Search results for: rotor position estimation

Authors: Stefanos Karanasios, Charkleia Koutri, Maria Moutzouri, Sofia A. Xergia, Vasiliki Sakellari, George Gioftsos

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The precise calculation of arterial occlusive pressure (AOP) is a critical step to accurately prescribe individualized pressures during blood flow restriction training (BFRT). AOP is usually measured in a supine position before training; however, previous reports suggested a significant influence in lower limb AOP across different body positions. The aim of the study was to investigate the effect of three different body positions on upper limb AOP and the reliability of the method for its standardization in clinical practice. Forty-two healthy participants (Mean age: 28.1, SD: ±7.7) underwent measurements of upper limb AOP in supine, seated, and standing positions by three blinded raters. A cuff with a manual pump and a pocket doppler ultrasound were used. A significantly higher upper limb AOP was found in seated compared with supine position (p < 0.031) and in supine compared with standing position (p < 0.031) by all raters. An excellent intraclass correlation coefficient (0.858- 0.984, p < 0.001) was found in all positions. Upper limb AOP is strongly dependent on body position changes. The appropriate measurement position should be selected to accurately calculate AOP before BFRT. The excellent inter-rater reliability and repeatability of the method suggest reliable and consistent results across repeated measurements.

Keywords: Kaatsu training, blood flow restriction training, arterial occlusion, reliability

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Authors: Fariza Yunus, Jasmee Jaafar, Zamalia Mahmud, Nurul Nisa’ Khairul Azmi, Nursalleh K. Chang, Nursalleh K. Chang

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Variation of air temperature from one place to another is cause by air temperature controls. In general, the most important control of air temperature is elevation. Another significant independent variable in estimating air temperature is the location of meteorological stations. Distances to coastline and land use type are also contributed to significant variations in the air temperature. On the other hand, in homogeneous terrain direct interpolation of discrete points of air temperature work well to estimate air temperature values in un-sampled area. In this process the estimation is solely based on discrete points of air temperature. However, this study presents that air temperature controls also play significant roles in estimating air temperature over homogenous terrain of Peninsular Malaysia. An Inverse Distance Weighting (IDW) interpolation technique was adopted to generate continuous data of air temperature. This study compared two different datasets, observed mean monthly data of T, and estimation error of T–T’, where T’ estimated value from a multiple regression model. The multiple regression model considered eight independent variables of elevation, latitude, longitude, coastline, and four land use types of water bodies, forest, agriculture and build up areas, to represent the role of air temperature controls. Cross validation analysis was conducted to review accuracy of the estimation values. Final results show, estimation values of T–T’ produced lower errors for mean monthly mean air temperature over homogeneous terrain in Peninsular Malaysia.

Keywords: air temperature control, interpolation analysis, peninsular Malaysia, regression model, air temperature

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Authors: Khalil H. Al-Bayati, Khalid Omar Al-Baiti

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The energy expectation value for Li-like ions systems (Li, Be+ and Be2+) hasbeen calculated and examined within the ground state (1s2sα)^2 S and the excited state (1s3sα)^2 S in position space. The partitioning technique of Hartree-Fock (H-F) has been used for existing wavefnctions.

Keywords: energy expectation value, atomic systems, ground and excited states, Hartree-Fock approximation

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Authors: Ladan Maijama’a, Jibril D. Jiya, Ejike C. Anene

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This paper presents Differential Evolution Algorithm (DEA) based Variable Structure Position Control (VSPC) of Laboratory DC servomotor (LDCSM). DEA is employed for the optimal tuning of Variable Structure Control (VSC) parameters for position control of a DC servomotor. The VSC combines the techniques of Sliding Mode Control (SMC) that gives the advantages of small overshoot, improved step response characteristics, faster dynamic response and adaptability to plant parameter variations, suppressed influences of disturbances and uncertainties in system behavior. The results of the simulation responses of the VSC parameters adjustment by DEA were performed in Matlab Version 2010a platform and yield better dynamic performance compared with the untuned VSC designed.

