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Is part of the Bibliography
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The maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future.
The integration of product data from heterogeneous sources and manufacturers into a single catalog is often still a laborious, manual task. Especially small- and medium-sized enterprises face the challenge of timely integrating the data their business relies on to have an up-to-date product catalog, due to format specifications, low quality of data and the requirement of expert knowledge. Additionally, modern approaches to simplify catalog integration demand experience in machine learning, word vectorization, or semantic similarity that such enterprises do not have. Furthermore, most approaches struggle with low-quality data. We propose Attribute Label Ranking (ALR), an easy to understand and simple to adapt learning approach. ALR leverages a model trained on real-world integration data to identify the best possible schema mapping of previously unknown, proprietary, tabular format into a standardized catalog schema. Our approach predicts multiple labels for every attribute of an inpu t column. The whole column is taken into consideration to rank among these labels. We evaluate ALR regarding the correctness of predictions and compare the results on real-world data to state-of-the-art approaches. Additionally, we report findings during experiments and limitations of our approach.
In the friction tests between honeycomb with film adhesive and prepreg, the relative displacement occurs between the film adhesive and the prepreg. The film adhesive does not shift relative to the honeycomb. This is consistent with the core crush behavior where the honeycomb moves together with the film adhesive, as can be seen in Figure 2(a). The pull-through forces of the friction measurements between honeycomb and prepreg at 1 mm deformation are plotted in Figure 17(a). While the friction at 100°C is similar to the friction at 120°C, it decreases significantly at 130°C and exhibits a minimum at 140°C. At 150°C, the friction rises again slightly and then sharply at 160°C. Since the viscosity of the M18/1 prepreg resin drops significantly before it cures [23], the minimum friction at 140°C could result from a minimum viscosity of the mixture of prepreg resin and film adhesive before the bond subsequently cures. Figure 17(b) shows the mean value curve of the friction measurements at 140°C. The error bars, which represent the standard deviation, reveal the good repeatability of the tests. The force curve is approximately horizontal between 1 mm and 2 mm. The friction then slightly rises. As with interlaminar friction measurements, this could be due to the fact that resin is removed by friction and the proportion of boundary lubrication increases. Figure 18 shows the surfaces after the friction measurement. The honeycomb cell walls are clearly visible in the film adhesive. There are areas where the film adhesive is completely removed and the carrier material of the film adhesive becomes visible. In addition, the viscosity of the resin changes as the curing progresses during the friction test. This can also affect the force-displacement curve.
To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.
Purpose
The aim of this study was to compare several osteosynthesis techniques (intramedullary headless compression screws, T-plates, and Kirschner wires) for distal epiphyseal fractures of proximal phalanges in a human cadaveric model.
Methods
A total of 90 proximal phalanges from 30 specimens (index, ring, and middle fingers) were used for this study. After stripping off all soft tissue, a transverse distal epiphyseal fracture was simulated at the proximal phalanx. The 30 specimens were randomly assigned to 1 fixation technique (30 per technique), either a 3.0-mm intramedullary headless compression screw, locking plate fixation with a 2.0-mm T-plate, or 2 oblique 1.0-mm Kirschner wires. Displacement analysis (bending, distraction, and torsion) was performed using optical tracking of an applied random speckle pattern after osteosynthesis. Biomechanical testing was performed with increasing cyclic loading and with cyclic load to failure using a biaxial torsion-tension testing machine.
Results
Cannulated intramedullary compression screws showed significantly less displacement at the fracture site in torsional testing. Furthermore, screws were significantly more stable in bending testing. Kirschner wires were significantly less stable than plating or screw fixation in any cyclic load to failure test setup.
Conclusions
Intramedullary compression screws are a highly stable alternative in the treatment of transverse distal epiphyseal phalangeal fractures. Kirschner wires seem to be inferior regarding displacement properties and primary stability.
Clinical relevance
Fracture fixation of phalangeal fractures using plate osteosynthesis may have the advantage of a very rigid reduction, but disadvantages such as stiffness owing to the more invasive surgical approach and soft tissue irritation should be taken into account. Headless compression screws represent a minimally invasive choice for fixation with good biomechanical properties.
We compare four different algorithms for automatically estimating the muscle fascicle angle from ultrasonic images: the vesselness filter, the Radon transform, the projection profile method and the gray level cooccurence matrix (GLCM). The algorithm results are compared to ground truth data generated by three different experts on 425 image frames from two videos recorded during different types of motion. The best agreement with the ground truth data was achieved by a combination of pre-processing with a vesselness filter and measuring the angle with the projection profile method. The robustness of the estimation is increased by applying the algorithms to subregions with high gradients and performing a LOESS fit through these estimates.
