Specific Transformation Research Articles

Operation State Identification Method for Converter Transformers Based on Vibration Detection Technology and Deep Belief Network Optimization Algorithm

The converter transformer is a special power transformer that connects the converter bridge to the AC system in the HVDC transmission system. Due to the special structure of the converter transformer, it is necessary to test its operation state during its manufacture and processing to ensure the safety of its future connection to the grid. Numerous studies have shown that vibration signals in transformers can reflect their operating state. Therefore, in order to achieve an effective identification of the operation state of the converter transformer, this paper proposes a method for identifying the operation state of the converter transformer based on vibration detection technology and a deep belief network optimization algorithm. This paper firstly describes the background, principle and application of vibration detection technology, using vibration measurement systems with piezoelectric acceleration sensors, piezoelectric actuators and data acquisition instruments to collect vibration signals at different measurement points on the converter transformer in states of no-load and on-load. By analyzing the time-frequency characteristics of the vibration signals, fast Fourier transform (FFT), wavelet packet decomposition (WPD) and time domain indexes (TDI) are combined into a fused feature extraction method to extract the eigenvalues of the vibration signals, so that the fused eigenvectors of the signals can be constructed. Considering the excellent performance of deep learning in classification, the deep belief network is used to classify the signals’ eigenvectors. To effectively improve the network classification efficiency, the sparrow search algorithm was introduced to build a mathematical model based on the behavioral characteristics of sparrow populations and combine the model with a deep belief network, so as to achieve adaptive parameter optimization of the network and accurate classification of the signals’ eigenvectors. The proposed method is applied to a 500 kV converter transformer for experimental verification. The experimental results show that the fused feature extraction method was able to fully extract the features of the vibration signal, and the deep belief network optimization algorithm had higher classification accuracy and better operational efficiency, and was able to effectively achieve accurate identification of the operation state of the converter transformer. In addition, the method achieved a precision response to the detection results of the vibration sensors, contributing to future improvements in converter transformer manufacturing technology.

Uncertainty Principle for the Short-time Special Affine Fourier Transform

The special affine Fourier transform (SAFT) generalizes a number of well known unitary transformations, signal processing transformations and optics related mathematical operations. For example, Fourier transform, fractional Fourier transform, linear canonical transform, etc. The short-time special affine Fourier transform (STSAFT) is a novel time-frequency analysis tool, which solve the limitation of SAFT in time-frequency signal description. In this paper, we generalize some different uncertainty principles (UPs) for the SAFT and STSAFT of complex signals. The UPs for the STSAFT of complex signals are obtained in both local and global cases. Then the uncertainty principle for two STSAFT time-frequency domains is discussed. Finally, we provide a class of signals to illustrate our results.

Research on Intelligent Mining Algorithm for Distribution Network Transformer Fault Early Warning

The distribution network is the end link of the power grid. The level of management directly affects the power supply capacity and power quality. It is related to the operation level and social image of the power grid enterprise. The transformer is a very important component in the distribution network. The transformer is continuously safe and stable. Grid power supply reliability. In this context, this paper proposes an intelligent gateway intelligent fault detection algorithm for transformer operation failure, which collects data of transformers in multiple dimensions and multiple source channels, such as electrical variables and non-electrical variables. Correlation analysis and causality analysis of the data to achieve an all-round warning of transformer operation failure. The traditional method of transformer fault warning is solved by relying on the special gas concentration or transformer vibration signal generated by the fault of the transformer fault to solve the problem of fault identification and early warning singleness and low reliability, and fully exert the technical advantages of the Internet of Things and data mining. The evaluation value of the five “ancestor“ elements is 0.2, 0.25, 0.15, 0.3, 0.1. Transformer operation fault trend early warning coefficient is set to 0.80. Once the early warning coefficient is found to exceed 0.80 during data collection and mining analysis, a transformer failure early warning will be issued, which can facilitate grid operators’ intervention and control in advance. The actual calculation case also demonstrates the correctness and effectiveness of the intelligent mining algorithm. This paper provides an effective support for the development and application of big data technology in the distribution network.

Contraction operator transformation for the complex heterogeneous Helmholtz equation

An efficient solution of the three-dimensional Helmholtz equation is known to be crucial in many applications, especially geophysics. In this paper, we present and test two preconditioning approaches for the discrete problem resulting from the second order finite-difference discretization of this equation. The first approach combines shifted-Laplacian preconditioner with inversion of a separable matrix, corresponding to the horizontally-layered velocity model, using fast Fourier based transforms. The second approach is novel and involves a special transformation resulting in a preconditioner with a contraction operator (CO preconditioner). The two approaches have near the same arithmetical complexity; however, the second approach, developed in this paper, provides a faster convergence of an iterative solver as illustrated by numerical experiments and analysis of the spectral properties of the preconditioned matrices. Our numerical experiments involve parallel modeling of highly heterogeneous lossy and lossless media at different frequencies. We show that the CO-based solver can tackle problems with hundreds of millions of unknowns on a conventional cluster node. The CO preconditioned solver demonstrates a very moderate increase of iteration count with the frequency. We have conducted a comparison of the performance of the developed method versus open-source parallel sweeping preconditioner. The results indicate that, the CO solver is several times faster with respect to the wall-clock time and consumes substantially less memory than the code based on the sweeping preconditioner at least in the example we tested.