Keywords: differential evolution algorithm, laboratory DC servomotor, sliding mode control, variable structure control

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Authors: Duy Nhat Tran, Van Tien Pham, Quang Trung Trinh, Tien Hai Tran, Van Cong Bui

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In recent years, artificial intelligence and the Internet of Things have experienced significant advancements. Collecting image data and real-time analysis and processing of tasks have become increasingly popular in various aspects of life. Optical scanning devices are widely used to observe and analyze different environments, whether fixed outdoors, mounted on mobile devices, or used in unmanned aerial vehicles. As a result, the interaction between the physical environment and these devices has become more critical in terms of safety. Two commonly used methods for addressing these challenges are active and passive approaches. Each method has its advantages and disadvantages, but combining both methods can lead to higher efficiency. One solution is to utilize direct-drive motors for position control and real-time feedback within the operational range to determine appropriate control parameters with high precision. If the maximum motor torque is smaller than the inertial torque and the rotor reaches the operational limit, the spring system absorbs the impact force. Numerous experiments have been conducted to demonstrate the effectiveness of device protection during operation.

Keywords: optical device, collision safety, collision absorption, precise mechanics

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Authors: Muhammad Nouman Qureshi, Muhammad Hanif

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Adaptive cluster sampling (ACS) is specifically developed for the estimation of highly clumped populations and applied to a wide range of situations like animals of rare and endangered species, uneven minerals, HIV patients and drug users. In this paper, we proposed a generalized semi-exponential estimator with two auxiliary variables under the framework of ACS design. The expressions of approximate bias and mean square error (MSE) of the proposed estimator are derived. Theoretical comparisons of the proposed estimator have been made with existing estimators. A numerical study is conducted on real and artificial populations to demonstrate and compare the efficiencies of the proposed estimator. The results indicate that the proposed generalized semi-exponential estimator performed considerably better than all the adaptive and non-adaptive estimators considered in this paper.

Keywords: auxiliary information, adaptive cluster sampling, clustered populations, Hansen-Hurwitz estimation

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Authors: Linhang Zhu, Hongyu Zhu, Jiahe Liu

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This paper investigated a method of indoor real-time positioning and mapping based on the Manhattan world assumption. In indoor environments, relying solely on feature matching techniques or other geometric algorithms for sensor pose estimation inevitably resulted in cumulative errors, posing a significant challenge to indoor positioning. To address this issue, we adopt the Manhattan world hypothesis to optimize the camera pose algorithm based on feature matching, which improves the accuracy of camera pose estimation. A special processing method was applied to image data frames that conformed to the Manhattan world assumption. When similar data frames appeared subsequently, this could be used to eliminate drift in sensor pose estimation, thereby reducing cumulative errors in estimation and optimizing mapping and positioning. Through experimental verification, it is found that our method achieves high-precision real-time positioning in indoor environments and successfully generates maps of indoor environments. This provides effective technical support for applications such as indoor navigation and robot control.

Keywords: Manhattan world hypothesis, real-time positioning and mapping, feature matching, loopback detection

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Authors: Akinola Ikudayisi, Josiah Adeyemo

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The correct estimation of reference evapotranspiration (ETₒ) is required for effective irrigation water resources planning and management. However, there are some variables that must be considered while estimating and modeling ETₒ. This study therefore determines the multivariate analysis of correlated variables involved in the estimation and modeling of ETₒ at Vaalharts irrigation scheme (VIS) in South Africa using Principal Component Analysis (PCA) technique. Weather and meteorological data between 1994 and 2014 were obtained both from South African Weather Service (SAWS) and Agricultural Research Council (ARC) in South Africa for this study. Average monthly data of minimum and maximum temperature (°C), rainfall (mm), relative humidity (%), and wind speed (m/s) were the inputs to the PCA-based model, while ETₒ is the output. PCA technique was adopted to extract the most important information from the dataset and also to analyze the relationship between the five variables and ETₒ. This is to determine the most significant variables affecting ETₒ estimation at VIS. From the model performances, two principal components with a variance of 82.7% were retained after the eigenvector extraction. The results of the two principal components were compared and the model output shows that minimum temperature, maximum temperature and windspeed are the most important variables in ETₒ estimation and modeling at VIS. In order words, ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity are less important and cannot be used to provide enough information about ETₒ estimation at VIS. The outcome of this study has helped to reduce input variable dimensionality from five to the three most significant variables in ETₒ modelling at VIS, South Africa.

