Search results for: input faults

Authors: K. Echchakhaoui, E. Abdelmounim, J. Zbitou, H. Bennis, N. Ababssi, M. Latrach

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In this paper a new design of a broadband microwave power limiter is presented and validated into simulation by using ADS software (Advanced Design System) from Agilent technologies. The final circuit is built on microstrip lines by using identical Zero Bias Schottky diodes. The power limiter is designed by Associating 3 stages Schottky diodes. The obtained simulation results permit to validate this circuit with a threshold input power level of 0 dBm until a maximum input power of 30 dBm.

Keywords: Limiter, microstrip, zero-biais, ADS

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Authors: A. Mohammadi, M. Moghimi, S. Mohammadi

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Engineers need computational methods which could provide solutions less sensitive to the environmental effects, so the techniques should be used which take the uncertainty to account to control and minimize the risk associated with design and operation. In order to consider uncertainty in engineering problem, the optimization problem should be solved for a suitable range of the each uncertain input variable instead of just one estimated point. Using deterministic optimization problem, a large computational burden is required to consider every possible and probable combination of uncertain input variables. Several methods have been reported in the literature to deal with problems under uncertainty. In this paper, different methods presented and analyzed.

Keywords: uncertainty, Monte Carlo simulated, stochastic programming, scenario method

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Authors: B. Touati, A. Saad, B. Lips, A. Abdenbi, M. Mokhtari.

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The purpose of this study is an application of experiment design method for dimensioning of a solar drying system. NIMROD software was used to build up the matrix of experiments and to analyze the results. The software has the advantages of being easy to use and consists of a forced way, with some choices about the number and range of variation of the parameters, and the desired polynomial shape. The first design of experiments performed concern the drying with constant input characteristics of the hot air in the dryer and a second design of experiments in which the drying chamber is coupled with a solar collector. The first design of experiments allows us to study the influence of various parameters and get the studied answers in a polynomial form. The correspondence between the polynomial thus determined, and the model results were good. The results of the polynomials of the second design of experiments and those of the model are worse than the results in the case of drying with constant input conditions. This is due to the strong link between all the input parameters, especially, the surface of the sensor and the drying chamber, and the mass of the product.

Keywords: solar drying, experiment design method, NIMROD, mint leaves

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Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

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Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

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Authors: Hechmi Saidi, Noureddine Hamdi

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The performance of Decode and Forward (DF) multihop Free Space Optical ( FSO) scheme deploying Multiple Input Multiple Output (MIMO) configuration under Gamma-Gamma (GG) statistical distribution, that adopts M-ary Pulse Position Modulation (MPPM) coding, is investigated. We have extracted exact and estimated values of Symbol-Error Rates (SERs) respectively. A closed form formula related to the Probability Density Function (PDF) is expressed for our designed system. Thanks to the use of DF multihop MIMO FSO configuration and MPPM signaling, atmospheric turbulence is combatted; hence the transmitted signal quality is improved.

Keywords: free space optical, multiple input multiple output, M-ary pulse position modulation, multihop, decode and forward, symbol error rate, gamma-gamma channel

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Authors: Salah Al-Din I. Badran, Samad Ahmadi, Ismail Shahin

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A blind source separation method is proposed; in this method, we use a non-uniform filter bank and a novel normalisation. This method provides a reduced computational complexity and increased convergence speed comparing to the full-band algorithm. Recently, adaptive sub-band scheme has been recommended to solve two problems: reduction of computational complexity and increase the convergence speed of the adaptive algorithm for correlated input signals. In this work, the reduction in computational complexity is achieved with the use of adaptive filters of orders less than the full-band adaptive filters, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each subband than the input signal at full bandwidth, and can promote better rates of convergence.

Keywords: blind source separation, computational complexity, subband, convergence speed, mixture

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Authors: Kazuyoshi Mori

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In this paper, we consider the parametrization of Anantharam’s model within the framework of the factorization approach. In the parametrization, we investigate the number of required parameters of Anantharam’s model. We consider single-input single-output systems in this paper. By the investigation, we find three cases that are (1) there exist plants which require only one parameter and (2) two parameters, and (3) the number of parameters is at most three.

