Determination of Weak Knock Characteristics for Two-Stroke Spark Ignition UAV Engines Based on Mallat Decomposition Algorithm

Two-stroke spark ignition (SI) unmanned aerial vehicle (UAV) engines do not allow heavy knock and require a certain knock safety margin. However, weak knock can help the engine increase power output and reduce fuel consumption. To accurately extract the knock characteristics of engine vibration signals under the condition of weak knock, a signal feature extraction method based on the Mallat decomposition algorithm was proposed. Mallat decomposition algorithm can decompose the signal into two parts: a low-frequency signal and a high-frequency noise signal. The decomposed high-frequency noise is eliminated, and the low-frequency signal is retained as the characteristic domain signal. Simulation results show the effectiveness of the proposed algorithm. The engine vibration signal of a two-stroke SI UAV engine was decomposed into the low-frequency signal and the high-frequency signal by the Mallat decomposition algorithm. The low-frequency signal is taken as the knock characteristic domain signal component, and the wavelet packet energy method is used to verify the correctness of the obtained signal component. The relative energy parameter is calculated by using the knock characteristic domain signal component, which can be used as the determination index of knock intensity. This method provides a reference for the weak knock control of two-stroke SI UAV engines.