Keywords: irrigation, principal component analysis, reference evapotranspiration, Vaalharts

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Authors: Andrew Tan Hwee Chye, Yeo Zhen Ning

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This study aims to meta-analyse clinical studies comparing femoral tunnel position (FTP), femoral tunnel length (FTL) and graft bending angle (GBA) of single-bundle Anterior Cruciate Ligament (ACL) reconstruction using Transtibial (TT), Anteromedial (AM) and Outside-in (OI) techniques. A meta-analysis comparing the FTP, FTL and GBA of single-bundle ACL reconstruction utilising the TT, AM and OI was performed. Prospective Comparative Studies (PCS) and Retrospective Comparative Studies (RCS) from PubMed, Cochrane Library, and Embase were included. A total of 17 studies were included in this study. TT had the longest FTL, when compared to AM (Mean difference = 7.38, 95% CI: 3.76 to 11.00, P < 0.001) and OI (Mean difference = 9.47, 95% CI: 4.89 to 14.05, P < 0.001). In the deep-to-shallow direction, the OI resulted in a significantly deeper femoral tunnel as compared to the TT (Mean difference = 4.36, 95% CI: 1.39 to 7.33, P = 0.004) (Figure 6B). The AM technique also contributed to a significantly lower tunnel position as compared to the OI technique (Mean difference = 2.34, 95% CI: 0.76 to 3.92, P = 0.004). There were no significant differences in the graft bending angle between TT, AM and OI techniques. AM and OI techniques provide a more anatomical position as compared to the TT. Although FTL in the TT is longer than the AM and OI, all three techniques exceed the critical length of 25mm. There are no differences in the GBA between the three techniques.

Keywords: femoral tunnel position, femoral tunnel length, anterior cruciate ligament, transtibial, graft bending angle, anteromedial, outside-in

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Authors: Lokesh Varshney, R. K. Saket

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This paper presents reliability indices evaluation of the rotor core magnetization of the induction motor operated as a self-excited induction generator by using probability distribution approach and Monte Carlo simulation. Parallel capacitors with calculated minimum capacitive value across the terminals of the induction motor operating as a SEIG with unregulated shaft speed have been connected during the experimental study. A three phase, 4 poles, 50Hz, 5.5 hp, 12.3A, 230V induction motor coupled with DC Shunt Motor was tested in the electrical machine laboratory with variable reactive loads. Based on this experimental study, it is possible to choose a reliable induction machine operating as a SEIG for unregulated renewable energy application in remote area or where grid is not available. Failure density function, cumulative failure distribution function, survivor function, hazard model, probability of success and probability of failure for reliability evaluation of the three phase induction motor operating as a SEIG have been presented graphically in this paper.

Keywords: residual magnetism, magnetization curve, induction motor, self excited induction generator, probability distribution, Monte Carlo simulation

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Authors: Andi Intan Purnamasari, Supriyadi, Sulbadana, Aminuddin Kasim

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Law functions as social control. Providing arrangements not only for legal certainty, but also in the scope of justice and expediency. The three values ​​achieved by law essentially function to bring comfort to each individual in carrying out daily activities. However, it is undeniable that global conditions have changed the orientation of people's lifestyles. Some people want to ensure their existence in the digital world which is popularly known as the metaverse. Some countries even project their city to be a metaverse city. The order of life is no longer limited to the real space, but also to the cyber world. Not infrequently, legal events that occur in the cyber world also force the law to position its position and even prevent crime in cyberspace. Through this research, conceptually it provides a view of the legal position in crime prevention in the Metaverse world. when the law acts to regulate the situation in the virtual world, of course some people will feel disturbed, this is due to the thought that the virtual world is a world in which an avatar can do things that cannot be done in the real world, or can be called a world without boundaries. Therefore, when the law is present to provide boundaries, of course the concept of the virtual world itself becomes no longer a cyber world that is not limited by space and time, it becomes a new order of life. approach, approach, approach, approach, and approach will certainly be the method used in this research.

