SIGNAL ANALYSIS AND PROCESSING OF SHOCK TUNNEL BALANCE BASED ON TIME-FREQUENCY TRANSFORM

Shock tunnel ground test is usually used to study the high-enthalpy aerodynamic characteristics of new hypersonic vehicles. As one of the basic researches of high-temperature aerodynamics, high-precision aerodynamic force measurement is the key technology of shock tunnel ground test. When a force test is conducted in the shock tunnel, the vibration of force measurement system is excited during the starting process of shock tunnel, which causes inertial interference to the output signal of the balance. The balance signals, with dynamic force and inertial-vibration, may not directly show regularity of the real dynamic force, resulting in a big error between the processed balance forces and the real loads, and making the results unreliable. Due to complex structure of the force measurement system, part of the high-frequency components of the balance signal (high-frequency interference caused by structural high-order modal vibration, unsteady aerodynamic load or other flow field interference) may not be fully attenuated within the extremely short-duration (millisecond level). At this time, traditional filter processing and Fourier transform may increase the error of results. In order to solve the problem of aerodynamic force measurement fast and accurately, wavelet transform and Hilbert-Huang transform are used in this study to carry out noise reduction and time-frequency transform analysis for the balance signal in a cone’s force test of shock tunnel, to effectively identify the different interference components and output reliable force results. In this paper, the time-frequency transform is applied to the signal processing of the step-load and balance output. The force results are compared and analyzed to verify the effectiveness and reliability of the current method in the data-processing of the shock tunnel test, and obtain good results. At the same time, the time-frequency processing method of signal in this study will be used in the sample data pre-processing of the shock tunnel balance intelligent research.