Stanisław Duer

Determination of the impact indicators of electromagnetic interferences on computer information systems

The present article covers an influence of the impact of electromagnetic interferences on computer information systems whose purpose is to control transport supervision systems. The primary objective of transport supervision systems is to detect hazards to human life and health that occur in the process of transport: traveling of people and/or cargos. This process needs to be characterized by a high level of reliability and safety. The measure of the transport safety is the confidence that the elements of a transport process will remain intact during its realization with the exception of those changes that are the result of the natural processes of aging and wear. The railway environment is one of the most difficult environments concerning the provision of electromagnetic compatibility. Those electromagnetic interferences that are intended and not intended being generated in a rail area have an impact on the operation process of a transport supervision system.

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.).

Artificial neural network in the control process of object’s states basis for organization of a servicing system of a technical objects

This paper presents a method to creation of a servicing expert system including an artificial neural network. The theoretical basis was presented with the model of an operation process of objects in the form of the following models: mathematical (analytical), graphical and descriptional. For the tests, a model was developed of an organization of a servicing technical system of those technical objects which require short shutdown times (aircrafts, radiolocation systems, etc.). The mathematical basis was presented for the execution of the task of servicing of a technical object. The idea of the servicing of the object was described as a transformation of the properties of the operational function of the object from the space of the current servicing to the form of the space of the features of the nominal (model) operation of the object. The results were presented of the radar system.

Applications of an artificial intelligence for servicing of a technical object

The paper presents an intelligent system for the servicing of a complex technical object with the use of an artificial neural network and expert system. Also, a general diagram of the complex technical object was presented, and its internal structure was described. 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. The present article covers a description and the structure of an automatic adjustment and control of the value of the qualitative operational function of a technical object. The elements of the adjustment system were characterized and described including the system of comparison and the system of adjustment. The qualitative operational function of a technical object being the target (object) of control and adjustment was described and defined. The adjustment system presented concerns special technical objects, which are characterized by a short time of their repairs. The organization of the maintenance system is carried out on the basis of information from an artificial neural network.

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.

Diagnostic system with an artificial neural network in diagnostics of an analogue technical object

This paper presents a method to control an operation process of a complex technical object, for example a car engine, with the use of trivalent diagnostic information. Also, a general diagram of the complex technical object was presented, and its internal structure was described. 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. The article also covers a diagnostic system which uses a DIAG computer programme for the recognition of the states of technical objects in trivalent logics. A programme was presented and described in an analytical form for diagnosis through an artificial neural network (ANN), which recognises the states of reparable technical objects in trivalent logics. The final results obtained from the computations conducted by the DIAG programme are presented in the table of the states of the object.

Taking decisions in the expert intelligent system to support maintenance of a technical object on the basis information from an artificial neural network

In this paper, an intelligent operation system, which consists of an intelligent diagnostic subsystem (with a neural network) and an intelligent maintenance subsystem (with an expert system), was presented and discussed. The artificial neural network and the expert system, which use the information developed in the neural network, perform a special function in this system. The functional combination of the artificial neural network and the expert system together created a new solution in the form of an intelligent system, which was referred to as an intelligent maintenance system. This article also covers decision-making methods that are used in an expert maintenance system and whose purpose is an organization and control of the process of the prevention of technical objects. For this purpose, the method was described of taking decisions by an expert for complex parametric type hypotheses and for simple finished type hypotheses in the set of possible decisions’ hypotheses. A considerable part of this paper covers the presentation of the method to transform diagnostic information into the required form of maintenance information. For this purpose, an algorithm of the work of maintenance system was performed and descried. In the creation process of the maintenance knowledge base, the specialist knowledge of a human specialist was also used. Hence, a skilful and proper taking of decisions by an expert to create this set of information is essential. Two inference methods were characterized and described in this paper. The theoretical results obtained were verified in the examination of the influence of each of these decision-making inference methods on the final results of the process of the prevention treatment of an object.

Diagnostic system for the diagnosis of a reparable technical object, with the use of an artificial neural network of RBF type

The paper presents a system for the diagnosis of repairable technical objects with the use of an artificial neural network of a radial basis function (RBF) type. The structure and the algorithm of the work of an RBF type neural network are described. This paper presents a method to control an operation process of a complex technical object with the use of trivalent diagnostic information. Also, a general diagram of the complex technical object was presented, and its internal structure was described. A diagnostic analysis was conducted, as a result of which the 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. The final results obtained for the computations conducted by the DIAG programme were presented in the table of the states of the object.

Examination of the reliability of a technical object after its regeneration in a maintenance system with an artificial neural network

This article presents the issues of an examination and evaluation of the reliability of a technical object after its regeneration in a maintenance system. The preventive activities (regeneration) of an object are conducted in a maintenance system which includes an artificial neural network. The author made an attempt in the paper to prove that an artificial neural network has an indirect influence on the quality of preventive activities organized for a technical object and hence on the level of its reliability. This influence is the result of the fact that information developed by a neural network constitutes the basis in the process of the generation of an expert knowledge base on the basis of which the maintenance system is organized. This paper also covers the theoretical basis. Those quantities were defined which may be used in reliability tests of technical objects. The possibilities were presented of testing the reliability: the quality of the use of an object after its regeneration. These tests may be carried out in a short period of time and in a longer period of time after the preventive activities have been carried out for a device. This article also presents the idea of a reliability test conducted for a technical object on the example of a device which controls the work of a petrol engine. For this purpose, the structure of a maintenance system was designed on the basis of an expert knowledge base determined for an object. Diagnostic information from an artificial neural network constitutes the basis for these activities. A substantial part of the article is devoted to the description of the method of the reliability test of the object and to an analysis of the results obtained. The test was carried out in a simulation manner after a long period of time following regeneration of a technical object.

Qualitative evaluation of the regeneration process of a technical object in a maintenance system with an artificial neural network

The present article includes a description of a qualitative evaluation of the regeneration process of a reparable technical object in a maintenance system with an artificial neural network. The delineated spaces of the operational features of a new technical object and of a technical object after regeneration in a maintenance system constitute the basis of the evaluation proposed of a maintenance system. The proposed evaluation of the maintenance system is realized in a graphical and analytical method. The graphical evaluation makes the use of the spaces of maintenance information: the operation features of a new technical object (as a model) and the spaces of maintenance information after a regeneration of an object was performed in a maintenance system. For this purpose, a nominal (model) space was described and defined of maintenance information: the operational properties of a technical object and the space of theoretical maintenance information: the current operational properties of a technical object after maintenance. In the proposed qualitative analysis of regeneration, examinations covered the level of the features of the object’s operation after regeneration was performed in relation to the level of the operational properties of a new object (which was only put to operation) as a model. The resulting differences in the metrics of the distances between these spaces of the object’s operational properties indicate directly the errors (the qualitative evaluation level) in the organization process of the maintenance system.