Keywords: crime, cyber, metaverse, law

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Authors: Maoxin Ye

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This study examines the relationship between social network sites (SNS) usage and social capital. Because SNS usage can expand the users’ networks, and people who are connected in this networks may become resources to SNS users and lead them to advantage in some situation, it is important to estimate the relationship between SNS usage and ‘who’ is connected or what resources the SNS users can get. Additionally, ‘who’ can be divided in two aspects – people who possess high position and people who are different, hence, it is important to estimate the relationship between SNS usage and high position people and different people. This study adapts Lin’s definition of social capital and the measurement of position generator which tells us who was connected, and can be divided into the same two aspects as well. A national data of America (N = 2,255) collected by Pew Research Center is utilized to do a general regression analysis about SNS usage and social capital. The results indicate that SNS usage is negatively associated with each factor of social capital, and it suggests that, in fact, comparing with non-users, although SNS users can get more connections, the variety and resources of these connections are fewer. For this reason, we could lose benefits through SNS usage.

Keywords: social network sites, social capital, position generator, general regression

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Authors: Sandro Bartolini, Alessandro Mecocci, Alessio Medaglini

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The growing popularity of systems based on unmanned aerial vehicles (UAVs) is highlighting their vulnerability, particularly in relation to the positioning system used. Typically, UAV architectures use the civilian GPS, which is exposed to a number of different attacks, such as jamming or spoofing. This is why it is important to develop alternative methodologies to accurately estimate the actual UAV position without relying on GPS measurements only. In this paper, we propose a position estimate method for UAVs based on monocular visual odometry. We have developed a flight control system capable of keeping track of the entire trajectory travelled, with a reduced dependency on the availability of GPS signals. Moreover, the simplicity of the developed solution makes it applicable to a wide range of commercial drones. The final goal is to allow for safer flights in all conditions, even under cyber-attacks trying to deceive the drone.

Keywords: visual odometry, autonomous uav, position measurement, autonomous outdoor flight

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Authors: Mohammad Borhani, Afshin Danehkar

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With the increase in population and the upward trend of energy demand, mankind has thought of using suppliers that guarantee a stable supply of energy, unlike fossil fuels, which, in addition to the widespread emission of greenhouse gases that one of the main factors in the destruction of the ozone layer and it will be finished in a short time in the not-so-distant future. In this regard, one of the sustainable ways of energy supply is the use of wind converters. That convert wind energy into electricity. For this reason, this research focused on wind turbines and their installation conditions. The main classification of wind turbines is based on the axis of rotation, which is divided into two groups: horizontal axis and vertical axis; each of these two types, with the advancement of technology in man-made environments such as cities, villages, airports, and other human environments can be installed and operated. The main difference between offshore and onshore wind turbines is their installation and foundation. Which are usually divided into five types; including of Monopile Wind Turbines, Jacket Wind Turbines, Tripile Wind Turbines, Gravity-Based Wind Turbines, and Floating Offshore Wind Turbines. For installation in a wind power plant requires an arrangement that produces electric power, the distance between the turbines is usually between 5 or 7 times the diameter of the rotor and if perpendicular to the wind direction be If they are 3 to 5 times the diameter of the rotor, they will be more efficient.

Keywords: wind farms, Savonius, Darrieus, offshore wind turbine, renewable energy

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Authors: Krzysztof Skiba, Zdzislaw Kaminski

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Wind power is based on a variety of construction solutions to convert wind energy into electrical energy. These constructions are constrained by the correlation between their energy conversion efficiency and the area they occupy. Their energy conversion efficiency can be improved by wind tunnel tests of a rotor as a diffuser to optimize shapes of aerodynamic elements, to adapt these elements to changing conditions and to increase airflow intensity. This paper discusses the results of computer simulations and aerodynamic analyzes of this innovative diffuser design. The research aims at determining the aerodynamic phenomena triggered by the airflow inside this construction, and developing a design to improve the efficiency of the wind turbine. The research results enable us to design a diffuser with a double Venturi nozzle and specially shaped blades. The design of this type uses Bernoulli’s law on the behavior of the flowing medium in the tunnel of a decreasing diameter. The air flowing along the tunnel changes its velocity so the rotor inside such a decreased tunnel diameter rotates faster in this airflow than does the wind outside this tunnel, which makes the turbine more efficient. Additionally, airflow velocity is improved by applying aerodynamic rings with extended trailing edges to achieve controlled turbulent vortices.

