Loss Calculation Research Articles

Soft charging and fewer switches based single‐source double‐boost multilevel DC‐AC converter for low/medium voltage applications

AbstractThis paper presents a novel generalized step‐up switched‐capacitor multilevel inverter (SCMLI) appropriate for low/medium voltage input applications. To reduce the overall number of power switches, the suggested topology makes use of reduction switch count (SC) technology. The complementary working mechanism of each pair of switches simplifies the modulation method. The complete inductive‐load capability is taken into account in the proposed inverter. Furthermore, because capacitor voltages are automatically balanced, complex voltage control circuitry is not necessary. Due to a reduction in current spikes on the devices, the topology also has the ability to soft‐charge the capacitors in a quasi‐resonant manner. Performance is also enhanced by extending the lifetime and dependability of the inverters. The construction, operation, modulation method, values of the capacitors, and circuit losses are explained to demonstrate how the suggested topology should function. One of the inverter's primary differentiators from the others is its double‐boosting capability based on reduced components. Based on loss calculations, a thorough analysis of the suggested topology's efficiency of 98.31% is presented. Next, the benefits of the suggested inverter are compared to those of other inverters that have been recently suggested. The steady‐state and dynamic performance of the suggested topology is then confirmed by modeling the system on the Simulink platform and performing experiments using a DSP‐based prototype experimental setup.

Influence of loss function and electron dose on ptychography of 2D materials using the Wirtinger flow

Iterative phase retrieval is based on minimising a loss function as a measure of the consistency of an initial guess and underlying experimental data. Under ideal experimental conditions, real data contains Poissonian noise due to counting statistics. In this work, we use the Wirtinger Flow concept in combination with four common loss functions, being the L1 loss, the mean-squared error (MSE), the amplitude loss and the Poisson loss. Since only the latter reflects the counting statistics as an asymmetric Poisson distribution correctly, our simulation study focuses on two main cases. Firstly, high-dose momentum-resolved scanning transmission electron microscopy (STEM) of an MoS2 monolayer is considered for phase retrieval. In this case, it is found that the four losses perform differently with respect to chemical sensitivity and frequency transfer, which we interprete in terms of the substantially different signal level in the bright and dark field part of diffraction patterns. Remedies are discussed using further simulations, addressing the use of virtual ring detectors for the dark field, or restricting loss calculation to the bright field. Secondly, a dose series is presented down to 100 electrons per diffraction pattern. It is found that all losses yield qualitatively reasonable structural data in the phase, whereas only MSE and Poisson loss range at the correct amplitude level. Chemical contrast is, in general, reliably obtained using the Poisson concept, which also provides the most continuous spatial frequency transfer as to the reconstructed object transmission function.

Time-Limited Aging Analysis of the Containment of Nuclear Power Plants without Monitoring Tendons

A prestressed concrete containment is the enclosure structure of a nuclear reactor that serves as the last physical barrier of a nuclear power plant (NPP) safety defense system. It plays a key role in the prestress time-limited aging analysis (TLAA) required for operating license extensions for NPPs. Considering prestress containment systems without long-term monitoring tendons in a nuclear power plant, the technical route for prestress TLAAs involves analyzing operating license extension regulations and in-service monitoring technical requirements for prestressed tendons performance. Using tendons based on theoretical calculations of prestress loss in a nuclear power plant and the minimum required value of prestress determined by numerical simulation, the theoretical predictive value can be compared with the minimum required value for prestressed steel tendons. This comparison can be used to evaluate the 20-year life extension of the prestress system and provide a reference for aging and life management of NPPs.

