On the noise power spectral density of particulate recording media

The ac-noise power spectrum is investigated. Because of the interaction forces between the particles, the structure of the particulate layer has a dominant influence. This structure is quantified by means of the dc-noise power spectrum. Depending on the dispersion and coating technique the duster structure appears to vary. The ac-noise power is described by a mechanism of negative and positive interactions which occur simultaneously. Flux-closuring particles are near to each other at distances less than 0.1 μm, whereas magnetic strings appear to extend over tens of microns.     

脉象采集方法及功率谱分析研究

在对压力脉搏波的分析及中医理论研究基础上,提出了一种多点三维动态压力脉搏波的采集方案,以获得有效的脉象数据用于模拟传统中医诊脉.根据信号功率谱的特点,在数据采集过程中结合了功率谱分析手段动态提取脉象的位置及力度特征,同时通过实验得出脉象变化与压力脉搏波功率谱变化的内在相关性,从而得到一种简单有效的脉象特征分析和提取的实验和研究方法.     

A study of methods of measuring the spectral density of the power of the phase noise of precision quantum frequency and time standards

An analysis of existing methods used in the measurement of the spectral density of the power of phase noise is performed, the advantages and disadvantages of these methods are considered, and results from studies of the phase noise of rubidium and hydrogen frequency and time standards found with the use of different methods are presented.     

Shape of the power spectral density matrix components: Influence on fatigue damage

The damage estimation for a structure under random loading is a challenge in fatigue assessment, especially when the loading is multiaxial. The comparison of the effect of different spectra on fatigue damage is essential when the structure can be subjected to different types of loadings. Therefore, in the present paper, the expected fatigue damage produced on metallic structures by combined bending and torsion stationary proportional and nonproportional loading is evaluated varying the shape of spectra of the normal and shear stress tensor components.     

Reliability analysis of hydraulic systems of LHD machines using the power law process model

Earlier, a preliminary study of the reliability characteristics of a fleet of load-haul-dump (LHD) machines deployed at Kiruna mine showed that the engine and the hydraulics are the two most critical subsystems. Hydraulic systems are selected for further study because such systems are still under a development phase. Maintenance data for two years for these machines are analyzed. The tests for trends and serial correlation showed that times between successive failures for the hydraulic systems are in most cases not independent and identically distributed. Goodness-of-fit tests showed that the power law process model provides a good fit to the failure data of the hydraulic systems. Methods for parameter estimation in the power law process model and estimation of optimal maintenance intervals for such systems are presented. Emphasis is on the use of graphical methods for data analysis.     

A new approach to model isobaric heat capacity and density of some nitride-based nanofluids using Monte Carlo method

A serious gap in the field of nanofluids' modeling is disregarding the effect of molecular structure that must be highlighted. For the first time, the Monte Carlo method was utilized to model isobaric heat capacity and density of nanofluids. A creditable data set was selected contains nitride-based nanofluids (aluminum nitride, titanium nitride, and silicon nitride all dispersed in ethylene glycol). Quasi-simplified molecular-input line-entry system (quasi-SMILES) was applied to represent the structure of nanofluids, successfully. This format made possible incorporating molecular structure besides experimental conditions into the modeling process. The developed models were evaluated precisely; it was found that the statistical qualities were good and their performance was superior to the classical equation. Also, results revealed that some molecular features of nanofluids such as double and triple bond affects isobaric heat capacity and density, while the size of nanoparticles did not impressive affect these properties. It is remarkable to point out that the proposed models introduce a new trend to estimate the thermophysical properties of nanofluids. The utilized approach could be useful for a more reliable and accurate prediction of the other nanofluids' properties.     

A compressive MUSIC spectral approach for identification of closely-spaced structural natural frequencies and post-earthquake damage detection

Motivated by practical needs to reduce data transmission payloads in wireless sensors for vibration-based monitoring of engineering structures, this paper proposes a novel approach for identifying resonant frequencies of white-noise excited structures using acceleration measurements acquired at rates significantly below the Nyquist rate. The approach adopts the deterministic co-prime sub-Nyquist sampling scheme, originally developed to facilitate telecommunication applications, to estimate the autocorrelation function of response acceleration time-histories of low-amplitude white-noise excited structures treated as realizations of a stationary stochastic process. Next, the standard multiple signal classification (MUSIC) spectral estimator is applied to the estimated autocorrelation function enabling the identification of structural natural frequencies with high resolution by simple peak picking in the frequency domain without posing any sparsity conditions to the signals. This is achieved by processing autocorrelation estimates without undertaking any (typically computationally expensive) signal reconstruction step in the time-domain, as required by various recently proposed in the literature sub-Nyquist compressive sensing-based approaches for structural health monitoring, while filtering out any broadband noise added during data acquisition. The accuracy and applicability of the proposed approach is first numerically assessed using computer-generated noise-corrupted acceleration time–history data obtained by a simulation-based framework examining white-noise excited structural systems with two closely-spaced modes of vibration carrying the same amount of energy, and a third isolated weakly excited vibrating mode. Further, damage detection potential of the developed method is numerically illustrated using a white-noise excited reinforced concrete 3-storey frame in a healthy and two damaged states caused by ground motions of increased intensity. The damage assessment relies on shifts in natural frequencies between the pre-earthquake and post-earthquake state. Overall, numerical results demonstrate that the considered approach can accurately identify structural resonances and detect structural damage associated with changes to natural frequencies as minor as 1% by sampling up to 78% below Nyquist rate for signal to noise ratio as low as 10dB. These results suggest that the adopted approach is robust and noise-immune while it can reduce data transmission requirements in acceleration wireless sensors for natural frequency identification and damage detection in engineering structures.     

