Chaos Theory Approach as Advanced Technique for GDI Spray Analysis 2017-01-0839
The paper reports an innovative method of analysis based on an advanced statistical techniques applied to images captured by a high-speed camera that allows highlighting phenomena and anomalies hardly detectable by conventional optical diagnostic techniques. The images, previously elaborated by neural network tools in order for clearly identifying the contours, have been analyzed in their time evolution as pseudo-chaotic variables that may have internal periodic components. In addition to the Fourier analysis, tools as Lyapunov and Hurst exponents and average Kω permitted to detect the chaos level of the signals. The use of this technique has permitted to distinguish periodic oscillations from chaotic variations and to detect those parameters that actually determine the spray behavior.
Citation: Allocca, L., Montanaro, A., Amoresano, A., Langella, G. et al., "Chaos Theory Approach as Advanced Technique for GDI Spray Analysis," SAE Technical Paper 2017-01-0839, 2017, https://doi.org/10.4271/2017-01-0839. Download Citation
Author(s):
Luigi Allocca, Alessandro Montanaro, Amedeo Amoresano, Giuseppe Langella, Vincenzo Niola, Giuseppe Quaremba
Affiliated:
Istituto Motori CNR, Università Federico II
Pages: 9
Event:
WCX™ 17: SAE World Congress Experience
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Neural networks
Optics
Imaging and visualization
Statistical analysis
Technical review
Tools and equipment
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