Wide area condition monitoring of power electric drives in wind power generation system using radiated electromagnetic fields

Electric components in numerous applications (particularly wind generation) are not straightforwardly accessible for monitoring. Therefore, the monitoring and protection through voltage/current measurement may not be dependable since the current value passes numerous segments to reach the observing element. Accordingly, finding an unusual phenomenon of a specific element is difficult. To resolve this issue, using transmitted electromagnetic field of an element for wide area condition monitoring is proposed. It is planned to diagnose and locate short-circuit in induction generator drive such as interturn, intercoil and terminal-to-turn failures. The frequency characteristics of the propagated field is then utilized for finding the short-circuit. The theoretical foundation that relate the behavior of each elements to their frequency response is analyzed and used. To utilize the derived technique for different practical circumstances, two distinctive methods are used for locating the short-circuit. As the experimental test of major fault cases could destruct the winding, the full three-dimensional finite element analysis is used in these cases and some are verified experimentally through the wide area communication. Identifying the areas of partial faults Prevents the whole winding failure prior to a massive destruction, which is costly especially for cases in inaccessible situations such as offshore wind towers

The Benefits of the Arkansas Rice Check-Off Program

As margins are reducing for agricultural producers there is a concerted effort to analyze all costs. One such cost for rice producers in Arkansas is their contribution to the Rice Check-off Program. This study analyzes the cost-benefit ratio of funds contributed by Arkansas rice producers and the holistic (both economic and environmental) benefits they receive. This study analyzes just five of the many programs the Rice Check-off Program invests in through the University of Arkansas System Division of Agriculture (UASDA) and suggests that every dollar invested generated an average return of $28.49 between 2002–2018 ($70.45 when ecosystem benefits are included). That being said, our benefit-cost ratios of 28.49 to 1 and 70.45 to 1, are conservative estimates as we are comparing the total Rice Checkoff funding provided to the UASDA to the benefits of just five of its funded programs. These same investments have resulted in an increase in the rice supply sufficient enough to feed 4.15 million people annually. Rice Check-off funds have consistently provided substantial benefits from their investments

An Open Data and Citizen Science Approach to Building Resilience to Natural Hazards in a Data-Scarce Remote Mountainous Part of Nepal

The citizen science approach has gained momentum in recent years. It can enable both experts and citizen scientists to co-create new knowledge. Better understanding of local environmental, social, and geographical contexts can help in designing appropriate plans for sustainable development. However, a lack of geospatial data, especially in the context of developing countries, often precludes context-specific development planning. This study therefore tests an innovative approach of volunteer citizen science and an open mapping platform to build resilience to natural hazards in the remote mountainous parts of western Nepal. In this study, citizen scientists and mapping experts jointly mapped two districts of Nepal (Bajhang and Bajura) using the OpenStreetMap (OSM) platform. Remote mapping based on satellite imagery, capacity building, and mobilization of citizen scientists was performed to collect the data. These data were then uploaded to OSM and later retrieved in ArcGIS to produce a usable map that could be exploited as a reference resource for evidence-based decision-making. The collected data are freely accessible to community members as well as government and humanitarian actors, and can be used for development planning and risk reduction. By piloting in two communities of western Nepal, we found that using open data platforms for collecting and analyzing location-based data has a mutual benefit for researchers and communities. Such data could be vital in understanding the local landscape, environmental risk, and distribution of resources. Furthermore, they enable both researchers and local people to transfer technical knowledge, collect location-specific data, and use them for better decision-making

Magnetic Field Mapping of a Large-Grain 1.3 GHz Single-Cell Cavity

A new magnetic field mapping system for 1.3 GHz single-cell cavities was developed in order to reveal the impact of ambient magnetic field and temperature gradients during cool-down on the flux trapping phenomenon. Measurements were done at 2 K for different cool-down conditions of a large-grain cavity before and after 120 °C bake. The fraction of applied magnetic field trapped in the cavity walls was ~ 50% after slow cool-down and ~ 20% after fast cool-down. The results showed a weak correlation between between trapped flux locations and hot-spots causing the high-field Q-slope. The results also showed an increase of the trapped flux at the quench location, after quenching, and a local redistribution of trapped flux with increasing RF field

Real-time EMG based pattern recognition control for hand prostheses : a review on existing methods, challenges and future implementation

Upper limb amputation is a condition that significantly restricts the amputees from performing their daily activities. The myoelectric prosthesis, using signals from residual stump muscles, is aimed at restoring the function of such lost limbs seamlessly. Unfortunately, the acquisition and use of such myosignals are cumbersome and complicated. Furthermore, once acquired, it usually requires heavy computational power to turn it into a user control signal. Its transition to a practical prosthesis solution is still being challenged by various factors particularly those related to the fact that each amputee has different mobility, muscle contraction forces, limb positional variations and electrode placements. Thus, a solution that can adapt or otherwise tailor itself to each individual is required for maximum utility across amputees. Modified machine learning schemes for pattern recognition have the potential to significantly reduce the factors (movement of users and contraction of the muscle) affecting the traditional electromyography (EMG)-pattern recognition methods. Although recent developments of intelligent pattern recognition techniques could discriminate multiple degrees of freedom with high-level accuracy, their efficiency level was less accessible and revealed in real-world (amputee) applications. This review paper examined the suitability of upper limb prosthesis (ULP) inventions in the healthcare sector from their technical control perspective. More focus was given to the review of real-world applications and the use of pattern recognition control on amputees. We first reviewed the overall structure of pattern recognition schemes for myo-control prosthetic systems and then discussed their real-time use on amputee upper limbs. Finally, we concluded the paper with a discussion of the existing challenges and future research recommendations