Plasma Powder Interaction Process System Identification

The interior ballistic performance of the electrothermal-chemical gun depends on effective utilization of the electrical energy and chemical energy. The interaction of plasma with propellant is the pivotal factor that influences energy efficiency of electrothermal chemical launch. Under this condition, the paper takes the relationship of electric power -pressure and the relationship of pressure- burning rate as researching objects, and establishes their relations identification models. The Models can predict pressure according to electric power, and then predict the burning rate. The researches provides a new research method for improving the ballistic performance.The main contents are as follows:Firstly, the knowledge of the wavelet transform is used for denoising. While measuring the signals in the closed bomb, it will make the data dithering owing to the noises and combustion phenomena. The paper does the decomposition of time-frequency signals according to the theory of wavelet and filters out high-frequency signals in the coupling of the useful signals.Secondly, the paper establishes the identification model of "electric power-pressure" in Plasma-Propellant interactions process using wavelet neural network of knowledge. After the network training and testing, the error between the final model output and the actual data is very small, which proves that the final model can accurately predict the pressure signal.Finally, the paper establishes the identification model of "pressure - the burning rate" based on the burning rate formula and exerting the knowledge of wavelet neural network. The simulated results are in accord with the actual situation basically, which proves that we can master the law of electric power-pressure and the pressure-burning rate. Moreover, the research results can guide the future researches and reduce times of the experiments.