Diagnóstico automático de eventos e distúrbios em unidades geradoras e usinas utilizando lógica fuzzy

The electric power systems are getting more complex and covering larger areas day by day. This fact has been contribuiting to the development of monitoring techniques that aim to help the analysis, control and planning of power systems. Supervisory Control and Data Acquisition (SCADA) systems, Wide Area Measurement Systems and disturbance record systems. Unlike SCADA and WAMS, disturbance record systems are mainly used for offilne analysis in occurrences where a fault resulted in tripping of and apparatus such as a transimission line, transformer, generator and so on. The device responsible for record the disturbances is called Digital Fault Recorder (DFR) and records, basically, electrical quantities as voltage and currents and also, records digital information from protection system devices. Generally, in power plants, all the DFRs data are centralized in the utility data centre and it results in an excess of data that difficults the task of analysis by the specialist engineers. This dissertation shows a new methodology for automated analysis of disturbances in power plants. A fuzzy reasoning system is proposed to deal with the data from the DFRs. The objective of the system is to help the engineer resposnible for the analysis of the DFRs’s information by means of a pre-classification of data. For that, the fuzzy system is responsible for generating unit operational state diagnosis and fault classification.

Estatística das aplicações de métodos multicritério nas áreas da engenharia de produção

Currently, the decision analysis in production processes involves a level of detail, in which the problem is subdivided to analyze it in terms of different and conflicting points of view. The multi-criteria analysis has been an important tool that helps assertive decisions related to the production process. This process of analysis has been incorporated into various areas of production engineering, by applying multi-criteria methods in solving the problems of the productive sector. This research presents a statistical study on the use of multi-criteria methods in the areas of Production Engineering, where 935 papers were filtered from 20.663 publications in scientific journals, considering a level of the publication quality based on the impact factor published by the JCR between 2010 and 2015. In this work, the descriptive statistics is used to represent some information and statistical analysis on the volume of applications methods. Relevant results were found with respect to the "amount of advanced methods that are being applied and in which areas related to Production Engineering." This information may provide support to researchers when preparing a multi-criteria application, whereupon it will be possible to check in which issues and how often the other authors have used multi-criteria methods.