Search results for: Time domain analysis

Authors: Fathi N. Mayoof

Abstract:

Rolling element bearings are widely used in industry, especially where high load capacity is required. The diagnosis of their conditions is essential matter for downtime reduction and saving cost of maintenance. Therefore, an intensive analysis of frequency spectrum of their faults must be carried out in order to determine the main reason of the fault. This paper focus on a beating phenomena observed in the waveform (time domain) of a cylindrical rolling element bearing. The beating frequencies were not related to any sources nearby the machine nor any other malfunctions (unbalance, misalignment ...etc). More investigation on the spike energy and the frequency spectrum indicated a problem with races of the bearing. Multi-harmonics of the fundamental defects frequencies were observed. Two of them were close to each other in magnitude those were the source of the beating phenomena.

Keywords: Bearing, beating, spike energy, vibration.

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Authors: N. Manoj

Abstract:

The aeroelastic behavior of engine nacelle strake when subjected to unsteady aerodynamic flows is investigated in this paper. Geometric nonlinear characteristics and modal parameters of nacelle strake are studied when it is under dynamic loading condition. Here, an N-S based Finite Volume solver is coupled with Finite Element (FE) based nonlinear structural solver to investigate the nonlinear characteristics of nacelle strake over a range of dynamic pressures at various phases of flight like takeoff, climb, and cruise conditions. The combination of high fidelity models for both aerodynamics and structural dynamics is used to predict the nonlinearities of strake (chine). The methodology adopted for present aeroelastic analysis is partitioned-based time domain coupled CFD and CSD solvers and it is validated by the consideration of experimental and numerical comparison of aeroelastic data for a cropped delta wing model which has a proven record. The present strake geometry is derived from theoretical formulation. The amplitude and frequency obtained from the coupled solver at various dynamic pressures is discussed, which gives a better understanding of its impact on aerodynamic design-sizing of strake.

Keywords: Aeroelasticity, finite volume, geometric nonlinearity, limit cycle oscillations, strake.

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Authors: Mohd Iqbal Ridwan, Kerk Lee Yen, Aminuddin Musa, Bahisham Yunus

Abstract:

Protective relays are components of a protection system in a power system domain that provides decision making element for correct protection and fault clearing operations. Failure of the protection devices may reduce the integrity and reliability of the power system protection that will impact the overall performance of the power system. Hence it is imperative for power utilities to assess the reliability of protective relays to assure it will perform its intended function without failure. This paper will discuss the application of reliability analysis using statistical method called Life Data Analysis in Tenaga Nasional Berhad (TNB), a government linked power utility company in Malaysia, namely Transmission Division, to assess and evaluate the reliability of numerical overcurrent protective relays from two different manufacturers.

Keywords: Life data analysis, Protective relays, Reliability, Weibull Distribution.

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Authors: Ricardo Espinosa

Abstract:

The coherent Self-Averaging (CSA), is a new method proposed in this work; applied to simulated signals evoked potentials related to events (ERP) to find the wave P300, useful systems in the brain computer interface (BCI). The CSA method cleans signal in the time domain of white noise through of successive averaging of a single signal. The method is compared with the traditional method, coherent averaging or synchronized (CA), showing optimal results in the improvement of the signal to noise ratio (SNR). The method of CSA is easy to implement, robust and applicable to any physiological time series contaminated with white noise

Keywords: Evoked potentials, wave P300, Coherent Self-averaging, brain - computer interface (BCI).

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Authors: Alia Alghosoun, Michael Herty, Mohammed Seaid

Abstract:

We present a new class of numerical techniques to solve shallow water flows over dry areas including run-up. Many recent investigations on wave run-up in coastal areas are based on the well-known shallow water equations. Numerical simulations have also performed to understand the effects of several factors on tsunami wave impact and run-up in the presence of coastal areas. In all these simulations the shallow water equations are solved in entire domain including dry areas and special treatments are used for numerical solution of singularities at these dry regions. In the present study we propose a new method to deal with these difficulties by reformulating the shallow water equations into a new system to be solved only in the wetted domain. The system is obtained by a change in the coordinates leading to a set of equations in a moving domain for which the wet/dry interface is the reconstructed using the wave speed. To solve the new system we present a finite volume method of Lax-Friedrich type along with a modified method of characteristics. The method is well-balanced and accurately resolves dam-break problems over dry areas.

Keywords: Run-up waves, Shallow water equations, finite volume method, wet/dry interface, dam-break problem.

