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This research proposes a novel type of variable stiffness tuned particle damper (TPD) for reducing vibrations in boring bars. The TPD integrates the developments of particle damping and dynamical vibration absorber, whose frequency tuning principle is established through an equivalent theoretical model. Based on the multiphase flow theory of gas-solid, it is effective to obtain the equivalent damping and stiffness of the particle damping. The dynamic equations of the coupled system, consisting of a boring bar with the TPD, are built by Hamilton's principle. The vibration suppression of the TPD is assessed by calculating the amplitude responses of the boring bar both with and without the TPD by the Newmark-beta algorithm. Moreover, an improvement is proposed to the existing gas-solid flow theory, and a comparative analysis of introducing the stiffness term on the damping effect is presented. The parameters of the TPD are optimized by the genetic algorithm, and the results indicate that the optimized TPD effectively reduces the peak response of the boring bar system. [ABSTRACT FROM AUTHOR]

An adaptive dynamic vibration absorber (ADVA) is designed for low-frequency vibration suppression. The leaf springs are applied as the tuning stiffness elements. The principle of variable stiffness is analyzed to obtain the effective range of the first natural frequency variation. A classic simply supported manipulator is selected as the controlled system. The coupled dynamic model of the manipulator-ADVA system is built to obtain the maximum damping efficiency and the vibration absorption capacity of the designed ADVA. An experimental platform is set up to verify the theoretical results. It is revealed that the ADVA can adjust the first natural frequency on a large scale by changing the curvature of the leaf springs. The amplitude of the manipulator is reduced obviously with the installation of the designed ADVA. Finally, based on the short-time Fourier transformation (STFT), a stepwise optimization algorithm is proposed to achieve a quick tuning of the natural frequency of the ADVA so that it can always coincide with the frequency of the prime structure. Through the above steps, the intelligent frequency tuning of the ADVA is realized with high vibration absorption performance in a wide frequency range. [ABSTRACT FROM AUTHOR]

Under α stable distribution impulse noise environment, the least mean p-power algorithm (LMP) cannot handle the instability of the algorithm well, due to the large amplitude of the input signal and the large number of useless small weight coefficients in the sparse channel, which delay the convergence speed of the algorithm. In this paper, we develop a new adaptive filtering algorithm, named the proportional normalization least mean p-power (PNLMP) adaptive filtering algorithm. We first introduce a step size control matrix to improve the overall convergence speed and convergence accuracy of the algorithm. Next, to reduce the influence of a large impulse response on the LMP algorithm, a high-order tongue-line function about error is introduced in the normalization processing. Finally, we extend the tongue-line function to ensure that the cost function can also switch freely between V-shaped and M-shaped. This new algorithm overcomes the problem that the traditional LMP algorithm is only applicable to a specific environment and solves the problem of slow convergence speed and low convergence accuracy. Under α stable distribution impulse noise environment, the simulations show that the PNLMP algorithm can improve the convergence speed and stronger system tracking capability compared with existing algorithms, overcoming the problems of slow overall convergence and low convergence accuracy in the traditional algorithm. [ABSTRACT FROM AUTHOR]