Higher Institute on Territorial Systems for Innovation
PORTO Publications Open Repository TOrinoNot a member yet
91193 research outputs found
Sort by
Droplet breakage and coalescence in liquid-liquid dispersions: Comparison of different kernels with EQMOM and QMOM
No full textDroplet coalescence and breakage in turbulent liquid-liquid dispersions is simulated by using computational fluid dynamics (CFD) and population balance modeling. The multifractal (MF) formalism that takes into account internal intermittency was here used for the first time to describe breakage and coalescence in a surfactant-free dispersion. The log-normal Extended Quadrature Method of Moments (EQMOM) was for the first time coupled with a CFD multiphase solver. To assess the accuracy of the model, predictions are compared with experiments and other models (i.e., Coulalogou and Tavlarides kernels and Quadrature Method of Moments [QMOM]). EQMOM and QMOM resulted in similar predictions, but EQMOM provides a continuous reconstruction of the droplet-size distribution. Transient predictions obtained with the MF kernels result in a better agreement with the experiments
Reframing China's heritage conservation discourse. Learning by testing civic engagement tools in a historic rural village
No full textUsing Unbiased Autocorrelation to Enhance Kurtogram and Envelope Analysis Results for Rolling Element Bearing Diagnostics
No full textEnvelope analysis is one of the most advantageous methods for rolling element bearing diagnostics but finding the suitable frequency band for demodulation has been a substantial challenge for a long time. Introduction of spectral kurtosis (SK) mostly solved this problem but in situations where signal to noise ratio is very low or in presence of non-Gaussian noise this method will fail. This major drawback may noticeably decrease the effectiveness of the SK and goal of this paper is to overcome this problem. Vibration signals from rolling element bearings exhibit high levels of 2nd order cyclostationarity, especially in the presence of localised faults. A second-order cyclostationary signal is one whose autocovariance function is a periodic function of time: the proposed method, named Autogram by the authors, takes advantage of this property to enhance the conventional spectral kurtosis. First, a maximal overlap discrete wavelet packet transform (MODWPT) is adopted to split a signal in different frequency bands and central frequencies. Second, unbiased autocorrelation of the squared envelope is calculated to reduce the level of uncorrelated random noise. Third, kurtosis of the autocorrelation is computed and a two dimensional colormap, named Autogram, is presented in order to locate the optimal frequency band for demodulation. The purpose is to increase the detection and characterization of transients in the temporal signal, which contains the bearing defect frequencies as well as appropriate frequency at which the fault impulses are modulated. Finally, the Fourier transform is used to obtain a frequency domain representation of the envelope signal so to identify the defect frequencies of the bearing. The proposed method has been tested on experimental data and compared with literature results so to assess its performances in rolling element bearing diagnostics. The results are very positive, and bearing characteristic frequencies from signals masked by Gaussian and non-Gaussian background noise can be extracted
I molti linguaggi della tribù degli Houdini
No full textIL paper analizza sinteticamente i modi contemporanei del linguaggio per il progetto e la comunicazione del design contemporane
Fault-tolerant feature-based estimation of space debris motion and inertial properties
No full textThe exponential increase of the needs of people in the modern society and the contextual development of the space technologies have led to a significant use of the lower Earth's orbits for placing artificial satellites. The current overpopulation of these orbits also increased the interest of the major space agencies in technologies for the removal of at least the biggest spacecraft that have reached their end-life or have failed their mission. One of the key functionalities required in a mission for removing a non-cooperative spacecraft is the assessment of its kinematics and inertial properties. In a few cases, this information can be approximated by ground observations. However, a re-assessment after the rendezvous phase is of critical importance for refining the capture strategies preventing accidents. The CADET program (CApture and DE-orbiting Technologies), funded by Regione Piemonte and led by Aviospace s.r.l., involved Politecnico di Torino in the research for solutions to the above issue. This dissertation proposes methods and algorithms for estimating the location of the center of mass, the angular rate, and the moments of inertia of a passive object. These methods require that the chaser spacecraft be capable of tracking several features of the target through passive vision sensors. Because of harsh lighting conditions in the space environment, feature-based methods should tolerate temporary failures in detecting features. The principal works on this topic do not consider this important aspect, making it a characteristic trait of the proposed methods. Compared to typical v treatments of the estimation problem, the proposed techniques do not depend solely on state observers. However, methods for recovering missing information, like compressive sampling techniques, are used for preprocessing input data to support the efficient usage of state observers. Simulation results showed accuracy properties that are comparable to those of the best-known methods already proposed in the literature. The developed algorithms were tested in the laboratory staged by Aviospace s.r.l., whose name is CADETLab. The results of the experimental tests suggested the practical applicability of such algorithms for supporting a real active removal mission
Development of a Virtual Collision Sensor for Industrial Robots
No full textCollision detection is a fundamental issue for the safety of a robotic cell. While several common methods require specific sensors or the knowledge of the robot dynamic model, the proposed solution is constituted by a virtual collision sensor for industrial manipulators, which requires as inputs only the motor currents measured by the standard sensors that equip a manipulator and the estimated currents provided by an internal dynamic model of the robot (i.e., the one used inside its controller), whose structure, parameters and accuracy are not known. The collision detection is achieved by comparing the absolute value of the current residue with a time-varying, positive-valued threshold function, including an estimate of the model error and a bias term, corresponding to the minimum collision torque to be detected. The value of such a term, defining the sensor sensitivity, can be simply imposed as constant, or automatically customized for a specific robotic application through a learning phase and a subsequent adaptation process, to achieve a more robust and faster collision detection, as well as the avoidance of any false collision warnings, even in case of slow variations of the robot behavior. Experimental results are provided to confirm the validity of the proposed solution, which is already adopted in some industrial scenarios