Search results for: fault tree analysis (FTA) method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 39516

Search results for: fault tree analysis (FTA) method

39246 Robust Diagnosability of PEMFC Based on Bond Graph LFT

Authors: Ould Bouamama, M. Bressel, D. Hissel, M. Hilairet

Abstract:

Fuel cell (FC) is one of the best alternatives of fossil energy. Recently, the research community of fuel cell has shown a considerable interest for diagnosis in view to ensure safety, security, and availability when faults occur in the process. The problematic for model based FC diagnosis consists in that the model is complex because of coupling of several kind of energies and the numerical values of parameters are not always known or are uncertain. The present paper deals with use of one tool: the Linear Fractional Transformation bond graph tool not only for uncertain modelling but also for monitorability (ability to detect and isolate faults) analysis and formal generation of robust fault indicators with respect to parameter uncertainties.The developed theory applied to a nonlinear FC system has proved its efficiency.

Keywords: bond graph, fuel cell, fault detection and isolation (FDI), robust diagnosis, structural analysis

Procedia PDF Downloads 342
39245 The Time-Frequency Domain Reflection Method for Aircraft Cable Defects Localization

Authors: Reza Rezaeipour Honarmandzad

Abstract:

This paper introduces an aircraft cable fault detection and location method in light of TFDR keeping in mind the end goal to recognize the intermittent faults adequately and to adapt to the serial and after-connector issues being hard to be distinguished in time domain reflection. In this strategy, the correlation function of reflected and reference signal is used to recognize and find the airplane fault as per the qualities of reflected and reference signal in time-frequency domain, so the hit rate of distinguishing and finding intermittent faults can be enhanced adequately. In the work process, the reflected signal is interfered by the noise and false caution happens frequently, so the threshold de-noising technique in light of wavelet decomposition is used to diminish the noise interference and lessen the shortcoming alert rate. At that point the time-frequency cross connection capacity of the reference signal and the reflected signal based on Wigner-Ville appropriation is figured so as to find the issue position. Finally, LabVIEW is connected to execute operation and control interface, the primary capacity of which is to connect and control MATLAB and LABSQL. Using the solid computing capacity and the bottomless capacity library of MATLAB, the signal processing turn to be effortlessly acknowledged, in addition LabVIEW help the framework to be more dependable and upgraded effectively.

Keywords: aircraft cable, fault location, TFDR, LabVIEW

Procedia PDF Downloads 449
39244 Failure Analysis of the Gasoline Engines Injection System

Authors: Jozef Jurcik, Miroslav Gutten, Milan Sebok, Daniel Korenciak, Jerzy Roj

Abstract:

The paper presents the research results of electronic fuel injection system, which can be used for diagnostics of automotive systems. In the paper is described the construction and operation of a typical fuel injection system and analyzed its electronic part. It has also been proposed method for the detection of the injector malfunction, based on the analysis of differential current or voltage characteristics. In order to detect the fault state, it is needed to use self-learning process, by the use of an appropriate self-learning algorithm.

Keywords: electronic fuel injector, diagnostics, measurement, testing device

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39243 An Enhanced MEIT Approach for Itemset Mining Using Levelwise Pruning

Authors: Tanvi P. Patel, Warish D. Patel

Abstract:

Association rule mining forms the core of data mining and it is termed as one of the well-known methodologies of data mining. Objectives of mining is to find interesting correlations, frequent patterns, associations or casual structures among sets of items in the transaction databases or other data repositories. Hence, association rule mining is imperative to mine patterns and then generate rules from these obtained patterns. For efficient targeted query processing, finding frequent patterns and itemset mining, there is an efficient way to generate an itemset tree structure named Memory Efficient Itemset Tree. Memory efficient IT is efficient for storing itemsets, but takes more time as compare to traditional IT. The proposed strategy generates maximal frequent itemsets from memory efficient itemset tree by using levelwise pruning. For that firstly pre-pruning of items based on minimum support count is carried out followed by itemset tree reconstruction. By having maximal frequent itemsets, less number of patterns are generated as well as tree size is also reduced as compared to MEIT. Therefore, an enhanced approach of memory efficient IT proposed here, helps to optimize main memory overhead as well as reduce processing time.

