1,213 research outputs found

    Functional Nanomaterials and Polymer Nanocomposites: Current Uses and Potential Applications

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    This book covers a broad range of subjects, from smart nanoparticles and polymer nanocomposite synthesis and the study of their fundamental properties to the fabrication and characterization of devices and emerging technologies with smart nanoparticles and polymer integration

    In-line quality control for Zero Defect Manufacturing: design, development and uncertainty analysis of vision-based instruments for dimensional measurements at different scales

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    Lo scopo di questo progetto di dottorato industriale finanziato attraverso una borsa di studio della Regione Marche è stato quello di sviluppare ricerca con potenziale impatto su un settore industriale, promuovere il coinvolgimento delle fabbriche e delle imprese locali nella ricerca e innovazione svolta in collaborazione con l'università e produrre ricerca in linea con le esigenze dell'ambiente industriale, non solo a livello regionale. Quindi, attraverso la collaborazione con una torneria locale (Zannini SpA) e una piccola azienda high-tech focalizzata sull'introduzione dell'innovazione meccatronica nel settore della tornitura (Z4Tec srl), e anche grazie a una collaborazione internazionale con l'Università di Anversa, abbiamo progettato e sviluppato nuovi strumenti per il controllo qualità in linea, basati su tecnologie senza contatto, in particolare tecnologie elettro-ottiche. Portando anche l'attenzione sull'importanza di prendere in considerazione l'incertezza, poiché è fondamentale nel processo decisionale basato sui dati che sono alla base di una strategia di Zero Defect Manufacturing. Infatti, la scarsa qualità delle misure può pregiudicare la qualità dei dati. In particolare, questo lavoro presenta due strumenti di misura che sono stati progettati e sviluppati con lo scopo di effettuare controllo qualità in linea di produzione e l’incertezza di misura di ogni strumento è stata analizzata in confronto ad altri strumenti presenti sul mercato. Nella parte finale di questo lavoro si è valutata l’incertezza di un profilometro a triangolazione di linea laser. Pertanto, la ricerca condotta in questa tesi può essere organizzata in due obiettivi principali: lo sviluppo di nuovi sistemi di misura dimensionale basati sulla visione da implementare in linea di produzione e l'analisi dell'incertezza di questi strumenti di misura. Per il primo obiettivo ci siamo concentrati su due tipi di misure dimensionali imposte dall'industria manifatturiera: macroscopiche (misure in mm) e microscopiche (misure in µm). Per le misure macroscopiche l'obiettivo era il controllo in linea della qualità dimensionale di pezzi torniti attraverso la profilometria ottica telecentrica. Il campione da ispezionare è stato posto tra l'illuminatore e l'obiettivo per ottenere la proiezione dell'ombra del campione. Le misure sono state eseguite mediante analisi grafica dell'immagine. Abbiamo discusso le disposizioni meccaniche mirate a ottimizzare le immagini acquisite e i problemi che eventuali disallineamenti meccanici dei componenti potrebbero introdurre nella qualità delle immagini. Per le misure microscopiche abbiamo progettato un sistema di misurazione della rugosità superficiale basato sulla visione retroilluminata, con l'obiettivo di determinare le condizioni ottimali di imaging utilizzando la modulation transfer function e l'uso di una electrically tunable lens. Un campione tornito (un cilindro) è posto di fronte a una telecamera ed è retroilluminato da una sorgente di luce collimata; tale configurazione ottica fornisce l'immagine del bordo del campione. Per testare la sensibilità del sistema di misura è stata utilizzata una serie di campioni di acciaio torniti con diverse rugosità superficiali. Per il secondo obiettivo, le tecniche di valutazione dell'incertezza di misura utilizzate in questo lavoro sono state un'analisi dell'incertezza statistica di tipo A e un'analisi Gage R&R. Nel caso del profilometro telecentrico, l'analisi è stata eseguita in confronto con altri dispositivi presenti sul mercato con un'analisi di tipo A e una Gage R&R. L'incertezza di misura del profilometro si è rivelata sufficiente per ottenere risultati nell'intervallo di tolleranza richiesto. Per il sistema di visione retroilluminato, il confronto dei risultati è stato effettuato con altri strumenti allo stato dell'arte, con un'analisi di Tipo A. Il confronto ha mostrato che le prestazioni dello strumento retroilluminato dipendono dai valori di rugosità superficiale considerati; mentre a valori maggiori di rugosità l'offset aumenta, per valori inferiori di rugosità i risultati sono compatibili con quelli dello strumento di riferimento (a stilo). Infine, sono state valutate la ripetibilità e la