Keywords: wind turbine, renewable energy, cfd, numerical analysis

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Authors: Abderrahmane El Kachani, El Mahjoub Chakir, Anass Ait Laachir, Abdelhamid Niaaniaa, Jamal Zerouaoui, Tarik Jarou

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This paper presents a wind turbine based on the doubly fed induction generator (DFIG) connected to the utility grid through a shunt active power filter (SAPF). The whole system is controlled by a double nonlinear predictive controller (DNPC). A Taylor series expansion is used to predict the outputs of the system. The control law is calculated by optimization of the cost function. The first nonlinear predictive controller (NPC) is designed to ensure the high performance tracking of the rotor speed and regulate the rotor current of the DFIG, while the second one is designed to control the SAPF in order to compensate the harmonic produces by the three-phase diode bridge supplied by a passive circuit (rd, Ld). As a result, we obtain sinusoidal waveforms of the stator voltage and stator current. The proposed nonlinear predictive controllers (NPCs) are validated via simulation on a 1.5 MW DFIG-based wind turbine connected to an SAPF. The results obtained appear to be satisfactory and promising.

Keywords: wind power, doubly fed induction generator, shunt active power filter, double nonlinear predictive controller

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Authors: Ramy H. Mohammed

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In heat sinks, the flow within the core exhibits separation and hence does not lend itself to simple analytical boundary layer or duct flow analysis of the wall friction. In this paper, I present some findings from an experimental and numerical study aimed to obtain physical insight into the influence of the presence of the shield and its position on the hydraulic and thermal performance of square pin fin heat sink without top by-pass. The variations of the Nusselt number and friction factor are obtained under varied parameters, such as the Reynolds number and the shield position. The numerical code is validated by comparing the numerical results with the available experimental data. It is shown that, there is a good agreement between the temperature predictions based on the model and the experimental data. Results show that, as the presence of the shield, the heat transfer of fin array is enhanced and the flow resistance increased. The surface temperature distribution of the heat sink base is more uniform when the dimensionless shield position equals to 1/3 or 2/3. The comprehensive performance evaluation approach based on identical pumping power criteria is adopted and shows that the optimum shield position is at x/l=0.43 where energy is saved.

Keywords: shield, fin array, performance evaluation, heat transfer, energy

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Authors: H. Bakhshi, E. Khayyamian

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Cognitive radios have been recognized as one of the most promising technologies dealing with the scarcity of the radio spectrum. In cognitive radio systems, secondary users are allowed to utilize the frequency bands of primary users when the bands are idle. Hence, how to accurately detect the idle frequency bands has attracted many researchers’ interest. Detection performance is sensitive toward noise power and gain fluctuation. Since signal to noise ratio (SNR) between primary user and secondary users are not the same and change over the time, SNR and noise power estimation is essential. In this paper, we present a cooperative spectrum sensing algorithm using SNR estimation to improve detection performance in the real situation.

Keywords: cognitive radio, cooperative spectrum sensing, energy detection, SNR estimation, spectrum sensing, rayleigh fading channel

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Authors: Tigist Girma Kedane

