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In this two‐part paper, aeroelastic analysis of turbomachinery blade rows and phase‐lagged boundary conditions used for analysis are described. Part I of the paper describes a study of phase‐lagged boundary condition methods used for non‐zero interblade phase angle analysis. The merits of time‐shifted (direct‐store), Fourier decomposition and multiple passage methods are compared. These methods are implemented in a time marching Euler/Navier‐Stokes solver and are applied to a fan for subsonic and supersonic inflow and to a turbine geometry with supersonic exit flow. Results showed good comparisons with published results and measured data. The time‐shifted and Fourier decomposition methods compared favorably in computational costs with respect to multiple passage analysis despite a slower rate of convergence. The Fourier‐decomposition method was found to be better suited for workstation environment as it required significantly less storage, although at the expense of slightly higher computational cost. The time‐shifted method was found to be better suited for computers where fast input‐output devices are available.

An equivalent linear damping model is developed for forward flight condition, with the flap/lag/pitch kinematics and nonlinear characteristics of hydraulic damper taken into account. Damper axial velocity is analyzed from the velocities of the damper‐to‐blade attachment point in time domain. For the case of blade lead‐lag oscillations without forced excitation and kinematics, the equivalent linear damping is calculated from transient response with energy balance method, Fourier series based moving block analysis and Hilbert transform based technology, respectively. Results indicate that equivalent linear damping decreases significantly with lead‐lag forced excitation and flap/lag/pitch kinematics, especially with the latter in flight condition.

Provides an introduction into wavelets and illustrates their application with two examples. The wavelet transform provides the analyst with a scaleable time‐frequency representation of the signal, which may uncover details not evidenced by conventional signal processing techniques. The signals used in this paper are Doppler ultrasound recordings of blood flow velocity taken from the internal carotid artery and the femoral artery. Shows how wavelets can be used as an alternative signal processing tool to the short time Fourier transform for the extraction of the time‐frequency distribution of Doppler ultrasound signals. Implements wavelet‐based adaptive filtering for the extraction of maximum blood velocity envelopes in the post processing of Doppler signals.

The purpose of this paper is to study the fault diagnosis of internal combustion (IC) engine gearbox using vibration signals with signal processing and machine learning (ML) techniques.

Vibration signals from the gearbox are acquired for healthy and induced faulty conditions of the gear. In this study, 50% tooth fault and 100% tooth fault are chosen as gear faults in the driver gear. The acquired signals are processed and analyzed using signal processing and ML techniques.

The obtained results show that variation in the amplitude of the crankshaft rotational frequency (CRF) and gear mesh frequency (GMF) for different conditions of the gearbox with various load conditions. ML techniques were also employed in developing the fault diagnosis system using statistical features. J48 decision tree provides better classification accuracy about 85.1852% in identifying gearbox conditions.

The proposed approach can be used effectively for fault diagnosis of IC engine gearbox. Spectrum and continuous wavelet transform (CWT) provide better information about gear fault conditions using time–frequency characteristics.

In this paper, experiments are conducted on real-time running condition of IC engine gearbox while considering combustion. Eddy current dynamometer is attached to output shaft of the engine for applying load. Spectrum, cepstrum, short-time Fourier transform (STFT) and wavelet analysis are performed. Spectrum, cepstrum and CWT provide better information about gear fault conditions using time–frequency characteristics. ML techniques were used in analyzing classification accuracy of the experimental data to detect the gearbox conditions using various classifiers. Hence, these techniques can be used for detection of faults in the IC engine gearbox and other reciprocating/rotating machineries.

This study examines the tracking error (TE) of a sample of sector exchange traded funds (ETFs) using spectral techniques.

TE is examined by computing its power spectrum using the wavelet transform. The wavelet transform maps the TE time series from the time domain to the time–frequency domain. Albeit the wavelet transform is a more complicated mathematical tool compared with the Fourier transform, it also has important advantages such as that it allows to analyze non-stationary data and to detect transient behavior.

Results show that changes in the TE of a sample of sector ETFs are captured by the wavelet transform. Moreover, the authors also find that the wavelet coherence function can be used as a measure of TE in the time–frequency domain.

The study shows that the wavelet coherence function can be used as a reliable measure of TE.

The purpose of this research is to show that wavelets are mathematical tools capable of separating vibration data into different frequency components, allowing the study of each component with a resolution matched to its specific time scale. Wavelets have advantages over traditional Fourier methods, particularly when a signal contains sharp spikes, discontinuities, and transients.

This paper presents a brief description of wavelets and shows their application to the analysis of typical transient signals due to vibrations in a steel‐reinforced concrete beam.

The research clearly shows that it is possible to evaluate modes and components separately by using the wavelet analysis.

