Radosław Duer

Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network

The present article covers a description of the structures of maintenance systems with a diagnostic artificial neural network as well as a description of those systems that are without a neural network (organized in a classical manner). Such a maintenance system that is organized on the basis of information from an artificial neural network is a rational system. In this system, maintenance costs are significantly reduced (a reduced time required for regeneration and reduced expenditures on preventative activities). Also, theoretical basis is presented of the modelling of the structure of the maintenance system of objects in the form of the following models: mathematical (analytical), graphical and descriptive. For the purpose of the research being conducted, the methodology was developed of a synthesis of the structure of the maintenance system of technical objects (continuous operation), that is such technical objects that require short shutdown times (aircrafts, radiolocation systems, power engineering equipment, etc.).

Diagnostic system with an artificial neural network which determines a diagnostic information for the servicing of a reparable technical object

In this paper, the features of a diagnostic measurement setup have been determined. The purpose of the setup was registration of diagnostic signals taken from an electronically controlled gasoline-powered engine. Special attention has been paid to the presentation of the features of an analog–digital converter card used, as well as to the possibility of its practical use. Another important aspect is the design and programming of computer software dedicated for action along with the setup. The results of the work have been presented using the example of the engine’s microprocessor control module. A diagnostic analysis was conducted, as a result of which sets of the functional elements of the object and its diagnostic signals were determined. Also, the methodology of the diagnostic examination of the technical system was presented. The result was a functional and diagnostic model, which constituted the basis for initial diagnostic information, which is provided by the sets of information concerning the elements of the basic modules and their output signals.

Training of an artificial neural network in the diagnostic system of a technical object

The present paper covers the issue of training of an artificial neural network in an intelligent diagnostic system whose purpose is to evaluate repairable technical objects. The structure of the diagnostic system was characterized, and the measurement and diagnostic subsystems were described. An artificial neural network is an important element in an intelligent diagnostic subsystem. The structure, the algorithm, the organization of a neural network and the basic relations that describe its work were presented. The information presented in the form of the vectors of diagnostic signals, and their standard vectors constitute the primary information base used in “DIAG” computer program. Training of an artificial neural network is an important aspect that is presented in the paper. The issue concerning these problems is not presented in the literature. Training of a network was presented on the grounds of teaching vectors, which are determined in a diagnostic system in the process of a simulation of a specific state in the object examined. An example of training of a network was presented in a diagnostic system which evaluates a control system of the operation of a car engine. Appropriate connections were presented for the purpose of a qualitative assessment of the training process of a neural network.

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.

Diagnostic testing the solar power equipment in logic 2- and 3- valuable

Streszczenie. W artykule zaprezentowano problematykę badania wypracowanych diagnoz w logice 2i 3-wartościowej przez system diagnostyczny (DIAG 2) dla urządzeń elektrowni słonecznej. W tym celu przedstawiono i opisano model funkcjonalno-diagnostyczny urządzeń elektrowni słonecznej. Na podstawie opracowanego modelu badanego obiektu wyznaczono zbiór elementów podstawowych oraz zbiór sygnałów diagnostycznych, które są wypracowane przez j-te elementy funkcjonalne obiektu. Przedstawiono także krótki opis wykorzystywanego w badaniu inteligentnego systemu diagnostycznego (DIAG 2). System (DIAG 2) jest autorskim opracowaniem autorów. Program diagnostyczny w systemie (DIAG 2) pracuje na zasadzie porównania zbioru wektorów sygnałów diagnostycznych z ich wektorami wzorcami. W wyniku porównania sygnałów wyznaczane są przez sieć neuronową elementarne metryki rozbieżności wektorów sygnałów diagnostycznych. Na podstawie metryk odległości różnicowej następuje wnioskowanie systemu co do rozpoznania stanu elementów podstawowych obiektu. Słowa kluczowe: diagnostyka techniczna, wnioskowanie diagnostyczne, logiki wielowartościowe, sztuczna inteligencja DOI: 10.5604/01.3001.0009.9485

Zastosowanie logiki czterowartościowej w procesie wnioskowania w systemach diagnostycznych

The article presents application of logic 4-valuable in the process of reasoning in diagnostic systems. For this purpose, the structure of an intelligent diagnostic system (DIAG 2) is presented and defined. Its essential modules: measurement, calculation, and analysis modules (program of neural network) and diagnostic inference are described. In the literature, there is no development in the field of description and implementation of the logic of the tetravalent in diagnostic systems. The author’s works in this field are innovative ones. Noteworthy is the present diagnostic method used in the system (DIAG 2). The proposed diagnostic method (assessment of the state of the examined object) is based on a comparison of vectors of diagnostic signals with their patterns’ vectors. By comparing the signals, elementary metrics of disparity vectors of diagnostic signals are determined by the neural network. On the basis of the metrics of differential distance, the system requests for diagnostics of the state of elements of the basic object.