Failures’ Diagnosis of High Voltage Power Supply System for Low Power Magnetrons

This paper treats the study of the equivalent magnetic flux leakage transformer core type; it uses three-phase high voltage power supplies for a magnetron in each phase. This special transformer feeds a voltage doubler, a current stabilizer cell in series per phase. It ensures the anodic current stabilization in each magnetron by saturation of its magnetic circuit. It has additional leakage flux, which protects the magnetron against any eventual voltage variation; it is considered the basic element of this power supply.The simulation results with MATLAB-Simulink environment of the electrical operation of this power supply device were consistent with the experimental laboratory tests in the case of single-phase high voltage for one magnetron. This results obtained shows the feasibility of the proposed simulation model

Perturbation and construction of almost self‐located robust frames with applications to erasure recovery

In the frame theory, stability is one of the most important properties of frames. In this paper, we investigate the stability of the almost self‐located robust frames, which can reconstruct signals from its unordered partial frame coefficients. We give conditions on the stability of almost self‐located robustness of frames in erasure recovery. We prove that the property of almost self‐located robustness is preserved with respect to an invertible operator, and consequently, every almost self‐robust frame can be transformed into an almost self‐located robust Parseval frame by using a special invertible transformation. We also present some construction methods of almost self‐located robust frames. In particular, we show that every frame can be rescaled to an almost self‐located frame after adding a suitable vector.

Portable DC Supply Based on SiC Power Devices for High-Voltage Marx Generator

The paper describes major issues related to the design of a portable SiC-based DC supply developed for evaluation of a high-voltage Marx generator. This generator is developed to be a part of an electromagnetic cannon providing very high voltage and current pulses aiming at the destruction of electronics equipment in a specific area. The portable DC supply offers a very high voltage gain: input voltage is 24 V, while the generator requires supply voltages up to 50 kV. Thus, the system contains two stages designed on the basis of SiC power devices operating with frequencies up to 100 kHz. At first, the input voltage is boosted up to 400 V by a non-isolated double-boost converter, and then a resonant DC-DC converter with a special transformer elevates the voltage to the required level. In the paper, the main components of the laboratory setup are presented, and experimental results of the DC supply and whole system are also shown.

The dual conformal box integral in Minkowski space

The dual conformal box integral in Minkowski space is not fully determined by the conformal invariants z and z¯. Depending on the kinematic region its value is on a ‘branch’ of the Bloch-Wigner function which occurs in the Euclidean case. Dual special conformal transformations in Minkowski space can change the kinematic region in such a way that the value of the integral jumps to another branch of this function, encoding a subtle breaking of dual conformal invariance for the integral. We classify conformally equivalent configurations of four points in compactified Minkowski space. We show that starting with any configuration, one can reach up to four branches of the integral using dual special conformal transformations. We also show that most configurations with real z and z¯ can be conformally mapped to a configuration in the same kinematic region with two points at infinity, where the box integral can be calculated directly in Minkowski space using only the residue theorem.

Evaluation of user dynamics created by weak ties among divided communities

Flaming phenomena represent the divergence in the strength of user dynamics as created by user interactions in online social networks (OSNs). Although it has been known that flaming phenomena occur when the Laplacian matrix of the OSN has non-real eigenvalues, it was recently shown that flaming phenomena may occur even if all the eigenvalues are real numbers. This effect appears only in the situation that some eigenvalues are degenerate, and a special unitary transformation is applied to the equations representing user dynamics; whether actual OSNs satisfy this condition has not been fully discussed. In this paper, we clarify that the user dynamics caused by the degeneration of eigenvalue 0 is one specific example of the above condition. We also investigate the mechanism and characteristics of flaming phenomena generated by degenerated eigenvalues. Furthermore, we demonstrate through numerical simulations that the degeneration of eigenvalues can cause divergence.