Keywords: association rule mining, itemset mining, itemset tree, meit, maximal frequent pattern

Procedia PDF Downloads 346
39242 Application of Groundwater Level Data Mining in Aquifer Identification

Authors: Liang Cheng Chang, Wei Ju Huang, You Cheng Chen

Abstract:

Investigation and research are keys for conjunctive use of surface and groundwater resources. The hydrogeological structure is an important base for groundwater analysis and simulation. Traditionally, the hydrogeological structure is artificially determined based on geological drill logs, the structure of wells, groundwater levels, and so on. In Taiwan, groundwater observation network has been built and a large amount of groundwater-level observation data are available. The groundwater level is the state variable of the groundwater system, which reflects the system response combining hydrogeological structure, groundwater injection, and extraction. This study applies analytical tools to the observation database to develop a methodology for the identification of confined and unconfined aquifers. These tools include frequency analysis, cross-correlation analysis between rainfall and groundwater level, groundwater regression curve analysis, and decision tree. The developed methodology is then applied to groundwater layer identification of two groundwater systems: Zhuoshui River alluvial fan and Pingtung Plain. The abovementioned frequency analysis uses Fourier Transform processing time-series groundwater level observation data and analyzing daily frequency amplitude of groundwater level caused by artificial groundwater extraction. The cross-correlation analysis between rainfall and groundwater level is used to obtain the groundwater replenishment time between infiltration and the peak groundwater level during wet seasons. The groundwater regression curve, the average rate of groundwater regression, is used to analyze the internal flux in the groundwater system and the flux caused by artificial behaviors. The decision tree uses the information obtained from the above mentioned analytical tools and optimizes the best estimation of the hydrogeological structure. The developed method reaches training accuracy of 92.31% and verification accuracy 93.75% on Zhuoshui River alluvial fan and training accuracy 95.55%, and verification accuracy 100% on Pingtung Plain. This extraordinary accuracy indicates that the developed methodology is a great tool for identifying hydrogeological structures.

Keywords: aquifer identification, decision tree, groundwater, Fourier transform

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39241 Bridging Urban Planning and Environmental Conservation: A Regional Analysis of Northern and Central Kolkata

Authors: Tanmay Bisen, Aastha Shayla

Abstract:

This study introduces an advanced approach to tree canopy detection in urban environments and a regional analysis of Northern and Central Kolkata that delves into the intricate relationship between urban development and environmental conservation. Leveraging high-resolution drone imagery from diverse urban green spaces in Kolkata, we fine-tuned the deep forest model to enhance its precision and accuracy. Our results, characterized by an impressive Intersection over Union (IoU) score of 0.90 and a mean average precision (mAP) of 0.87, underscore the model's robustness in detecting and classifying tree crowns amidst the complexities of aerial imagery. This research not only emphasizes the importance of model customization for specific datasets but also highlights the potential of drone-based remote sensing in urban forestry studies. The study investigates the spatial distribution, density, and environmental impact of trees in Northern and Central Kolkata. The findings underscore the significance of urban green spaces in met-ropolitan cities, emphasizing the need for sustainable urban planning that integrates green infrastructure for ecological balance and human well-being.

Keywords: urban greenery, advanced spatial distribution analysis, drone imagery, deep learning, tree detection

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39240 Assessment of the Tectonic Effects on Soil Radon Activity along the Margin of the Arabian Plate Boundary in Northwestern Syria

Authors: Mohamed Al-Hilal

Abstract:

The main purpose of the present study is to assess the role of active tectonics in influencing the emanation level of soil radon across two tectonically active structures of the Northern Dead Sea Fault (NDSF) in northwestern Syria: namely, the Qastoon and Al-Harif fault segments. The radon measurements were basically directed by the results drawn from earlier studies of archaeoseismic and paleoseismic investigation in Al-Harif, besides integrated geophysical and morphotectonic survey at the Qastoon site. In view of that, a total of 80 soil gas radon points were measured in this work with a sampling depth of 75 cm, using the AlphaGUARD PQ 2000Pro radon detector. The background range of normal radon emission from local soil was determined in area located away from the influence of the tectonic disturbances. The obtained radon data were statistically analyzed, and the mean values have been standardized in terms of probability of magnitude, which enhances the comparison process and so facilitating the separation of normal radon variations from other anomalous or geotectonic related values. The overall results revealed remarkable occurrences of fault-associated radon anomalies with maximum peak values of ~6 to 7 times above the background, trending in accordance with the predicted traces of the fault ruptures at the Qastoon and Al-Harif, respectively.

Keywords: soil gas radon, active tectonic structure, northern dead sea fault, western Syria

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39239 Application of Fuzzy Approach to the Vibration Fault Diagnosis

Authors: Jalel Khelil

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In order to improve reliability of Gas Turbine machine especially its generator equipment, a fault diagnosis system based on fuzzy approach is proposed. Three various methods namely K-NN (K-nearest neighbors), F-KNN (Fuzzy K-nearest neighbors) and FNM (Fuzzy nearest mean) are adopted to provide the measurement of relative strength of vibration defaults. Both applications consist of two major steps: Feature extraction and default classification. 09 statistical features are extracted from vibration signals. 03 different classes are used in this study which describes vibrations condition: Normal, unbalance defect, and misalignment defect. The use of the fuzzy approaches and the classification results are discussed. Results show that these approaches yield high successful rates of vibration default classification.

