2010
DOI: 10.1016/j.ymssp.2009.12.004
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Model-based diagnosis of large diesel engines based on angular speed variations of the crankshaft

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Cited by 102 publications
(71 citation statements)
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“…The torsional stiffnesses of diesel crankshaft and the shaft of generator are far larger than that of flexible coupling. 13 Hence, the torsional angle of left hand of the flexible coupling is close to that of the front end of the diesel generator set, and the torsional angle of right hand of the flexible coupling is close to that of the rear end of the diesel generator set. It is assumed that the relative torsional angles at the ends of flexible coupling can be replaced by those at the ends of diesel generator set.…”
Section: Measurement System Configuration Of Double-encodermentioning
confidence: 77%
“…The torsional stiffnesses of diesel crankshaft and the shaft of generator are far larger than that of flexible coupling. 13 Hence, the torsional angle of left hand of the flexible coupling is close to that of the front end of the diesel generator set, and the torsional angle of right hand of the flexible coupling is close to that of the rear end of the diesel generator set. It is assumed that the relative torsional angles at the ends of flexible coupling can be replaced by those at the ends of diesel generator set.…”
Section: Measurement System Configuration Of Double-encodermentioning
confidence: 77%
“…In addition, several important work have identified crankshaft classification. An automated diagnosis using an artificially intelligent system was proposed by [11] to monitor large diesel engines by analysing a crankshaft's angular speed variations and identifying a failure risk level at a greatest cost concern. Linear parametric classifiers were applied by [12] to diagnose misfire in internal combustion engines by using crank-angle domain digital filters to extract features from the measured engine speed signal, one of the characteristics of a misfire.…”
Section: Introductionmentioning
confidence: 99%
“…Three methodologies are commonly used in crankshaft speed-based torque estimation, consisting of black-box model-based estimation, frequency analysis-based mapping, and crankshaft dynamic model-based estimation [13]. The first solution is to use a black-box model (such as a neural network and nominal function) to describe the relationship between the engine torque and crankshaft instantaneous speed [14][15][16][17][18]. However, these methods need an amount of data to train the black-box model.…”
Section: Introductionmentioning
confidence: 99%