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1 – 10 of over 1000
Article
Publication date: 23 September 2019

H.S. Kumar, P. Srinivasa Pai and Sriram N. S

The purpose of this paper is to classify different conditions of the rolling element bearing (REB) using vibration signals acquired from a customized bearing test rig.

Abstract

Purpose

The purpose of this paper is to classify different conditions of the rolling element bearing (REB) using vibration signals acquired from a customized bearing test rig.

Design/methodology/approach

An effort has been made to develop health index (HI) based on singular values of the statistical features to classify different conditions of the REB. The vibration signals from the normal bearing (N), bearing with defect on ball (B), bearing with defect on inner race (IR) and bearing with defect on outer race (OR) have been acquired from a customized bearing test rig under variable load and speed conditions. These signals were subjected to “modified kurtosis hybrid thresholding rule” (MKHTR)-based denoising. The denoised signals were decomposed using discrete wavelet transform. A total of 17 statistical features have been extracted from the wavelet coefficients of the decomposed signal.

Findings

Singular values of the statistical features can be effectively used for REB classification.

Practical implications

REB are critical components of rotary machinery right across the industrial sectors. It is a well-known fact that critical bearing failures causes major breakdowns resulting in untold and most expensive downtimes that should be avoided at all costs. Hence, intelligently based bearing failure diagnosis and prognosis should be an integral part of the asset maintenance and management activity in any industry using rotary machines.

Originality/value

It is found that singular values of the statistical features exhibit a constant value and accordingly can be assigned to each type of bearing fault and can be used for fault characterization in practical applications. The effectiveness of this index has been established by applying this to data from Case Western Reserve University data base which is a standard bench mark data for this application. HIs minimizes the computation time when compared to fault diagnosis using soft computing techniques.

Details

Journal of Quality in Maintenance Engineering, vol. 26 no. 2
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 1 January 1985

JAN SIKORA, JERZY SKOCZYLAS, JAN SROKA and STANISLAW WINCENCIAK

This paper discusses an electrostatic, homogeneous field in a uniform two‐dimensional domain with Neumann's boundary conditions. The boundary conditions are known only at some…

Abstract

This paper discusses an electrostatic, homogeneous field in a uniform two‐dimensional domain with Neumann's boundary conditions. The boundary conditions are known only at some segments of the boundary. The synthesis is understood as the computation of the remaining boundary conditions which would ensure the required potential distribution in some subdomains within the boundary. The introduction of a single‐layer potential leads to Fredholm's equation of the second order. Stepwise approximation of the source distribution along the boundary rearranges Fredholm's equation and the requirements concerning the single layer potential distribution. It leads to a matrix equation with a rectangular coefficient matrix. In order to solve approximately this equation, in the sense of the least squares minimization, the singular value decomposition (SVD) method is used. The choice of subdomains with determined potential distribution influences significantly the conditioning of the equation. Easy selection of an acceptable solution among all possible solutions proves the suitability of the SVD method in the above problem. The numerical experiments reported in the paper are a good illustration of this.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 4 no. 1
Type: Research Article
ISSN: 0332-1649

Article
Publication date: 9 August 2022

Xiangnan Liu and Kuanfang He

The purpose of this paper is to propose a new fault feature extraction scheme for the rolling element bearing.

Abstract

Purpose

The purpose of this paper is to propose a new fault feature extraction scheme for the rolling element bearing.

Design/methodology/approach

The generalized Stockwell transform (GST) and the singular value ratio spectrum (SVRS) methods are combined. A time-frequency distribution measurement criterion named the energy concentration measurement (ECM) is initially used to determine the parameter of the optimal GST method. Then, the optimal GST is applied to conduct a time-frequency transformation for a raw signal. Subsequently, the two-dimensional time-frequency matrix is obtained. Finally, the improved singular value decomposition (SVD) analysis is used to conduct a noise reduction of the time-frequency matrix. The SVRS is proposed to select the effective singular values. Furthermore, the time-domain feature of the impact signal is obtained by taking the inverse GST transform.

Findings

The simulated and experimental signals are used to verify the superiority of the proposed method over conventional methods. The obtained results show that the proposed method can effectively extract fault features of the rolling element bearing.

