Description:
Frequency Response Analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relies on graphical analysis, it calls for an expert person to analyse the results as so far, there is no standard code for FRA interpretation worldwide. In this paper an online technique is introduced to detect the internal faults within a power transformer by constructing the voltage-current (V-I) locus diagram to provide a current state of the transformer health condition. The technique does not call for any special equipment as it uses the existing metering devices attached to any power transformer to monitor the input voltage, output voltage and the input current at the power frequency and hence online monitoring can be realised. Various types of faults have been simulated to assess its impact on the proposed locus. A Matlab code based on digital image processing is developed to calculate any deviation of the V-I locus with respect to the reference one and to identify the type of fault.
Description:
Frequency Response Analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relies on graphical analysis, it calls for an expert person to analyse the results as so far, there is no standard code for FRA interpretation worldwide. In this paper an online technique is introduced to detect the internal faults within a power transformer by constructing the voltage-current (V-I) locus diagram to provide a current state of the transformer health condition. The technique does not call for any special equipment as it uses the existing metering devices attached to any power transformer to monitor the input voltage, output voltage and the input current at the power frequency and hence online monitoring can be realised. Various types of faults have been simulated to assess its impact on the proposed locus. A Matlab code based on digital image processing is developed to calculate any deviation of the V-I locus with respect to the reference one and to identify the type of fault.
Description:
Frequency response analysis (FRA) is gaining global popularity in detecting power transformer winding movement due to the development of FRA test equipment. However, because FRA relies on graphical analysis, interpretation of its signatures is still a very specialized area that calls for skillful personnel to detect the sort and likely place of the fault as so far, there is no reliable standard code for FRA signature classification and quantification. This paper investigates the impact of transformer winding axial displacement on its FRA signature as a step toward the establishment of reliable codes for FRA interpretation. In this context a detailed model for a singlephase transformer is simulated using 3D finite element analysis to emulate a close to real transformer. The impact of axial displacement on the electrical distributed parameters model that are calculated based on the transformer physical dimension is examined to investigate how model’s parameters including inductance and capacitance matrices change when axial displacement takes place within a power transformer.
Description:
Frequency response analysis (FRA) is gaining global popularity in detecting power transformer winding movement due to the development of FRA test equipment. However, because FRA relies on graphical analysis, interpretation of its signatures is still a very specialized area that calls for skillful personnel to detect the sort and likely place of the fault as so far, there is no reliable standard code for FRA signature classification and quantification. This paper investigates the impact of transformer winding axial displacement on its FRA signature as a step toward the establishment of reliable codes for FRA interpretation. In this context a detailed model for a singlephase transformer is simulated using 3D finite element analysis to emulate a close to real transformer. The impact of axial displacement on the electrical distributed parameters model that are calculated based on the transformer physical dimension is examined to investigate how model’s parameters including inductance and capacitance matrices change when axial displacement takes place within a power transformer.
Description:
Power transformer is an important asset within the electrical power system network. Frequency Response Analysis (FRA) has been developing in popularity in recent years as a tool to detect mechanical deformation of power transformers winding. Since the FRA has been relying on graphical analysis, it calls for an expert person to analyze the results to detect the type of the fault and its location. There are no reliable guidelines for FRA signature in the event that a failure occurs in service and the impact can be far reaching. The concept of FRA has been successfully used as a diagnostic technique to detect the winding deformation, core and clamping structure for the power transformers. This paper investigated the impact of the forced and free winding buckling based on the variation of the electrical parameters to show how these faults vary the FRA signature.
Description:
This paper investigates the impact of conducting materials on the correlation of furan concentration in transformer oil and its spectral response characteristics. The presence of furan derivatives in aged-transformer oil has been one of the key indicators for solid dielectric deterioration. Identification and quantification of furan derivatives are currently performed using high performance liquid chromatography or gas chromatography-mass spectrometry based on ASTM D5837 standard. Although these techniques are well established, they need an expert personal to conduct the test and to analyse its results. Moreover, the test is relatively expensive and the analysis of oil sample may take days as most utilities sending transformer oil samples to external laboratories to be tested. Recently, it has been proven that furan concentration in transformer oil has a strong correlation to the oil spectral response. This paper is to validate this finding and to investigate the impact of conducting materials within transformer oil on this correlation. In this context, extensive experimental tests are conducted to assess the impact of various concentration of conducting materials (e.g., copper dust) dissolved in transformer oil samples of different furan contents on its absorption and transmission spectra. The measured experimental results show that, the impact of such small amount ofdissolved conducting materials on the oil spectral response is minimal.
Description:
System reliability optimization has been considered as an area to improve the operational availability of electrical and manufacturing systems. This research area addresses system reliability estimation and mathematical model development. This paper presents a -review on system reliability optimization techniques based on different classification of criteria. The main criteria considered in this study are system structure, system state, optimization model, allocation model, modeling and solution methods. The classification can provide an overview of all criteria that should be used to make optimal decisions in a system by taking the reliability into account. Not only it can assist the researchers to develop new optimization models, but also it presents the practitioners how system reliability optimization models can help industries. The paper also discusses the limitations of the present techniques in this area.
