Online friction parameter estimation for machine tools

Abstract

Accurate description of frictional phenomena is essential in applications that require high‐accuracy control. Online monitoring of friction parameters in machine tools greatly improves the control accuracy making condition‐based feedforward compensation possible and, at the same time, facilitates equipment wear assessment, which enables efficient scheduling of maintenance. Existing friction estimation methods that use detailed dynamical models offer accurate description of friction phenomena, but often rely on a priori knowledge of the static friction parameters, which have to be identified offline. This article suggests an adaptive estimation strategy suitable for online use while the machine works in its normal production cycle. Smooth approximations are introduced to account for stiction, viscous and bidirectional Coulomb friction in order to make online estimation possible. A parallel architecture is used with two adaptive estimators that segregate the frictional phenomena that dominate in different parts of the motion regime. Stability properties are analyzed and performance is experimentally validated on a single‐axis state‐of‐the‐art industrial test rig.

Condition Monitoring of Machine Tool Feed Drives: A Review

“…Linear encoder [111] -KF [111] Prognosis/RUL -Vibration [112][113][114] Exponential [112,113], PF [112][113][114] Sensing methods/ technologies -Vibration [115] K F [ 115] Other methods Rotary encoder [116], linear encoder [116], torque [116], NC data [117] -Adaptive estimation [116], parameter estimation [117] Linear guide/slide Wear/degradation Current [118] Vibration [119], strain [64], capacitance [119] Analytic [62,64,118,119] Preload and force -Vibration [102,120], strain [63], piezoresistive [62] EMA [102], OMA [120], empirical [63],…”

“…The online estimation of parameters in nonlinearly parameterized systems can be challenging. Papageorgiou et al [106] designed online adaptive estimators to estimate the backlash and friction parameters [116] in ball screw drives.…”

“…Offline identification of static friction parameters is generally needed to develop accurate dynamic models for friction estimation. Papageorgiou et al [116] present an online adaptive estimation method. The method describes the quasi-discontinuous characteristics of friction while sustaining the required level of smoothness needed for online estimation.…”