The powerful tool for defect analysis is an expert system. It is a computer programme based on the knowledge of experts for solving the quality of castings. We present the expert system developed in the VSB-Technical University of Ostrava called ‘ESWOD’. The ESWOD programme consists of three separate modules: identification, diagnosis / causes and prevention / remedy. The identification of casting defects in the actual form of the system is based on their visual aspect.
In these considerations, I undertake a polemic with thinking based on the assumption that the value of scientific achievements can be measured with almost mathematical accuracy and give fully reliable point indicators for them. It is not only part of those who introduce the current reform of higher education and science in Poland, but also experts who support them, as well as some representatives of science and natural sciences. This thinking was called point syndrome and expert syndrome. Although it was diagnosed as a manifestation of academic disease a few years ago, it still not only finds its supporters, but also translates into activities, which in some scholars cause astonishment, in others indignation, and still strong opposition in others.
The generic mathematical model and computational algorithm considering hydrodynamics, heat and mass transfer processes during casting and forming steel ingots and castings are offered. Usage domains for turbulent, convective and non-convective models are determined depending on ingot geometry and thermal overheating of the poured melt. The expert system is developed, enabling to choose a mathematical model depending on the physical statement of a problem.
As one of the key techniques in the fully mechanized mining process, equipment selection and matching has a great effect on security, production and efficiency. The selection and matching of fully mechanized mining equipment in thin coal seam are restricted by many factors. In fully mechanized mining (FMM) faced in thin coal seams (TCS), to counter the problems existing in equipment selection, such as many the parameters concerned and low automation, an expert system (ES) of equipment selection for fully mechanized mining longwall face was established. A database for the equipment selection and matching expert system in thin coal seam, fully mechanized mining face has been established. Meanwhile, a decision-making software matching the ES was developed. Based on several real world examples, the reliability and technical risks of the results from the ES was discussed. Compared with the field applications, the shearer selection from the ES is reliable. However, some small deviations existed in the hydraulic support and scraper conveyor selection. Then, the ES was further improved. As a result, equipment selection in fully mechanized mining longwall face called 4301 in the Liangshuijing coal mine was carried out by the improved ES. Equipment selection results of the interface in the improved ES is consistent with the design proposal of the 4301 FMM working face. The reliability of the improved ES can meet the requirements of the engineering. It promotes the intelligent and efficient mining of coal resources in China.
The article presents a shock safety model of an indirect contact with a low-voltage electric device. This model was used for computations and analyses concerning the following: the probabilities of appearance of the particular shock protection unreliability states, electric shock states (ventricular fibrillation), contributions of the unreliability of different shock protection elements to the probability of occurrence of these states, as well as the risk of electric shock (and the shock safety), and contributions of the intensity of occurrence of damages to different shock protection elements to this risk. An example of a possibility to reduce the risk of an electric shock through changing the intensity of occurrence of damages to the selected protection elements was provided.
The article describes a shock safety modeling method for low-voltage electric devices, based on using a Bayesian network. This method allows for taking into account all possible combinations of the reliability and unreliability states for the shock protection elements under concern. The developed method allows for investigating electric shock incidents, analysing and assessing shock risks, as well as for determining criteria of dimensioning shock protection means, also with respect to reliability of the particular shock protection elements. Dependencies for determining and analysing the probability of appearance of reliability states of protection as well as an electric shock risk are presented in the article.