Combustion Faults Diagnosis in Internal Combustion Engines Using Angular Speed Measurements and Artificial Neural Networks

Cruz-Peragón, Fernando; Aguilar, Francisco José Jiménez-Espadafor; Palomar, J.M.; Dorado, M.P.

doi:10.1021/ef800159r

Cited by 14 publications

(11 citation statements)

References 16 publications

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“…For this reason, in the present work results from the previously described response surface experimental design of a DI CIE have been used. Thus, conclusions may be taken as indicative of the procedure to follow in futures studies. , …”

Section: Sensitivity Analysis Methodologymentioning

confidence: 99%

“…To improve the exhaust emissions and performance of internal combustion engines, the influence of the design parameters over the engine behavior must be identified . Depending on the purpose (design, control, or diagnosis), pressure cycle measurements and modeling may be required. − Among the different procedures to model the combustion process into a combustion chamber, − the Wiebe’s parametric model that provides the mass burned fraction (MBF) corresponds to one of the most internationally extended . In this sense, many studies predict the correlations between some of the previous parameters. , …”

Section: Introductionmentioning

confidence: 99%

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Influence of a Combustion Parametric Model on the Cyclic Angular Speed of Internal Combustion Engines. Part II: Statistical Sensitivity Assessment Results

et al. 2009

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The most extended parametric form that describes the combustion process in an engine is based on the fuel rate of heat release (ROHR), derived from a mass burned fraction function (MBF), such as Wiebe's function. When a combustion model is included in either identification or optimization processes, the obtained cyclic pressure and speed profiles must be very close to real values, thus helping to estimate the ROHR accurately. However, in most cases deep knowledge about the input parameters associated to the combustion model is not available, thus indicating the same system response (engine instantaneous angular speed) can lead to multiple solutions. In this work, a procedure to establish a relationship between the combustion model input parameters and the engine dynamic response (cyclic angular speed), next to the interrelation between input factors, is presented. In a previous work, the necessity of a sensitivity assessment has been justified. (Cruz-Peragon, F.; Jimenez-Espadafor, F. J.; Palomar, J. M.; Dorado, M. P. Energy Fuels 2009, 23, 2921-2929.) According to this, a design of experiment (DoE) including data from a test set provided by a single-cylinder direct injection compression ignition engine (CIE) has been carried out. Later, a statistical assessment has been performed to evaluate both the influence of the main parameters of the combustion model over the system response and the interrelation between parameters. Finally, some improvements about the parameters estimation procedure are discussed. It can be concluded that the equivalence ratio, the ignition timing for spark ignition engines or SIE (injection timing for CIE), and the form factor are parameters with high influence over the engine response. The proposed methodology helps to analyze engine combustion but needs adjustments to extend its application to other engines. However, the procedure demonstrates the effectiveness of this methodology if both adequate experimental designs and system model are used.

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Section: Sensitivity Analysis Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Influence of a Combustion Parametric Model on the Cyclic Angular Speed of Internal Combustion Engines. Part II: Statistical Sensitivity Assessment Results

et al. 2009

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“…However, the detection of multiple failures from in-cylinder pressure measurements is still an open issue. Different Fuzzy-based methods also provide remarkable results for detecting only one single fault such as in [3], [4], [17], and [18].…”

Section: Introductionmentioning

confidence: 99%

Model-Based Condition and State Monitoring of Large Marine Diesel Engines

Watzenig¹,

Sommer²,

Steiner³

2013

Diesel Engine - Combustion, Emissions and Condition Monitoring

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“…Insulation fault is one of the most common faults of the ignition coils nowadays, especially for the low-end products. With the development of testing technology [2] the fault phenomenon is concerned about [3,4].…”

Section: Introductionmentioning

confidence: 99%

Ignition Coil Insulation Fault Detection Algorithm

Li¹,

Zhao²,

Wang³

2010

JDCTA

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Pulse singularities with variable amplitudes appear in the corresponding positions of ignition coil primary current waveform when insulation fault occurs during the ignition process. We propose an algorithm to detect the singularities in ignition coil primary current signal. First calculate the multiscale continuous wavelet transform of the fault signal. Then pursue modulus maxima from the coarsest scale to the finest scale along the links between the adjacent scales. The pursue method avoids that the distribution characterization of modulus maxima on the modulus maxima map affects the detection outcome. Last draw the modulus maxima lines and determine the locations of the singularities. The results of experiments show that it has approximate computational complexity with the traditional modulus maxima singularity detection algorithm. In addition the algorithm has less error than traditional algorithm and some more complicated algorithms on identifying the singularities' locations in a noisy environment.

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Combustion Faults Diagnosis in Internal Combustion Engines Using Angular Speed Measurements and Artificial Neural Networks

Cited by 14 publications

References 16 publications

Influence of a Combustion Parametric Model on the Cyclic Angular Speed of Internal Combustion Engines. Part II: Statistical Sensitivity Assessment Results

Influence of a Combustion Parametric Model on the Cyclic Angular Speed of Internal Combustion Engines. Part II: Statistical Sensitivity Assessment Results

Model-Based Condition and State Monitoring of Large Marine Diesel Engines

Ignition Coil Insulation Fault Detection Algorithm

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