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Authors: S. Sendhil Kumar, M. Senthil Kumar

Abstract:

Maintenance and design engineers have great concern for the functioning of rotating machineries due to the vibration phenomenon. Improper functioning in rotating machinery originates from the damage to rolling element bearings. The status of rolling element bearings require advanced technologies to monitor their health status efficiently and effectively. Avoiding vibration during machine running conditions is a complicated process. Vibration simulation should be carried out using suitable sensors/ transducers to recognize the level of damage on bearing during machine operating conditions. Various issues arising in rotating systems are interlinked with bearing faults. This paper presents an approach for fault diagnosis of bearings using neural networks and time/frequencydomain vibration analysis.

Keywords: Bearing vibration, Condition monitoring, Fault diagnosis, Frequency domain.

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Authors: Darwin Gouwanda, S. M. N. Arosha Senanayake, M. M. Danushka Ranjana Marasinghe, Mervin Chandrapal, Jeya Mithra Kumar, Tung Mun Hon, Yulius

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This paper presents a real time force sensing instrument that is designed for human gait analysis purposes. This instrument mainly consists of three main elements: the force sensing mat, signal conditioning and switching circuit and data acquisition device. In order to control and to process the incoming signals from the force sensing mat, Force-Logger and Force-Reloader program are developed using Labview 8.0. This paper describes the architecture of the force sensing mat, signal conditioning and switching circuit and the real time streaming of the incoming data from the force sensing mat.

Keywords: Force platform, Force sensing resistor, human gait analysis

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Authors: Ke Wang, Zhi-Qiang Zhang, Z. Chen

Abstract:

A submerged horizontal plate type breakwater is pointed out as an efficient wave protection device for cage culture in marine fishery. In order to reveal the wave elimination principle of this type breakwater, boundary element method is utilized to investigate this problem. The flow field and the trajectory of water particles are studied carefully. The flow field analysis shows that: the interaction of incident wave and adverse current above the plate disturbs the water domain drastically. This can slow down the horizontal velocity and vertical velocity of the water particles.

Keywords: boundary element method, plate type breakwater, flow field analysis

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Authors: S. A. Eftekhari

Abstract:

In this paper, a numerical algorithm using a coupled Galerkin-Differential Quadrature (DQ) method is proposed for the solution of dam-reservoir interaction problem. The governing differential equation of motion of the dam structure is discretized by the Galerkin method and the DQM is used to discretize the fluid domain. The resulting systems of ordinary differential equations are then solved by the Newmark time integration scheme. The mixed scheme combines the simplicity of the Galerkin method and high accuracy and efficiency of the DQ method. Its accuracy and efficiency are demonstrated by comparing the calculated results with those of the existing literature. It is shown that highly accurate results can be obtained using a small number of Galerkin terms and DQM sampling points. The technique presented in this investigation is general and can be used to solve various fluid-structure interaction problems.

Keywords: Dam-reservoir system, Differential quadrature method, Fluid-structure interaction, Galerkin method, Integral quadrature method.

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Authors: Hazem M. El-Bakry, Qiangfu Zhao

Abstract:

Recently, neural networks have shown good results for detection of a certain pattern in a given image. In our previous papers [1-5], a fast algorithm for pattern detection using neural networks was presented. Such algorithm was designed based on cross correlation in the frequency domain between the input image and the weights of neural networks. Image conversion into symmetric shape was established so that fast neural networks can give the same results as conventional neural networks. Another configuration of symmetry was suggested in [3,4] to improve the speed up ratio. In this paper, our previous algorithm for fast neural networks is developed. The frequency domain cross correlation is modified in order to compensate for the symmetric condition which is required by the input image. Two new ideas are introduced to modify the cross correlation algorithm. Both methods accelerate the speed of the fast neural networks as there is no need for converting the input image into symmetric one as previous. Theoretical and practical results show that both approaches provide faster speed up ratio than the previous algorithm.

Keywords: Fast Pattern Detection, Neural Networks, Modified Cross Correlation

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Authors: Rongguo Yan, Guozheng Yan, Banghua Yang

Abstract:

The colonic tissue is a complicated dynamic system and the colonic activities it generates are composed of irregular segmental waves, which are referred to as erratic fluctuations or spikes. They are also highly irregular with subunit fractal structure. The traditional time-frequency domain statistics like the averaged amplitude, the motility index and the power spectrum, etc. are insufficient to describe such fluctuations. Thus the fractal box-counting dimension is proposed and the fractal scaling behaviors of the human colonic pressure activities under the physiological conditions are studied. It is shown that the dimension of the resting activity is smaller than that of the normal one, whereas the clipped version, which corresponds to the activity of the constipation patient, shows with higher fractal dimension. It may indicate a practical application to assess the colonic motility, which is often indicated by the colonic pressure activity.

