System of the Automatic Preventive On-Line Monitoring and Diagnostics of Car Engines on the Basis of the New Methods of Preventive Diagnostics

Paper #:
  • 2011-01-0747

Published:
  • 2011-04-12
Citation:
Kirillov, S., Kirillov Sr, A., and Kirillova, O., "System of the Automatic Preventive On-Line Monitoring and Diagnostics of Car Engines on the Basis of the New Methods of Preventive Diagnostics," SAE Technical Paper 2011-01-0747, 2011, https://doi.org/10.4271/2011-01-0747.
Pages:
11
Abstract:
This paper introduces architecture of an integrated system of preventive diagnostics and mathematical and computational methods, based on which such a system is being developed.The present work aims to: describe the methods of preventive diagnostics based on mathematical models and computing algorithms, allowing to detect the hidden harbingers of engine dysfunctions and future failures;describe the architecture of the system of preventive diagnostics, its further evolution;describe the process of integration of preventive diagnostics system to the car engine.A necessary condition for the development system of preventive diagnosis is the condition of their economic efficiency, including the requirement of low cost sensors and computing systems of diagnostics.The paper shows: A set of telemetry data for preventive diagnostics should include data of the crankshaft rotation angle sensor and data of vibrations of the engine case, received by means of the sensor control of vibrations installed additionally on its case;The basis for the analysis of preventive signs of dysfunction and future failures of engine is the analysis of stochastic components in indications of established sensors, crankshaft rotation angle sensor and vibration sensor. The greatest number of hidden preventive diagnostic signs is defined by the analysis of stochastic components of signals from the vibration sensor.Algorithms for detecting of preventive signs of dysfunctions of the engine represent the analysis of multidimensional empirical probability distribution functions of stochastic components in signals of crankshaft rotation angle sensor and vibration sensor.Along with the analysis of multidimensional distribution functions such characteristic as K-complexity, K-entropy of stochastic trajectory of process is introduced and analyzed.
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