Research on Giant Magnetostrictive Actuator for Turning Vibration Control

Magnetostriction is a phenomenon in which a magneti c field is used to produce a change in size of some materials. This property has b een known in elements such as nickel, iron and cobalt. Because the rare-ear th alloy Terfenol-D can offer much larger strains than nickel, iron, cobalt, an d other smart materials such as piezoelectric materials, it is called giant magn etostrictive material. Making use of the giant magnetostrictive material, the gi ant magnetostrictive actuator has higher bandwidth and rapider response than oth er actuators. So it is widely used in active vibration control, especially in lo w frequency stage. In this paper, a turning vibration control system is develope d. The system has an actuator clamped in a flexor that is rigid in the feed and main cutting force directions, yet is flexible in the radial direction. The stru cture of the giant magnetostrictive actuator is developed after magnetic circuit and some structure parameter are calculated. According to the turning frequency , the transient and stable-state output of the giant magnetostrictive actuator is measured. The test result demonstrated that the actuator responses the input rapidly, and the actuator has perfect stable-state and transient output charact eristic. The characteristic includes the stable-state output linearity, repeata bility and transient delay between output displacement and input current.

Robust intelligent modeling for giant magnetostrictive actuators with rate-dependent hysteresis

Purpose–This paper proposes a robust modeling method of a giant magnetostrictive actuator which has a rate-dependent nonlinear property.Design/methodology/approach–It is known in statistics that the Least Wilcoxon learning method developed using Wilcoxon norm is robust against outliers.Thus,it is used in the paper to determine the consequence parameters of the fuzzy rules to reduce the sensitiveness to the outliers in the input-output data.The proposed method partitions the input space adaptively according to the distribution of samples and the partition is irrelative to the dimension of the input data set.Findings–The proposed modeling method can effectively construct a unique dynamic model that describes the rate-dependent hysteresis in a given frequency range with respect to different single-frequency and multi-frequency input signals no matter whether there exist outliers in the training set or not.Simulation results demonstrate that the proposed method is effective and insensitive against the outliers.Originality/value–The main contributions of this paper are:first,an intelligent modeling method is proposed to deal with the rate-dependent hysteresis presented in the giant magnetostrictive actuator and the modeling precision can fulfill the requirement of engineering,such as the online modeling issue in the active vibration control;and second,the proposed method can handle the outliers in the input-output data effectively.