Keywords: Colonic pressure activity, erratic fluctuations, fractal dimension and spikes.

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Authors: S. Chonsatidjamroen , K-N. Areerak, K-L. Areerak

Abstract:

This paper presents the averaging model of a buck converter derived from the generalized state-space averaging method. The sliding mode control is used to regulate the output voltage of the converter and taken into account in the model. The proposed model requires the fast computational time compared with those of the full topology model. The intensive time-domain simulations via the exact topology model are used as the comparable model. The results show that a good agreement between the proposed model and the switching model is achieved in both transient and steady-state responses. The reported model is suitable for the optimal controller design by using the artificial intelligence techniques.

Keywords: Generalized state-space averaging method, buck converter, sliding mode control, modeling, simulation.

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Authors: Takashi Mitsuishi, Koji Saigusa

Abstract:

This paper presents circular polar coordinates transformation of periodic fuzzy membership function. The purpose is identification of domain of periodic membership functions in consequent part of IF-THEN rules. Proposed methods in this paper remove complicatedness concerning domain of periodic membership function from defuzzification in fuzzy approximate reasoning. Defuzzification on circular polar coordinates is also proposed.

Keywords: Defuzzification, periodic membership function, polar coordinates transformation.

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Authors: M. Yousefi, N. Nasirzadeh

Abstract:

In this paper, behavior of an oscillator under injection of another signal has been investigated. Also, variation of output signal amplitude versus injected signal phase variation, the effect of varying the amplitude of injected signal and quality factor of the oscillator has been investigated. The results show that the locking time depends on phase and the best locking time happens at 180-degrees phase. Also, the effect of injected lock has been discussed. Simulations show that the locking time decreases with signal injection to bulk. Locking time has been investigated versus various phase differences. The effect of phase and amplitude changes on locking time of a typical LC oscillator in 180 nm technology has been investigated.

Keywords: Injection-lock oscillator, oscillator, analysis, phase modulation.

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Authors: Shigeaki Sakurai, Ken Ueno, Ryohei Orihara

Abstract:

This paper proposes a method that discovers time series event patterns from textual data with time information. The patterns are composed of sequences of events and each event is extracted from the textual data, where an event is characteristic content included in the textual data such as a company name, an action, and an impression of a customer. The method introduces 7 types of time constraints based on the analysis of the textual data. The method also evaluates these constraints when the frequency of a time series event pattern is calculated. We can flexibly define the time constraints for interesting combinations of events and can discover valid time series event patterns which satisfy these conditions. The paper applies the method to daily business reports collected by a sales force automation system and verifies its effectiveness through numerical experiments.

Keywords: Text mining, sequential mining, time constraints, daily business reports.

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Authors: A. Rawangpai, B. Maraungsri, N. Chomnawang

Abstract:

This paper presents the experimental results on artificial ageing test of 22 kV XLPE cable for distribution system application in Thailand. XLPE insulating material of 22 kV cable was sliced to 60-70 μm in thick and was subjected to ac high voltage at 23 Ôùª C, 60 Ôùª C and 75 Ôùª C. Testing voltage was constantly applied to the specimen until breakdown. Breakdown voltage and time to breakdown were used to evaluate life time of insulating material. Furthermore, the physical model by J. P. Crine for predicts life time of XLPE insulating material was adopted as life time model and was calculated in order to compare the experimental results. Acceptable life time results were obtained from Crine-s model comparing with the experimental result. In addition, fourier transform infrared spectroscopy (FTIR) for chemical analysis and scanning electron microscope (SEM) for physical analysis were conducted on tested specimens.

Keywords: Artificial accelerated ageing test, XLPE cable, distribution system, insulating material, life time, life time model

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Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin

Abstract:

Mostly the real life signals are time varying in nature. For proper characterization of such signals, time-frequency representation is required. The STFT (short-time Fourier transform) is a classical tool used for this purpose. The limitation of the STFT is its fixed time-frequency resolution. Thus, an enhanced version of the STFT, which is based on the cross-level sampling, is devised. It can adapt the sampling frequency and the window function length by following the input signal local variations. Therefore, it provides an adaptive resolution time-frequency representation of the input. The computational complexity of the proposed STFT is deduced and compared to the classical one. The results show a significant gain of the computational efficiency and hence of the processing power. The processing error of the proposed technique is also discussed.

