Diagnostic Criteria for the Signal of the First-Order Derivative of Diesel Engine in-Cylinder Pressure

Davydov, I.; Konkova, Irina; Konkov, Aleksei

doi:10.1007/978-3-030-37916-2_32

Cited by 1 publication

(1 citation statement)

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“…The issues of technical diagnostics of the engine CPG and GDM have been studied by some researchers. Authors [10] examined an alternative method, which consists in analyzing a signal obtained using a current-voltage converter, the output of which is proportional to the first-order derivative of the measured pressure. The researchers propose new dimensionless criteria defined in the analysis of such a signal.…”

Section: Introductionmentioning

confidence: 99%

Method for diagnosing the ICE cylinder-piston group in the combustion chamber in the mode of cranking the engine crankshaft

Гриценко

Shepelev

Baryshnikov³

2020

Preprint

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To increase the diagnostic efficiency, significantly reduce the unproductive time, and mainly increase the reliability and accuracy, we propose a new method and tools implementing it - an oscillographic method for monitoring the pressure and phase parameters during the dynamic change in the operating parameters. The proposed work is aimed at improving the internal combustion engine (ICE) performance by timely diagnosing the cylinder-piston group (CPG) and its maintenance based on the diagnostic results. The scientific novelty of the work lies in the establishment of the interconnection of the CPG parameters obtained in the test modes of the ICE operation, allowing us to justify the diagnostic modes and their limiting values; the development of diagnostic methods and tools allowing us to justify the test modes for diagnosing the ICE CPG; the experimental data, which revealed that the instantaneous pressure signal in the combustion chamber is a sensitive diagnostic sign, which reflects the technical condition of the ICE CPG and its elements; the results of the experimental studies of diagnosing the ICE CPG in test modes. The results of the experimental work were compared with the results of theoretical modeling, the convergence between them was 97–99%. The production validation of the new method demonstrated the reliability within 0.92–0.97.

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Section: Introductionmentioning

confidence: 99%