Description:
Our approach to the author identification task uses existing authorship attribution methods using local n-grams (LNG) and performs a weighted ensemble. This approach came in third for this year's competition, using a relatively simple scheme of weights by training set accuracy. LNG models create profiles, consisting of a list of character n-grams that best represent a particular author's writing. The use of a weighted ensemble improved upon the accuracy of the method without reducing the speed of the algorithm; the submitted solution was not only near the top of the leaderboard in terms of accuracy, but it was also one of the faster algorithms submitted.
Description:
Our approach to the author identification task uses existing authorship attribution methods using local n-grams (LNG) and performs a weighted ensemble. This approach came in third for this year's competition, using a relatively simple scheme of weights by training set accuracy. LNG models create profiles, consisting of a list of character n-grams that best represent a particular author's writing. The use of a weighted ensemble improved upon the accuracy of the method without reducing the speed of the algorithm; the submitted solution was not only near the top of the leaderboard in terms of accuracy, but it was also one of the faster algorithms submitted.
Description:
WSNs generate a large amount of data in the form of data stream; and mining these streams to extract useful knowledge is a highly challenging task. Existing works proposed in literature use sensor association rules measured in terms of occurrence frequency of patterns. However, these rules often generate a huge number of rules, most of which are non-informative or fail to reflect the true correlation among data objects. Additionally mining associated sensor patterns from sensor stream data, which is vital for real-time applications, has not been addressed yet in literature. In this paper, we address these problems and propose a new type of sensor behavioral pattern called associated sensor patterns which capture simultaneously association-like co-occurrence as well as substantial temporal correlations implied by such co-occurrences in sensor data. We propose a novel tree structure, called associated sensor pattern stream tree (ASPS-tree) and a new technique, called associated sensor pattern mining of data stream (ASPMS), using sliding window-based associated sensor pattern mining for WSNs. By capturing the useful knowledge of the data stream into an ASPS-tree, our ASPMS algorithm can mine associated sensor patterns in the current window with frequent pattern (FP)-growth like pattern-growth method. Extensive experimental analyses show that our technique is very efficient in discovering associated sensor patterns over sensor data stream.
Description:
This paper focuses on the behavior of maximum power point tracking (MPPT) on photovoltaic (PV) cell systems using MATLAB/Simulink software. The PV cells can offer better simulation results when a double-exponential type, i.e., double-diode model is used. The reason, it is more accurate with the real testing condition even though the efficiency is a bit less. This confirms that theoretical single-diode model still require more improvements. In addition, multijunction solar cell also investigated to obtain its maximum performance compared with the conventional silicon PV cell. The obtained results show that the tandem (or multijunction) cell can provide almost 3-times maximum power compared to the conventional PV cell. Therefore, the multijunction/ tandem PV cells can produce higher power throughout the sunny day due to the higher MPPT capacity. Furthermore, perturb and observe method seems to be very useful because of its simplicity despite the unresolved algorithm for different methods, such as constant voltage tracking technique.
Description:
Condition monitoring of power transformers is essential to maintain the reliability of electricity grid. Frequency response analysis (FRA) is a useful tool for the detection of incipient mechanical faults within power transformers. There are various methods of evaluating the frequency spectrum for fault classification and quantification. This paper presents a useful method to detect and to identify various winding faults of a power transformer based on its FRA signature. Simulation results show that location of resonance frequencies which are the key parameters in identifying various winding deformations are uniquely altered due to different faults.
Description:
This paper presents the application of IEC 61850 protocol in electrical power engineering industry for data communication systems between substations. This IEC 61850 protocol presents new challenges for real-time communication performance between Intelligent Electronic Devices (IEDs) within substation because of the Generic Object Oriented Substation Event (GOOSE) messages. The analyses of substation Ethernet communication delay, its impact factors, various methods and different network topologies which can improve the real-time performance are discussed. For basic analysis of data flow within a substation, the Optimized Network Engineering Tool (OPNET) software is used. The process to bay level network simulation model is performed by using the OPNET software. The Ethernet delay performance of the process to bay level network simulation results are analyzed which is based on switched, shared Ethernet network or Peer to Peer network.