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The purpose of the current research work is to measure the physical properties of bamboo species in Ethiopia on the impact of age, harvesting seasons and culm height. Three representatives of bamboo plants are harvested in three groups of ages, 2 harvesting months, and 3 regions of Ethiopia. Research has not been done on the physical properties of bamboo species in Ethiopia so far. Moisture content and shrinkage of bamboo culm increase when the culm ages younger and moves from top to bottom position. The harvesting month of November has a higher moisture content and shrinkage compared to February. One year old of Injibara, Kombolcha, and Mekaneselam bamboo culm has 40%, 30%, and 33% higher moisture content, 29%, 24%, and 28% higher radial shrinkage, 32%, 37%, and 32% higher tangential shrinkage compared to 3 years old respectively. The bottom position of Injibara, Kombolcha, and Mekaneselam in November have 45%, 28%, and 25% higher moisture content, 41%, 29%, and 34% radial shrinkage, 29%, 28%, and 42% tangential shrinkage than the top position, respectively. The basic density increases as the age of the bamboo becomes older and moves from the bottom to the top position. November has the lowest basic density compared to February. 3 years old of Injibara, Kombolcha, and Mekaneselam at the age of 3 years have 32%, 50%, and 24% higher basic density compared to 1 year, whereas the top position has 35%, 26%, and 22% higher than the bottom position in February, respectively. The current research proposed that 3 years and February are suited for structural purposes and furniture making, but 1 year and November are suited for fiber extraction in the composite industry. The existence of water in the culm improves an easy extraction of the fibers without damage from the culm.

Keywords: bamboo age, bamboo height, harvesting seasons, physical properties

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Authors: Raghunath Arnab

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The two-phase sampling which is also known as double sampling was introduced in 1938. In two-phase sampling, samples are selected in phases. In the first phase, a relatively large sample of size is selected by some suitable sampling design and only information on the auxiliary variable is collected. During the second phase, a sample of size is selected either from, the sample selected in the first phase or from the entire population by using a suitable sampling design and information regarding the study and auxiliary variable is collected. Evidently, two phase sampling is useful if the auxiliary information is relatively easy and cheaper to collect than the study variable as well as if the strength of the relationship between the variables and is high. If the sample is selected in more than two phases, the resulting sampling design is called a multi-phase sampling. In this article we will consider how one can use data collected at the first phase sampling at the stages of estimation of the parameter, stratification, selection of sample and their combinations in the second phase in a unified setup applicable to any sampling design and wider classes of estimators. The problem of the estimation of variance will also be considered. The variance of estimator is essential for estimating precision of the survey estimates, calculation of confidence intervals, determination of the optimal sample sizes and for testing of hypotheses amongst others. Although, the variance is a non-negative quantity but its estimators may not be non-negative. If the estimator of variance is negative, then it cannot be used for estimation of confidence intervals, testing of hypothesis or measure of sampling error. The non-negativity properties of the variance estimators will also be studied in details.

Keywords: auxiliary information, two-phase sampling, varying probability sampling, unbiased estimators

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Authors: Longxiang Guo, Haoyan Hao, Xueli Sheng, Hanjun Yu, Jingwei Yin

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In order to prevent target splitting and ensure the accuracy of fusion, system error registration is an important step in multi-static sonar fusion detection system. To eliminate the inherent system errors including distance error and angle error of each sonar in detection, this paper uses offline estimation method for error registration. Suppose several sonars from different platforms work together to detect a target. The target position detected by each sonar is based on each sonar’s own reference coordinate system. Based on the two-dimensional stereo projection method, this paper uses real-time quality control (RTQC) method and least squares (LS) method to estimate sensor biases. The RTQC method takes the average value of each sonar’s data as the observation value and the LS method makes the least square processing of each sonar’s data to get the observation value. In the underwater acoustic environment, matlab simulation is carried out and the simulation results show that both algorithms can estimate the distance and angle error of sonar system. The performance of the two algorithms is also compared through the root mean square error and the influence of measurement noise on registration accuracy is explored by simulation. The system error convergence of RTQC method is rapid, but the distribution of targets has a serious impact on its performance. LS method can not be affected by target distribution, but the increase of random noise will slow down the convergence rate. LS method is an improvement of RTQC method, which is widely used in two-dimensional registration. The improved method can be used for underwater multi-target detection registration.

