The master's dissertation consists of the introduction and 6 sections, the conclusion and the list of used literature. The full volume is 89 pages, including 41 illustrations, 26 tables and 25 literary sources.
The urgency of this topic is that automation of production simplifies the control process, and also can replace some processes of production. Known foreign work-manipulators have a significant drawback - a high price, and in our country work manipulators of the same type or the same type are not manufactured. Because of this, the automation of domestic production and further control of manufactured products is high value, and not every manufacturer or company can afford to use a robot-manipulator. Therefore, it is proposed to create a robot-manipulator model for the training of specialists who in the future will program such robot manipulators for work. Due to the high price of industrial robot manipulators, their availability in higher education institutions is impossible, therefore, it is proposed to print a design of this similar model using a 3D printer and using as a source of propulsion power and stepper motors.
The master's dissertation contains 82 pages, 27 figures, 27 tables, 18 sources according to the list of references.
The dissertation deals with the issues of control of heat exchangers of steam generators in nuclear power plants. The internal diameter of the heat exchanger tubes is only 16 mm, which necessitates the miniaturization of the sensor and access to the testing object only from inside of tube. The functional scheme and algorithm of work according to system requirements are proposed. The novelty of the work is combining the amplitude and phase methods of signal processing from the eddy current sensor in order to increase the probability of detecting defect signals. Also, the project proposed a sensor for control presented a harvesting drawing. Appropriate simulations have been carried out to confirm the relevance of the proposed processing method, in particular to improve the accuracy of the method using phase processing, which suggests the use of R-statistics.
This master's dissertation consists of 86 pages, 26 figures, 22 tables and 22 sources according to the list of references.
The main technical characteristics of the tractor Joon Deere 8430 are considered in the dissertation. The fuel supply system was analyzed and the cost calculation was done. The scheme of fuel consumption control is proposed. It is proposed to determine the cost by determining the difference between the volume of feed and the volume of fuel return. This scheme is optimal and does not require additional interference with the fuel system. Since the diameter of the fuel supply pipe is only 10 mm, the design of the flow meter was proposed. It is monoblock, that is, piezoelectric converters are mounted in a pipe stationary.
The dissertation has a volume of 80 pages, the main part consists of an introduction, five sections, contains 29 figures, 25 tables, 4 annexes and 13 sources of literature.
The purpose of the research is to investigate the possibility of using the neural networks for decision-making process of mechanical impedance analysis.
The object of the research is the methods of machine learning for detecting flaws by mechanical impedance analysis of composite materials. The subject of the research is the decision-making process based on the analysis of the informational parameters of the mechanical impedance defectoscope transducer.
In the first two sections of the dissertation, an analytical review of existing testing of composites, major flaws in them, and description of existing devices and systems that implement this method are carried out. Also the physical foundations of the mechanical impedance testing method is described.
The following sections reveal the process of forming an array of input data for research, the development and testing of the neural network, and graphs that show the dependencies of errors on the parameters of the neural network. To investigate the ability of the neural network to learn on the data and to further classification of the testing object’s area on the basis of the presence or absence of a defect, the creation and testing of the neural network was carried out using the Keras library based on the Python programming language, which confirmed the expediency of using this method of information processing in the mechanical impedance testing of compositional materials.
The dissertation has a volume of 80 pages, the main part consists of an introduction, five sections, contains 29 figures, 25 tables, 4 annexes and 13 sources of literature.
The purpose of the research is to investigate the possibility of using the neural networks for decision-making process ofmechanical impedance analysis.
The object of the research is the methods of machine learning for detecting flawsbymechanical impedance analysis of composite materials.
The subject of the research is the decision-making process based on the analysis of the informational parameters of the mechanical impedance defectoscope transducer.
In the first two sections of the dissertation, an analytical review of existing testing of composites, major flaws in them, and description of existing devices and systems that implement this method are carried out. Also the physical foundations of the mechanical impedance testing method is described.
The following sections reveal the process of forming an array of input data for research, the development and testing of the neural network, and graphs that show the dependencies of errors on the parameters of the neural network. To investigate the ability of the neural network to learn on the data and to further classification of the testing object’s area on the basis of the presence or absence of a defect, the creation and testing of the neural network was carried out using the Keras library based on the Python programming language, which confirmed the expediency of using this method of information processing in the mechanical impedance testing of compositional materials.
At present, special attention is paid to automation of the processes of measuring control of product parameters, since the level of automation largely determines the economic costs and the quality of management of various technological processes. When creating modern measuring systems it is necessary to focus on the use of specialized devices, which in turn introduces certain additional difficulties in the design of automated control devices for many product parameters.
In a number of industries it is necessary to control the homogeneity of the electrophysical properties of conductive materials in products of complex forms. The heterogeneity of the conductive material is most often determined by the presence of defects that arise in the manufacturing process in violation of the production technology. For detected defects it is important to know both the volume and their orientation in space (local or elongated along the axis or radius). Rejection of products with detected defects is carried out according to the size of detected heterogeneity of the controlled material of the product.
The task of control is that when the object is controlled relative to the converter on the elements of the signals to draw a conclusion about the location of the defect in the volume of the product, its nature and size.
The volume of the defect is determined, first of all, by the amplitude of the signal. Signal the specific element of the converter depends on its location relative to the defect. Case where the defect is placed directly under one of the elements - the simplest. The volume of the defect can be judged directly in the amplitude of the signal from this element. If the amplitude of the signal exceeds the set threshold level, the defect is inadmissible the volume and object of control must be rejected. But if the same defect of inadmissible volume is located between the elements of the converter, the amplitude of the signal of each of them will be less than in the previous case, and may not exceed the threshold level, and the product must be rejected. Therefore, the development of an algorithm for the processing of data obtained with the help of differential converters, which allows to determine the volume of the defect regardless of its location relative to the elements of the converter, an urgent task of non-destructive testing.
The purpose and objectives of the study
The purpose of the research is to develop an automated system of eddy current control and simulation of signal formation processes in the system object control - eddy current converter
Run simulation of eddy current fields in object control
To substantiate the general structure of the system of eddy current control of products of complex geometry
Object of study The object is the process of automated non-destructive control of products of complex geometry by means of eddy current defectoscopy.
Subject Methods and tools for automated eddy current control of products of complex geometry
Scientific novelty
The structure of the automated eddy current control is proposed, which combines the technical vision, eddy current control and industrial work into a single complex of means for the achievement of the sole purpose of defectoscopy of complex geometry products from conductive materials of complex shape and defect coordinate definitions
Modeling. Adapted the program to the task of calculating the parameters of field elements of vortex currents in the complex control object The general requirements for systems of robotic eddy current control of products are formulated.