The beam analysed can be used as a simple model of other more complicated structures, such as bridges and other high scale civil engineering constructions, where vibration analysis is a key issue for maintenance and failure assessments, thus representing an alternative mathematical tool for condition monitoring.

The purpose of this paper is to examine the causal relationship between Chinese housing and stock markets. The authors discuss the three transmission mechanisms between the two markets: wealth effect, modern portfolio theory and credit-price effect. Moreover, the authors focus on the effects of inflation on the relationship between the two markets.

This paper uses wavelet analysis to test the housing and stock markets relationship both in the frequency domain and time domain.

The empirical results indicate that housing prices have a positive effect on stock prices, and these have the same effect on housing prices. Moreover, this positive effect means that stock prices have a wealth effect on housing prices and these have a credit-price effect on stock prices.

These results provide information to financial institutions and individual investors in China to assist them in constructing investment portfolios within these two asset markets.

The authors first use wavelet analysis to analyze Chinese housing and stock markets and to provide information both on the frequency domain and time domain. Moreover, the authors take the inflation factor as a control variable in the causal relationship between the housing and stock markets.

The purpose of this paper is to extract features from vibration signals measured from induction motors subjected to accelerated aging of bearings by fluting tests.

Aging tests were performed according to IEEE test procedures. The data acquisition involved the measurement of vibration signals using accelerometers that were installed on the bearings and on the motor casing. In this application, only two accelerometers, which were placed near the process end of the motor bearing, are used for data analysis and feature extraction studies. After the data collection, information from the two sensors was combined using simple sensor fusion method under the linearity conditions, and then spectral analysis and time‐scale analysis were performed. The fused vibration signal is decomposed into several scales using continuous wavelet transform (CWT) and its first scale is used to indicate the bearing degradation.

Bearing damage characterization was determined between 2‐4 kHz and some specific frequencies were calculated as harmonics of the bearing characteristic frequencies.

The bearing damage characteristics used in this study is occurred by the experimental study. In terms of the methodology, the use of the CWT shows the fault characteristics from the initial case.

The experimental study and data acquisition are based on the accelerated aging of the motor bearings. Hence, the real aging is represented by the accelerated one. But, this situation reflects same properties of the aging occurred in industrial environments. The methodology is also applicable to the hardware application.

There are two important aspects of this research: the experimental study and the application of CWT to get the potential defects, which will appear as a failure in future, from the healthy case of the motor bearings.

Drape of the fabric is its ability to hang freely in graceful folds when some area of it is supported over a surface and the rest is unsupported. When two‐dimensional fabrics are converted to three‐dimensional garment forms, a number of operations are required which affect drape behaviour of the fabric while present in garment form. In the present study, the effect of sewing and fusing of interlining on drape behaviour of men's suiting fabrics is investigated.Design/methodology/approach – The effect of sewing and fusing of interlining on drape behaviour of men's suiting fabrics is investigated. Comparisons were also made between different stitches (chain stitch and lock stitch), different seams for lock stitch and different types of interlinings for their effect on drape behaviour of fabrics. In addition to drape coefficient and number of folds, a new drape parameter – average amplitude to average radius (A/r) ratio – was also defined and calculated for drape image geometry.Findings – Drape coefficient has a good to strong correlation with A/r ratio and number of folds for most of the shell, sewn and interlining fused fabrics except for a few cases. A/r defines image in a more descriptive manner than drape coefficient. Drape coefficient changes with the types of seams and stitches used, as well as with the interlining used.Originality/value – This paper provides information on the effects of sewing (seams and stitch types) and fused interlining on drape behaviour of men's suiting fabrics.

The use of lasers to selectively solder joints in electronic assemblies has a number of advantages over methods which involve heating of the whole assembly. However, the localised energy delivery means that the heating and melting behaviour of the solder is particularly dependent on external and process influences. This paper aims to propose a new approach to monitoring and feedback control of the melting process through image acquisition and processing.

In order to evaluate the proposed feedback strategy, a series of experiments have been performed using a semiconductor diode laser controlled by a PC, which also performs image acquisition and processing operations. Two main processing techniques, based on edge detection and Fourier analysis, have been evaluated.

It has been shown that the proposed technique is capable of controlling laser pulse duration to correct for variations in joint geometry, material parameters and laser energy delivery and results in more consistent solder joint formation than is achieved using fixed pulse durations.

The results demonstrate that image processing is a viable technique for the control of laser soldering processes. This could significantly increase the range of applications of laser soldering techniques where determination and control of pulse parameters have been one of the major challenges.

Although some work has been conducted on the use of pyrometer feedback to control laser processing, it appears that no work has been published on the use of image processing. While the processing algorithms themselves are not novel, this is a new application of these algorithms.