Keywords: linear systems, parametrization, coprime factorization, number of parameters

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Authors: Syed Amer Mahmood, Rao Mansor Ali Khan

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This study deals with the remote sensing analysis of tectonic deformation and its implications to understand the regional uplift conditions in the lower Jhelum and eastern Potwar. Identification and mapping of active structures is an important issue in order to assess seismic hazards and to understand the Quaternary deformation of the region. Digital elevation models (DEMs) provide an opportunity to quantify land surface geometry in terms of elevation and its derivatives. Tectonic movement along the faults is often reflected by characteristic geomorphological features such as elevation, stream offsets, slope breaks and the contributing drainage area. The river profile analysis in this region using SRTM digital elevation model gives information about the tectonic influence on the local drainage network. The steepness and concavity indices have been calculated by power law of scaling relations under steady state conditions. An uplift rate map is prepared after carefully analysing the local drainage network showing uplift rates in mm/year. The active faults in the region control local drainages and the deflection of stream channels is a further evidence of the recent fault activity. The results show variable relative uplift conditions along MBT and Riasi and represent a wonderful example of the recency of uplift, as well as the influence of active tectonics on the evolution of young orogens.

Keywords: quaternary deformation, SRTM DEM, geomorphometric indices, active tectonics and MBT

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Authors: Sukran Acikel, Mehmet Ekmekci, Otgonbayar Namkhai

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Lignite coal fields in western Turkey generally occurs in tensional Neogene basins bordered by major faults. Karacahisar coal field in Mugla province of western Turkey is a large Neogene basin filled with alternation of silisic and calcerous layers. The basement of the basin is composed of mainly karstified carbonate rocks of Mesozoic and schists of Paleozoic age. The basement rocks are exposed at highlands surrounding the basin. The basin fill deposits forms shallow, low yield and local aquifers whereas karstic carbonate rock masses forms the major aquifer in the region. The karstic aquifer discharges through a spring zone issuing at intersection of two major faults. Municipal water demand in Bodrum city, a touristic attraction area is almost totally supplied by boreholes tapping the karstic aquifer. A well field has been constructed on the eastern edge of the coal basin, which forms a ridge separating two Neogene basins. A major concern was raised about the plausible impact of mining activities on groundwater system in general and on water supply well field in particular. The hydrogeological studies carried out in the area revealed that the coal seam is located below the groundwater level. Mining operations will be affected by groundwater inflow to the pits, which will require dewatering measures. Dewatering activities in mine sites have two-sided effects: a) lowers the groundwater level at and around the pit for a safe and effective mining operation, b) continuous dewatering causes expansion of cone of depression to reach a spring, stream and/or well being utilized by local people, capturing their water. Plausible effect of mining operations on the flow of the spring zone was another issue of concern. Therefore, a detailed representative hydrogeological conceptual model of the site was developed on the basis of available data and field work. According to the hydrogeological conceptual model, dewatering of Neogene layers will not hydraulically affect the water supply wells, however, the ultimate perimeter of the open pit will expand to intersect the well field. According to the conceptual model, the coal seam is separated from the bottom by a thick impervious clay layer sitting on the carbonate basement. Therefore, the hydrostratigraphy does not allow a hydraulic interaction between the mine pit and the karstic carbonate rock aquifer. However, the structural setting in the basin suggests that deep faults intersecting the basement and the Neogene sequence will most probably carry the deep groundwater up to a level above the bottom of the pit. This will require taking necessary measure to lower the piezometric level of the carbonate rock aquifer along the faults. Dewatering the carbonate rock aquifer will reduce the flow to the spring zone. All findings were put together to recommend a strategy for safe and effective mining operation.

Keywords: conceptual model, dewatering, groundwater, mining operation

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Authors: Arefeh Arabaninezhad, Ali Fakher