Description:
Generally, an industrial robot is named the Single-Function Robot (SFR) if it is only able to perform one task like material handling. However, a Multi-Function Robot (MFR) predominantly performs two tasks concurrently: material handling and a special operation. This type of recent robot with this ability can raise production rate. A robot equipped by a special kind of gripper namely Grip-Gage-Go is a real-life applications of MFRs. This gripper makes MFR competent to measure the diameter of the part in transit. These MFRs are widely employed in the inspection of automotive products including crankshaft, gears, and engine valves [1]
Description:
This paper introduces a new methodology to optimise the cycle time of dual-gripper robotic workcells. The workcell under study is composed of a group of m production machines. In order to produce a completed part, a chain of m-1 secondary operations are performed by m-1 different machines, and a hub machine is alternately visited for m primary operations. Indeed, parts must reenter the hub machine after any one of secondary operations. Those types of robotics workcells are used for high capacity production such as in photolithography manufacturing, These cells are cluster tools for semiconductor manufacturing where a wafer visits a processing stage several times for the atomic layer deposition (ALD) processes. For electroplating lines, these cells are also common in practice where there is a multifunction production stage that is visited by parts over once. This optimisation methodology is limited to the dual-gripper robotic cells, where identical parts are produced and these parts completely follow a similar sequence. The lower bound of cycle time for such dual-gripper robotic cells is obtained by finding the cycle time of all related robot move cycles, and subsequently optimal robot task sequence, which is a two-unit cycle, is determined.
Description:
Modern distribution networks are increasingly vulnerable to disturbances and improving the security of supply to customers are complex and challenging with the traditional approach. This paper presents a new approach to enhance the security of power supply in an active distribution network by integrating PHEV (Plug-in Hybrid Electric Vehicle) based micro grids on the basis of the nodal criticality. The nodal criticality is assessed by integrating operational uncertainties of events into samples of Monte Carlo simulation and classifying load interruptions on the basis of their magnitudes and frequencies. Criticality of the system stress that results nodal loads shedding is classified into arrays of clusters based on the magnitudes of interrupted loads at samples. The critical clusters that represent largest disturbances to the respective nodal loads are served with PHEV micro grids. Case studies are performed, and the results suggest that the security of distribution networks can be significantly improved with the proposed approach.
Description:
Distributed video coding (DVC) aims at achieving low-complexity encoding in contrast to the existing video coding standards' high complexity encoding. According to the Wyner-Ziv theorem this can be achieved, under certain conditions, by independent encoding of the frames while resorting to joint decoding. However, the performance of a Wyner-Ziv coding scheme significantly depends on its knowledge about the spatio-temporal correlation of the video. Unfortunately, correlation statistics in a video widely varies both along the spatial and temporal directions. Therefore, we argue that in a feedback free transform domain DVC scheme the decoder will fail to recover all the transform coefficients with a nonzero probability. Thus, we suggest to integrate a recovery method with the decoder that aims at recovering the undecoded coefficients by exploiting the spatio-temporal correlation of the video. Besides, we extend and modify a recovery scheme, recently proposed in the context of images, for DVC so that it exploits both spatial and temporal correlations in recovering the undecoded coefficients. The essential idea of this scheme is to formulate the recovery problem as a linear optimization problem which can be solved efficiently using linear programming. Our simulation results demonstrated that the proposed scheme can significantly improve the PSNR and visual quality of the erroneous video frames produced by a DVC decoder.
Description:
Designing a trustworthy voting system that uses electronic voting machines (EVMs) for efficiency and accuracy is a challenging task. It is difficult, if not impossible, to ensure the trustworthiness of EVMs that possess computation, storage, and communication capabilities. Thus an electronic voting system that does not assume trusted EVMs is clearly desirable. In this paper, we have proposed a k-anonymized electronic voting scheme that achieves this goal by assuming a hardware-controlled trusted random number generator external to the EVM. The proposed scheme relies on a k-anonymization technique to protect privacy and resort to joint de-anonymization of the votes for counting. Since the joint de-anonymization takes into account all the votes, it is difficult to manipulate an individual vote, even by the EVM, without being detected. Besides the anonymization technique, the proposed scheme relies on standard cryptographic hashing and the concept of floating receipt to provide end-to-end verifiability that prevents coercion or vote trading.
Description:
Kinesin nanomotor is a tiny vehicle that transports molecular cargoes within the cells. Many kinesin nanomotors can attach to a single cargo and coordinate their behaviors to transport the cargo. This behavioral coordination of kinesin nanomotors can be defined through a communicational language that kinesin nanomotors follow to transport the cargo. This paper proposes a computational language for kinesin nanomotor which is inspired by the nanomotor's natural behavior. In this technique, we have used behavioral Deterministic Finite Automaton (DFA) model of kinesin nanomotor which indicated internal intelligent and autonomous decision-making process of the nanomotor in response to its cell. In addition, the behavioral responses of kinesin nanomotor to its cell, behavioral DFA model of the nanomotor, were mapped to a computational regular language for the nanomotor. The proposed computational language for kinesin nanomotor was acceptable by the behavioral DFA model and also in good agreement with the natural behavior of the nanomotor. The development of such computational languages among intelligent and autonomous nanoparticles in nature paves the way for constructing potential bio-inspired nanorobotic systems as well as designing of some computational languages for their controlling.