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Machine fault diagnosis collects massive amounts of vibration data about complex mechanical systems. Performing feature detection from these data sets has already led to a major challenge. Compressive sensing theory is a new sampling framework that provides an alternative to the well-known Shannon sampling theory. This theory enables the recovery of sparse or compressible signals from a small set of nonadaptive linear measurements. However, it is suboptimal to recover the whole signals from the compressive measurements and then solve feature identification problems through traditional DSP techniques. Thus, a novel mechanical feature identification method is proposed in this paper. Its main advantage is that fault features are extracted directly in the compressive measurement domain without sacrificing accuracy, while a significant reduction in the dimensionality of the measurement data is achieved. Moreover, Gaussian white noises are significantly alleviated, which dramatically enhances the reliability of machine fault diagnosis. Parameter analysis is also profoundly investigated through a set of numerical experiments. Numerical simulations and experiments are further performed to prove the reliability and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The built-in motor of the motorized spindle is the key to realizing its movement. However, the unbalanced magnetic pull (UMP) generated in the built-in motor seriously affects its dynamic stability. In this work, a generalized time-varying dynamic model of the motorized spindle is proposed to evaluate the effect of dynamic loads on the spindle system. The external dynamic loads on the spindle mainly include the UMP generated by the built-in motor, the nonlinear restoring force of the bearing, and the eccentric excitation of the system mass. Considering the change of magnetic path caused by the dynamic displacement of the rotor, the radial and axial projection model and additional torque model of UMP are proposed. Numerical simulations are employed to handle the dynamical equation containing the time-varying UMP function. Based on the simulation results, the effects of built-in motor parameters, bearing parameters, rotor static eccentricity, and other factors on the dynamic characteristics of the spindle system are analyzed. The numerical results of the vibrations are verified experimentally. [ABSTRACT FROM AUTHOR]

• The thermal-mechanical interaction in motorized spindles considering nonlinear vibration is investigated. • An iterative algorithm for thermal and dynamic characteristics is proposed to improve the modeling accuracy. • The nonlinear dynamic model with thermal effects of the spindle system under electromagnetic excitation is developed. • A multi-node thermal resistance network model considering the nonlinear vibration is established. • The equivalent circuit model of the built-in induction motor is analyzed to calculate its electrical parameters. The neglection of thermal-mechanical interaction of the high-speed motorized spindle system may lead to modeling errors of thermal and dynamic characteristics. In this work, the thermal-mechanical interaction mechanism is analyzed, and a closed-loop iterative modeling method for thermal and dynamical characteristics is proposed to improve the modeling accuracy. The nonlinear dynamic model with thermal effects of the spindle system under unbalanced magnetic pull and unbalanced mass excitation is established to evaluate its transient dynamic behavior. A multi-node thermal resistance network model of the motorized spindle system considering the nonlinear vibration of the spindle system is established to evaluate transient thermal behavior. Based on the load-displacement relationship, the nonlinear stiffness and restoring force model of bearing considering thermal effects and nonlinear vibration is established. The heat generation of the bearing and the built-in motor are calculated by Palmgren's formula and the equivalent circuit model of the induction motor, respectively. The bearing heating is improved considering the comprehensive effects of lubricant viscosity change, bearing thermal expansion, and nonlinear dynamic load. The mechanical power loss of the motorized spindle is analyzed to calculate the electrical parameters required to study the spindle dynamics and motor heat generation. The accuracy and effectiveness of the proposed theoretical method are experimentally verified. Numerical simulations show that the thermal and mechanical effects in the motorized spindle system exhibit a non-negligible dynamic interaction. [Display omitted] [ABSTRACT FROM AUTHOR]