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Since the deterministic analysis methods fail to take system uncertainties into account, probabilistic and non-probabilistic methods are suggested. Geotechnical analyses are used to determine the stress and deformation caused by construction; accordingly, many input variables which depend on ground behavior are required for geotechnical analyses. The Random Set approach is an applicable reliability analysis method when comprehensive sources of information are not available. Using Random Set method, with relatively small number of simulations compared to fully probabilistic methods, smooth extremes on system responses are obtained. Therefore random set approach has been proposed for reliability analysis in geotechnical problems. In the present study, the application of random set method in reliability analysis of deep excavations is investigated through three deep excavation projects which were monitored during the excavating process. A finite element code is utilized for numerical modeling. Two expected ranges, from different sources of information, are established for each input variable, and a specific probability assignment is defined for each range. To determine the most influential input variables and subsequently reducing the number of required finite element calculations, sensitivity analysis is carried out. Input data for finite element model are obtained by combining the upper and lower bounds of the input variables. The relevant probability share of each finite element calculation is determined considering the probability assigned to input variables present in these combinations. Horizontal displacement of the top point of excavation is considered as the main response of the system. The result of reliability analysis for each intended deep excavation is presented by constructing the Belief and Plausibility distribution function (i.e. lower and upper bounds) of system response obtained from deterministic finite element calculations. To evaluate the quality of input variables as well as applied reliability analysis method, the range of displacements extracted from models has been compared to the in situ measurements and good agreement is observed. The comparison also showed that Random Set Finite Element Method applies to estimate the horizontal displacement of the top point of deep excavation. Finally, the probability of failure or unsatisfactory performance of the system is evaluated by comparing the threshold displacement with reliability analysis results.

Keywords: deep excavation, random set finite element method, reliability analysis, uncertainty

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Authors: Mohammad Hadi Khorashadi Zadeh ‎

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An entrepreneur is a manager or the owner of the commercial company that creates resources and money by risking and initiative. The Netpreneur is the capability to run an online business. It needs only the Connectivity. An Entrepreneur, as long as he has a service which the market demands can set up a feasible and viable trade with his Intellectual Capital as the principle input and the Connectivity Infrastructure as the only physical input. The internet is possibly the most significant revolution in science and technology that our generation could fantasize or imagine. It has introduced in various benefits to the society, culture, economics and politics. The entrepreneur is a premium member in the community. She/he provides services to the society and community including employment.

Keywords: entrepreneur, Netpreneur, intellectual capital, infrastructure

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Authors: Suriya

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Rapid socio-economic development and urbanization have led to an increasingly serious air pollution problem in Ulaanbaatar (UB), the capital of Mongolia. PM₂.₅ pollution has become the most pressing aspect of UB air pollution. Therefore, monitoring and predicting PM₂.₅ concentration in UB is of great significance for the health of the local people and environmental management. As of yet, very few studies have used models to predict PM₂.₅ concentrations in UB. Using data from 0:00 on June 1, 2018, to 23:00 on April 30, 2020, we proposed two deep learning models based on Bayesian-optimized LSTM (Bayes-LSTM) and CNN-LSTM. We utilized hourly observed data, including Himawari8 (H8) aerosol optical depth (AOD), meteorology, and PM₂.₅ concentration, as input for the prediction of PM₂.₅ concentrations. The correlation strengths between meteorology, AOD, and PM₂.₅ were analyzed using the gray correlation analysis method; the comparison of the performance improvement of the model by using the AOD input value was tested, and the performance of these models was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The prediction accuracies of Bayes-LSTM and CNN-LSTM deep learning models were both improved when AOD was included as an input parameter. Improvement of the prediction accuracy of the CNN-LSTM model was particularly enhanced in the non-heating season; in the heating season, the prediction accuracy of the Bayes-LSTM model slightly improved, while the prediction accuracy of the CNN-LSTM model slightly decreased. We propose two novel deep learning models for PM₂.₅ concentration prediction in UB, Bayes-LSTM, and CNN-LSTM deep learning models. Pioneering the use of AOD data from H8 and demonstrating the inclusion of AOD input data improves the performance of our two proposed deep learning models.

Keywords: deep learning, AOD, PM2.5, prediction, Ulaanbaatar

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Hossein Mardani, Neil Buchanan, Robert Cahill, Vincent Fusco

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In this paper, we study the input impedance characteristics of axial mode helical antennas to find an effective way for matching it to 50 Ω. The study is done on the important matching parameters such as like wire diameter and helix to the ground plane gap. It is intended that these parameters control the matching without detrimentally affecting the radiation pattern. Using transmission line theory, a simple broadband technique is proposed, which is applicable for perfect matching of antennas with similar design parameters. We provide design curves to help to choose the proper dimensions of the matching section based on the antenna’s unmatched input impedance. Finally, using the proposed technique, a 4-turn axial mode helix is designed at 2.5 GHz center frequency and the measurement results of the manufactured antenna will be included. This parametric study gives a good insight into the input impedance characteristics of axial mode helical antennas and the proposed impedance matching approach provides a simple, useful method for matching these types of antennas.