One-dimensional deep learning driven geospatial analysis for flash flood susceptibility mapping: a case study in North Central Vietnam

Flash floods rank among the most catastrophic natural disasters worldwide, inflicting severe socio-economic, environmental, and human impacts. Consequently, accurately identifying areas at potential risk is of paramount importance. This study investigates the efficacy of Deep 1D-Convolutional Neural Networks (Deep 1D-CNN) in spatially predicting flash floods, with a specific focus on the frequent tropical cyclone-induced flash floods in Thanh Hoa province, North Central Vietnam. The Deep 1D-CNN was structured with four convolutional layers, two pooling layers, one flattened layer, and two fully connected layers, employing the ADAM algorithm for optimization and Mean Squared Error (MSE) for loss calculation. A geodatabase containing 2540 flash flood locations and 12 influencing factors was compiled using multi-source geospatial data. The database was used to train and check the model. The results indicate that the Deep 1D-CNN model achieved high predictive accuracy (90.2%), along with a Kappa value of 0.804 and an AUC (Area Under the Curve) of 0.969, surpassing the benchmark models such as SVM (Support Vector Machine) and LR (Logistic Regression). The study concludes that the Deep 1D-CNN model is a highly effective tool for modeling flash floods.

Calculation of electrical energy losses in distribution networks for power supply using oil and vacuum circuit breakers

A method for approximate estimation of load losses in distribution networks from 6 to 10 kV, as well as for lower voltage networks, has been proposed. The main advantage of this method is that the root mean square current is calculated only once for a series of calculations. This approach significantly reduces the time required for calculations and improves their accuracy, as it eliminates the need for multiple determinations of the root mean square current for each individual calculation. The proposed approach contributes to a better understanding of the influence of various factors on load losses, which allows for more effective planning and management of distribution networks. This is particularly important in the context of increasing loads on electrical networks and higher demands for their reliability and efficiency. In the calculation of electrical energy losses in distribution networks from 6 to 10 kV, methods that use generalized coefficients of electrical circuits and operating modes in the form of regression equations are widely applied. The most significant and independent factors, such as the input of active energy, total line length, number of line sections, total number of transformers, and their total installed capacity, must be taken into account and are included in the calculation equation. Additionally, the components used and their regular maintenance play an important role in electrical energy losses in electrical networks. The main direction of research is the optimization of distribution network parameters, taking into account the latest technologies and materials, as well as the implementation of automated monitoring and control systems that will allow timely detection and elimination of problems associated with electrical energy losses. The proposed method for estimating load losses in distribution networks is a promising direction for the development of the energy sector, which will contribute to improving the efficiency and reliability of electrical networks, as well as reducing the costs of their operation and maintenance.

Minor Loss Coefficient for Abrupt Section Changes in a Cylindrical Pipe Using a Numerical Approach

Abrupt section changes are a classic problem in the study of flow in cylindrical ducts or pipes. For its analysis, there are a wide set of exiting data from previous studies, among which some authors stand out and will be mentioned. Those previous works have been used to obtain reliable results for the resolution of section changes along a pipe, either due to cross area increases or reductions on a 1D basis. It is also known that a numerical 2D axisymmetric simulation (CFD) could find a consistent result compared to experimental data in almost all fluid flow fields. The main novelty of the present study is the development of a simple numerical approach used to solve the minor loss calculation. Firstly, a theoretical analysis is developed, and then the results of the numerical simulations carried out on the behavior that affects the water and air flow rate in an abrupt section change, for both contraction and expansion problems, are presented. In both cases, the results are analyzed with different meshes (discretizations) and turbulence models. Finally, the obtained numerical results are compared with those in the technical literature. Also, a theoretical approach is shown in order to show a whole frame of the discussion. The core results are the loss coefficient evolution as a function of the section change both for the sudden contraction and the expansion of a pipe flow. As the results follow the existing experimental values, it is concluded that the developed model provides a feasible and quick design tool to analyze possible geometrical changes without the need for further experiments.