Keywords: data fusion, multi-static sonar detection, offline estimation, sensor registration problem

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Authors: Jeronimo Cox, Tomonari Furukawa

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Magnetometers have become more popular in inertial measurement units (IMU) for their ability to correct estimations using the earth's magnetic field. Accelerometer and gyroscope-based packages fail with dead-reckoning errors accumulated over time. Localization in robotic applications with magnetometer-inclusive IMUs has become popular as a way to track the odometry of slower-speed robots. With high-speed motions, the accumulated error increases over smaller periods of time, making them difficult to track with IMU. Tracking a high-speed motion is especially difficult with limited observability. Visual obstruction of motion leaves motion-tracking cameras unusable. When motions are too dynamic for estimation techniques reliant on the observability of the gravity vector, the use of magnetometers is further justified. As available magnetometer calibration methods are limited with the assumption that background magnetic fields are uniform, estimation in nonuniform magnetic fields is problematic. Hard iron distortion is a distortion of the magnetic field by other objects that produce magnetic fields. This kind of distortion is often observed as the offset from the origin of the center of data points when a magnetometer is rotated. The magnitude of hard iron distortion is dependent on proximity to distortion sources. Soft iron distortion is more related to the scaling of the axes of magnetometer sensors. Hard iron distortion is more of a contributor to the error of attitude estimation with magnetometers. Indoor environments or spaces inside ferrite-based structures, such as building reinforcements or a vehicle, often cause distortions with proximity. As positions correlate to areas of distortion, methods of magnetometer localization include the production of spatial mapping of magnetic field and collection of distortion signatures to better aid location tracking. The goal of this paper is to compare magnetometer methods that don't need pre-productions of magnetic field maps. Mapping the magnetic field in some spaces can be costly and inefficient. Dynamic measurement fusion is used to track the motion of a multi-link system with us. Conventional calibration by data collection of rotation at a static point, real-time estimation of calibration parameters each time step, and using two magnetometers for determining local hard iron distortion are compared to confirm the robustness and accuracy of each technique. With opposite-facing magnetometers, hard iron distortion can be accounted for regardless of position, Rather than assuming that hard iron distortion is constant regardless of positional change. The motion measured is a repeatable planar motion of a two-link system connected by revolute joints. The links are translated on a moving base to impulse rotation of the links. Equipping the joints with absolute encoders and recording the motion with cameras to enable ground truth comparison to each of the magnetometer methods. While the two-magnetometer method accounts for local hard iron distortion, the method fails where the magnetic field direction in space is inconsistent.

Keywords: motion tracking, sensor fusion, magnetometer, state estimation

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Authors: Kyoung-Jin Joo, In-Gun Kim, Hyun-Seok Hong, Dong-Woo Kang, Ju Lee

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Recently, the permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) that can be substituted for the induction motor has been studying because of the needs of the development of the premium high efficiency motor for the minimum energy performance standard (MEPS). PMa-SynRM is required to the speed and position information for motor speed and torque controls. However, to apply the sensors has many problems that are sensor mounting space shortage and additional cost, etc. Therefore, in this paper, speed-sensorless control based on model reference adaptive system (MRAS) is introduced to eliminate the sensor. The sensorless method is constructed in a reference model as standard and an adaptive model as the state observer. The proposed algorithm is verified by the simulation.

Keywords: PMa-SynRM, sensorless control, robust estimation, MRAS method

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Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

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In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

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Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

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The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

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Authors: Abdel-Aziz M. Mohamed

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This research proposes a methodology to estimate the customer order lead time in the supply chain based on the process capability index. The cases when the process output is normally distributed and when it is not are considered. The relationships between the system capability indices in both service and manufacturing applications, delivery system reliability and the percentages of orders delivered after their promised due dates are presented. The proposed method can be used to examine the current process capability to deliver the orders before the promised lead-time. If the system was found to be incapable, the method can be used to help revise the current lead-time to a proper value according to the service reliability level selected by the management. Numerical examples and a case study describing the lead time estimation methodology and testing the system capability of delivering the orders before their promised due date are illustrated.