Keywords: antenna, helix, helical, axial mode, wireless power transfer, impedance matching

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Authors: Hong Yu, Ion Matei

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Carbon fiber reinforced composites (CFRP) used as aircraft structure are subject to lightning strike, putting structural integrity under risk. Indirect damage may occur after a lightning strike where the internal structure can be damaged due to excessive heat induced by lightning current, while the surface of the structures remains intact. Three damage modes may be observed after a lightning strike: fiber breakage, inter-ply delamination and intra-ply cracks. The assessment of internal damage states in composite is challenging due to complicated microstructure, inherent uncertainties, and existence of multiple damage modes. In this work, a model based approach is adopted to diagnose faults in carbon composites after lighting strikes. A resistor network model is implemented to relate the overall electrical and thermal conduction behavior under simulated lightning current waveform to the intrinsic temperature dependent material properties, microstructure and degradation of materials. A fault detection and identification (FDI) module utilizes the physics based model and a particle filtering algorithm to identify damage mode as well as calculate the probability of structural failure. Extensive simulation results are provided to substantiate the proposed fault diagnosis methodology with both single fault and multiple faults cases. The approach is also demonstrated on transient resistance data collected from a IM7/Epoxy laminate under simulated lightning strike.

Keywords: carbon composite, fault detection, fault identification, particle filter

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Authors: Armel Asongu Nkembi, Ahmad Fawad

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The aim of this paper is to determine in a concise way the transfer function that characterizes a DC electrical motor with a helix. In practice it can be obtained by applying a particular input to the system and then, based on the observation of its output, determine an approximation to the transfer function of the system. In our case, we use a step input and find the transfer function parameters that give the simulated first-order time response. The simulation of the system is done using MATLAB/Simulink. In order to determine the parameters, we assume a first order system and use the Broida approximation to determine the parameters and then its Mean Square Error (MSE). Furthermore, we design a PID controller for the control process first in the continuous time domain and tune it using the Ziegler-Nichols open loop process. We then digitize the controller to obtain a digital controller since most systems are implemented using computers, which are digital in nature.

Keywords: transfer function, step input, MATLAB, Simulink, DC electrical motor, PID controller, open-loop process, mean square process, digital controller, Ziegler-Nichols

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Authors: Baye Berihun Getahun, Mulugeta Atnaf Tiruneh, Richard G. F. Visser

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Resource-poor farmers practice low-input farming systems, and yet, most breeding programs give less attention to this huge farming system, which serves as a source of food and income for several people in developing countries. The high-input conventional breeding system appears to have failed to adequately meet the needs and requirements of 'difficult' environments operating under this system. Moreover, the unavailability of resources for crop production is getting for their peaks, the environment is maltreated by excessive use of agrochemicals, crop productivity reaches its plateau stage, particularly in the developed nations, the world population is increasing, and food shortage sustained to persist for poor societies. In various parts of the world, genetic gain at the farmers' level remains low which could be associated with low adoption of crop varieties, which have been developed under high input systems. Farmers usually use their local varieties and apply minimum inputs as a risk-avoiding and cost-minimizing strategy. This evidence indicates that the conventional high-input plant breeding system has failed to feed the world population, and the world is moving further away from the United Nations' goals of ending hunger, food insecurity, and malnutrition. In this review, we discussed the rationality of focused breeding programs for low-input farming systems and, the technical aspect of crop breeding that accommodates future food needs and its significance for developing countries in the decreasing scenario of resources required for crop production. To this end, the application of exotic introgression techniques like polyploidization, pan-genomics, comparative genomics, and De novo domestication as a pre-breeding technique has been discussed in the review to exploit the untapped genetic diversity of the crop wild relatives (CWRs). Desired recombinants developed at the pre-breeding stage are exploited through appropriate breeding approaches such as evolutionary plant breeding (EPB), rhizosphere-related traits breeding, and participatory plant breeding approaches. Populations advanced through evolutionary breeding like composite cross populations (CCPs) and rhizosphere-associated traits breeding approach that provides opportunities for improving abiotic and biotic soil stress, nutrient acquisition capacity, and crop microbe interaction in improved varieties have been reviewed. Overall, we conclude that low input farming system is a huge farming system that requires distinctive breeding approaches, and the exotic pre-breeding introgression techniques and the appropriate breeding approaches which deploy the skills and knowledge of both breeders and farmers are vital to develop heterogeneous landrace populations, which are effective for farmers practicing low input farming across the world.