Purpose
This study aims to investigate the biomechanics of handcycling during a continuous load trial (CLT) to assess the mechanisms underlying fatigue in upper body exercise.
Methods
Twelve able-bodied triathletes performed a 30-min CLT at a power output corresponding to lactate threshold in a racing recumbent handcycle mounted on a stationary ergometer. During the CLT, ratings of perceived exertion (RPE), tangential crank kinetics, 3D joint kinematics, and muscular activity of ten muscles of the upper extremity and trunk were examined using motion capturing and surface electromyography.
Results
During the CLT, spontaneously chosen cadence and RPE increased, whereas crank torque decreased. Rotational work was higher during the pull phase. Peripheral RPE was higher compared to central RPE. Joint range of motion decreased for elbow-flexion and radial-duction. Integrated EMG (iEMG) increased in the forearm flexors, forearm extensors, and M. deltoideus (Pars spinalis). An earlier onset of activation was found for M. deltoideus (Pars clavicularis), M. pectoralis major, M. rectus abdominis, M. biceps brachii, and the forearm flexors.
Conclusion
Fatigue-related alterations seem to apply analogously in handcycling and cycling. The most distal muscles are responsible for force transmission on the cranks and might thus suffer most from neuromuscular fatigue. The findings indicate that peripheral fatigue (at similar lactate values) is higher in handcycling compared to leg cycling, at least for inexperienced participants. An increase in cadence might delay peripheral fatigue by a reduced vascular occlusion. We assume that the gap between peripheral and central fatigue can be reduced by sport-specific endurance training.
Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research. Thereby, in each decade the rapid development of technologies opened new room for investigation. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. The third wave of BI & A comprises unstructured and sensor data of mobile devices. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. By this means, the paper’s contribution is fourfold. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. The analysis provides an overview on the status quo of BI & A 3.0. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda.
For short take-off and landing (STOL) aircraft, a parallel hybrid-electric propulsion system potentially offers superior performance compared to a conventional propulsion system, because the short-take-off power requirement is much higher than the cruise power requirement. This power-matching problem can be solved with a balanced hybrid propulsion system. However, there is a trade-off between wing loading, power loading, the level of hybridization, as well as range and take-off distance. An optimization method can vary design variables in such a way that a minimum of a particular objective is attained. In this paper, a comparison between the optimization results for minimum mass, minimum consumed primary energy, and minimum cost is conducted. A new initial sizing algorithm for general aviation aircraft with hybrid-electric propulsion systems is applied. This initial sizing methodology covers point performance, mission performance analysis, the weight estimation process, and cost estimation. The methodology is applied to the design of a STOL general aviation aircraft, intended for on-demand air mobility operations. The aircraft is sized to carry eight passengers over a distance of 500 km, while able to take off and land from short airstrips. Results indicate that parallel hybrid-electric propulsion systems must be considered for future STOL aircraft.
Mechano-pharmacological testing of L-Type Ca²⁺ channel modulators via human vascular celldrum model
(2020)
Background/Aims: This study aimed to establish a precise and well-defined working model, assessing pharmaceutical effects on vascular smooth muscle cell monolayer in-vitro. It describes various analysis techniques to determine the most suitable to measure the biomechanical impact of vasoactive agents by using CellDrum technology. Methods: The so-called CellDrum technology was applied to analyse the biomechanical properties of confluent human aorta muscle cells (haSMC) in monolayer. The cell generated tensions deviations in the range of a few N/m² are evaluated by the CellDrum technology. This study focuses on the dilative and contractive effects of L-type Ca²⁺ channel agonists and antagonists, respectively. We analyzed the effects of Bay K8644, nifedipine and verapamil. Three different measurement modes were developed and applied to determine the most appropriate analysis technique for the study purpose. These three operation modes are called, particular time mode" (PTM), "long term mode" (LTM) and "real-time mode" (RTM). Results: It was possible to quantify the biomechanical response of haSMCs to the addition of vasoactive agents using CellDrum technology. Due to the supplementation of 100nM Bay K8644, the tension increased approximately 10.6% from initial tension maximum, whereas, the treatment with nifedipine and verapamil caused a significant decrease in cellular tension: 10nM nifedipine decreased the biomechanical stress around 6,5% and 50nM verapamil by 2,8%, compared to the initial tension maximum. Additionally, all tested measurement modes provide similar results while focusing on different analysis parameters. Conclusion: The CellDrum technology allows highly sensitive biomechanical stress measurements of cultured haSMC monolayers. The mechanical stress responses evoked by the application of vasoactive calcium channel modulators were quantified functionally (N/m²). All tested operation modes resulted in equal findings, whereas each mode features operation-related data analysis.