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Please use this identifier to cite or link to this item: http://dspace.lib.cranfield.ac.uk/handle/1826/7478

Document Type: Article
Title: Acoustic monitoring of engine fuel injection based on adaptive filtering techniques
Authors: Albarbar, A.
Gu, F.
Ball, A. D.
Starr, Andrew G.
Issue Date: 2010
Citation: A. Albarbar, F. Gu, A. D. Ball, A. Starr, Acoustic monitoring of engine fuel injection based on adaptive filtering techniques, Applied Acoustics, Volume 71, Issue 12, 2010, Pages 1132- 1141.
Abstract: Diesel engines injection process is essential for optimum operation to maintain the design power and torque requirements and to satisfy stricter emissions legislations. In general this process is highly dependent upon the injection pump and fuel injector health. However, extracting such information about the injector condition using needle movements or vibration measurements without affecting its operation is very difficult. It is also very difficult to extract such information using direct air-borne acoustic measurements.In this work adaptive filtering techniques are employed to enhance diesel fuel injector needle impact excitations contained within the air-borne acoustic signals. Those signals are remotely measured by a condenser microphone located 25cm away from the injector head, band pass filtered and processed in a personal computer using MatLab. Different injection pressures examined were 250, 240, 230, 220 and 210 bars and fuel injector needle opening and closing impacts in each case were thus revealed in the time-frequency domain using the Wigner-Ville distribution (WVD) technique. The energy of 7-15kHz frequency bands was found to vary according to the injection pressure. The developed enhancement scheme parameters are determined and its consistency in extracting and enhancing signal to noise ratio of injector signatures is examined using simulation and real measured signals; this allows much better condition monitoring information extraction.
URI: http://dx.doi.org/10.1016/j.apacoust.2010.07.001
Appears in Collections:Staff publications - School of Applied Sciences

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