Exploring the efficiency of a source-level model to predict hydrophone-based received noise levels of the St. Lawrence Estuary’s merchant fleet

The Enhancing Cetacean Habitat and Observation (ECHO) source-level model was statistically derived using nearly 10,000 vessel transits along Canada’s western coast. Before using this model in other areas, it is important to examine its efficiency in new environments and on other fleets. In this work, hydrophone-based acoustic recordings collected between August 3rd and September 16th of 2022 within the Saguenay-St. Lawrence Marine Park were used to investigate the applicability of the ECHO source-level model to Canada’s eastern fleet. Opportunistic transits of 71 merchant ships near (i.e., ≲3 km) the hydrophone were obtained. As an attempt to reduce computing times in the context of agent-based modeling, the reliability of the proposed analytic seabed critical angle (SCA) method for propagation losses calculations was examined and compared to robust, although time-consuming, numerical methods. Results generally show that the combination of the ECHO source-level model and our best estimates for propagation losses calculations does allow to reliably predict the acoustic footprint of the radiated noise levels by merchant ships in the acoustic module of the Marine Mammal and Maritime Traffic Simulator (3MTSim). However, computational gains could be marginal at best due to the analytic SCA method quickly becoming inconsistent with the numerical approach in range-dependent scenarios that often translate into long-range encounters.

SIM-MultiDepth: Self-Supervised Indoor Monocular Multi-Frame Depth Estimation Based on Texture-Aware Masking

Self-supervised monocular depth estimation methods have become the focus of research since ground truth data are not required. Current single-image-based works only leverage appearance-based features, thus achieving a limited performance. Deep learning based multiview stereo works facilitate the research on multi-frame depth estimation methods. Some multi-frame methods build cost volumes and take multiple frames as inputs at the time of test to fully utilize geometric cues between adjacent frames. Nevertheless, low-textured regions, which are dominant in indoor scenes, tend to cause unreliable depth hypotheses in the cost volume. Few self-supervised multi-frame methods have been used to conduct research on the issue of low-texture areas in indoor scenes. To handle this issue, we propose SIM-MultiDepth, a self-supervised indoor monocular multi-frame depth estimation framework. A self-supervised single-frame depth estimation network is introduced to learn the relative poses and supervise the multi-frame depth learning. A texture-aware depth consistency loss is designed considering the calculation of the patch-based photometric loss. Only the areas where multi-frame depth prediction is considered unreliable in low-texture regions are supervised by the single-frame network. This approach helps improve the depth estimation accuracy. The experimental results on the NYU Depth V2 dataset validate the effectiveness of SIM-MultiDepth. The zero-shot generalization studies on the 7-Scenes and Campus Indoor datasets aid in the analysis of the application characteristics of SIM-MultiDepth.

An enhanced meta-learning network with sensitivity penalty for cross-domain few-shot fault diagnosis

Abstract Big data-driven rotating machine intelligent diagnostic technology has gained widespread applications. In practice, however, fault data are limited as well as inconsistencies in fault categories among different domains are widespread. These make developing robust intelligent diagnostic models a challenge. To this end, this paper develops an enhanced meta-learning network with a sensitivity penalization mechanism (EMLN-SP) for few-shot fault diagnosis in severe domain bias. First, lightweight channel attention is introduced to establish an enhanced feature encoder under meta-learning framework, which elevates the key feature expression to facilitate the extraction of generalized diagnostic knowledge within limited samples. Second, a boundary-enhanced loss calculation method is designed, which boosts the focus for decision boundary information to prevent the model from the overfitting dilemma in the case of few-shot. Finally, a sensitivity penalty mechanism is constructed to adjust the optimization direction, which prevents the model from falling into a local optimum, to boost the generalization of the model performance. The effectiveness of EMLN-SP is validated by three cross-domain diagnostic cases with diverse domain offsets.

Numerical Calculation and Direct Measurement of Local Hot Spot Temperatures in Transformer Clamping Plates

A verified multiphysics model is developed to simulate local hot spot temperatures in clamping structures. Stray field losses in clamping plates are obtained with the use of nonlinear impedance boundary condition through finite element method (FEM) while hot spot temperatures are simulated with the use of computational fluid dynamics (CFD). This multiphysics coupling is validated through direct measurements of local hot spot temperatures that were carried out with fiber optic temperature probes in real transformer. The local hot spot temperatures obtained with the simulations were in good agreement with the measured values, thus verifying overall approach and indirectly the calculation of local stray field losses.