Keywords: Level Crossing Sampling, Activity Selection, Adaptive Resolution Analysis, Computational Complexity

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Authors: Jun-Oh Kim, Seol-Min Yang, Seok-Heum Baek, Sangmo Kang

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In this paper, the shape design process is briefly discussed emphasizing the use of topology optimization in the conceptual design stage. The basic idea is to view feasible domains for sensitivity region concepts. In this method, the main process consists of two steps: as the design moves further inside the feasible domain using Taguchi method, and thus becoming more successful topology optimization, the sensitivity region becomes larger. In designing a double-eccentric butterfly valve, related to hydrodynamic performance and disc structure, are discussed where the use of topology optimization has proven to dramatically improve an existing design and significantly decrease the development time of a shape design. Computational Fluid Dynamics (CFD) analysis results demonstrate the validity of this approach.

Keywords: Double-eccentric butterfly valve, CFD, Topology optimization

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Authors: Kyunghee Oh, Dooho Choi

Abstract:

Although there is no theoretical weakness in a cryptographic algorithm, Side Channel Analysis can find out some secret data from the physical implementation of a cryptosystem. The analysis is based on extra information such as timing information, power consumption, electromagnetic leaks or even sound which can be exploited to break the system. Differential Power Analysis is one of the most popular analyses, as computing the statistical correlations of the secret keys and power consumptions. It is usually necessary to calculate huge data and takes a long time. It may take several weeks for some devices with countermeasures. We suggest and evaluate the methods to shorten the time to analyze cryptosystems. Our methods include distributed computing and parallelized processing.

Keywords: DPA, distributed computing, parallelized processing.

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Authors: Alessandro Bevilacqua, Alessandro Gherardi, Filippo Piccinini

Abstract:

The mosaicing technique has been employed in more and more application fields, from entertainment to scientific ones. In the latter case, often the final evaluation is still left to human beings, that assess visually the quality of the mosaic. Many times, a lack of objective measurements in microscopic mosaicing may prevent the mosaic from being used as a starting image for further analysis. In this work we analyze three different metrics and indexes, in the domain of signal analysis, image analysis and visual quality, to measure the quality of different aspects of the mosaicing procedure, such as registration errors and visual quality. As the case study we consider the mosaicing algorithm we developed. The experiments have been carried out by considering mosaics with very different features: histological samples, that are made of detailed and contrasted images, and live stem cells, that show a very low contrast and low detail levels.

Keywords: Mosaicing, quality assessment, microscopy, stem cells.

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Authors: Irshad Ahmad, Abdul Muhamin Naeem, Muhammad Islam

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Information on weed distribution within the field is necessary to implement spatially variable herbicide application. Since hand labor is costly, an automated weed control system could be feasible. This paper deals with the development of an algorithm for real time specific weed recognition system based on Histogram Analysis of an image that is used for the weed classification. This algorithm is specifically developed to classify images into broad and narrow class for real-time selective herbicide application. The developed system has been tested on weeds in the lab, which have shown that the system to be very effectiveness in weed identification. Further the results show a very reliable performance on images of weeds taken under varying field conditions. The analysis of the results shows over 95 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.

Keywords: Image Processing, real-time recognition, Weeddetection.

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Authors: M. Pushparani, A. Sagaya

Abstract:

Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.

Keywords: Embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems.

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Authors: K. Hardy, A. Maurushat

Abstract:

Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: Big data, open data, productivity, transparency.

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Authors: Amir-Massoud Bidgoli, Mehdi Naseri Parsa

Abstract:

In this paper a combined feature selection method is proposed which takes advantages of sample domain filtering, resampling and feature subset evaluation methods to reduce dimensions of huge datasets and select reliable features. This method utilizes both feature space and sample domain to improve the process of feature selection and uses a combination of Chi squared with Consistency attribute evaluation methods to seek reliable features. This method consists of two phases. The first phase filters and resamples the sample domain and the second phase adopts a hybrid procedure to find the optimal feature space by applying Chi squared, Consistency subset evaluation methods and genetic search. Experiments on various sized datasets from UCI Repository of Machine Learning databases show that the performance of five classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First Decision Tree and JRIP) improves simultaneously and the classification error for these classifiers decreases considerably. The experiments also show that this method outperforms other feature selection methods.

