Nonlinear Analysis of Combustion Engine Vibroacoustic Signals for Misfire Detection

2003 ◽  
Author(s):  
Piotr Boguś ◽  
Jerzy Merkisz ◽  
Rafał Grzeszczyk ◽  
Stanisław Mazurek
Keyword(s):  
Nonlinear Analysis ◽  
Combustion Engine ◽  
Misfire Detection ◽  
Vibroacoustic Signals

scholarly journals Impact of external interferences on vibroacoustic signals coming from combustion engine during cold test

2015 ◽  
Vol 160 (1) ◽  
pp. 26-35
Author(s):  
Zdzisław STELMASIAK ◽  
Mariusz RUDNICKI
Keyword(s):  
Combustion Engine ◽  
Piezoelectric Sensor ◽  
Cold Test ◽  
Spark Ignition ◽  
Measuring System ◽  
Cylinder Block ◽  
Spark Ignition Engines ◽  
Order Tracking ◽  
Compression Spring ◽  
Vibroacoustic Signals

In the paper is presented impact of external interferences on vibroacoustic signals coming from a spark ignition engine’s vibrations in cold test performed on engine assembly line. As the basis to the analysis were used signals of piezoelectric sensor mounted on cylinder block of the engine driven by electric motor. In course of the testing it has been used the order tracking analysis of the vibrations during the cold test, while experimental results were used to statistic analysis of significance of influence with use of the MiniTab computer program. The main objective of the investigations was to verify actually obtained vibroacoustic signals and to minimize interferences coming from the measuring system. It should contribute to reduction of tolerance limits and improved detection of faulty engines with use of vibroacoustic methods. The investigations have shown significant impact of contact surface of the cylinder block with the sensor and impact of deformations of compression spring on results of recorded vibroacoustic signal. Such impact should be taken into considerations in numerical analysis of the signal. It has been proposed to perform activities to reduce influence of the interferences on recorded signals. Results of the investigations have been already utilized in production cold tests of spark ignition engines.

Misfire detection of an internal combustion engine based on vibration and acoustic analysis

2021 ◽  
Vol 43 (7) ◽  
Author(s):  
João L. Firmino ◽  
João M. Neto ◽  
Andersson G. Oliveira ◽  
José C. Silva ◽  
Koje V. Mishina ◽  
...  
Keyword(s):  
Internal Combustion Engine ◽  
Acoustic Analysis ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Misfire Detection

Technical Diagnosis of Internal Combustion Engines in the Parameters of Vibration

2015 ◽  
Vol 756 ◽  
pp. 53-58 ◽  
Author(s):  
A.P. Syrbakov ◽  
M.A. Korchuganova
Keyword(s):  
Internal Combustion Engines ◽  
Combustion Engine ◽  
Technical Diagnostics ◽  
Combustion Engines ◽  
Laptop Computer ◽  
Diagnostic Complex ◽  
General Aspects ◽  
Vibration Parameters ◽  
Technical Assessment ◽  
Vibroacoustic Signals

Several ways of technical diagnostics have been researched. General aspects have been considered of the mechanism diagnostics by vibroacoustic signals. The assessment of the vibroacoustic engine diagnostics method is provided. On the basis of a laptop computer, a portable diagnostic complex has been elaborated for the pre-assessment of combustion engine mechanisms' condition using parameters of a vibroacoustic signal. For technical assessment of combustion engines a diagnostic scheme has been proposed for mechanical components by vibration parameters.

scholarly journals Detectability of gear damage in combustion engines through a vibroacoustic method

2014 ◽  
Vol 158 (3) ◽  
pp. 12-22
Author(s):  
Zdzisław STELMASIAK ◽  
Mariusz RUDNICKI
Keyword(s):  
Vibration Amplitude ◽  
Internal Combustion Engines ◽  
Combustion Engine ◽  
Cold Test ◽  
Combustion Engines ◽  
Gear Teeth ◽  
Order Analysis ◽  
Vibroacoustic Diagnostics ◽  
Harmonic Components ◽  
Vibroacoustic Signals

The paper presents a new methodology in vibroacoustic diagnostics of internal combustion engines during a cold test on the production line. This method utilizes order analysis of harmonic components of vibroacoustic signals taken from a combustion engine driven with an electric motor to identify the source of noise and vibration amplitude. The presented analysis of the harmonic orders was used to diagnose the damage of the gear teeth.

scholarly journals Misfire detection in a diesel engine using clustering in a short-time analysis of vibroacoustic signals

2005 ◽  
Vol 123 (4) ◽  
pp. 31-40
Author(s):  
Piotr BOGUŚ
Keyword(s):  
Parameter Space ◽  
Time Window ◽  
Diagnostic Methods ◽  
General Idea ◽  
Detection Methods ◽  
Time Signal ◽  
Engine Operation ◽  
Short Time ◽  
Misfire Detection ◽  
Vibroacoustic Signals

The paper presents some results of the research on new diagnostic methods in combustion engines. It describes the application of short-time signal analysis together with pattern recognition techniques in the diagnosis of misfire in Diesel engines through vibroacoustic signals. One considered Diesel locomotive in particular. In the area of the nonroad sources of combustion gases the locomotives rate relatively high as air polluters. There are some regulations in the area of locomotives (e.g. Cart UIC 623 1-2-3 in Europe) but we still observe a lack of obligatory requirements for systems monitoring emission critical damage. Such obligatory on-board diagnostic systems were introduced for passenger cars (OBD II, EOBD). The OBD system performs a continuous monitoring of basic system parameters and one of its most important tasks is misfire detection. All these facts inclined the author to research the new relevant detection methods. The main aim of the research is to distinguish between two states: normal engine operation and the state of misfire. The general idea of the method was taken from the short-time Fourier analysis. The method is based on calculation of the values of some selected parameters in the time window sliding along the signal. For each window position one has a set of parameter values which gives the point in a corresponding multidimensional parameter space. Hence, the time evolution of the signal can be observed as the evolution plot in the parameter space. We suspect that the different system states (misfire) can be distinguished by the different position of points in the parameter space. In order to detect them, the clustering in the parameter space was performed. The first results show the possibility of distinguishing some different clusters within the parameter space which may correspond to different engine states.

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