TSD‐YOLO: Small traffic sign detection based on improved YOLO v8

AbstractTraffic sign detection is critical for autonomous driving technology. However, accurately detecting traffic signs in complex traffic environments remains challenge despite the widespread use of one‐stage detection algorithms known for their real‐time processing capabilities. In this paper, the authors propose a traffic sign detection method based on YOLO v8. Specifically, this study introduces the Space‐to‐Depth (SPD) module to address missed detections caused by multi‐scale variations of traffic signs in traffic scenes. The SPD module compresses spatial information into depth channels, expanding the receptive field and enhancing the detection capabilities for objects of varying sizes. Furthermore, to address missed detections caused by complex backgrounds such as trees, this paper employs the Select Kernel attention mechanism. This mechanism enables the model to dynamically adjust its focus and more effectively concentrate on key features. Additionally, considering the uneven distribution of training data, the authors adopted the WIoUv3 loss function, which optimizes loss calculation through a weighted approach, thereby improving the model's detection performance across various sizes and frequencies of instances. The proposed methods were validated on the CCTSDB and TT100K datasets. Experimental results demonstrate that the authors’ method achieves substantial improvements of 3.2% and 5.1% on the mAP50 metric compared to YOLOv8s, while maintaining high detection speed, significantly enhancing the overall performance of the detection system. The code for this paper is located at https://github.com/dusongjie/TSD‐YOLO‐Small‐Traffic‐Sign‐Detection‐Based‐on‐Improved‐YOLO‐v8

Analysis of welding conditions at synchronous operation of resistance welding machines

The paper is devoted to analysis of power losses in a resistance welding machine including supplying system and examination of welding conditions of the welding machine current in a case of synchronous (simultaneous) operation of multiple welding machines, i.e., during the conduction of welding current. Analysis of the most important contributors of power losses generated on the current path between a power source and the welded joint is carried out. The analysis is carried out for a DC (direct current) welding machine with power electronics inverter. AC (alternating current) welding machines are also taken into account. The analysis is divided in two parts. The first one is the analysis of single welding machine operation, while in the second part, coexistence (mutual operation) of two synchronous welding machines is considered. The analysis is based on results of numerical and experimental investigations. The first one is focused on calculation of power losses in the energy path (including a Sankey type power loss distribution diagrams), and the second one is based on experimental tests carried out to determine the diameter of the weld nugget and the strength of the joints, for cases of reducing the welding current. An example of simultaneous operation of welding machines was presented and discussed. The percentage voltage drops and power losses in the entire power supply path of the resistance welder are shown. The analysis carried out is extremely important from this point quality of welded joints.

Online Loss Calculation and Optimization of an M3C-Driven Externally Excited SM

Online Loss Calculation and Optimization of an M3C-Driven Externally Excited SM

A calculation method of winding loss of high frequency transformer based on finite element method

In this paper, a winding loss calculation method used in the field of converter transformers is introduced into the realm of high-frequency transformers for the first time. In addition, the impact of winding structure on the calculation accuracy of the method is considered for the first time. Comparing the calculation results of this method with those of the formula method, based on the results of finite element simulation. The feasibility of using this method to calculate the winding loss of a high-frequency transformer is verified. First, the winding loss of rectangular wire commonly used in small-capacity high-frequency transformers is analyzed. Based on the finite element simulation results, the accuracy of the hybrid method is compared with the formula calculation method to demonstrate the feasibility of the hybrid method. Then, using the same method, the accuracy of the hybrid method in calculating the winding loss of the circular wire, which is also used in small-capacity high-frequency transformers, is compared with the formula method. The maximum number of continuous winding layers has been modified, and the outcomes for various layers are being computed. Finally, the cross-transposition winding structure is also calculated, demonstrating that the hybrid method is not only applicable to wires of various shapes but also compatible with different winding structures. The results show that the hybrid method has good calculation accuracy and applicability. It can provide more precise calculation results for the winding loss of high-frequency transformers with various winding shapes.