Dimension reduction model for two-spatial dimensional stochastic wind field: Hybrid approach of spectral decomposition and wavenumber spectral representation

A renewed methodology for simulating two-spatial dimensional stochastic wind field is addressed in the present study. First, the concept of cross wavenumber spectral density (WSD) function is defined on the basis of power spectral density (PSD) function and spatial coherence function to characterize the spatial variability of the stochastic wind field in the two-spatial dimensions. Then, the hybrid approach of spectral representation and wavenumber spectral representation and that of proper orthogonal decomposition and wavenumber spectral representation are respectively derived from the Cholesky decomposition and eigen decomposition of the constructed WSD matrices. Immediately following that, the uniform hybrid expression of spectral decomposition and wavenumber spectral representation is obtained, which integrates the advantages of both the discrete and continuous methods of one-spatial dimensional stochastic field, allowing for reflecting the spatial characteristics of large-scale structures. Moreover, the dimension reduction model for two-spatial dimensional stochastic wind field is established via adopting random functions correlating the high-dimensional orthogonal random variables with merely 3 elementary random variables, such that this explicitly describes the probability information of stochastic wind field in probability density level. Finally, the numerical investigations of the two-spatial dimensional stochastic wind fields respectively acting on a long-span suspension bridge and a super high-rise building are implemented embedded in the FFT algorithm. The validity and engineering applicability of the proposed method are thus fully verified, providing a potentially effective approach for refined wind-resistance dynamic reliability analysis of large-scale complex engineering structures.     

An approach for the Pasternak elastic foundation parameters estimation of beams using simulated frequencies

As a first attempt, a mix of differential quadrature (DQ) and simplex (S) method for the Pasternak elastic foundation parameters estimation of beams using simulated frequencies is presented. The method is applied for the parameters estimation of functionally graded (FG) beams. The first-order shear deformation theory is employed to derive governing equations of FG beam on the Pasternak elastic foundation. The equations are discretized by utilizing the DQ method and frequencies of the beam are calculated. Then, the simulated frequencies are obtained by applying random error to the calculated frequencies. The simulated frequencies are used as input data for estimating parameters of the problem. An objective function as a root-mean-square error between the calculated and simulated frequencies is defined. The DQ method and simplex technique as a classical optimization technique are coupled to minimize the function via finding the best foundation parameters, iteratively. Some examples are solved to show applicability, robustness and accuracy of the mixed method for elastic foundation parameters estimation of the beam. Also, it has been found that using only the first simulated frequency of the beam cannot give correct parameters of the foundation.     

Standard apparatus for representing the unit of spectral power density over the range 1–100 MHz

Conclusions We propose employing an LFM signal as wideband test signal for checking correlator spectrum analyzers. Standard apparatus for reproducing LFM signals can, in the opinion of the authors, form a basis for the development of a standard to reproduce the unit of spectral power density in the frequency range 1–100 MHz.Translated from Izmeritel'naya Tekhnika, No. 6, pp. 58–60, June, 1978.     

An efficient simulation approach for multivariate nonstationary process: Hybrid of wavelet and spectral representation method

Currently, the classical spectral representation method (SRM) for nonstationary process simulation is widely used in the engineering community. Although this scheme has the higher accuracy, the time-dependent spectra results in unavailability of fast Fourier transform (FFT) and thus the simulation efficiency is lower. On the other hand, the approach based on stochastic decomposition can apply FFT in the simulation. However, the algorithm including the fitting procedure is relatively complicated and thus limits its use in practice.In this paper, the hybrid efficient simulation method is proposed for the vector-valued nonstationary process, which contains the spectra decomposition via wavelets and SRM. This method can take advantage of FFT and is also straightforward to engineering application. Numerical examples are employed to evaluate the proposed method. Results show that the method performs fairly well for the scalar process and vector-valued process with real coherence function. In the case of complex coherence function, the majority of the phase in the coherence function cannot be remained in the simulation. In addition, the validity of proper orthogonal decomposition (POD) in nonstationary process simulation via the decomposition of the time-dependent nonstationary spectra is studied. Analysis shows that the direct use of POD in nonstationary spectra decomposition may not be useful in nonstationary process simulations.     

The method of separation for evolutionary spectral density estimation of multi-variate and multi-dimensional non-stationary stochastic processes

The method of separation can be used as a non-parametric estimation technique, especially suitable for evolutionary spectral density functions of uniformly modulated and strongly narrow-band stochastic processes. The paper at hand provides a consistent derivation of method of separation based spectrum estimation for the general multi-variate and multi-dimensional case. The validity of the method is demonstrated by benchmark tests with uniformly modulated spectra, for which convergence to the analytical solution is demonstrated. The key advantage of the method of separation is the minimization of spectral dispersion due to optimum time- or space–frequency localization. This is illustrated by the calibration of multi-dimensional and multi-variate geometric imperfection models from strongly narrow-band measurements in I-beams and cylindrical shells. Finally, the application of the method of separation based estimates for the stochastic buckling analysis of the example structures is briefly discussed.