Dariusz Bernatowicz

The Diagnostic System with an Artificial Neural Network for Identifying States in Multi-valued Logic of a Device Wind Power

The present article covers the idea of the examination of the value of the k-th logics of diagnostic information related to the assessment of the states of complex technical items. For this purpose, an intelligent diagnostic system was presented whose particular property is the possibility to select any k-th logic of inference from set {k = 4, 3, 2}. An important part of this study is the presentation of theoretical grounds that describe the idea of inference in the multi-valued logic examined. Furthermore, it was demonstrated that the permissible range of the values of the properties of diagnostic signals constitutes the basis of the classification of states in multi-valued logic in the DIAG 2 diagnostic system. For this purpose, a procedure of the classification of states in selected values of multi-valued logic was presented and described. An important element in the functioning of diagnostic systems, i.e. the module of inference was presented, as well. The rules of diagnostic inference were characterized and described based on which the process of inference is realized in the system.

Diagnosing of a complex technical object in four-valued logic

This paper presents the essence of an investigation of a complex technical object with the use of four-valued logic. To this end, an intelligent diagnostic system (DIAG 2) is described. A special feature of this system was its capability of inferring k at {k = 4, 3, 2}, in which case the logic {k = 4} is applied. An important part of this work was to present the theoretical foundations describing the essence of inference in the four-valued logic contemplated. It was also pointed out that the basis for classification of states in the multiple-valued logic of the diagnostic system (DIAG 2) was the permissible interval of changes in the values of diagnostic signal features. Four-valued logic testing was applied to a system of wind turbine equipment.

Expert System Supporting the Diagnosis of the Wind Farm Equipments

An expert system that supports diagnosing of wind farm equipments is presented in this paper. First, the created functional and diagnostic models were presented for two basic elements of farms, such as: the wind power plant (turbine) and the electrical substation. Next, a division was made of the aforementioned elements into internal structure components (blocks), and diagnostic signals were determined for them. Based on these signals and their properties, a set of input data, parameters and an expert knowledge base in the form of facts and rules were developed. On further stages, the inference process of the expert system was characterized and the individual paths of obtaining a diagnosis of the working condition of wind farm devices were described. Additionally, the graphical user interface was discussed, and the manner of the presentation of inference process results was explained for general and detailed diagnosis.