Keywords: feature selection, resampling, reliable features, Consistency Subset Evaluation.

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Authors: Francisco Miranda

Abstract:

The optimization problem using time scales is studied. Time scale is a model of time. The language of time scales seems to be an ideal tool to unify the continuous-time and the discrete-time theories. In this work we present necessary conditions for a solution of an optimization problem on time scales. To obtain that result we use properties and results of the partial diamond-alpha derivatives for continuous-multivariable functions. These results are also presented here.

Keywords: Lagrange multipliers, mathematical programming, optimization problem, time scales.

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Authors: S. Madhavi, S. Abirami, C. Bharathi, B. Ekambaram, T. Krishna Sankar, A. Nattudurai, N. Vijayarangan

Abstract:

The high utilization rate of Automated Teller Machine (ATM) has inevitably caused the phenomena of waiting for a long time in the queue. This in turn has increased the out of stock situations. The ATM utilization helps to determine the usage level and states the necessity of the ATM based on the utilization of the ATM system. The time in which the ATM used more frequently (peak time) and based on the predicted solution the necessary actions are taken by the bank management. The analysis can be done by using the concept of Data Mining and the major part are analyzed based on the predictive data mining. The results are predicted from the historical data (past data) and track the relevant solution which is required. Weka tool is used for the analysis of data based on predictive data mining.

Keywords: ATM, Bank Management, Data Mining, Historical data, Predictive Data Mining, Weka tool.

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Authors: Sung Uk Park, Young Su Kang, Sangmo Kang, Yong Kweon Suh

Abstract:

Mineral product, waste concrete (fine aggregates), waste in the optical field, industry, and construction employ separators to separate solids and classify them according to their size. Various sorting machines are used in the industrial field such as those operating under electrical properties, centrifugal force, wind power, vibration, and magnetic force. Study on separators has been carried out to contribute to the environmental industry. In this study, we perform CFD analysis for understanding the basic mechanism of the separation of waste concrete (fine aggregate) particles from air with a machine built with a rotor with blades. In CFD, we first performed two-dimensional particle tracking for various particle sizes for the model with 1 degree, 1.5 degree, and 2 degree angle between each blade to verify the boundary conditions and the method of rotating domain method to be used in 3D. Then we developed 3D numerical model with ANSYS CFX to calculate the air flow and track the particles. We judged the capability of particle separation for given size by counting the number of particles escaping from the domain toward the exit among 10 particles issued at the inlet. We confirm that particles experience stagnant behavior near the exit of the rotating blades where the centrifugal force acting on the particles is in balance with the air drag force. It was also found that the minimum particle size that can be separated by the machine with the rotor is determined by its capability to stay at the outlet of the rotor channels.

Keywords: Environmental industry, Separator, CFD, Fine aggregate.

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

Abstract:

Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: Phu-Cuong Nguyen, Seung-Eock Kim

Abstract:

This paper presents nonlinear elastic dynamic analysis of 3-D semi-rigid steel frames including geometric and connection nonlinearities. The geometric nonlinearity is considered by using stability functions and updating geometric stiffness matrix. The nonlinear behavior of the steel beam-to-column connection is considered by using a zero-length independent connection element comprising of six translational and rotational springs. The nonlinear dynamic equilibrium equations are solved by the Newmark numerical integration method. The nonlinear time-history analysis results are compared with those of previous studies and commercial SAP2000 software to verify the accuracy and efficiency of the proposed procedure.

Keywords: Geometric nonlinearity, nonlinear time-historyanalysis, semi-rigid connection, stability functions.

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Authors: Farid Saeidi, Serkan Dag

Abstract:

In this study, fracture analysis of a fibrous composite laminate with variable fiber spacing is carried out using Jk-integral method. The laminate is assumed to be under thermal loading. Jk-integral is formulated by using the constitutive relations of plane orthotropic thermoelasticity. Developed domain independent form of the Jk-integral is then integrated into the general purpose finite element analysis software ANSYS. Numerical results are generated so as to assess the influence of variable fiber spacing on mode I and II stress intensity factors, energy release rate, and T-stress. For verification, some of the results are compared to those obtained using displacement correlation technique (DCT).

Keywords: Jk-integral, variable fiber spacing, thermoelasticity, t-stress, finite element method, fibrous composite.

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