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Electrostatic Field Calculations for Liquid Nitrogen Gaps Assuming A Decisive Field Factor
No full textVolume effect on breakdown voltage is well known in high voltage engineering. The breakdown voltage behavior of liquid nitrogen depending on a high field volume had been quantitatively described for gap lengths up to 20 mm. Breakdown curves for longer gap lengths up to 96 mm derived from measurements with a facility “Fatelini 2” show oscillations and partly low withstand voltages. Electrostatic field calculation for such long gaps shows remarkable high field volume differences between a model for ideal sphere and models including fixation rods. Calculation for the used setup does not show monotonically increasing high field volume depending on gap length but a maximum around 60 mm which can explain the special breakdown behavior in a “mid range” gap length. Further high field calculations were done for not yet used setups in order to make considerations, e.g. for the influence of cryostat material or diameter
The Impact of Different Missing Data Handling Methods on DINA Model
No full textIn this study, it was aimed to investigate the impact of different missing data handling methods on DINA model parameter estimation and classification accuracy. In the study, simulated data were used and the data were generated by manipulating the number of items and sample size. In the generated data, two different missing data mechanisms (missing completely at random and missing at random) were created according to three different amounts of missing data. The generated missing data was completed by using methods of treating missing data as incorrect, person mean imputation, two-way imputation, and expectation-maximization algorithm imputation. As a result, it was observed that both s and g parameter estimations and classification accuracies were effected from, missing data rates, missing data handling methods and missing data mechanisms
Force Multiplier Effect of Futuristic Battlefield Preparedness by Adapting the Internet of Things (IoT) Concept
No full textThe present-day Battlefield environment depicts a scenario wherein various heterogeneous warfighting vehicles/equipment are conglomerated, and the high command takes a decision based on the different inputs and data received from the warfighting entities. This aspect generates voluminous data and communication directives occupying the complete frequency spectrum and moving up and down. This paper proposes a scheme based on the Internet of Things (IoT) philosophy. The primary focus will be to deploy ubiquitous sensing enabled technologies (IoT) in all the battlefield fighting entities. This medium in effect means the interconnection of uniquely identifiable embedded computing-like devices and formulation of an internet infrastructure. The newly proposed IoT devices in all the battlefield fighting entities will gather, infer and understand in-situ commands and data and in turn pass on to the highest decision-making authority. A simple IoT based model will be deployed in the battlefield scenario enhancing the force multiplier effect
Fusion of Random Projection, Multi-Resolution Features and Distance Weighted K Nearest Neighbor for Masses Detection in Mammographic Images
No full textBreast cancer is the top cancer in women both in the developed and the developing world. For early detection of the disease, mammography is still the most effective method beside ultrasound and magnetic resonance imaging. Computer Aided Detection systems have been developed to aid radiologists in diagnosing breast cancer. Different methods were proposed to overcome the main drawback of producing large number of False Positives. In this paper, we presented a novel method for masses detection in mammograms. To describe masses, multi-resolution features were utilized. In feature extraction step, we calculated multi-resolution Block Difference Inverse Probability features and multi-resolution statistical features. Once the descriptors were extracted, we deployed random projection and distance weighted K Nearest Neighbor to classify the detected masses. The result is quite sanguine with sensitivity, false positive reduction and time for carrying out the algorith
A Novel M-SEPIC DC-DC Converter for BLDC Pumping System with Active PFC using ANFIS Controller
No full textAn exigent consumer related concerns confronted due to utilization of massive front-end AC-DC rectifier in a grid-tied BLDC pumping system. Harmonic distortions are acquired, which prompts the disruption of power quality at utility grid system due to AC-DC conversion. Several factors for enhancing power-quality concerns are ameliorate the grid power-factor along with reduction of harmonic distortions, tightened regulation of DC output voltage. In this way, the DC-DC boost converter plays a unique role; operated in Continuous Conduction Mode. Based on summarizing advantages & disadvantages of classical DC-DC converters, a single switch high voltage gain M-SEPIC DC-DC converter is more suggestive for water pumping system due to non-existence of coupled inductors, low switching loss, low di/dt stress, high efficiency, compact structure, low cost, etc. This work proposes the novel M-SEPIC DC-DC converter fed brushless-DC motor drive is controlled by voltage source inverter and powered by single-phase grid system with improved power-quality features. Moreover, Adaptive Neuro-Fuzzy Inference System is recommended for prediction of optimal switching states to amplify the BLDC motor speed and torque-ripple depreciation. The effectiveness of the proposed scheme is validated under constant speed situations by real-time operating conditions which are evaluated by Matlab /Simulink tool; and simulation results are conferred with attractive comparisons
Preliminary Study of a New Topology Permanent Magnet Flux Switching Motor for Electric Buses
