Piezoelectric self-sensing actuator for active vibration control of motorized spindle based on adaptive signal separation

Abstract

The motorized spindle is the core component of CNC machine tools, and the vibration of it reduces the machining precision and service life of the machine tools. Owing to the fast response, large output force, and displacement of the piezoelectric stack, it is often used as the actuator in the active vibration control of the spindle. A piezoelectric self-sensing actuator (SSA) can reduce the cost of the active vibration control system and simplify the structure by eliminating the use of a sensor, because a SSA can have both actuating and sensing functions at the same time. The signal separation method of a SSA based on a bridge circuit is widely applied because of its simple principle and easy implementation. However, it is difficult to maintain dynamic balance of the circuit. Prior research has used adaptive algorithm to balance of the bridge circuit on the flexible beam dynamically, but those algorithms need no correlation between sensing and control voltage, which limit the applications of SSA in the vibration control of the rotor-bearing system. Here, the electromechanical coupling model of the piezoelectric stack is established, followed by establishment of the dynamic model of the spindle system. Next, a new adaptive signal separation method based on the bridge circuit is proposed, which can separate relative small sensing voltage from related mixed voltage adaptively. The experimental results show that when the self-sensing signal obtained from the proposed method is used as a displacement signal, the vibration of the motorized spindle can be suppressed effectively through a linear quadratic Gaussian (LQG) algorithm.

An Overview of Piezoelectric Self-Sensing Actuation for Nanopositioning Applications: Electrical Circuits, Displacement, and Force Estimation

“…Since it is difficult to maintain a dynamic balance of the voltage-based SSA, this results in a significant error in signal separation, which hampers the applicability of this technique and adversely affects performance and stability of the closed-loop control system. Ye He et al [35] proposed an adaptative signal separation algorithm to estimate the gain between halfbridges to automatically adjust the bridge circuit balance to eliminate the part of v s that is related to v c . Although innovative, this method does not take into account the impact of the control input voltage, v c , on C pea .…”

“…where α Q is denoted as the PEA charge-displacement coefficient. The coefficients α Q and α v are identified empirically [35], [39].…”

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