Keywords: fault diagnosis, fuzzy classification k-nearest neighbor, vibration

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39238 Processing and Economic Analysis of Rain Tree (Samanea saman) Pods for Village Level Hydrous Bioethanol Production

Authors: Dharell B. Siano, Wendy C. Mateo, Victorino T. Taylan, Francisco D. Cuaresma

Abstract:

Biofuel is one of the renewable energy sources adapted by the Philippine government in order to lessen the dependency on foreign fuel and to reduce carbon dioxide emissions. Rain tree pods were seen to be a promising source of bioethanol since it contains significant amount of fermentable sugars. The study was conducted to establish the complete procedure in processing rain tree pods for village level hydrous bioethanol production. Production processes were done for village level hydrous bioethanol production from collection, drying, storage, shredding, dilution, extraction, fermentation, and distillation. The feedstock was sundried, and moisture content was determined at a range of 20% to 26% prior to storage. Dilution ratio was 1:1.25 (1 kg of pods = 1.25 L of water) and after extraction process yielded a sugar concentration of 22 0Bx to 24 0Bx. The dilution period was three hours. After three hours of diluting the samples, the juice was extracted using extractor with a capacity of 64.10 L/hour. 150 L of rain tree pods juice was extracted and subjected to fermentation process using a village level anaerobic bioreactor. Fermentation with yeast (Saccharomyces cerevisiae) can fasten up the process, thus producing more ethanol at a shorter period of time; however, without yeast fermentation, it also produces ethanol at lower volume with slower fermentation process. Distillation of 150 L of fermented broth was done for six hours at 85 °C to 95 °C temperature (feedstock) and 74 °C to 95 °C temperature of the column head (vapor state of ethanol). The highest volume of ethanol recovered was established at with yeast fermentation at five-day duration with a value of 14.89 L and lowest actual ethanol content was found at without yeast fermentation at three-day duration having a value of 11.63 L. In general, the results suggested that rain tree pods had a very good potential as feedstock for bioethanol production. Fermentation of rain tree pods juice can be done with yeast and without yeast.

Keywords: fermentation, hydrous bioethanol, fermentation, rain tree pods, village level

Procedia PDF Downloads 263
39237 Conceptual Methods of Mitigating Matured Urban Tree Roots Surviving in Conflicts Growth within Built Environment: A Review

Authors: Mohd Suhaizan Shamsuddin

Abstract:

Urbanization exacerbates the environment quality and pressures of matured urban trees' growth and development in changing environment. The growth of struggled matured urban tree-roots by spreading within the existences of infrastructures, resulting in large damage to the structured and declined growth. Many physiological growths declined or damages by the present and installations of infrastructures within and nearby root zone. Afford to remain both matured urban tree and infrastructures as a service provider causes damage and death, respectively. Inasmuch, spending more expenditure on fixing both or removing matured urban trees as risky to the future environment as the mitigation methods to reduce the problems are unconcerned. This paper aims to explain mitigation method practices of reducing the encountered problems of matured urban tree-roots settling and infrastructures while modified urban soil to sustain at an optimum level. Three categories capturing encountered conflicts growth of matured urban tree-roots growth within and nearby infrastructures by mitigating the problems of limited soil spaces, poor soil structures and soil space barrier installations and maintenance. The limited soil space encountered many conflicts and identified six methods that mitigate the survival tree-roots, such as soil volume/mounding, soil replacement/amendment for the radial trench, soil spacing-root bridge, root tunneling, walkway/pavement rising/diverted, and suspended pavement. The limited soil spaces are mitigation affords of inadequate soil-roots and spreading root settling and modification of construction soil media since the barrier existed and installed in root trails or zones. This is the reason for enabling tree-roots spreading and finds adequate sources (nutrients, water uptake and oxygen), spaces and functioning to stability stand of root anchorage since the matured tree grows larger. The poor soil structures were identified as three methods to mitigate soil materials' problems, and fewer soil voids comprise skeletal soil, structural soil, and soil cell. Mitigation of poor soil structure is altering the existing and introducing new structures by modifying the quantities and materials ratio allowing more voids beneath for roots spreading by considering the above structure of foot and vehicle traffics functioning or load-bearing. The soil space barrier installations and maintenance recognized to sustain both infrastructures and tree-roots grown in limited spaces and its benefits, the root barrier installations and root pruning are recommended. In conclusion, these recommended methods attempt to mitigate the present problems encountered at a particular place and problems among tree-roots and infrastructures exist. The combined method is the best way to alleviates the conflicts since the recognized conflicts are between tree-roots and man-made while the urban soil is modified. These presenting methods are most considered to sustain the matured urban trees' lifespan growth in the urban environment.

