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• DEVELOPMENT OF KNOCK MATHEMATICAL MODEL FOR MODERN IC ENGINE

  A.L. Beresnev, М. А. Beresnev

  2020-07-20

  Abstract ▼

  The paper examines under-studied aspects of internal combustion engine management, such
  as the use of knock. In knock, instead of a constant frontal flame, a detonation wave is formed in
  the combustion zone, carrying at supersonic speed. Fuel and oxidant are detonated in compression
  wave. This process, from the point of view of thermodynamics, increases the efficiency of the engine.
  In internal combustion engines, there are two different modes of combustion propagation of
  air mixture fuel: deflagration and detonation. Engines operating in detonation combustion mode
  are currently not used and their capabilities are most interesting. Modern internal combustion
  engines do not carry the detonation mode well, but the possibility of short-term combustion of part
  of the fuel-air mixture with detonation is embedded in their design. The situation of detonation is
  currently constantly being studied, it is considered as a harmful component of the combustion
  process, which requires improvement of the engine, its control and use of modern fuel. It is proposed
  to use this, considered random, process to increase the torque and power of the internal
  combustion engine. The possibility of using detonation combustion of fuel-air mixture in internal
  combustion engine as a useful part of the working process is considered, and the possibility of
  controlling combustion of fuel-air mixture in a mixed mode is assumed, which allows to improve
  indicator parameters. Assumptions have been made to create a model and the cylinder pressure
  has been simulated during the combustion phase of the partially detonated fuel-air mixture. The
  method of heat generation calculation has been determined, which is one of the most important
  stages of mathematical model creation, as this determines accuracy and adequacy of calculated
  parameters, both for deflagration combustion modes of fuel-air mixture and using detonation
  combustion. Proposed procedure for calculation of internal combustion engine operating cycle
  parameters makes it possible to carry out real-time calculations and account for influence of binary
  fuel composition on parameters of power, economy, mechanical and dynamic load on parts of
  crank mechanism, as well as thermal load on engine.

• VIBRATION MONITORING OF INTERNAL COMBUSTION ENGINE

  A.V. Logunov, A.L. Beresnev

  2022-01-31

  Abstract ▼

  The work is devoted to the problem of diagnostics of automotive internal combustion engines.
  The problem of monitoring the state of internal combustion engine is now most relevant due
  to the increase in the number of cars and the tightening of environmental requirements. In the
  work the consequences of operation of faulty internal combustion engine are considered. The purpose
  of the work is to justify the choice from existing diagnostic methods of such a method, which
  can help to detect the fault most accurately and quickly. For this purpose, the work details modern
  diagnostic tools, highlights the principles of work, advantages and disadvantages. With the advent
  of modern technologies, the long-known method of estimating the state of internal combustion
  engine by sound can become the most advanced, as the human factor is excluded, for signal processing
  the computational technique of analysis of the audio spectrum in which is carried out with
  the help of artificial neural networks is used. The use of artificial neural networks for sound spectrum
  analysis has found application in speech recognition and for diagnosis of respiratory system
  diseases. The article considers mechanisms that are capable of generating sound signals during
  internal combustion engine operation, some of them are phased, i.e. they are tied to operating
  cycles, some are not phased. The proposed diagnostic technique allows to distinguish "useful"
  sounds from the total number of internal combustion engine noises, after comparative analysis to
  point to the node the sound of which differs from the reference, serviceable one. Scientific novelty
  consists in the fact that the diagnostic process becomes automated, all sounds captured by sensors
  are processed in a computer or a special scanner, the display shows information about the condition of certain nodes, unlike traditional methods where the diagnosis is carried out visually or by
  ear. This increases diagnostic accuracy and reduces overall labor intensity by avoiding partial or
  complete engine disassembly

• APPLICATION OF THE NEURAL NETWORK APPROACH TO DIAGNOSE THE INTERNAL COMBUSTION ENGINE OF VEHICLES

  А. V. Logunov, А. L. Beresnev

  2022-04-21

  Abstract ▼

  The work is devoted to the problem of diagnosing the internal combustion engine of vehicles
  this problem is now the most relevant due to the constant growth of the car fleet and the tightening
  of requirements for safe operation. Timely and accurate control of the internal combustion engine
  is able to prevent the failure of entire vehicle assemblies, as well as to avoid such serious consequences
  as a traffic accident. With the advent of modern technologies the long-known method of
  engine condition estimation by sound can become the most advanced, since the human factor is
  excluded, for signal processing the computer technique is applied, the analysis of a sound spectrum
  in which is carried out by means of artificial neural networks. The application of artificial
  neural networks for analyzing the sound spectrum has found application in speech recognition and
  for diagnosing diseases of the respiratory system. The article deals with the failure of one of the
  main parts of internal combustion engine - the bearing. All possible types of bearing faults and the
  reasons why they occur are presented. The nodes and mechanisms of the internal combustion engine
  in which bearings are used are listed. The algorithm of the experimental part is described.
  The experiment which includes transformation of the received sound signals into spectrograms
  and extraction of features with the help of which the classification is carried out, is executed. The
  executed experimental part has proved the possibility of diagnosing of the internal combustion
  engine by means of artificial neural networks. Scientific novelty lies in the fact that the diagnostic
  process becomes automated, all the sounds taken by sensors are processed in a computer or in the
  future in a special scanner, the display shows information about the state of certain nodes, unlike
  traditional methods where the diagnosis is carried out visually or by ear. Thus, the diagnostic
  accuracy increases and the overall labor intensity decreases due to the exclusion of partial or
  complete engine disassembly.