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The easiest way to identify knock conditions during the operation of a SI engine is represented by the knowledge of the in-cylinder pressure. Traditional techniques like MAPO (Maximum Amplitude Pressure Oscillation) based method rely on the frequency domain processing of the pressure data. This technique may present uncertainties due to the correct specification of some model parameters, like the band-pass frequency range and the crank angle window of interest. In this paper two innovative techniques for knock detection, which make use of the in-cylinder pressure, are explained in detail, and the results are compared with those coming from the MAPO method. The first procedure is based on the use of statistical analysis by applying an Auto Regressive (AR) technique, while the second technique makes use of the Discrete Wavelet Transform (DWT). The data useful for the analysis have been acquired on a high compression ratio four cylinder, spark ignition engine.

In the present work, an Auto Regressive Moving Average (ARMA) model and a Discrete Wavelet Transform (DWT) are applied on vibrational signals, acquired by an accelerometer placed on the cylinder block of a Spark Ignition (SI) engine, for knock detection purposes. To the aim of tuning such procedures, the same analysis has been carried out by using the traditional MAPO (Maximum Amplitude of Pressure Oscillations) index and an Inverse Kinetic Model (IKM), both applied on the in-cylinder pressure signals. Vibrational and in-cylinder pressure signals have been collected on a four cylinder, four stroke engine, for different engine speeds, load conditions and spark advances. The results of the two vibrational based methods are compared and in depth discussed to the aim of highlighting the pros and cons of each methodology.

This work presents the results of an experimental investigation on a GDI injector, in order to analyze fuel injection process and atomization phenomenon, correlating imaging and vibro-acoustic diagnostic techniques. A single-hole, axially-disposed, 0.200 mm diameter GDI injector was used to spray commercial gasoline in a test chamber at room temperature and atmospheric backpressure. The explored injection pressures were ranged from 5.0 to 20.0 MPa. Cycle-resolved acquisitions of the spray evolution were acquired by a high-speed camera. Simultaneously, the vibro-acoustic response of the injector was evaluated. More in detail, noise data acquired by a microphone sensor were analyzed for characterizing the acoustic emission of the injection, while a spherical loudspeaker was used to excite the spray injection at a proper distance detecting possible fuel spray resonance phenomena.