Keywords: urban tree-roots, limited soil spaces, poor soil structures, soil space barrier and maintenance

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39236 Case Study Analysis of 2017 European Railway Traffic Management Incident: The Application of System for Investigation of Railway Interfaces Methodology

Authors: Sanjeev Kumar Appicharla

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This paper presents the results of the modelling and analysis of the European Railway Traffic Management (ERTMS) safety-critical incident to raise awareness of biases in the systems engineering process on the Cambrian Railway in the UK using the RAIB 17/2019 as a primary input. The RAIB, the UK independent accident investigator, published the Report- RAIB 17/2019 giving the details of their investigation of the focal event in the form of immediate cause, causal factors, and underlying factors and recommendations to prevent a repeat of the safety-critical incident on the Cambrian Line. The Systems for Investigation of Railway Interfaces (SIRI) is the methodology used to model and analyze the safety-critical incident. The SIRI methodology uses the Swiss Cheese Model to model the incident and identify latent failure conditions (potentially less than adequate conditions) by means of the management oversight and risk tree technique. The benefits of the systems for investigation of railway interfaces methodology (SIRI) are threefold: first is that it incorporates the “Heuristics and Biases” approach advanced by 2002 Nobel laureate in Economic Sciences, Prof Daniel Kahneman, in the management oversight and risk tree technique to identify systematic errors. Civil engineering and programme management railway professionals are aware of the role “optimism bias” plays in programme cost overruns and are aware of bow tie (fault and event tree) model-based safety risk modelling techniques. However, the role of systematic errors due to “Heuristics and Biases” is not appreciated as yet. This overcomes the problems of omission of human and organizational factors from accident analysis. Second, the scope of the investigation includes all levels of the socio-technical system, including government, regulatory, railway safety bodies, duty holders, signaling firms and transport planners, and front-line staff such that lessons are learned at the decision making and implementation level as well. Third, the author’s past accident case studies are supplemented with research pieces of evidence drawn from the practitioner's and academic researchers’ publications as well. This is to discuss the role of system thinking to improve the decision-making and risk management processes and practices in the IEC 15288 systems engineering standard and in the industrial context such as the GB railways and artificial intelligence (AI) contexts as well.

Keywords: accident analysis, AI algorithm internal audit, bounded rationality, Byzantine failures, heuristics and biases approach

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39235 Co-Seismic Surface Deformation Induced By 24 September 2019 Mirpur, Pakistan Earthquake Along an Active Blind Fault Estimated Using Sentinel-1 TOPS Interferometry

Authors: Muhammad Ali, Zeeshan Afzal, Giampaolo Ferraioli, Gilda Schirinzi, Muhammad Saleem Mughal, Vito Pascazio

Abstract:

On 24 September 2019, an earthquake with 5.6 Mw and 10 km depth stroke in Mirpur. The Mirpur area was highly affected by this earthquake, with the death of 34 people. This study aims to estimate the surface deformation associated with this earthquake. The interferometric synthetic aperture radar (InSAR) technique is applied to study earthquake induced surface motion. InSAR data using 9 Sentinel-1A SAR images from 11 August 2019 to 22 October 2019 is used to investigate the pre, co-, and post-seismic deformation trends. Time series investigation reveals that there was not such deformation in pre-seismic time period. In the co-seismic time period, strong displacement was observed, and in post-seismic results, small displacement is seen due to aftershocks. Our results show the existence of a previously unpublished blind fault in Mirpur and help to locate the fault line. Previous this fault line was triggered during the 2005 earthquake, and now it’s activated on 24 September 2019. Study area is already facing many problems due to natural hazards where additional surface deformations, particularly because of an earthquake with an activated blind fault, have increased its vulnerability.

