Abstract

A dynamic advancement of the design of combustion engines generates a necessity of introduction of strategies of operation based on the information related to their technical condition. The paper analyzes problems related to vibration based diagnostics of valve clearance of a piston combustion engine, significant in terms of its efficiency and durability. Methods of classification have been proposed for the assessment of the valve clearance. Experiments have been performed and described that aimed at providing information necessary to develop and validate the proposed methods. In the performed investigations, the vibration signals were obtained from a triaxial accelerometer located in the engine cylinder head. A parameterization of the obtained vibration signal has been carried out for the engine operating under different engine loads, rotation speeds and valve clearance settings. The parameterization pertained to the specific features of the vibration signals, the derivative of the vibration signal as a function of time as well as the envelope of this derivative. In the first approach, the authors developed a classifier in the form of a set of binary trees that additionally allowed distinguishing the features significant in terms of the identification of adopted classes. For comparison, the authors also developed classifiers in the form of a neural network as well as a k-nearest neighbors algorithm using the Euclidean metric. Based on the performed investigations and analyses a method of valve clearance assessment has been proposed.

Highlights

  • Internal combustion engines are commonly applied in vehicles and stationary equipment

  • The results showed that acoustic emission (AE) signals have a significant advantage over the other sensors involved, indicating sensitivity to both mechanical action and mechanical-smooth combustion

  • This paper presents a new approach to identification of valve clearance of an engine operating at different loads and speeds based on an appropriately processed vibration signal

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Summary

Introduction

Internal combustion engines are commonly applied in vehicles and stationary equipment. A methodology of valve clearance class identification has been proposed based on the absolute vibration accelerations measured on the cylinder head and a supervised learning systems - classifiers Such a solution allows an automatic assessment of the correctness of the valve clearance adjustment on an operating engine without the necessity of seeking a mathematical model describing the relation between the vibration signal and the valve clearance. During the experiment the folthose diagnostic measures that are significant in the process of condi- lowing were adjusted: valve clearance, engine load and speed while tions classification Those that will not be used by the algorithm are of recording the vibration accelerations of the engine cylinder head. It allows a parallel recording of fast-varying processes on 6 channels with the dynamics of up to 160 dB

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