Noise Leakage Suppression in Multivariate FRF Measure- ments Using Periodic Excitations

نویسنده

  • R. Pintelon
چکیده

Due to the non-periodic nature of noise, the steady state response of a dynamic system to a periodic input is still subject to noise transients (noise leakage errors). For lightly damped systems these noise transients (significantly) increase the variance of frequency response function (FRF) measurements [1]. This paper presents a method for suppressing the noise transients in FRF measurements using periodic excitations. It is based on a local polynomial approximation of the noise leakage error and is an extension of the results of [1] to multivariable systems. Compared with the local polynomial method for random excitations [2, 3], no local polynomial approximation of the frequency response matrix is made. Irrespective of the number of inputs and outputs, it is shown in this paper that 2 periods of the state state response are enough to suppress the noise transients and to estimate the input-output noise covariance matrix. Since no distinction can be made between the system and noise transients, the presented method is also applicable to the first 2 periods of the transient response of the system to a periodic input. For lightly damped systems this results in a significant reduction of the measurement time.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

An FPGA-based frequency response analyzer for multisine and stepped sine measurements on stationary and time-varying impedance

We report the development of a field programmable gate array (FPGA) based frequency response analyzer (FRA) for impedance frequency response function (FRF) measurements using periodic excitations, i.e. sine waves and multisines. The stepped sine measurement uses two dedicated hardware-built digital embedded multiplier blocks to extract the phase and quadrature components of the output signal. T...

متن کامل

Excitation design for FRF measurements in the presence of nonlinear distortions

In this paper, we discuss optimized strategies to measure the frequency response function in the presence of (nonlinear) distortions. To do so we will compare three classes of excitation signals. These signals will be used in an optimized measurement strategy, reducing the leakage effects to acceptable (user defined) levels, allowing to separate the disturbing noise influence from the impact of...

متن کامل

Measuring a linear approximation to weakly nonlinear MIMO systems

The choice of the input signals has impact on the nonparametric frequency response function (FRF) measurements of a nonlinear MIMO system. It is shown that Gaussian noise, periodic noise, and random multisines are equivalent, yielding in the limit the same linear approximation to a nonlinear MIMO system. Even in the noiseless case, variability of the FRF is observed due to the presence of the n...

متن کامل

ONE Oscillator Dynamics

A well-designed free-running oscillator provides a periodic signal of constant amplitude and frequency fo from the energy delivered by direct-current (dc) sources. This has an immediate application for the realization of local oscillators used in the frequency-conversion stages of communication systems [1]. In receivers, the modulated signal at radio-frequency (RF) fRF is mixed with the output ...

متن کامل

Nonparametric time-variant frequency response function estimates using arbitrary excitations

The time-variant frequency response function (TV-FRF) uniquely characterizes the dynamic behaviour of a linear timevariant (LTV) system. This paper proposes a method for estimating nonparametrically the dynamic part of the TV-FRF from known input, noisy output observations. The arbitrary time-variation of the TV-FRF is modelled by Legendre polynomials. In opposition to existing solutions, the p...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010