Keywords: lead-time estimation, process capability index, delivery system reliability, statistical analysis, service achievement index, service quality

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

Abstract:

In biomedical researches and randomized clinical trials, the most commonly interested outcomes are time-to-event so-called survival data. The importance of robust models in this context is to compare the effect of randomly controlled experimental groups that have a sense of causality. Causal estimation is the scientific concept of comparing the pragmatic effect of treatments conditional to the given covariates rather than assessing the simple association of response and predictors. Hence, the causal effect based semiparametric transformation model was proposed to estimate the effect of treatment with the presence of possibly time-varying covariates. Due to its high flexibility and robustness, the semiparametric transformation model which shall be applied in this paper has been given much more attention for estimation of a causal effect in modeling left-truncated and right censored survival data. Despite its wide applications and popularity in estimating unknown parameters, the maximum likelihood estimation technique is quite complex and burdensome in estimating unknown parameters and unspecified transformation function in the presence of possibly time-varying covariates. Thus, to ease the complexity we proposed the modified estimating equations. After intuitive estimation procedures, the consistency and asymptotic properties of the estimators were derived and the characteristics of the estimators in the finite sample performance of the proposed model were illustrated via simulation studies and Stanford heart transplant real data example. To sum up the study, the bias of covariates was adjusted via estimating the density function for truncation variable which was also incorporated in the model as a covariate in order to relax the independence assumption of failure time and truncation time. Moreover, the expectation-maximization (EM) algorithm was described for the estimation of iterative unknown parameters and unspecified transformation function. In addition, the causal effect was derived by the ratio of the cumulative hazard function of active and passive experiments after adjusting for bias raised in the model due to the truncation variable.

Keywords: causal estimation, EM algorithm, semiparametric transformation models, time-to-event outcomes, time-varying covariate

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Authors: Farzaneh Khorram

Abstract:

This paper endeavors to construct a block model to assess grinding energy consumption (CCE) and pinpoint blocks with the highest potential for energy usage during the grinding process within a specified region. Leveraging geostatistical techniques, particularly joint estimation, or simulation, based on geometallurgical data from various mineral processing stages, our objective is to forecast CCE across the study area. The dataset encompasses variables obtained from 2754 drill samples and a block model comprising 4680 blocks. The initial analysis encompassed exploratory data examination, variography, multivariate analysis, and the delineation of geological and structural units. Subsequent analysis involved the assessment of contacts between these units and the estimation of CCE via cokriging, considering its correlation with SPI. The selection of blocks exhibiting maximum CCE holds paramount importance for cost estimation, production planning, and risk mitigation. The study conducted exploratory data analysis on lithology, rock type, and failure variables, revealing seamless boundaries between geometallurgical units. Simulation methods, such as Plurigaussian and Turning band, demonstrated more realistic outcomes compared to cokriging, owing to the inherent characteristics of geometallurgical data and the limitations of kriging methods.

Keywords: geometallurgy, multivariate analysis, plurigaussian, turning band method, cokriging

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Authors: Shih-Pin Chen, Shih-Syuan You

Abstract:

This study proposes a regression model with flexible spreads for fuzzy input-output data to cope with the situation that the existing measures cannot reflect the actual estimation error. The main idea is that a dissemblance index (DI) is carefully identified and defined for precisely measuring the actual estimation error. Moreover, the graded mean integration (GMI) representation is adopted for determining more representative numeric regression coefficients. Notably, to comprehensively compare the performance of the proposed model with other ones, three different criteria are adopted. The results from commonly used test numerical examples and an application to Taiwan's business monitoring indicator illustrate that the proposed dissemblance index method not only produces valid fuzzy regression models for fuzzy input-output data, but also has satisfactory and stable performance in terms of the total estimation error based on these three criteria.

Keywords: dissemblance index, forecasting, fuzzy sets, linear regression

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Authors: I. Nižetić Kosović, T. Jagušt

Abstract:

Lately, with the increasing number of location-based applications, demand for highly accurate and reliable indoor localization became urgent. This is a challenging problem, due to the measurement variance which is the consequence of various factors like obstacles, equipment properties and environmental changes in complex nature of indoor environments. In this paper we propose low-cost custom-setup infrastructure solution and localization algorithm based on the Weighted Centroid Localization (WCL) method. Localization accuracy is increased by several enhancements: calibration of RSSI values gained from wireless nodes, repetitive measurements of RSSI to exclude deviating values from the position estimation, and by considering orientation of the device according to the wireless nodes. We conducted several experiments to evaluate the proposed algorithm. High accuracy of ~1m was achieved.

Keywords: indoor environment, received signal strength indicator, weighted centroid localization, wireless localization

Procedia PDF Downloads 212