Julian Florez

Reduction of detent force in flat permanent magnet linear synchronous machines by means of three different methods

This paper proposes two different techniques to reduce detent force in flat permanent magnet linear synchronous motors (PMLSM). The first one is the choice of an optimal constructive design, taking into account the width and arrangement of the magnets, and the length and shape of the solid iron core. The second is the employment of a force compensator in the control algorithm, which counteracts the detent force effects. Both methods are based on a Fourier analysis of the detent force curve as a function of the machine position. The curve is broken down into harmonics. The constructive method considers that each harmonic has its peculiar source and is independent from the others. The force compensator employs a detent force model based on the Fourier series of the curve. The two methods were tested separately, and their results were compared. Experimental tests were performed to verify the effectiveness of the methods. A very important reduction with a constructive optimization of the machine was achieved. The reduction by means of a compensator in the control scheme also reaches excellent results. In order to achieve the maximum reduction of detent force, both techniques can be combined. This measure will increase the precision features of this kind of machine.

Advanced Hybrid Technology for Neurorehabilitation: The HYPER Project

Disabilities that follow cerebrovascular accidents and spinal cord injuries severely impair motor functions and thereby prevent the affected individuals from full and autonomous participation in activities of daily living. Rehabilitation therapy is needed in order to recover from those severe physical traumas. Where rehabilitation is not enough to restore completely human functions then functional compensation is required. In the last years the field of rehabilitation has been inspired by new available technologies. An example is given by rehabilitation robotics where machines are used to assist the patient in the execution of specific and physical task of the therapy. In both rehabilitation and functional compensation scenarios, the usability and cognitive aspects of human-machine interaction have yet to be solved efficiently by robotic-assisted solutions. Hybrid systems combining exoskeletal robots (ERs) with motor neuroprosthesis (MNPs) emerge as promising techniques that blends together technologies that could overcome the limitations of each individual one. Another promising technology which is rapidly becoming a popular application for physical rehabilitation and motor control research is Virtual Reality (VR). In this chapter, we present our research focuses on the development of a new rehabilitation therapy based on an integrated ER-MNP hybrid systems combined with virtual reality and brain neuro-machine interface (BNMI). This solution, based on improved cognitive and physical human-machine interaction, aims to overcome the major limitations regarding the current available robotic-based therapies.

A Low Cost Linear Induction Motor for Laboratory Experiments

In this paper we present a linear induction motor (LIM) prototype for education. LIMs allow easy identification and study of the different concepts and parameters of the electromagnetic circuit that they have in common with other types of electrical machine. Some experiments are presented that highlight the proposed approach.

Perspective Multiscale Detection of Vehicles for Real-Time Forward Collision Avoidance Systems

This paper presents a single camera vehicle detection technique for forward collision warning systems suitable to be integrated in embedded platforms. It combines the robustness of detectors based on classification methods with an innovative perspective multi-scale procedure to scan the images that dramatically reduces the computational cost associated with robust detectors. In our experiments we compare different implementation classifiers in search for a trade-off between the real-time constraint of embedded platforms and the high detection rates required by safety applications.

Modeling of linear induction motors as linear drives

There is a large bibliography in simulation models for linear induction motors (LIMs). However, most of them only consider steady state performance. LIMs working as linear drives generally operate under transient conditions. The aim of this paper is to investigate the suitability of different mathematical models to simulate LIMs as linear drives. A study of most major techniques of calculating lumped parameters is provided. The most representative models capable of simulating transients of LIMs are described and applied to a laboratory prototype. Finally, the results obtained are compared to experimental data.

A Web-based distributed architecture for multi-device adaptation in media applications

Abstract HTML5 is driving a strong trend towards interoperable Web-based applications, enabling a wider range of devices to run this kind of applications. The key challenge of next-generation media applications is to federate cooperative devices to provide multi-device experiences overcoming current second screen solutions within the connected TV industry. There is a gap on the experience of users, since they perceive devices as isolated pieces of applications when they would prefer to have a single experience through multiple devices at the same time. This paper proposes a unified methodology and a common specification over Web Components for the adaptation of a single application, seamlessly running different instances on one or more devices simultaneously, according to the multi-device context of the user and the specific features of the devices. The solution presented in this paper extends current Web standards towards an interoperable architecture and offers broadcasters and media application developers the possibility to easily design applications that will automatically provide a unique consistent experience across the connected devices. The architectural design is targeted to be included in the roadmap of the standards.

Trace Transform Based Method for Color Image Domain Identification

Context categorization is a fundamental pre-requisite for multi-domain multimedia content analysis applications. Most feature extraction methods require prior knowledge to decide if they are suitable for a specific domain and to optimize their input parameters. In this paper, we introduce a new color image context categorization method (DITEC) based on the trace transform. The problem of dimensionality reduction of the obtained trace transform signal is addressed through statistical descriptors of its frequency representation that keep the underlying information. We also analyze the distortions produced by the parameters that determine the sampling of the discrete trace transform. Moreover, Feature Subset Selection (FSS) is applied to both, improve the classification performance and compact the final length of the descriptor that will be provided to the classifier. These extracted features offer a highly discriminant behavior for content categorization without prior knowledge requirements. The method has been experimentally validated through two different datasets.

Technology Roadmapping (TRM) and Strategic Alignment for an Applied Research Centre: A Case Study with Methodological Contributions

Technology roadmapping provides a strategic tool to help companies develop an outside�?in view and challenge their current competitive perspectives. In this paper, the authors describe the roadmapping process, which is aligned, with the research and development (R&D) strategy of an applied research centre. This process is based in an adapted combination of state�?of�?the�?art methodologies, and as a result, the case study shows interesting findings in terms of R&D strategy, technology strategy and roadmapping processes and methodology.

A middleware to enhance current multimedia retrieval systems with content-based functionalities

Nowadays the retrieval of multimedia assets is mainly performed by text-based retrieval systems with powerful and stable indexing mechanisms. Migration from those systems to content-aware multimedia retrieval systems is a common aim for companies from very diverse sectors. In this paper we present a semantic middleware designed to achieve a seamless integration with existing systems. This middleware outsources the semantic functionalities (e.g. knowledge extraction, semantic query expansion,…) that are not covered by traditional systems, thereby allowing the use of complementary content-based techniques. We include a list of key criteria to successfully deploy this middleware, which provides semantic support to many different steps of the retrieval process. Both the middleware and the design criteria are validated by two real complementary deployments in two very different industrial domains.

Architecture for semi-automatic multimedia analysis by hypothesis reinforcement

The digitalization of the audiovisual production chain has introduced new opportunities and challenges in the asset management workflow. The huge amount of accesible content requieres new annotation and indexing paradigms that overcome the current limitations in terms of resources and level of detail. A novel approach to improve and automatize professional Media Asset Management systems is proposed in this paper. Our proposed architecture enhances the metadata with new objective concepts that can be ported to the semantic level and can also used through “query by sample” methods. Moreover, the implicit and explicit knowledge about a certain domain can be introduced in the system with a combination of classifiers and a semantic middleware. Last, the system can be replicated in different domains and combined via an initial hypothesis, allowing the scalability of the system to multiple content domains.