Keywords: surface deformation, InSAR, earthquake, sentinel-1, mirpur

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39234 Thermochemical and Biological Pretreatment Study for Efficient Sugar Release from Lignocellulosic Biomass (Deodar and Sal Wood Residues)

Authors: Neelu Raina, Parvez Singh Slathia, Deepali Bhagat, Preeti Sharma

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Pretreatment of lignocellulosic biomass for generating suitable substrates (starch/ sugars) for conversion to bioethanol is the most crucial step. In present study waste from furniture industry i.e sawdust from softwood Cedrus deodara (deodar) and hardwood Shorea robusta (sal) was used as lignocellulosic biomass. Thermochemical pretreatment was given by autoclaving at 121°C temperature and 15 psi pressure. Acids (H2SO4,HCl,HNO3,H3PO4), alkali (NaOH,NH4OH,KOH,Ca(OH)2) and organic acids (C6H8O7,C2H2O4,C4H4O4) were used at 0.1%, 0.5% and 1% concentration without giving any residence time. 1% HCl gave maximum sugar yield of 3.6587g/L in deodar and 6.1539 g/L in sal. For biological pretreatment a fungi isolated from decaying wood was used , sawdust from deodar tree species was used as a lignocellulosic substrate and before thermochemical pretreatment sawdust was treated with fungal culture at 37°C under submerged conditions with a residence time of one week followed by a thermochemical pretreatment methodology. Higher sugar yields were obtained with sal tree species followed by deodar tree species, i.e., 6.0334g/L in deodar and 8.3605g/L in sal was obtained by a combined biological and thermochemical pretreatment. Use of acids along with biological pretreatment is a favourable factor for breaking the lignin seal and thus increasing the sugar yield. Sugar estimation was done using Dinitrosalicyclic assay method. Result validation is being done by statistical analysis.

Keywords: lignocellulosic biomass, bioethanol, pretreatment, sawdust

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39233 Improve B-Tree Index’s Performance Using Lock-Free Hash Table

Authors: Zhanfeng Ma, Zhiping Xiong, Hu Yin, Zhengwei She, Aditya P. Gurajada, Tianlun Chen, Ying Li

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Many RDBMS vendors use B-tree index to achieve high performance for point queries and range queries, and some of them also employ hash index to further enhance the performance as hash table is more efficient for point queries. However, there are extra overheads to maintain a separate hash index, for example, hash mapping for all data records must always be maintained, which results in more memory space consumption; locking, logging and other mechanisms are needed to guarantee ACID, which affects the concurrency and scalability of the system. To relieve the overheads, Hash Cached B-tree (HCB) index is proposed in this paper, which consists of a standard disk-based B-tree index and an additional in-memory lock-free hash table. Initially, only the B-tree index is constructed for all data records, the hash table is built on the fly based on runtime workload, only data records accessed by point queries are indexed using hash table, this helps reduce the memory footprint. Changes to hash table are done using compare-and-swap (CAS) without performing locking and logging, this helps improve the concurrency and avoid contention. The hash table is also optimized to be cache conscious. HCB index is implemented in SAP ASE database, compared with the standard B-tree index, early experiments and customer adoptions show significant performance improvement. This paper provides an overview of the design of HCB index and reports the experimental results.

Keywords: B-tree, compare-and-swap, lock-free hash table, point queries, range queries, SAP ASE database

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39232 Fault Prognostic and Prediction Based on the Importance Degree of Test Point

Authors: Junfeng Yan, Wenkui Hou

Abstract:

Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

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39231 Neotectonic Characteristics of the Western Part of Konya, Central Anatolia, Turkey

Authors: Rahmi Aksoy

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The western part of Konya consists of an area of block faulted basin and ranges. Present day topography is characterized by alternating elongate mountains and depressions trending east-west. A number of depressions occur in the region. One of the large depressions is the E-W trending Kızılören-Küçükmuhsine (KK basin) basin bounded on both sides by normal faults and located on the west of the Konya city. The basin is about 5-12 km wide and 40 km long. Ranges north and south of the basin are composed of undifferentiated low grade metamorphic rocks of Silurian-Cretaceous age and smaller bodies of ophiolites of probable Cretaceous age. The basin fill consists of the upper Miocene-lower Pliocene fluvial, lacustrine, alluvial sediments and volcanic rocks. The younger and undeformed Plio-Quaternary basin fill unconformably overlies the older basin fill and is composed predominantly of conglomerate, mudstone, silt, clay and recent basin floor deposits. The paleostress data on the striated fault planes in the basin indicates NW-SE extension and associated with an NE-SW compression. The eastern end of the KK basin is cut and terraced by the active Konya fault zone. The Konya fault zone is NE trending, east dipping normal fault forming the western boundary of the Konya depression. The Konya depression consists mainly of Plio-Quaternary alluvial complex and recent basin floor sediments. The structural data gathered from the Konya fault zone support normal faulting with a small amount of dextral strike-slip tensional tectonic regime that shaped under the WNW-ESE extensional stress regime.