riproducibilità di un profilometro a triangolazione di linea laser, attraverso uno studio Gage R&R. Ogni punto di misura è stato ispezionato da tre operatori e l'insieme dei dati è stato elaborato con un'analisi dell'incertezza di Tipo A. Successivamente, uno studio Gage R&R ha contribuito a indagare la ripetibilità, la riproducibilità e la variabilità del sistema. Questa analisi ha dimostrato un'incertezza accettabile.The purpose of this industrial PhD project financed through a scholarship from the Regione Marche was to develop research with potential impact on an industrial sector, to promote the involvement of local factories and companies in research and innovation performed jointly with the university and to produce research in line with the needs of the industrial environment, not only at regional level. Hence, through collaborating with a local turning factory (Zannini SpA) and a small high-tech company focused on introducing mechatronic innovation in the turning sector (Z4Tec srl), and also thanks to an international collaboration with the University of Antwerp, we designed and developed new instruments for in-line quality control, based on non-contact technologies, specifically electro-optical technologies. While also bringing attention to the importance of taking uncertainty into consideration, since it is pivotal in data-based decision making which are at the base of a Zero Defect Manufacturing strategy. This means that poor quality of measurements can prejudice the quality of the data. In particular, this work presents two measurement instruments that were designed and developed for the purpose of in-line quality control and the uncertainty of each of the two instruments was evaluated and analyzed in comparison with instruments already present on the market. In the last part of this work, the uncertainty of a hand-held laser-line triangulation profilometer is estimated. Hence, the research conducted in this thesis can be organized in two main objectives: the development of new vision-based dimensional measurement systems to be implemented in production line and the uncertainty analysis of these measurement instruments. For the first objective we focused on two types of dimensional measurements imposed by the manufacturing industry: macroscopic (measuring dimensions in mm) and microscopic (measuring roughness in µm). For macroscopic measurements the target was the in-production dimensional quality control of turned parts through telecentric optical profilometry. The sample to be inspected was placed between illuminator and objective in order to obtain the projection of the shadow of the sample over a white background. Dimensional measurements were then performed by means of image processing over the image obtained. We discussed the mechanical arrangements targeted to optimize images acquired as well as the main issues that eventual mechanical misalignments of components might introduce in the quality of images. For microscopic measurements we designed a backlit vision-based surface roughness measurement system with a focus on smart behaviors such as determining the optimal imaging conditions using the modulation transfer function and the use of an electrically tunable lens. A turned sample (a cylinder) is placed in front of a camera and it is backlit by a collimated source of light; such optical configuration provides the image of the edge of the sample. A set of turned steel samples with different surface roughness was used to test the sensitivity of the measurement system. For the second objective, the measurement uncertainty evaluation techniques used in this work were a Type A statistical uncertainty analysis and a Gage R&R analysis. In the case of the telecentric profilometer, the analysis was performed in comparison with other on-the-market devices with a Type A analysis and a Gage R&R analysis. The measurement uncertainty of the profilometer proved to be sufficient to obtain results within the tolerance interval required. For the backlit vision system, the comparison of the results was made with other state-of-the-art instruments, with a Type A analysis. The comparison showed that the performance of the backlit instrument depends on the values of surface roughness considered; while at larger values of roughness the offset increases, the results are compatible with the ones of the reference instrument (stylus-based) at lower values of roughness. Lastly, the repeatability and reproducibility of a laser-line triangulation profilometer were assessed, through a Gage R&R study. Each measuring point was inspected by three different operators and the data set has been, at first, processed by a Type A uncertainty analysis. Then, a Gage R&R study helped investigate repeatability, reproducibility and the system variability. This analysis showed that the presented laser-line triangulation system has an acceptable uncertainty