Keywords: low input farming, evolutionary plant breeding, composite cross population, participatory plant breeding

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Authors: Elena Ginghina

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There are two major categories of language acquisition: first and second language acquisition, which distinguish themselves in their learning process and in their ultimate attainment. However, in the case of a bilingual child, one of the languages he grows up with receives gradually the features of a second language. This phenomenon characterizes the successive first language acquisition, when the initial state of the child is already marked by another language. Nevertheless, the dominance of the languages can change throughout the life, if the exposure to language and the quality of the input are better in 2L1. Related to the exposure to language and the quality of the input, there are cases even at the simultaneous bilingualism, where the two languages although learned from birth one, differ from one another at some point. This paper aims to see, what makes a 2L1 to become a second language and under what circumstances can a L2 learner reach a native or a near native speaker level.

Keywords: bilingualism, first language acquisition, native speakers of German, second language acquisition

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Authors: John Gaber

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Planners regularly use citizen input as empirical data to help them better understand community issues they know very little about. This type of community data is based on the lived experiences of local residents and is known as "emic" data. What is becoming more common practice for planners is their use of data from local experts and stakeholders (known as "etic" data or the outsider perspective) to help them fill in the gaps in their analysis of applied planning research projects. Utilizing international Health Impact Assessment (HIA) data, I look at who planners invite to their citizen input investigations. Research presented in this paper shows that planners access a wide range of emic and etic community perspectives in their search for the “community’s view.” The paper concludes with how planners can chart out a new empirical path in their execution of emic/etic citizen participation strategies in their applied planning research projects.

Keywords: citizen participation, emic data, etic data, Health Impact Assessment (HIA)

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Authors: Somkiat Korbuakaew, Winai Mankhatitham, Anchan Chongcharoen, Wichar Kunkum

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This research’s objective is to evaluate the online broadcasting of Suan Dusit Rajabhat Univeristy by CIPP model. The evaluation was separated into 4 parts: context factor, input factor, process factor and product factor. Sample group in this research were 399 participants who were university’s executive, staff and students. Questionnaires and interview were the research tools. Data were analyzed by computer program. Statistics used here were percentage, mean, and standard deviation. Findings are as follows: 1. Context factor: The context factor here in this research was university’s executives, staff and students. The study shows that they would like to use online broadcasting to be the educational tool and IT development. 2. Input factor: The input factor was the modern IT equipment to create interesting teaching materials and develop education in general. 3. Process factor: The process factor in this study was the publication of the program that it should be promoted more among students and should be more objective. 4. Product factor: The product factor in this study was the purpose of the program that it expands the educational channel for students.

Keywords: evaluation, project, internet, online broadcasting

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Authors: Roza Afarin, Saeed Mozaffari

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The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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Authors: Mohammad Arabi

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The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

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Authors: Alaeddin Ebrahimi, Narasimman Sundararajan, Bernhard Pracejus

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Development of salt domes, often a rising from depths of some 10 km or more, causes an intense faulting of the surrounding host rocks (salt tectonics). The fractured rocks then present ideal space for oil that can migrate and get trapped. If such moving of hydrocarbons passes uranium-carrying rock units (e.g., shales), uranium is collected and enriched by organic carbon compounds. Brines from the salt body are also ideal carriers for oxidized uranium species and will further dislocate uranium when in contact with uranium-enriched oils. Uranium then has the potential to mineralize in the vicinity of the dome (blue halite is evidence for radiation having affected salt deposits elsewhere in the world). Based on this knowledge, the Qarat Kibrit salt dome was investigated by a well-established geophysical method like very low frequency electromagnetic (VLF-EM) along five traverses approximately 250 m in length (10 m intervals) in order to identify subsurface fault systems. In-phase and quadrature components of the VLF-EM signal were recorded at two different transmitter frequencies (24.0 and 24.9 kHz). The images of Fraser filtered response of the in-phase components indicate a conductive zone (fault) in the southeast and southwest of the study area. The Karous-Hjelt current density pseudo section delineates subsurface faults at depths between 10 and 40 m. The stacked profiles of the Fraser filtered responses brought out two plausible trends/directions of faults. However, there seems to be no evidence for uranium enrichment has been recorded in this area.