Research limitations/implications

This paper mainly discusses the application of GST and SVRS methods to analyze the weak fault feature extraction problem. The next research direction is to explore the application of the Hilbert Huang transform (HHT) and variational modal decomposition (VMD) in the impact feature extraction of rolling bearing.

Originality/value

In the present study, a new SVRS method is proposed to select the number of effective singular values. This paper proposed an effective way to obtain the fault feature in monitoring of rotating machinery.

Article
Publication date: 11 April 2023

Zhenzhen Shang, Libo Yang, Wendong Zhang, Guojun Zhang, Xiaoyong Zhang, Hairong Kou, Junbing Shi and Xin Xue

This paper aims to solve the problem that strong noise interference seriously affects the direction of arrival (DOA) estimation in complex underwater acoustic environment. In this…

Abstract

Purpose

This paper aims to solve the problem that strong noise interference seriously affects the direction of arrival (DOA) estimation in complex underwater acoustic environment. In this paper, a combined noise reduction algorithm and micro-electro-mechanical system (MEMS) vector hydrophone DOA estimation algorithm based on singular value decomposition (SVD), variational mode decomposition (VMD) and wavelet threshold denoising (WTD) is proposed.

Design/methodology/approach

Firstly, the parameters of VMD are determined by SVD, and the VMD method can decompose the signal into multiple intrinsic mode functions (IMFs). Secondly, the effective IMF component is determined according to the correlation coefficient criterion and the IMF less than the threshold is processed by WTD. Then, reconstruction is carried out to achieve the purpose of denoising and calibration baseline drift. Finally, DOA estimation is achieved by the combined directional algorithm of preprocessed signal.

Findings

Simulation and field experiments results show that the algorithm has good noise reduction and baseline drift correction effects for nonstationary underwater signals, and high-precision azimuth estimation is realized.

Originality/value

This research provides the basis for MEMS hydrophone detection and positioning and has great engineering significance in underwater detection system.

Article
Publication date: 1 April 1995

Lorraine G. Olson and Robert D. Throne

We compare a recently proposed generalized eigensystem approach and anew modified generalized eigensystem approach to more widely used truncatedsingular value decomposition and…

Abstract

We compare a recently proposed generalized eigensystem approach and a new modified generalized eigensystem approach to more widely used truncated singular value decomposition and zero‐order Tikhonov regularization for solving multidimensional elliptic inverse problems. As a test case, we use a finite element representation of a homogeneous eccentric spheres model of the inverse problem of electrocardiography. Special attention is paid to numerical issues of accuracy, convergence, and robustness. While the new generalized eigensystem methods are substantially more demanding computationally, they exhibit improved accuracy and convergence compared with widely used methods and offer substantially better robustness.

Details

Engineering Computations, vol. 12 no. 4
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 21 November 2023

Heping Liu, Sanaullah, Angelo Vumiliya and Ani Luo

The aim of this article is to obtain a stable tensegrity structure by using the minimum knowledge of the structure.

Abstract

Purpose

The aim of this article is to obtain a stable tensegrity structure by using the minimum knowledge of the structure.

Design/methodology/approach

Three methods have been formulated based on the eigen value decomposition (EVD) and singular value decomposition theorems. These two theorems are being implemented on the matrices, which are computed from the minimal data of the structure. The required minimum data for the structure is the dimension of the structure, the connectivity matrix of the structure and the initial force density matrix computed from the type of elements. The stability of the structure is analyzed based on the rank deficiency of the force density matrix and equilibrium matrix.

Findings

The main purpose of this article is to use the defined methods to find (1) the nodal coordinates of the structure, (2) the final force density values of the structure, (3) single self-stress from multiple self-stresses and (4) the stable structure.

Originality/value

By using the defined approaches, one can understand the difference of each method, which includes, (1) the selection of eigenvalues, (2) the selection of nodal coordinates from the first decomposition theorem, (3) the selection of mechanism mode and force density values further and (4) the solution of single feasible self-stress from multiple self-stresses.

