5 resultados para New sequencing methods

em SAPIENTIA - Universidade do Algarve - Portugal


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The challenge on implementation of the EU Water Framework Directive (WFD) fosters the development of new monitoring methods and approaches. It is now commonly accepted that the use of classical monitoring campaigns in discrete point is not sufficient to fully assess and describe a water body. Due to this the WFD promote the use of modelling techniques in surface waters to assist all phases of the process, from characterisation and establishment of reference conditions to identification of pressures and assessment of impact. The work presented in this communication is based on these principles. A classical monitoring of the water status of the main transitional water bodies of Algarve (south of Portugal) is combined with advanced in situ water profiling and hydrodynamic, water quality and ecological modelling of the systems to build a complete description of its state. This approach extends spatially and temporally the resolution of the classical point sampling. The methodology was applied during a 12 month program in Ria Formosa coastal lagoon, the Guadiana estuary and the Arade estuary. The synoptic profiling uses an YSI 6600 EDS multi-parameter system attached to a boat and a GPS receiver to produce monthly synoptic maps of the systems. This data extends the discrete point sampling with laboratory analysis performed monthly in several points of each water body. The point sampling is used to calibrate the profiling system and to include variables, such as nutrients, not measured by the sensors. A total of 1427 samplings were performed for physical and chemical parameters, chlorophyll and microbiologic contamination in the water column. This data is used to drive the hydrodynamic, transport and ecological modules of the MOHID water modelling system (www.mohid.com), enabling an integrate description of the water column.

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This paper addresses the subject of condition monitoring and diagnostics of power transformers. The main results of two reliability surveys, carried out under the auspices of CIGRE and IEEE in order to assemble objective data on the performance of transformers in service, are presented, providing useful information on the main causes of transformer failures, the most likely affected components and the related outages times. A survey of the most important methods, actually in use, for condition monitoring and diagnostics of power transformers is also given, which stresses the need for the development of new diagnostic methods, that can be applied without taking the transformers out of service, and that can also provide a fault severity criteria, in particular for determining transformers windings integrity. Preliminary results, concerning the on-going research activity on the development of a new approach for inter-turn winding fault diagnosis in three-phase transformers, are also reported in the paper.

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This paper addresses the subject of condition monitoring and diagnostics of power transformers. The main results of two reliability surveys, carried out under the auspices of CIGRE and IEEE in order to assemble objective data on the performance of transformers in service, are presented, providing useful information on the main causes of transformer failures, the most likely affected components and the related outages times. A survey of the most important methods, actually in use, for condition monitoring and diagnostics of power transformers is also given, which stresses the need for the development of new diagnostic methods, that can be applied without taking the transformers out of service, and that can also provide a fault severity criteria, in particular for determining transformers windings integrity. Preliminary results, concerning the on-going research activity on the development of a new approach for inter-turn winding fault diagnosis in three-phase transformers, are also reported in the paper.

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In this paper a recent approach for PID autotuning, involving neural networks, is ferther developed. To make this approach adaptive, optimal PID values must be known on-line. In this paper neural network models of tuning criteria, together with the use of genetic algorithms, are proposed to solve this problem.

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Despite the developments in the control theory and technology achieved in the last decade, PID controllers still remain the type of controller most used in industry. This fact is due to its simplicity (only three terms to tune) and to their robust performance.