Abstract:

Using the aero-engine chaotic vibration signals to monitor the state and make diagnosis for an aircraft is a valuable method, because the signals contain plenty of state information of nonlinear systems. However, it is difficult to separate chaos signal from other vibration signals by traditional means, for the chaotic signals have fake random characteristics and a wide frequency spectrum in the low frequency range. In this article, the chaotic vibration signal among aero-engine vibration signals is first separated by means of fast ICA blind source separation. Secondly, the chaos is detected via a power spectrum and Lyapunov exponent based on the characteristics of chaos. From the computation results a judgment can be made of the aero-engine vibration state. This proves that fast ICA blind source separation is effective in separating chaotic vibration signals. Separating the chaotic vibration signal using blind source separation not only makes it possible to monitor the state of a plane according to the characteristics of chaos, but also provides a way to predict and control the state of an aircraft.

Key words: aero-engine, chaos vibration signal, blind source separation, Lyapunov exponent, spectrum analysis