Details

Engineering Computations, vol. 41 no. 1
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 17 March 2016

suryanarayana gunnam and Ravindra Dhuli

The purpose of this paper is to present an improved wavelet based approach in single image super resolution (SISR). The proposed method generates high resolution (HR) images by…

Abstract

Purpose

The purpose of this paper is to present an improved wavelet based approach in single image super resolution (SISR). The proposed method generates high resolution (HR) images by preserving the image contrast and edges simultaneously.

Design/methodology/approach

Covariance based interpolation algorithm is employed to obtain an initial estimate of the unknown HR image. The proposed method preserves the image contrast, by applying singular value decomposition (SVD) based correction on the dual-tree complex wavelet transform (DT-CWT) coefficients. In addition, the dual operating mode diffusion based shock filter (DBSF) ensures noise mitigation and edge preservation.

Findings

Experimental results on various test images reveal superiority of the proposed method over the existing SISR techniques in terms of peak signal to noise ratio (PSNR), structural similarity index measure (SSIM) and visual quality.

Originality/value

With SVD based correction, the proposed method preserves the image contrast and also the DBSF operation helps to achieve sharper edges.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 35 no. 3
Type: Research Article
ISSN: 0332-1649

Open Access
Article
Publication date: 8 July 2019

Giovana Sordi Schiavi, Ariel Behr and Carla Bonato Marcolin

This paper aims to elaborate a set of characteristics that conceptualize and qualify a disruptive business model.

2477

Abstract

Purpose

This paper aims to elaborate a set of characteristics that conceptualize and qualify a disruptive business model.

Design/methodology/approach

The literature on disruptive business models will be analyzed using the latent semantic analysis (LSA) technique, complemented by content analysis, to obtain a more precise qualification and conceptualization regarding disruptive business models.

Findings

The results found described concepts already described in the theory. However, such findings, highlighted by the LSA, bring new perspectives to the analysis of the disruptive business models, little discussed in the literature and which reveal important considerations to be made on this subject.

Research limitations/implications

It should be noted, about the technique used, a limitation on the choice of the number of singular values. For this to be a problem in the open literature, the authors tried to work not just with the cost-benefit ratio given the addition of each new dimension in the analysis, as well as a criterion of saturation of the terms presented.

Practical implications

The presentation of this set of characteristics can be used as a validation tool to identify if a business is or is not a disruptive business model by managers.

Originality/value

The originality of this paper is the achievement of a consolidated set of characteristics that conceptualize and qualify the disruptive business models by conducting an in-depth analysis of the literature on disruptive business models through the LSA technique, considering the difficulty of obtaining precise concepts on this subject in the literature.

Details

RAUSP Management Journal, vol. 54 no. 3
Type: Research Article
ISSN: 2531-0488

Keywords

Article
Publication date: 6 March 2017

Yujie Cheng, Hang Yuan, Hongmei Liu and Chen Lu

The purpose of this paper is to propose a fault diagnosis method for rolling bearings, in which the fault feature extraction is realized in a two-dimensional domain using scale…

Abstract

Purpose

The purpose of this paper is to propose a fault diagnosis method for rolling bearings, in which the fault feature extraction is realized in a two-dimensional domain using scale invariant feature transform (SIFT) algorithm. This method is different from those methods extracting fault feature directly from the traditional one-dimensional domain.

Design/methodology/approach

The vibration signal of rolling bearings is first transformed into a two-dimensional image. Then, the SIFT algorithm is applied to the image to extract the scale invariant feature vector which is highly distinctive and insensitive to noises and working condition variation. As the extracted feature vector is high-dimensional, kernel principal component analysis (KPCA) algorithm is utilized to reduce the dimension of the feature vector, and singular value decomposition technique is used to extract the singular values of the reduced feature vector. Finally, these singular values are introduced into a support vector machine (SVM) classifier to realize fault classification.

Findings

The experiment results show a high fault classification accuracy based on the proposed method.

Originality/value

The proposed approach for rolling bearing fault diagnosis based on SIFT-KPCA and SVM is highly effective in the experiment. The practical value in engineering application of this method can be researched in the future.

