value – The method proposed in this research yields very accurate seam tracking as compared to previous research. This accuracy, in turn, is crucial for the quality of the resulting material.Keywords Friction stir welding, Robotics, Force control, Seam-tracking control, Control, Sensors, Robot weldin

Support vector machine based classification in condition monitoring of induction motors

Continuous and trouble-free operation of induction motors is an essential part of modern power and production plants. Faults and failures of electrical machinery may cause remarkable economical losses but also highly dangerous situations. In addition to analytical and knowledge-based models, application of data-based models has established a firm position in the induction motor fault diagnostics during the last decade. For example, pattern recognition with Neural Networks (NN) is widely studied. Support Vector Machine (SVM) is a novel machine learning method introduced in early 90's. It is based on the statistical learning theory presented by V.N. Vapnik, and it has been successfully applied to numerous classification and pattern recognition problems such as text categorization, image recognition and bioinformatics. SVM based classifier is built to minimize the structural misclassification risk, whereas conventional classification techniques often apply minimization of the empirical risk. Therefore, SVM is claimed to lead enhanced generalisation properties. Further, application of SVM results in the global solution for a classification problem. Thirdly, SVM based classification is attractive, because its efficiency does not directly depend on the dimension of classified entities. This property is very useful in fault diagnostics, because the number of fault classification features does not have to be drastically limited. However, SVM has not yet been widely studied in the area of fault diagnostics. Specifically, in the condition monitoring of induction motor, it does not seem to have been considered before this research. In this thesis, a SVM based classification scheme is designed for different tasks in induction motor fault diagnostics and for partial discharge analysis of insulation condition monitoring. Several variables are compared as fault indicators, and forces on rotor are found to be important in fault detection instead of motor current that is currently widely studied. The measurement of forces is difficult, but easily measurable vibrations are directly related to the forces. Hence, vibration monitoring is considered in more detail as the medium for the motor fault diagnostics. SVM classifiers are essentially 2-class classifiers. In addition to the induction motor fault diagnostics, the results of this thesis cover various methods for coupling SVMs for carrying out a multi-class classification problem.reviewe

Human-Robot Collaborative Force-Controlled Micro-Drilling for Advanced Manufacturing and Medical Applications

Robotic drilling finds applications in diverse fields ranging from advanced manufacturing to the medical industry. Recent advances in low-cost, and human-safe, collaborative robots (e.g., Sawyer) are enabling us to rethink the possibilities in which robots can be deployed for such tedious and time-consuming tasks. This thesis presents a robotic drilling methodology with features of force-control enabled micro-drilling and human-robot collaboration to reduce programming efforts and enhance drilling performance. A Sawyer robot from Rethink Robotics, which offers safe physical interactions with a human co-worker, kinesthetic teaching, and force control, is used as the test bed. The robot’s end-effector was equipped with a Dremel drill fit into a housing, which was custom designed and 3D-printed using an Object Prime 3D-printer. The proposed approach applies human-robot collaboration in two cases. First, a human kinesthetically teaches a set of drill coordinates by physically holding the robot and guiding it to those locations. The robot then executes the drilling task by moving to these recorded locations. This thereby avoids the need to specify the drill coordinates with respect to a fixed reference frame, leading to reduction in programming effort and setup time while transitioning between different drilling jobs. Second, drilled hole quality is shown to be enhanced when a human provides nominal physical support to the robot during certain drilling tasks. An experimental analysis of the impact of force control on micro-drilling revealed that the proposed robotic system is capable of successfully drilling holes with a drill bit of 0.5 mm diameter with an error of +/- 0.05 mm, without breaking it for more than 100 holes. The proposed robotic drilling was validated in the following application domain: micro-drilling for composite repairs based on the through-thickness reinforcement (TTR) technique. For this purpose, sandwich beam samples were prepared by using pre-preg unidirectional carbon fabric face sheets with a honeycomb core, and they were subjected to four-point static loading until de-bonding occurred between the face sheet and the core. The samples were then repaired using the TTR technique, where the proposed robotic drilling was used to drill holes of 0.75 mm diameter in the damaged area of the sample and carbon fiber rods and with low-viscosity epoxy, were manually inserted into these drilled holes. The results revealed that the sandwich beam regained effective compressive strength after going through the TTR technique. Experiments also reveal the potential of the proposed robotic drilling technique in aerospace and automotive manufacturing involving drilling in complex postures and micro-drilling for orthopedic applications

Horizon 2020-funded security research projects with dual-use potential: An overview (2014-2018)

The analysis carried out in this report facilitates the identification of dual-use research topics and projects funded under Horizon 2020 that have a dual-use civilian/military potential, the results of which could be applied both by security and defence stakeholders (including industry). In this way, it could support the future security and defence research programmes in their attempt of avoiding duplication of investments and promoting synergies.JRC.E.7-Knowledge for Security and Migratio

Novel robot arm design and implementation for hot forging press automation

Manual handling of hot and heavy workpiece in forging press industry increases the process time and causes safety risks to workers. To increase the productivity and optimise the use of manpower, manipulators are needed to be designed for supporting the workers handling the workpiece. Designing robots for such applications is challenging since the robot suffers from a heavy payload at the arm tip, and it operates at a high speed in a large workspace. This research addresses the design and implementation of a novel robot for handling workpiece for a given forging press cell. A novel robotic mechanism is designed with two key features: (i) the addition of parallel links in between serial links and (ii) the use of hydraulic actuators for driving robot’s joints. The addition of parallel links and the use of hydraulic cylinders are to increase the structural rigidity. It is also to reduce the number of joint variables and restrict the end-effector moving parallel to the ground surface so that the robot grips and releases the workpiece in a more efficient and simplified manner. The effectiveness of the designed robot mechanism is demonstrated through functional tests, and experimental results are carried out on the implemented robot

Process monitoring for material extrusion additive manufacturing: a state-of-the-art review

Qualitative uncertainties are a key challenge for the further industrialization of additive manufacturing. To solve this challenge, methods for measuring the process states and properties of parts during additive manufacturing are essential. The subject of this review is in-situ process monitoring for material extrusion additive manufacturing. The objectives are, first, to quantify the research activity on this topic, second, to analyze the utilized technologies, and finally, to identify research gaps. Various databases were systematically searched for relevant publications and a total of 221 publications were analyzed in detail. The study demonstrated that the research activity in this field has been gaining importance. Numerous sensor technologies and analysis algorithms have been identified. Nonetheless, research gaps exist in topics such as optimized monitoring systems for industrial material extrusion facilities, inspection capabilities for additional quality characteristics, and standardization aspects. This literature review is the first to address process monitoring for material extrusion using a systematic and comprehensive approach