In this paper, techniques for machining and micro-structuring dimples and grooves on the interior of cylinders using an active rotating tool are discussed. Microscopic dimples and grooves patterned on the inner surfac...
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In this paper, techniques for machining and micro-structuring dimples and grooves on the interior of cylinders using an active rotating tool are discussed. Microscopic dimples and grooves patterned on the inner surface of a cylinder act as lubrication and reduce friction. The active rotating tool presented here is equipped with a gap sensor that can measure the distance between the tool, workpiece, and machining tip so that micron-scale dimples and grooves can be patterned and connected to piezoelectric actuators. Electronic control and power connections are made to the external controller via a slip ring. Accurate measurements of the distance between the tool and workpiece were used to increase the lubrication effect by machining patterns with uniform size and depth. It is difficult to accurately measure errors in cylinders of various shapes using a single gap sensor;thus, we employed two gap sensors to ensure accurate assessment of cylinder shape, and a least mean square algorithm was implemented to compensate for the measured runout errors, which were tracked and compensated using the gap sensor. The method presented here reduces errors on the inner face of a cylinder, and produces a uniform pattern.
In this study, commutation error (CE) is defined in adaptive infinite impulse response (IIR) filter-based ANC systems. CE is subsequently introduced into a new residual error to develop a new lms-based ANC algorithm i...
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In this study, commutation error (CE) is defined in adaptive infinite impulse response (IIR) filter-based ANC systems. CE is subsequently introduced into a new residual error to develop a new lms-based ANC algorithm in an aim to liberate the restriction of slow adaptation posed on traditional ANC algorithms. A new deterministic analysis based on a linear time-varying system is performed to investigate convergence properties of the developed algorithm: (1) An optimal step size for the fastest convergence rate can be derived. (2) Given a persistent excitation condition and a step-size constraint, we find that the algorithm is uniformly asymptotically stable. Computer simulations indeed demonstrate a greatly improved convergence rate and efficient ANC performance for the developed algorithm as compared with that using the conventional algorithms. Experimental results verify the enhanced ANC performance in real applications. These together support the new IIR filter-based adaptive algorithm that includes CE for superior ANC performance with respect to the convergence rate and noise reduction level. (C) 2008 Elsevier Ltd. All rights reserved.
In describing the mean square convergence of the lms algorithm, the update formula based on independence assumption will bring explicit errors, especially when step-size is large. A modifier formula that describes the...
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In describing the mean square convergence of the lms algorithm, the update formula based on independence assumption will bring explicit errors, especially when step-size is large. A modifier formula that describes the convergence well, is proposed. Simulations support the proposed formula in different conditions.
An independence assumption on the input vectors is commonly used when stating the convergence of the least mean square algorithm is adaptive filtering. From this hypothesis a range in which the convergence factor must...
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An independence assumption on the input vectors is commonly used when stating the convergence of the least mean square algorithm is adaptive filtering. From this hypothesis a range in which the convergence factor must be chosen is determined. In this paper the independence assumption, unrealistic in the case of adaptive filtering, is avoided. From stability theory of discrete-time systems, a new range for the convergence factor is obtained. (C) 2004 Elsevier B.V. All rights reserved.
When the rotor is rotating at high speed, magnetically suspended control and sensitive gyroscope (MSCSG) will generate synchronous and multifrequency vibration due to rotor mass unbalance and sensor runout, which will...
