Research on active vibration control of blade using variable-step-size filtered-x least mean square algorithm

Abstract

The engine blade is one of the important parts of the aero engine, vibration can lead to engine blade off or fracture. Active Vibration Control (AVC) has a higher flexibility is increasingly used to suppress the vibration of the blade. The filtered-x least mean square (FxLMS) algorithm is an adaptive algorithm commonly used in active vibration control, but its fixed step size has a contradiction between convergence speed and steady-state error. A new variable-step-size FxLMS (VSSFxLMS) algorithm based on hyperbolic secant function was proposed, and the sech function ensures the control signal is bounded. In the early stage, a larger step size enables the error to decrease rapidly. The step size decreases as the error decreases, and a smaller step size ensures a smaller steady-state error. Firstly, this paper summarizes three VSSFxLMS algorithms and proposes an improved algorithm; Secondly, it compares and analyses the mentioned algorithms; Then, a joint simulation platform using ADAMS and Simulink is built to verify the effectiveness of the proposed algorithms; Finally, an experimental platform was built to complete the blade vibration active control experiments using several VSSFxLMS algorithms, and the results of the experiment verify the better vibration suppression effect of the proposed algorithm.