Details

Engineering Computations, vol. 34 no. 1
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 7 November 2019

Sk Abdul Kaium, Sayed Abul Hossain and Jafar Sadak Ali

The purpose of this paper is to highlight that the need for improved system identification methods within the domain of modal analysis increases under the impulse of the…

Abstract

Purpose

The purpose of this paper is to highlight that the need for improved system identification methods within the domain of modal analysis increases under the impulse of the broadening field of applications, e.g., damage detection and vibro-acoustics, and the increased complexity of today’s structures. Although significant research efforts during the last two decades have resulted in an extensive number of parametric identification algorithms, most of them are certainly not directly applicable for modal parameter extraction. So, based on this, the aim of the present work is to develop a technique for modal parameter extraction from the measured signal.

Design/methodology/approach

A survey and classification of the different modal analysis methods are made; however, the focus of this thesis is placed on modal parameter extraction from measured time signal. Some of the methods are examined in detail, including both single-degree-of-freedom and multi-degree-of-freedom approaches using single and global frequency-response analysis concepts. The theory behind each of these various analysis methods is presented in depth, together with the development of computer programs, theoretical and experimental examples and discussion, in order to evaluate the capabilities of those methods. The problem of identifying properties of structures that possess close modes is treated in particular detail, as this is a difficult situation to handle and yet a very common one in many structures. It is essential to obtain a good model for the behavior of the structure in order to pursue various applications of experimental modal analysis (EMA), namely: updating of finite element models, structural modification, subsystem-coupling and calculation of real modes from complex modes, to name a few. This last topic is particularly important for the validation of finite element models, and for this reason, a number of different methods to calculate real modes from complex modes are presented and discussed in this paper.

Findings

In this paper, Modal parameters like mode shapes and natural frequencies are extracted using an FFT analyzer and with the help of ARTeMiS, and subsequently, an algorithm has been developed based on frequency domain decomposition (FDD) technique to check the accuracy of the results as obtained from ARTeMiS. It is observed that the frequency domain-based algorithm shows good agreement with the extracted results. Hence the following conclusion may be drawn: among several frequency domain-based algorithms for modal parameter extraction, the FDD technique is more reliable and it shows a very good agreement with the experimental results.

Research limitations/implications

In the case of extraction techniques using measured data in the frequency domain, it is reported that the model using derivatives of modal parameters performed better in many situations. Lack of accurate and repeatable dynamic response measurements on complex structures in a real-life situation is a challenging problem to analyze exact modal parameters.

Practical implications

During the last two decades, there has been a growing interest in the domain of modal analysis. Evolved from a simple technique for troubleshooting, modal analysis has become an established technique to analyze the dynamical behavior of complex mechanical structures. Important examples are found in the automotive (cars, trucks, motorcycles), railway, maritime, aerospace (aircrafts, satellites, space shuttle), civil (bridges, buildings, offshore platforms) and heavy equipment industry.

Social implications

Presently structural health monitoring has become a significantly important issue in the area of structural engineering particularly in the context of safety and future usefulness of a structure. A lot of research is being carried out in this area incorporating the modern sophisticated instrumentations and efficient numerical techniques. The dynamic approach is mostly employed to detect structural damage, due to its inherent advantage of having global and location-independent responses. EMA has been attempted by many researchers in a controlled laboratory environment. However, measuring input excitation force(s) seems to be very expensive and difficult for the health assessment of an existing real-life structure. So Ambient Vibration Analysis is a good alternative to overcome those difficulties associated with the measurement of input excitation force.

Originality/value

Three single bay two storey frame structure has been chosen for the experiment. The frame has been divided into six small elements. An algorithm has been developed to determine the natural frequency of those frame structures of which one is undamaged and the rest two damages in single element and double element, respectively. The experimental results from ARTeMIS and from developed algorithm have been compared to verify the effectiveness of the developed algorithm. Modal parameters like mode shapes and natural frequencies are extracted using an FFT analyzer and with the help of ARTeMiS, and subsequently, an algorithm has been programmed in MATLAB based on the FDD technique to check the accuracy of the results as obtained from ARTeMiS. Using singular value decomposition, the power Spectral density function matrix is decomposed using the MATLAB program. It is observed that the frequency domain-based algorithm shows good consistency with the extracted results.

Details

International Journal of Structural Integrity, vol. 11 no. 2
Type: Research Article
ISSN: 1757-9864

Keywords

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