Keywords: central Anatolia, fault kinematics, Kızılören-Küçükmuhsine basin, Konya fault zone, neotectonics

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39230 Competing Risks Modeling Using within Node Homogeneity Classification Tree

Authors: Kazeem Adesina Dauda, Waheed Babatunde Yahya

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To design a tree that maximizes within-node homogeneity, there is a need for a homogeneity measure that is appropriate for event history data with multiple risks. We consider the use of Deviance and Modified Cox-Snell residuals as a measure of impurity in Classification Regression Tree (CART) and compare our results with the results of Fiona (2008) in which homogeneity measures were based on Martingale Residual. Data structure approach was used to validate the performance of our proposed techniques via simulation and real life data. The results of univariate competing risk revealed that: using Deviance and Cox-Snell residuals as a response in within node homogeneity classification tree perform better than using other residuals irrespective of performance techniques. Bone marrow transplant data and double-blinded randomized clinical trial, conducted in other to compare two treatments for patients with prostate cancer were used to demonstrate the efficiency of our proposed method vis-à-vis the existing ones. Results from empirical studies of the bone marrow transplant data showed that the proposed model with Cox-Snell residual (Deviance=16.6498) performs better than both the Martingale residual (deviance=160.3592) and Deviance residual (Deviance=556.8822) in both event of interest and competing risks. Additionally, results from prostate cancer also reveal the performance of proposed model over the existing one in both causes, interestingly, Cox-Snell residual (MSE=0.01783563) outfit both the Martingale residual (MSE=0.1853148) and Deviance residual (MSE=0.8043366). Moreover, these results validate those obtained from the Monte-Carlo studies.

Keywords: within-node homogeneity, Martingale residual, modified Cox-Snell residual, classification and regression tree

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39229 Fuzzy Logic-Based Approach to Predict Fault in Transformer Oil Based on Health Index Using Dissolved Gas Analysis

Authors: Kharisma Utomo Mulyodinoto, Suwarno, Ahmed Abu-Siada

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Transformer insulating oil is a key component that can be utilized to detect incipient faults within operating transformers without taking them out of service. Dissolved gas-in-oil analysis has been widely accepted as a powerful technique to detect such incipient faults. While the measurement of dissolved gases within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straightforward as it depends on personnel expertise more than mathematical formulas. In analyzing such data, the generation rate of each dissolved gas is of more concern than the absolute value of the gas. As such, history of dissolved gases within a particular transformer should be archived for future comparison. Lack of such history may lead to misinterpretation of the obtained results. IEEE C57.104-2008 standards have classified the health condition of the transformer based on the absolute value of individual dissolved gases along with the total dissolved combustible gas (TDCG) within transformer oil into 4 conditions. While the technique is easy to implement, it is considered as a very conservative technique and is not widely accepted as a reliable interpretation tool. Moreover, measured gases for the same oil sample can be within various conditions limits and hence, misinterpretation of the data is expected. To overcome this limitation, this paper introduces a fuzzy logic approach to predict the health condition of the transformer oil based on IEEE C57.104-2008 standards along with Roger ratio and IEC ratio-based methods. DGA results of 31 chosen oil samples from 469 transformer oil samples of normal transformers and pre-known fault-type transformers that were collected from Indonesia Electrical Utility Company, PT. PLN (Persero), from different voltage rating: 500/150 kV, 150/20 kV, and 70/20 kV; different capacity: 500 MVA, 60 MVA, 50 MVA, 30 MVA, 20 MVA, 15 MVA, and 10 MVA; and different lifespan, are used to test and establish the fuzzy logic model. Results show that the proposed approach is of good accuracy and can be considered as a platform toward the standardization of the dissolved gas interpretation process.

Keywords: dissolved gas analysis, fuzzy logic, health index, IEEE C57.104-2008, IEC ratio method, Roger ratio method

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39228 An Accurate Method for Phylogeny Tree Reconstruction Based on a Modified Wild Dog Algorithm

Authors: Essam Al Daoud

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This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.

Keywords: least square, neighbor joining, phylogenetic tree, wild dog pack

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39227 Urban and Rural Children’s Knowledge on Biodiversity in Bizkaia: Tree Identification Skills and Animal and Plant Listing

Authors: Joserra Díez, Ainhoa Meñika, Iñaki Sanz-Azkue, Arritokieta Ortuzar

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Biodiversity provides humans with a great range of ecosystemic services; it is therefore an indispensable resource and a legacy to coming generations. However, in the last decades, the increasing exploitation of the Planet has caused a great loss of biodiversity and its acquaintance has decreased remarkably; especially in urbanized areas, due to the decreasing attachment of humans to nature. Yet, the Primary Education curriculum primes the identification of flora and fauna to guarantee the knowledge of children on their surroundings, so that they care for the environment as well as for themselves. In order to produce effective didactic material that meets the needs of both teachers and pupils, it is fundamental to diagnose the current situation. In the present work, the knowledge on biodiversity of 3rd cycle Primary Education students in Biscay (n=98) and its relation to the size of the town/city of their school is discussed. Two tests have been used with such aim: one for tree identification and the other one so that the students enumerated the species of trees and animals they knew. Results reveal that knowledge of students on tree identification is scarce regardless the size of the city/town and of their school. On the other hand, animal species are better known than tree species.