Thermal analysis of sinusoidal doubly salient Electro-Magnetic Machine with distributed magnetomotive forces considering complex heat distribution and material thermal characteristics

Sinusoidal doubly salient electro-magnetic machine with distributed magnetomotive forces has DC excitation and AC armature windings in the same stator slot, which leads to the complicated distribution of heat sources and thermal resistances. One of the keys to design this motor is to estimate the temperature rise accurately. In this paper, the thermal performance of the motor materials at different temperatures was tested. According to the complex structure characteristics, the layered and sub-regional equivalent model of the stator slot is proposed. The model not only uses the material thermal data obtained from experiments, but also considers the complex thermal resistances and AC/DC losses distribution in the slots, as well as the influence of winding and insulation processes on the temperature rise of the motor, which is conducive to obtaining the highest point of the motor temperature and ensuring the calculation accuracy. The 3-D global steady-state temperature distribution of sinusoidal doubly salient electro-magnetic machine with distributed magnetomotive forces is studied, and the temperature rise of each part under different current densities is also analyzed. Finally, the temperature experiment of the prototype is carried out. The experiments show that the accurate loss calculation and thermal parameters make the maximum error between the simulation model and the actual measurement is 3.8 °C. The results not only guide the selection of reasonable armature and excitation winding current density of sinusoidal doubly salient electro-magnetic machine with distributed magnetomotive forces, but also provide data and experience support for temperature estimation of motors with complex winding distribution.

Research on the Material Characteristics and Loss Calculation Method of Cryogenic Permanent Magnet Motor Stator for LNG Pump

This paper explores the applicability of cryogenic permanent magnet motor stator materials for LNG pumps. First, this study selected four kinds of silicon steel sheets for motor stators tested at room temperature and ultra-low temperature and obtained the magnetization characteristics and loss characteristics of the four silicon steel sheets at room temperature and ultra-low temperature. Then, through a comparative analysis of experimental data, the applicability of silicon steel sheet material in an ultra-low-temperature environment was verified. Finally, the improved methods of the basic iron loss model of silicon steel sheets and the basic iron loss model of motors were proposed, and the accuracy and feasibility of the improved models were verified.

Using Gaussian process regression for building a data-driven drag loss model of wet clutches

Drag loss calculation models support designing low-loss wet clutch systems and determining drivetrain efficiency. Available numerical models require high computational effort, whereas analytical models provide only limited accuracy. In contrast, data-driven models unite the advantages of fast and effective drag loss prediction and, thus, enable practice-oriented development. Therefore, this study aimed to build a data-driven model of the wet clutches’ drag losses, enabling predictions with low computational effort and, at the same time, sufficient accuracy while taking seven relevant influencing parameters into account. The dataset used originates from prior research projects that experimentally investigated the wet clutches’ drag loss behavior under consideration of various influencing parameters. Different machine learning algorithms were considered for model building, and it was found that Gaussian process regression best met the requirements of flexibility and interpretability. Four sub-models were built to predict four characteristic drag loss values based on the model input parameters of mean diameter, diameter ratio, number of gaps, clearance, dynamic viscosity, oil level, and groove design. Subsequently, the predicted characteristic drag loss values can be used as support points for approximating the drag loss curve. The sub-models show high R² values, ranging from 0.84 to 0.95, indicating a high model performance. The mean relative error of the sub-models was used for evaluating the models’ performance from an engineering perspective, ranging from 4.6 % to 14.2 %. The drag loss model was also validated based on documented knowledge of wet clutches’ drag loss behavior. The model enables the prediction of the drag loss curve within a few split-seconds and, simultaneously, with sufficient accuracy.