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    Fast Sensing and Adaptive Actuation for Robust Legged Locomotion

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    Robust legged locomotion in complex terrain demands fast perturbation detection and reaction. In animals, due to the neural transmission delays, the high-level control loop involving the brain is absent from mitigating the initial disturbance. Instead, the low-level compliant behavior embedded in mechanics and the mid-level controllers in the spinal cord are believed to provide quick response during fast locomotion. Still, it remains unclear how these low- and mid-level components facilitate robust locomotion. This thesis aims to identify and characterize the underlining elements responsible for fast sensing and actuation. To test individual elements and their interplay, several robotic systems were implemented. The implementations include active and passive mechanisms as a combination of elasticities and dampers in multi-segment robot legs, central pattern generators inspired by intraspinal controllers, and a synthetic robotic version of an intraspinal sensor. The first contribution establishes the notion of effective damping. Effective damping is defined as the total energy dissipation during one step, which allows quantifying how much ground perturbation is mitigated. Using this framework, the optimal damper is identified as viscous and tunable. This study paves the way for integrating effective dampers to legged designs for robust locomotion. The second contribution introduces a novel series elastic actuation system. The proposed system tackles the issue of power transmission over multiple joints, while featuring intrinsic series elasticity. The design is tested on a hopper with two more elastic elements, demonstrating energy recuperation and enhanced dynamic performance. The third contribution proposes a novel tunable damper and reveals its influence on legged hopping. A bio-inspired slack tendon mechanism is implemented in parallel with a spring. The tunable damping is rigorously quantified on a central-pattern-generator-driven hopping robot, which reveals the trade-off between locomotion robustness and efficiency. The last contribution explores the intraspinal sensing hypothesis of birds. We speculate that the observed intraspinal structure functions as an accelerometer. This accelerometer could provide fast state feedback directly to the adjacent central pattern generator circuits, contributing to birds’ running robustness. A biophysical simulation framework is established, which provides new perspectives on the sensing mechanics of the system, including the influence of morphologies and material properties. Giving an overview of the hierarchical control architecture, this thesis investigates the fast sensing and actuation mechanisms in several control layers, including the low-level mechanical response and the mid-level intraspinal controllers. The contributions of this work provide new insight into animal loco-motion robustness and lays the foundation for future legged robot design

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Tradition and Innovation in Construction Project Management

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    This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings

    Modern meat: the next generation of meat from cells

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    Modern Meat is the first textbook on cultivated meat, with contributions from over 100 experts within the cultivated meat community. The Sections of Modern Meat comprise 5 broad categories of cultivated meat: Context, Impact, Science, Society, and World. The 19 chapters of Modern Meat, spread across these 5 sections, provide detailed entries on cultivated meat. They extensively tour a range of topics including the impact of cultivated meat on humans and animals, the bioprocess of cultivated meat production, how cultivated meat may become a food option in Space and on Mars, and how cultivated meat may impact the economy, culture, and tradition of Asia

    Evaluating EEG–EMG Fusion-Based Classification as a Method for Improving Control of Wearable Robotic Devices for Upper-Limb Rehabilitation