Keywords: biodiversity, population, tree identification, animal identification

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39226 Model-Based Fault Diagnosis in Carbon Fiber Reinforced Composites Using Particle Filtering

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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39225 Solid Phase Micro-Extraction/Gas Chromatography-Mass Spectrometry Study of Volatile Compounds from Strawberry Tree and Autumn Heather Honeys

Authors: Marinos Xagoraris, Elisavet Lazarou, Eleftherios Alissandrakis, Christos S. Pappas, Petros A. Tarantilis

Abstract:

Strawberry tree (Arbutus unedo L.) and autumn heather (Erica manipuliflora Salisb.) are important beekeeping plants of Greece. Six monofloral honeys (four strawberry tree, two autumn heather) were analyzed by means of Solid Phase Micro-Extraction (SPME, 60 min, 60 oC) followed by Gas Chromatography coupled to Mass Spectrometry (GC-MS) for the purpose of assessing the botanical origin. A Divinylbenzene/Carboxen/Polydimethylsiloxane (DVB/CAR/PDMS) fiber was employed, and benzophenone was used as internal standard. The volatile compounds with higher concentration (μg/ g of honey expressed as benzophenone) from strawberry tree honey samples, were α-isophorone (2.50-8.12); 3,4,5-trimethyl-phenol (0.20-4.62); 2-hydroxy-isophorone (0.06-0.53); 4-oxoisophorone (0.38-0.46); and β-isophorone (0.02-0.43). Regarding heather honey samples, the most abundant compounds were 1-methoxy-4-propyl-benzene (1.22-1.40); p-anisaldehyde (0.97-1.28); p-anisic acid (0.35-0.58); 2-furaldehyde (0.52-0.57); and benzaldehyde (0.41-0.56). Norisoprenoids are potent floral markers for strawberry-tree honey. β-isophorone is found exclusively in the volatile fraction of this type of honey, while also α-isophorone, 4-oxoisophorone and 2-hydroxy-isophorone could be considered as additional marker compounds. The analysis of autumn heather honey revealed that phenolic compounds are the most abundant and p-anisaldehyde; 1-methoxy-4-propyl-benzene; and p-anisic acid could serve as potent marker compounds. In conclusion, marker compounds for the determination of the botanical origin for these honeys could be identified as several norisoprenoids and phenolic components were found exclusively or in higher concentrations compared to common Greek honey varieties.

Keywords: SPME/GC-MS, volatile compounds, heather honey, strawberry tree honey

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39224 Adaptive Kaman Filter for Fault Diagnosis of Linear Parameter-Varying Systems

Authors: Rajamani Doraiswami, Lahouari Cheded

Abstract:

Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

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39223 Permanent Reduction of Arc Flash Energy to Safe Limit on Line Side of 480 Volt Switchgear Incomer Breaker

Authors: Abid Khan

Abstract:

A recognized engineering challenge is related to personnel protection from fatal arc flash incident energy in the line side of the 480-volt switchgear incomer breakers during maintenance activities. The incident energy is typically high due to slow fault clearance, and it can be higher than the available personnel protective equipment (PPE) ratings. A fault in this section of the switchgear is cleared by breakers or fuses in the upstream higher voltage system (4160 Volt or higher). The current reflection in the higher voltage upstream system for a fault in the 480-volt switchgear is low, the clearance time is slower, and the inversely proportional incident energy is hence higher. The installation of overcurrent protection at a 480-volt system upstream of the incomer breaker will operate fast enough and trips the upstream higher voltage breaker when a fault develops at the incomer breaker. Therefore, fault current reduction as reflected in the upstream higher voltage system is eliminated. Since the fast overcurrent protection is permanently installed, it is always functional, does not require human interventions, and eliminates exposure to human errors. It is installed at the maintenance activities location, and its operations can be locally monitored by craftsmen during maintenance activities.

Keywords: arc flash, mitigation, maintenance switch, energy level

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39222 Automated Process Quality Monitoring and Diagnostics for Large-Scale Measurement Data

Authors: Hyun-Woo Cho

Abstract:

Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.

Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring

Procedia PDF Downloads 375
39221 Modelling the Impact of Installation of Heat Cost Allocators in District Heating Systems Using Machine Learning

Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

Abstract:

Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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39220 Estimation of the Length and Location of Ground Surface Deformation Caused by the Reverse Faulting

Authors: Nader Khalafian, Mohsen Ghaderi

Abstract:

Field observations have revealed many examples of structures which were damaged due to ground surface deformation caused by the faulting phenomena. In this paper some efforts were made in order to estimate the length and location of the ground surface where large displacements were created due to the reverse faulting. This research has conducted in two steps; (1) in the first step, a 2D explicit finite element model were developed using ABAQUS software. A subroutine for Mohr-Coulomb failure criterion with strain softening model was developed by the authors in order to properly model the stress strain behavior of the soil in the fault rapture zone. The results of the numerical analysis were verified with the results of available centrifuge experiments. Reasonable coincidence was found between the numerical and experimental data. (2) In the second step, the effects of the fault dip angle (δ), depth of soil layer (H), dilation and friction angle of sand (ψ and φ) and the amount of fault offset (d) on the soil surface displacement and fault rupture path were investigated. An artificial neural network-based model (ANN), as a powerful prediction tool, was developed to generate a general model for predicting faulting characteristics. A properly sized database was created to train and test network. It was found that the length and location of the zone of displaced ground surface can be accurately estimated using the proposed model.

Keywords: reverse faulting, surface deformation, numerical, neural network

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39219 Pilot Directional Protection Scheme Using Wireless Communication

Authors: Nitish Sharma, G. G. Karady

Abstract:

This paper presents a scheme for the protection of loop system from all type of faults using the direction of fault current. The presence of distributed generation in today’s system increases the complexity of fault detection as the power flow is bidirectional. Hence, protection scheme specific to this purpose needs to be developed. This paper shows a fast protection scheme using communication which can be fiber optic or wireless. In this paper, the possibility of wireless communication for protection is studied to exchange the information between the relays. The negative sequence and positive sequence directional elements are used to determine the direction of fault current. A PSCAD simulation is presented and validated using commercial SEL relays.

Keywords: smart grid protection, pilot protection, power system simulation, wireless communication

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39218 Geological Characteristics of the Beni Snouss District

Authors: N. Hadj Mohamed, A. Boutaleb

Abstract:

The Beni Snouss area is characterized by horst and graben structures and it comprises deformed Palaeozoic sedimentary and magmatic rocks overlapping by Mesozoic sediments. Two structural units are distinguished: a Palaeozoic basement and a Mesozoic cover. The study area is densely faulted and major faults strike N110° to N140° and dip vertically The mineralized fault zones are readily distinguishable by their argillic wall rock alteration. The fault zones that are filled with mineralizations, aplites, microgranites and quartz run roughly parallel to each other and are apparently in the same fault system. The Palaeozoic basement rocks contain mineralization occurring as veins, veinlets and disseminations. The Liassic carbonate platform sequence contains Ba (Pb-Zn) sulphide deposits occurring mainly as strata bound, and open space filling.

Keywords: Algeria, basement, Beni Snouss, cover

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39217 The Influence of Forest Management Histories on Dead and Habitat Trees in the Old Growth Forest in Northern Iran

Authors: Kiomars Sefidi

Abstract:

Dead and habitat tree such as fallen logs, snags, stumps and cracks and loos bark etc. is regarded as an important ecological component of forests on which many forest dwelling species depend, yet its relation to management history in Caspian forest has gone unreported. The aim of research was to compare the amounts of dead tree and habitat in the forests with historically different intensities of management, including: forests with the long term implication of management (PS), the short-term implication of management (NS) which were compared with semi virgin forest (GS). The number of 405 individual dead and habitat trees were recorded and measured at 109 sampling locations. ANOVA revealed volume of the dead tree in the form and decay classes significantly differ within sites and dead volume in the semi virgin forest significantly higher than managed sites. Comparing the amount of dead and habitat tree in three sites showed that dead tree volume related with management history and significantly differ in three study sites. Also, the numbers of habitat trees including cavities, Cracks and loose bark and Fork split trees significantly vary among sites. Reaching their highest in virgin site and their lowest in the site with the long term implication of management, it was concluded that forest management cause reduction of the amount of dead and habitat tree. Forest management history affect the forest's ability to generate dead tree especially in a large size, thus managing this forest according to ecological sustainable principles require a commitment to maintaining stand structure that allow, continued generation of dead tree in a full range of size.

Keywords: forest biodiversity, cracks trees, fork split trees, sustainable management, Fagus orientalis, Iran

Procedia PDF Downloads 536