Keywords: salt dome, uranium, fault, in-phase component, quadrature component, Fraser filter, Karous-Hjelt current density

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Authors: Omer Altaf, Liam Wotherspoon, Rolando Orense

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The Wairau Plains are located in the north-east of the South Island of New Zealand in the region of Marlborough. The region is cut by many active crustal faults such as the Wairau, Awatere, and Clarence faults, which give rise to frequent seismic events. This paper presents the preliminary results of the overall project in which liquefaction-induced ground damage maps are developed in the Wairau Plains based on the Ministry of Business, Innovation and Employment NZ guidance. A suite of maps has been developed in relation to the level of details that was available to inform the liquefaction hazard mapping. Maps at the coarsest level of detail make use of regional geologic information, applying semi-quantitative criteria based on geological age, design peak ground accelerations and depth to the water table. The next level of detail incorporates higher resolution surface geomorphologic characteristics to better delineate potentially liquefiable and non-liquefiable deposits across the region. The most detailed assessment utilised CPT sounding data to develop ground damage response curves for areas across the region and provide a finer level of categorisation of liquefaction vulnerability. Linking these with design level earthquakes defined through NZGS guidelines will enable detailed classification to be carried out at CPT investigation locations, from very low through to high liquefaction vulnerability. To update classifications to these detailed levels, CPT investigations in geomorphic regions are grouped together to provide an indication of the representative performance of the soils in these areas making use of the geomorphic mapping outlined above.

Keywords: hazard, liquefaction, mapping, seismicity

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Authors: Meenu Kaushik, Ayon K. Bandhoyadhayay, Lalit M. Joshi

Abstract:

Inductive output tubes (IOTs) are widely used as microwave power amplifiers for broadcast and scientific applications. It is capable of amplifying radio frequency (RF) power with very good efficiency. Its compactness, reliability, high efficiency, high linearity and low operating cost make this device suitable for various applications. The device consists of an integrated structure of electron gun and RF cavity, collector and focusing structure. The working principle of IOT is a combination of triode and klystron. The cathode lies in the electron gun produces a stream of electrons. A control grid is placed in close proximity to the cathode. Basically, the input part of IOT is the integrated structure of gridded electron gun which acts as an input cavity thereby providing the interaction gap where the input RF signal is applied to make it interact with the produced electron beam for supporting the amplification phenomena. The paper presents the design, fabrication and testing of a radial re-entrant cavity for implementing in the input structure of IOT at 350 MHz operating frequency. The model’s suitability has been discussed and a generalized mathematical relation has been introduced for getting the proper transverse magnetic (TM) resonating mode in the radial narrow gap RF cavities. The structural modeling has been carried out in CST and SUPERFISH codes. The cavity is fabricated with the Aluminum material and the RF characterization is done using vector network analyzer (VNA) and the results are presented for the resonant frequency peaks obtained in VNA.

Keywords: inductive output tubes, IOT, radial cavity, coaxial cavity, particle accelerators

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Authors: Agustinus Rudatyo Himamunanto, Anastasia Rita Widiarti

Abstract:

Transliteration using Javanese manuscripts is one of methods to preserve and legate the wealth of literature in the past for the present generation in Indonesia. The transliteration manual process commonly requires philologists and takes a relatively long time. The automatic transliteration process is expected to shorten the time so as to help the works of philologists. The preprocessing and segmentation stage firstly done is used to manage the document images, thus obtaining image script units that will compile input document images free from noise and have the similarity in properties in the thickness, size, and slope. The next stage of characteristic extraction is used to find unique characteristics that will distinguish each Javanese script image. One of characteristics that is used in this research is the number of black pixels in each image units. Each image of Java scripts contained in the data training will undergo the same process similar to the input characters. The system testing was performed with the data of the book Hamong Tani. The book Hamong Tani was selected due to its content, age and number of pages. Those were considered sufficient as a model experimental input. Based on the results of random page automatic transliteration process testing, it was determined that the maximum percentage correctness obtained was 81.53%. The percentage of success was obtained in 32x32 pixel input image size with the 5x5 image window. With regard to the results, it can be concluded that the automatic transliteration model offered is relatively good.