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    Musculoskeletal disorders are the biggest cause of disability worldwide, and wearable mechatronic rehabilitation devices have been proposed for treatment. However, before widespread adoption, improvements in user control and system adaptability are required. User intention should be detected intuitively, and user-induced changes in system dynamics should be unobtrusively identified and corrected. Developments often focus on model-dependent nonlinear control theory, which is challenging to implement for wearable devices. One alternative is to incorporate bioelectrical signal-based machine learning into the system, allowing for simpler controller designs to be augmented by supplemental brain (electroencephalography/EEG) and muscle (electromyography/EMG) information. To extract user intention better, sensor fusion techniques have been proposed to combine EEG and EMG; however, further development is required to enhance the capabilities of EEG–EMG fusion beyond basic motion classification. To this end, the goals of this thesis were to investigate expanded methods of EEG–EMG fusion and to develop a novel control system based on the incorporation of EEG–EMG fusion classifiers. A dataset of EEG and EMG signals were collected during dynamic elbow flexion–extension motions and used to develop EEG–EMG fusion models to classify task weight, as well as motion intention. A variety of fusion methods were investigated, such as a Weighted Average decision-level fusion (83.01 ± 6.04% accuracy) and Convolutional Neural Network-based input-level fusion (81.57 ± 7.11% accuracy), demonstrating that EEG–EMG fusion can classify more indirect tasks. A novel control system, referred to as a Task Weight Selective Controller (TWSC), was implemented using a Gain Scheduling-based approach, dictated by external load estimations from an EEG–EMG fusion classifier. To improve system stability, classifier prediction debouncing was also proposed to reduce misclassifications through filtering. Performance of the TWSC was evaluated using a developed upper-limb brace simulator. Due to simulator limitations, no significant difference in error was observed between the TWSC and PID control. However, results did demonstrate the feasibility of prediction debouncing, showing it provided smoother device motion. Continued development of the TWSC, and EEG–EMG fusion techniques will ultimately result in wearable devices that are able to adapt to changing loads more effectively, serving to improve the user experience during operation

    Development of Motion Control Systems for Hydraulically Actuated Cranes with Hanging Loads

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    Automation has been used in industrial processes for several decades to increase efficiency and safety. Tasks that are either dull, dangerous, or dirty can often be performed by machines in a reliable manner. This may provide a reduced risk to human life, and will typically give a lower economic cost. Industrial robots are a prime example of this, and have seen extensive use in the automotive industry and manufacturing plants. While these machines have been employed in a wide variety of industries, heavy duty lifting and handling equipment such as hydraulic cranes have typically been manually operated. This provides an opportunity to investigate and develop control systems to push lifting equipment towards the same level of automation found in the aforementioned industries. The use of winches and hanging loads on cranes give a set of challenges not typically found on robots, which requires careful consideration of both the safety aspect and precision of the pendulum-like motion. Another difference from industrial robots is the type of actuation systems used. While robots use electric motors, the cranes discussed in this thesis use hydraulic cylinders. As such, the dynamics of the machines and the control system designmay differ significantly. In addition, hydraulic cranes may experience significant deflection when lifting heavy loads, arising from both structural flexibility and the compressibility of the hydraulic fluid. The work presented in this thesis focuses on motion control of hydraulically actuated cranes. Motion control is an important topic when developing automation systems, as moving from one position to another is a common requirement for automated lifting operations. A novel path controller operating in actuator space is developed, which takes advantage of the load-independent flow control valves typically found on hydraulically actuated cranes. By operating in actuator space the motion of each cylinder is inherently minimized. To counteract the pendulum-like motion of the hanging payload, a novel anti-swing controller is developed and experimentally verified. The anti-swing controller is able to suppress the motion from the hanging load to increase safety and precision. To tackle the challenges associated with the flexibility of the crane, a deflection compensator is developed and experimentally verified. The deflection compensator is able to counteract both the static deflection due to gravity and dynamic de ection due to motion. Further, the topic of adaptive feedforward control of pressure compensated cylinders has been investigated. A novel adaptive differential controller has been developed and experimentally verified, which adapts to system uncertainties in both directions of motion. Finally, the use of electro-hydrostatic actuators for motion control of cranes has been investigated using numerical time domain simulations. A novel concept is proposed and investigated using simulations.publishedVersio
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