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• DEVELOPMENT OF A DISTRIBUTED CONTROL SYSTEM OF THERMAL PROCESSES IN A HYDRAULIC PRESS

  A.L. Liashenko

  2021-12-24

  Abstract ▼

  The necessity of regulating the temperature of the coolant in hydraulic presses, providing
  hot gluing of plywood, regulating the pressure in the press channels and maintaining technological
  parameters at a given level, is considered. A column hydraulic press P-714-B for hot gluing of
  plywood, installed at the Ust-Izhora plywood mill, is considered as a control object. The article
  provides a description of the column hydraulic press. To monitor the parameters of the presented
  installation of plywood production, it is proposed to consider the heating press plates and plywood
  packages as an object with distributed parameters. To develop a mathematical model of the control
  object, a functional diagram of this device with the main equipment and technological flows of
  the coolant was considered. A technique has been developed for modeling objects of this class as
  objects with distributed parameters. Consideration of the processes occurring in the channels of
  the heating plates made it possible to formulate differential equations of motion that describe the
  flow of the working medium in the system of channels. The developed method of mathematical
  modeling of heat propagation in the heating plates of the press and plywood packages made it
  possible to draw up a mathematical model for the object under consideration. This mathematical
  model turned out to be quite complex, and it is not possible to solve the resulting system of partial
  differential equations analytically (to isolate the transfer function). For a numerical analysis of the
  considered control object, a discrete model of equations and a computational algorithm were
  compiled. In the process of compiling discrete models, the problems of “joining” the boundary
  conditions were solved, the stability of the computational scheme was ensured, and the steps of
  discretization with respect to spatial variables were selected. Software was specially developed for
  computer modeling. With its help, the temperature values at the control points were calculated.
  The presented mathematical model made it possible to carry out a numerical experiment, as a
  result of which the frequency characteristics of the object under study were obtained. These characteristics
  were used in the synthesis of a distributed high-precision controller.

• STUDY OF THE APPLICATION OF THE SPIKING NEURAL NETWORK AND FINITE ELEMENT METHOD FOR DIAGNOSTICS OF ROBOT ASSEMBLIES

  А. Y. Tamm, Е. А. Barymova, М. I. Kuzmin

  2025-04-27

  Abstract ▼

  One of the key parameters of any modern mechanical system is its vibration and acoustic characteristics,
  which have a direct impact on the environment and humans during operation. In this connection, the
  task of diagnosing the vibration characteristics of various complex mechanical objects, to which industrial
  robotic complexes can be referred, remains relevant. Due to the difficulty in carrying out diagnostics and
  experimental debugging of newly developed mechanisms, it is interesting to apply modern approaches to
  solving the problem of diagnostics, in particular, with the use of neural networks and numerical methods.
  The purpose of this work was to investigate the possibility of joint application of spike neural network and
  finite element method for estimation of vibration characteristics on the example of wave gearbox bearing.
  The paper describes in detail the algorithm of diagnostics, which includes the stages of development of both
  the finite element model of the investigated mechanical system and the development of the neural network
  architecture. At the same time, the generation of training and control datasets for the neural network is carried
  out on a simplified finite element model having characteristics similar to the detailed one, which is ensured
  by the coincidence of the first ten eigenforms of the assembly. The data sets were generated on the
  basis of numerical calculations using an explicit scheme of integration in time of a simplified model of a
  gearbox with several types of artificially introduced defects similar to those appearing during operation of a
  real bearing. To analyze the frequency characteristics, a spike neural network architecture was developed
  and further improved on a training set of single defects. As a result of the study it was determined that the
  developed spike neural network provides classification of data on the control dataset with 85% accuracy,
  which allows us to conclude about the applicability of the proposed method of determining the vibration state
  of mechanical systems with the joint use of neural networks and finite element method.