Active tool vibration control and tool condition monitoring using a self-sensing actuator

Abstract

The studies consist of two simulations of active tool vibration control and tool condition monitoring respectively and a hardware-in-the-loop laboratory demonstration of active tool vibration control typical to turning. Besides reducing the restricting effects of tool vibrations on productivity, work-piece surface finish and tool life, it is desirable to handle lack of space at the tool tip and the cost of control systems in turning processes in an effective way. These two aspects are here considered by means of the concept of a self-sensing actuator (SSA) in the simulation of tool vibration control. In the simulation an IIRfilter represents the structure of the passive tool holder. A known pre-filtering technique was applied to the error in a feedback filtered-x LMS algorithm to maintain the stability of the control system. The self-sensing path is modelled and illustrated. The IIR-filters and their inverses were used for modelling this path, with equations resulting from the nodal displacements associated with nodes that have forces acting on them. For the cantilever type structure a considerable reduction of 93% of the displacement r.m.s. values of the tool tip, was obtained when using this control system. Signal processing using orthogonal cutting force components for tool condition monitoring (TCM) has established itself in literature. Single axis strain sensors however limit TCM to linear combination of cutting force components. This situation may arise when a single axis piezoelectric actuator is simultaneously used as an actuator and a sensor, e.g. its vibration control feedback signal exploited for monitoring purposes. Processing of a linear combination of cutting force components to the reference case of processing orthogonal components is compared. The same time-delay neural network structure has been applied in each case. Reconstruction of the dynamic force acting at the tool tip in a turning process is described. By simulation this dynamic force signal was applied to a model of the tool holder equipped with a SSA. Using a wavelet packet analysis, wear-sensitive features were extracted. The probability of a difference less than 5 percentage points between the flank wear estimation errors of abovementioned two processing strategies is at least 95 %. This study proves the basic concept of adaptive feedback active vibration control in combination with a self-sensing actuator to control tool vibrations. The structure involved is representative of a tool post clamped tool holder. The advantages that adaptive control hold when applied to non-stationary vibrations motivate this investigation. Secondly the dual functionality of a piezoelectric element is utilized for system simplification. Actuator linearization measures are considered and a model for the system’s forward path identified. The tool vibrations signal for this work is of 100 Hz bandwidth around the representative tool holder bending mode. A downscaled force based on real cutting force characteristics was artificially applied to the representative tool holder. Limited form locking contact with the tool holder restricted the actuator’s reaction to compressive forces only. Results of up to 70% attenuation of vibration induced strain on the SSA were achieved. This method clearly shows concept viability.