Automatic Exploitation of Independencies for Covariance Bounding in Fully Decentralized Estimation

Especially in the field of sensor networks and multi-robot systems, fully decentralized estimation techniques are of particular interest. As the required elimination of the complex dependencies between estimates generally yields inconsistent results, several approaches, e.g., covariance intersection, maintain consistency by providing conservative estimates. Unfortunately, these estimates are often too conservative and therefore, much less informative than a corresponding centralized approach. In this paper, we provide a concept that conservatively decorrelates the estimates while bounding the unknown correlations as closely as possible. For this purpose, known independent quantities, such as measurement noise, are explicitly identified and exploited. Based on tight covariance bounds, the new approach allows for an intuitive and systematic derivation of appropriate tailor-made filter equations and does not require heuristics. Its performance is demonstrated in a comparative study within a typical SLAM scenario

Design and implementation of a test environment to study late-breakdowns in high voltage vacuum circuit breakers

In the last decades, the vacuum switching technology has established itself as the standard in the medium voltage level (Us <= 52kV). However, at higher voltages, this technology is not yet competitive to the current SF6 switching technology. Especially during switching of capacitive loads, a high number of restrikes (dielectric breakdowns) occur. This capacitive switching duty is dielectrically the most challenging for a vacuum circuit breaker and tested widely. However, the interpretation of these tests are difficult due to the absence of suitable diagnostic tools. Therefore, the present thesis deals with the development of a suitable test environment to investigate 72.5 kV vacuum circuit breakers. Based on experiences from the medium voltage level and established research findings in the field of restrikes two main requirements have been derived: 1. The synthetic test circuit needs to be realized using only test transformers. This is necessary to achieve a high number of test series because the use of power transformers is limited and not economical. In case of a capacitive switching duty, this limitation effects the generation of the recovery voltage and how it is applied to the test object. The recovery voltage itself consists in equal parts of a direct and alternating voltage component and must be applied precisely during its voltage zero crossing. This has been realized using two independent voltage sources and a voltage-making switch that has been specially designed for this purpose. 2. A simultaneous detection of field-emission currents and charged micro-particles is needed. Both phenomena can cause restrikes but are not necessarily independent from each other. To measure field-emission currents, a proven concept from the medium voltage level has been adapted towards a high number of capacitive switching operations in rapid succession. This has been achieved by exploiting the separate generation of current and voltage of a synthetic test circuit. Based on their identical interaction with the test circuit, micro-particles have been detected using partial discharge measurement equipment. As a consequence, the whole test environment must have a low partial discharge level to enable this detection. Within this work, the measurement systems as well as the test circuit have been commissioned and tested. It was possible to demonstrate the simultaneous detection of micro-particles and field-emission currents (>= 100 μA). Furthermore, a best practice has been defined for future investigations. Based on first measurements, micro-particle activity up to a second after a switching operation could be observed. In addition, it has been shown, that the recovery voltage can be applied to the test object precisely (+-100 μs) at the voltage zero crossing with an additional voltage-making switch. Thus, the main negative aspect in their generation, which arise from the use of test transformers, can be compensated

The teaching of surgery in the undergraduate curriculum – reforms and results

AbstractIn the past decade, the teaching of surgery in the undergraduate curriculum has undergone considerable changes in quantity, mode and method of delivery. This is a result of the radical reforms of higher education, the health service and the undergraduate medical curriculum. These reforms are often interrelated and are occurring in conjunction with major changes in healthcare delivery. In this article we discuss this reorganisation, the rationale behind it and the impact on surgical teaching

Non-enzymatic Electrochemical Determination of Glucose Concentration

There are a variety of applications for electrochemistry (including synthetic, physical and analytical chemistry), and here we present an experimental protocol for the non-enzymatic electrochemical quantitation of glucose in liquids that can be used in teaching laboratories. This offers an interesting experiential learning experience that is contextualized through a real world application where comparable technology the students employ touches the lives of humans across the world on a daily basis

TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials

Optical belt sorters are a versatile, state-of-the-art technology to sort bulk materials that are hard to sort based on only nonvisual properties. In this paper, we propose an extension to current optical belt sorters that involves replacing the line camera with an area camera to observe a wider field of view, allowing us to observe each particle over multiple time steps. By performing multitarget tracking, we are able to improve the prediction of each particle‘s movement and thus enhance the performance of the utilized separation mechanism. We show that our approach will allow belt sorters to handle new classes of bulk materials while improving cost efficiency. Furthermore, we lay out additional extensions that are made possible by our new paradig

Covariance Intersection in Nonlinear Estimation Based on Pseudo Gaussian Densities

Many modern fusion architectures are designed to process and fuse data in networked systems. Alongside the advantages, such as scalability and robustness, distributed fusion techniques particularly have to tackle the problem of dependencies between locally processed data. In linear estimation problems, uncertain quantities with unknown cross-correlations can be fused by means of the covariance intersection algorithm, which avoids overconfident fusion results. However, for nonlinear system dynamics and sensor models perturbed by arbitrary noise, it is not only a problem to characterize and parameterize dependencies between estimates, but also to find a proper notion of consistency. This paper addresses these issues by transforming the state estimates to a different state space, where the corresponding densities are Gaussian and only linear dependencies between estimates, i.e., correlations, can arise. These pseudo Gaussian densities then allow the notion of covariance consistency to be used in distributed nonlinear state estimation

Risk–risk governance in a low-carbon future: Exploring institutional, technological, and behavioral tradeoffs in climate geoengineering pathways

Deliberations are underway to utilize increasingly radical technological options to help address climate change and stabilize the climatic system. Collectively, these options are often referred to as “climate geoengineering.” Deployment of such options, however, can create wicked tradeoffs in governance and require adaptive forms of risk management. In this study, we utilize a large and novel set of qualitative expert interview data to more deeply and systematically explore the types of risk–risk tradeoffs that may emerge from the use of 20 different climate geoengineering options, 10 that focus on carbon dioxide or greenhouse gas removal, and 10 that focus on solar radiation management and reflecting sunlight. We specifically consider: What risks does the deployment of these options entail? What types of tradeoffs may emerge through their deployment? We apply a framework that clusters risk–risk tradeoffs into institutional and governance, technological and environmental, and behavioral and temporal dimensions. In doing so, we offer a more complete inventory of risk–risk tradeoffs than those currently available within the respective risk-assessment, energy-systems, and climate-change literatures, and we also point the way toward future research gaps concerning policy, deployment, and risk management