Sperm YOLOv8E-TrackEVD: A Novel Approach for Sperm Detection and Tracking.

Male infertility is a global health issue, with 40-50% attributed to sperm abnormalities. The subjectivity and irreproducibility of existing detection methods pose challenges to sperm assessment, making the design of automated semen analysis algorithms crucial for enhancing the reliability of sperm evaluations. This paper proposes a comprehensive sperm tracking algorithm (Sperm YOLOv8E-TrackEVD) that combines an enhanced YOLOv8 small object detection algorithm (SpermYOLOv8-E) with an improved DeepOCSORT tracking algorithm (SpermTrack-EVD) to detect human sperm in a microscopic field of view and track healthy sperm in a sample in a short period effectively. Firstly, we trained the improved YOLOv8 model on the VISEM-Tracking dataset for accurate sperm detection. To enhance the detection of small sperm objects, we introduced an attention mechanism, added a small object detection layer, and integrated the SPDConv and Detect_DyHead modules. Furthermore, we used a new distance metric method and chose IoU loss calculation. Ultimately, we achieved a 1.3% increase in precision, a 1.4% increase in recall rate, and a 2.0% improvement in mAP@0.5:0.95. We applied SpermYOLOv8-E combined with SpermTrack-EVD for sperm tracking. On the VISEM-Tracking dataset, we achieved 74.303% HOTA and 71.167% MOTA. These results show the effectiveness of the designed Sperm YOLOv8E-TrackEVD approach in sperm tracking scenarios.

Fast and accurate methodologies for the eddy current losses analysis in axially laminated rotor of synchronous reluctance machines under different loads

AbstractThe authors present two fast and accurate methodologies for the computation of eddy current losses in the axially laminated rotor of a synchronous reluctance machine. The methodologies are based on different combinations of the finite element method in time and frequency domains with 2D and 3D formulations. First, a comparative study of the 2D and 3D formulations for loss calculation is presented, considering various load angles of the machine to illustrate the problem of eddy‐current losses in this type of machines and its dependence on the load angle. The influence of the iron saturation on the loss calculation is also evaluated in these computations. A novel correction factor based on the computations at two load angles is proposed to convert the losses computed from a 2D model to match those computed from a 3D model. For the sake of generality, investigations are also conducted for various thicknesses of the lamination layers and different machine lengths, and an analytical method to describe the dependency of eddy‐current losses on the load angle of the machine is introduced. Moreover, a simplified method is proposed for modelling eddy currents in the frequency domain and calculating losses in an axially laminated structure based solely on the results of a magnetostatic solution. The results obtained by the simplified model demonstrate excellent agreement with the full 3D magneto‐dynamic simulation. Overall, the findings contribute to understanding and accurately characterising the eddy current losses in axially laminated rotors, offering potential insights for designing and optimising axially laminated synchronous reluctance electric machines.

Interactive and educational simulation tool for permanent magnet synchronous machines

PurposeThis paper aims to present an interactive design and simulation tool for permanent magnet synchronous machines based on the finite-element-method. The tool is intended for education and research on electrical machines.Design/methodology/approachA coupling between the software MATLAB and finite element method magnetics is used. Several functionalities are included as modular scripts and represented in the form of a graphical user interface. Included are fully parametrized motor models, automatic winding generations and the evaluation of torque waveforms, core losses and speed-torque-diagrams. A survey was conducted to determine how the motivation of students concerning the covered topics is influenced by using the tool.FindingsDue to its simplicity and the intuitive visualization of the results, the tool provides direct access to the topic of electrical machines without having to deal with separate scripts. The modular structure of the software allows simple extensions with new functions. Because students can directly contribute to the tool with their own work, their motivation for using and extending it increases.Originality/valueThe presented tool offers more functionalities compared to similar free software packages, e.g. the calculation of core losses and speed-torque diagrams. Also, it is designed in such a way that it can be easily understood and extended by students.