Keywords: Javanese script, character recognition, statistical, automatic transliteration

Procedia PDF Downloads 326

Authors: P. Javid, A. Aeenmehr, J. Taghavifar

Abstract:

In this paper, supply air pressure of HVAC system has been modeled with second-order transfer function plus dead-time. In HVAC system, the desired input has step changes, and the output of proposed control system should be able to follow the input reference, so the idea of using model based predictive control is proceeded and designed in this paper. The closed loop control system is implemented in MATLAB software and the simulation results are provided. The simulation results show that the model based predictive control is able to control the plant properly.

Keywords: air conditioning system, GPC, dead time, air supply control

Procedia PDF Downloads 514

Authors: Ata Khorami, Mohammad Sharifkhani

Abstract:

In the dynamic comparators, the pre-amplifier amplifies the input differential voltage and when the output Vcm of the pre-amplifier becomes larger than Vth of the latch input transistors, the latch is activated and finalizes the comparison. As a result, the pre-amplification delay is fixed to a value and cannot be set at the minimum required delay, thus, significant power and delay are imposed. In this paper, a novel structure is proposed through which the pre-amplification delay can be set at any low value saving power and time. Simulations show that using the proposed structure, by setting the pre-amplification delay at the minimum required value the power and comparison delay can be reduced by 55% and 100ps respectively.

Keywords: dynamic comparator, low power comparator, analog to digital converter, pre-amplification delay

Procedia PDF Downloads 191

Authors: Eunsu Jang, Kang Park

Abstract:

In developing an armored ground combat vehicle (AGCV), it is a very important step to analyze the vulnerability (or the survivability) of the AGCV against enemy’s attack. In the vulnerability analysis, the penetration equations are usually used to get the penetration depth and check whether a bullet can penetrate the armor of the AGCV, which causes the damage of internal components or crews. The penetration equations are derived from penetration experiments which require long time and great efforts. However, they usually hold only for the specific material of the target and the specific type of the bullet used in experiments. Thus, penetration simulation using ANSYS can be another option to calculate penetration depth. However, it is very important to model the targets and select the input parameters in order to get an accurate penetration depth. This paper performed a sensitivity analysis of input parameters of ANSYS on the accuracy of the calculated penetration depth. Two conflicting objectives need to be achieved in adopting ANSYS in penetration analysis: maximizing the accuracy of calculation and minimizing the calculation time. To maximize the calculation accuracy, the sensitivity analysis of the input parameters for ANSYS was performed and calculated the RMS error with the experimental data. The input parameters include mesh size, boundary condition, material properties, target diameter are tested and selected to minimize the error between the calculated result from simulation and the experiment data from the papers on the penetration equation. To minimize the calculation time, the parameter values obtained from accuracy analysis are adjusted to get optimized overall performance. As result of analysis, the followings were found: 1) As the mesh size gradually decreases from 0.9 mm to 0.5 mm, both the penetration depth and calculation time increase. 2) As diameters of the target decrease from 250mm to 60 mm, both the penetration depth and calculation time decrease. 3) As the yield stress which is one of the material property of the target decreases, the penetration depth increases. 4) The boundary condition with the fixed side surface of the target gives more penetration depth than that with the fixed side and rear surfaces. By using above finding, the input parameters can be tuned to minimize the error between simulation and experiments. By using simulation tool, ANSYS, with delicately tuned input parameters, penetration analysis can be done on computer without actual experiments. The data of penetration experiments are usually hard to get because of security reasons and only published papers provide them in the limited target material. The next step of this research is to generalize this approach to anticipate the penetration depth by interpolating the known penetration experiments. This result may not be accurate enough to be used to replace the penetration experiments, but those simulations can be used in the early stage of the design process of AGCV in modelling and simulation stage.

Keywords: ANSYS, input parameters, penetration depth, sensitivity analysis

Procedia PDF Downloads 375

Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

Abstract:

Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: color overlapping windows, image stitching, leukocyte detection, white blood cell detection

Procedia PDF Downloads 291