No full textElectric buses (EBs) as public transit that have been introduced in modern countries recently are an alternative effort to reduce climate change and environmental impacts of fossil fuels. One example of the successfully developed motor for EBs is interior permanent magnet synchronous motor (IPMSM) with merits of heat dissipating, high torque per frame size and reliability influence by absence of brushes. However, the three-phase armature windings are wounded in the form of distributed windings, results in much copper loss, high coil end length and reduced the efficiency. The embedded rectangular magnets inside the rotor make rotor less robust, increased rotor weight and reduced the torque and power density. The present IPMSM has a complex structure which is relatively difficult to manufacture and tough in optimization process. The 7.0 kg volume of PM used in IPMSM is very high, which increases the cost of the machine. Therefore, a new topology of permanent magnet flux switching motor using wedge-shaped PM and single stator structure with the advantages of simple stator design, robust rotor structure, high of torque and power, and high efficiency is proposed. The design, flux linkage, back-emf, cogging torque, average torque, speed, and power of this new topology are investigated by JMAG-Designer version 14.1 via a 2D-FEA. The initial design of proposed motor produces torque and power of 905.9 Nm and 57.75 kW, respectively
K-Means Clustering and Genetic Algorithm to Solve Vehicle Routing Problem with Time Windows Problem
No full textDistribution is an important aspect of industrial activity to serve customers on time with minimal operational cost. Therefore, it is necessary to design a quick and accurate distribution route. One of them can be design travel distribution route using the k-means method and genetic algorithms. This research will combine k-means method and genetic algorithm to solve VRPTW problem. K-means can do clustering properly and genetic algorithms can optimize the route. The proposed genetic algorithm employs initialize chromosome from the result of k-means and using replacement method of selection. Based on the comparison between genetic algorithm and hybrid k-means genetic algorithm proves that k-means genetic algorithm is a suitable combination method with relative low computation time, are the comparison between 2700 and 3900 seconds
Evaluation of Color Models for Palm Oil Fresh Fruit Bunch Ripeness Classification
No full textThis paper investigates the application of eight color models for automatic palm oil Fresh Fruit Bunch (FFB) ripeness classification with multi-class Support Vector Machine (SVM). Ripeness classification is important during harvesting to ensure that they are harvested during the correct ripe stage for optimum oil production. Since color is a significant indicator for agriculturists to determine the ripeness of FFB, it is critical to determine the right color model. Eight color models have been investigated namely, HSV, I1I2I3, LAB, XYZ, YCbCr, YIQ, YUV and RGB. Color moments were extracted from each of these color models for the classification of four stages of FFB ripeness that are unripe, under-ripe, ripe and over-ripe. A database of five hundred images of palm oil FFB has been constructed and experiments showed that YCbCr and YUV outperform the other color models
Enhancing Similarity Distances Using Mandatory and Optional for Early Fault Detection
No full textSoftware Product Line (SPL) describes procedures, techniques, and tools in software engineering by using a common method of production for producing a group of software systems that identical from a shared set of software assets. In SPL, the similarity-based prioritization can resemble combinatorial interaction testing in scalable and efficient way by choosing and prioritize configurations that most dissimilar. However, the similarity distances in SPL still not so much cover the basic detail of feature models which are the notations. Plus, the configurations always have been prioritized based on domain knowledge but not much attention has been paid to feature model notations. In this paper, we proposed the usage of mandatory and optional notations for similarity distances. The objective is to improve the average percentage of faults detected (APFD). We investigate four different distances and make modifications on the distances to increase APFD value. These modifications are the inclusion of mandatory and optional notations with the similarity distances. The results are the APFD values for all the similarity distances including the original and modified similarity distances. Overall, the results shown that by subtracting the optional notation value can increase the APFD by 3.71% from the original similarity distance
A Real Time Condition Monitoring System for Gears Operating under Variable Load Conditions
No full textGears are important component of the rotational power transmission system and are largely used in variable load and speed applications. The faults on the gear generate excessive vibration which leads to breakdown of the machine. Sensor based methods could diagnose gear faults but proved to be expensive and have limited applications due to heavy cost and need of access of gear box for sensor installation. The motor stator current analysis has been reported to overcome the drawbacks of the sensor based fault detection methods. However, motor stator current analysis has a limited capability for reliable detection of small gear fault signatures typically for low load conditions. This paper presents an alternative non-invasive approach based on instantaneous power analysis of the motor to reliably diagnose gear faults for variable load applications. The theoretical and experimental results indicates that the instantaneous power analysis offers three fault related harmonics and amplitude variations on these harmonics could give the indication of health status of the gear. The superiority of the proposed instantaneous power analysis technique has been confirmed through experiments performed on three operating points of the motor. The comparison of the amplitude sensitivity of the motor stator current and instantaneous power at three operating points has been performed to validate the superiority of the proposed technique