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When the rotor is rotating at high speed, magnetically suspended control and sensitive gyroscope (MSCSG) will generate synchronous and multifrequency vibration due to rotor mass unbalance and sensor runout, which will affect the measurement accuracy of output torque and attitude angular velocity. In order to suppress the above unbalanced vibration, first, the dynamic model of MSCSG with unbalance vibration torque is established, and the influence of unbalance vibration on the measurement accuracy of attitude angular velocity is analyzed. Then, combined with the strong coupling characteristics of two tilt channels, an unbalance vibration suppression method based on arsinh function of normalized variable step size lms (arsinh-Nlms) algorithm is proposed, which can adjust the step size according to different frequency components to improve the convergence rate. The arsinh function is used to ensure that there is a small error in the steady-state and the normalization process reduces the sensitivity of the algorithm to the input signal and tracks the harmonic components of the control current better. Finally, the simulation and experimental results show that the proposed method can effectively suppress the synchronous and multifrequency disturbance currents and vibration torques in MSCSG and reduce the influence of unbalance vibration on MSCSG performance and angular velocity measurement accuracy.
A Newton/lms algorithm using a modified DCT is proposed which uses an efficient technique of inverting the input autocorrelation matrix when the periodic pseudorandom sequence is used as the reference signal. The numb...
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A Newton/lms algorithm using a modified DCT is proposed which uses an efficient technique of inverting the input autocorrelation matrix when the periodic pseudorandom sequence is used as the reference signal. The number of operations is greatly reduced and the computational results show fast convergence rate and low misadjustment error. The application of the algorithm to the case of nonperiodic reference signal is also described.
This paper studies the stochastic behavior of the lms algorithm in a system identification framework for a cyclostationary colored input without assuming a Gaussian distribution for the input. The input cyclostationar...
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This paper studies the stochastic behavior of the lms algorithm in a system identification framework for a cyclostationary colored input without assuming a Gaussian distribution for the input. The input cyclostationary signal is modeled by a colored random process with periodically time-varying power. The generation of the colored non-Gaussian random process is parametrized in novel manner by passing a Gaussian random process through a coloring filter followed by a zero memory nonlinearity. The unknown system parameters are fixed in most of the cases studied here. Mathematical models are derived for the behavior of the mean and mean-square-deviation (MSD) and the excess mean-square error (EMSE) of the adaptive weights as a function of the input cyclostationarity. The models display the dependence of the algorithm upon the input nonlinearity and coloration. Three nonlinearities that are studied in detail with Monte Carlo simulations provide strong support for the theory. (C) 2019 Published by Elsevier Inc.
The computation of block-based discrete orthogonal transforms using the adaptive least-mean-square (lms) algorithm has been studied in literature. This brief extends this work by establishing the relationship between ...
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The computation of block-based discrete orthogonal transforms using the adaptive least-mean-square (lms) algorithm has been studied in literature. This brief extends this work by establishing the relationship between the running discrete Hartley transform (DHT), the discrete W transforms (DWT's), and the lms algorithm. As a result a new parallel approach for computing the running DHT and DWT's is proposed.
This paper presents a stochastic analysis of the delayed least-mean-square (Dlms) adaptive algorithm with leakage. This analysis is obtained taking into account that mismatches between the system delay and its estimat...
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This paper presents a stochastic analysis of the delayed least-mean-square (Dlms) adaptive algorithm with leakage. This analysis is obtained taking into account that mismatches between the system delay and its estimate may occur. Such an approach is not considered in previous models. In addition, it is shown that the introduction of a leakage factor into the adaptive algorithm keeps the adaptive algorithm stable under an imperfect delay estimate condition. Recursive difference equations for the first and second moments of the adaptive filter weights are derived. An expression for the critical value of the step size is also determined. Results of Monte Carlo simulations present excellent agreement with the proposed model for both white and colored Gaussian inputs.
Least mean square (lms)-based computation of block-based discrete orthogonal transforms has been extensively studied in literature [1]-[5], This paper establishes the relationship between the running discrete cosine t...
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Least mean square (lms)-based computation of block-based discrete orthogonal transforms has been extensively studied in literature [1]-[5], This paper establishes the relationship between the running discrete cosine transform II (DCT-II), discrete sine transform II (DST-II), and the adaptive lms algorithm, From this analysis a new parallel structure for computing the running DCT-II and DST-II is proposed.
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