The article considers methods of non-destructive testing based on various physical laws and phenomena. The possibility of creating a new topical tool for obtaining a wide range of data of mechanical engineering products such as shape, size and location in space is considered. It is proposed to use sound diagnostics using a high-frequency broadband signal to capture the frequency characteristics of the object. The purpose of the study is to develop a method of non-contact measurement of mechanical engineering products on several grounds. With the help of vibroacoustic diagnostics and the method of quantitative control, the distribution of the entire volume of products was 100 pieces. on two parties: the main and control, quantitative parameters of each unit of a product are removed. A signal from 0 to 20,000 Hz was applied by means of a frequency generator. The frequency response of each sample was recorded in the Spectrum Analiyser program. Estimation of the deviation of the product size and its frequency spectrum was performed in the NeuroPro 0.25 software. The created neural network allows is predicted in real time values of several quantitative signs irrespective of their nature. A working model for collecting statistical data for the efficient operation of the neural network is obtained. The developed technique allows detecting the configuration of products on the basis of indirect measurements through the frequency spectrum. This technique can be used to diagnose parts by geometric features, physical properties, defects. This requires an increase in input data for neural network training. With a sufficient selection of parts with different defects of the neural network on the acoustic frequency characteristics will be able to divide the parts into groups of worthy and unworthy on various grounds.
The technique of acoustic diagnostics for machine tools -robots is developed. A neural network reference model has been constructed that allows to diagnose the current characteristics of the state of objects under different conditions, namely, the configuration of the mechanism, the geometric parameters of the mechanism with the motor-spindle running, the dynamics of the movement of the nodes of the experimental stand mechanism with variable speed and load on the drive, and the temperature of the object. Experiments have been carried out to investigate the relationship between the parameters of the spectrum of an acoustic signal with a given discreteness, excited by a perturbing effect in the form of "white noise." The possibility of using the proposed approach to the management of complex technological machines, such as machines with mechanisms based on parallel kinematics, is shown to improve the accuracy of the positioning of the actuators, to ensure their dynamic tuning and to optimize the trajectories of the movements of the working organs of the equipment.
Relevance. The problem of controlling complex technological machines such as machines with mechanisms based on kinematics with parallel structure is given consideration in the article in order to improve accuracy of positioning of actuators, to ensure their dynamic adjustment and optimization of trajectories of displacement of operating elements of the equipment (cutting tools, assembling or controlling instruments). The object of the study is the model of the operating area of a mobile robotic machine tool. Objective. The goal of the work is to create a concept for controlling a mobile robotic machine tool applying acoustic control on the basis of a reference model based on deep neural networks. Method. A method of identification and control of a mobile robotic machine tool using spectral description of absorption of acoustic wave with further processing of obtained information is offered. This method allows determining accuracy of positioning of actuators, as well as conducting dynamic adjustment and optimization of trajectories of displacement of operating elements of the equipment. A method of acoustic analysis for precision machining on machine tools with parallel kinematics has been developed. Results. A neural network reference model has been constructed, which allows to diagnose current characteristics of the state of objects in different conditions, namely mechanism's configuration, mechanism's geometric parameters while running motor-spindle, dynamics of displacement of mechanism's nodes of the experimental stand with variable velocities and load on the drive, as well as temperature changes of the object. The developed neural network models also were tested for adequacy. Conclusions. The experiments on the study of the dependency between the parameters of the spectrum of the acoustic signal with a given discreteness disturbed by excitatory effect in the form of "white noise" confirmed efficiency of this approach. Prospects for further research may consist in creation of methods for optimal control of complex technological machines to improve accuracy of positioning of actuators and to improve their dynamic settings.
Topicality. Ensuring reliable functioning of equipment and mechanisms by forming a machine-building cluster, which reduces the idle time as a result of the creation of flexible technological systems based on numerically controlled machine tools. The reliability of the functioning of production facilities created at the machine-building and processing enterprises is achieved not only by high-quality manufacturing, but also by the level of service, which is a continuous support of the working capacity of machines and mechanisms, based on the timely provision of spare parts and repair and maintenance products.Aim and tasks The purpose of the article is to search for innovative model of repair production, based on ensuring its flexibility through adaptive reconfiguration of technological equipment, focused on supporting the life cycle of the main production. Development of high-performance technologies, aimed at achieving advantages in the selected sectors of the economy.Research results. The conceptualization of the maintenance of the machine-repair function in the structure of the reconfigurable multi-cluster cluster, formed on the innovation platform of the machine-assembly shop on the basis of mobile intelligent machines with kinematics of a parallel structure, was realized. The gamma (dimensional series) of elements of the reconfigurable manufacturing system on the basis of mobile machines with parallel kinematics and intelligent control systems, which allows maintenance of a machine-repair cluster on the basis of reconfigurable productions, is developed. The proposed concept can be offered as a market product in the form of a gamut of mobile machines with intelligent control for different productions. The concept of reconfigurable multi-nomenclature production, based on a fundamentally new approach to layout, in particular, a mechanic-assembly shop of competitive production with the use of mobile intelligent machines with kinematics of a parallel structure, has been formed. The method of position identification, kinematic and dynamic parameters of mechanisms with the parallel kinematics structure, of which mobile machines are composed, is developed.Conclusions. The proposed ideology of the formation of the production structure of the cluster will ensure the consolidation of all types of capital: production, labor, financial, social and create conditions for the synergistic effect as a result of constructive interaction in the process of functioning of the BRMK.
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