Advanced TSGL-EEGNet for Motor Imagery EEG-Based Brain-Computer Interfaces

Deep learning technology is rapidly spreading in recent years and has been extensive attempts in the field of Brain-Computer Interface (BCI). Though the accuracy of Motor Imagery (MI) BCI systems based on the deep learning have been greatly improved compared with some traditional algorithms, it is still a big problem to clearly interpret the deep learning models. To address the issues, this work first introduces a popular deep learning model EEGNet and compares it with the traditional algorithm Filter-Bank Common Spatial Pattern (FBCSP). After that, this work considers that the 1-D convolution of EEGNet can be explained by a special Discrete Wavelet Transform (DWT), and the depthwise convolution of EEGNet is similar to the Common Spatial Pattern (CSP) algorithm. Therefore, this work improves the EEGNet by using the algorithm Temporary Constrained Sparse Group Lasso (TCSGL) to enhance its performance. The proposed model TSGL-EEGNet is tested on the BCI Competition IV 2a and BCI Competition III IIIa datasets that both are 4-classes classification MI tasks. The testing results show that the proposed model has achieved 78.96% (0.7194) average classification accuracy (kappa) on the dataset BCI Competition IV 2a, which are greater than EEGNet, C2CM, MB3DCNN, SS-MEMDBF and FBCSP, especially on insensitive subjects. The proposed model has also achieved 85.30% (0.8040) average classification accuracy (kappa) on the dataset BCI Competition III IIIa, which are greater than the EEGNet, MFTFS et al. At last, this work uses average-validation and stacking to further enhance the effect of the model. The 4-classes classification average accuracy rates reach 81.34% and 88.89%, and the kappas reach 0.7511 and 0.8519 on dataset BCI Competition IV 2a and BCI Competition III IIIa, respectively. Additionally, this work also uses the Grad-CAM to visualize the frequency and spatial features that are learned by the neural network.

Non-singular terminal sliding mode control of converter-fed DC motor system with mismatched disturbance compensation

In this paper, the problem of angular velocity trajectory tracking for converter-fed DC motor system with disturbances/uncertainties is addressed. The combination power converters with DC motors for generating 'smooth start of drives' has numerous practical applications. Achieving high performance in such systems is however limited by the influence of multiple disturbances. Furthermore, the conventional mathematical model complicates the ability to compensate the multiple disturbances. In this paper, a control structure with non-singular terminal sliding mode controller and a finite-time disturbance observer is proposed. First, a special state transformation is applied, aggregating disturbances/uncertainties in a sole perturbing term of the system expressed in new coordinates. Then, the observer estimates the information about the lumped disturbances and the obtained estimated signals are used to construct a sliding surface. Finally, the sliding mode controller is applied to achieve desired result. The efficiency of the proposed control method is validated through numerical simulations.

УПРАВЛІННЯ ВАРТІСТЮ БІЗНЕСУ НА ОСНОВІ АКТУАРНОГО БАЛАНСУ РУХУ ГРОШОВИХ КОШТІВ

Approaches to business value management based on the accounting and analytical content of actuarial reporting are considered. This study is conducted to identify the information interdependence between the system of value-based management of the company, actuarial accounting and actuarial reporting management in a crisis in the economy of Ukraine. It is established that in order to build an effective management system of a domestic agricultural enterprise, actuarial accounting and actuarial reporting should be actively implemented. This gives the chance to form an image of the investment attractiveness of the country’s agricultural sector through a prism of administrative actuarial reporting forms in the international arena of agrarians. The author proposes a method of constructing a transformation table for filling in the Actuarial cash flow balance (form No.3-a), based on the traditional report on cash flow (form No.3) and some forms of actuarial reporting in 5D format on the example of a domestic agricultural enterprise. This will contribute to the construction of an effective system of value-based management of agribusiness through the prism of the concept of modern multidimensional actuarial accounting. The expediency of such a transformation from the point of view of value-based management is proved. The information necessary to compile the Actuarial cash flow balance is contained in the Actuarial balance (Statement of Financial Position), the Actuarial Profit and Loss Statement, and the traditional financial statements. To this end, the article developes a special transformation table, on the example of a domestic agricultural enterprise. The expediency of keeping an accurate accounting by a modern agricultural enterprise is substantiated because this accounting system generates information about changes in the economic value of business and cash flows in n-dimensional space and creates the necessary information content for management decisions for real and potential suppliers of temporarily free financial resources.

Метод обработки данных гидродинамических исследований скважин

Horner’s traditional method of processing well test data can be improved by a special transformation of the pressure curves, which reduces the time the converted curves reach the asymptotic regimes necessary for processing these data. In this case, to take into account the action of the «skin factor» and the effect of the wellbore, it is necessary to use a more complete asymptotic expansion of the exact solution of the conductivity equation at large values of time. At the same time, this method does not allow to completely eliminate the influence of the wellbore, since the used asymptotic expansion of the solution for small values of time is limited by the existence of a singular point, in the vicinity of which the asymptotic expansion ceases to be valid. To solve this problem, a new method of processing well test data is proposed, which allows completely eliminating the influence of the wellbore. The method is based on the introduction of a modified inflow function to the well, which includes a component of the boundary condition corresponding to the influence of the wellbore.

TRANSFORMATION OF GENDER STEREOTYPES IN THE KARACHAY-CHERKASS REPUBLIC (ON THE BASIS OF THE SOCIOLOGICAL RESEARCH)

The study of the processes of genesis, renewal and evolution of the modern Russian society is impossible without studying innovative social and cultural roles and norms, where special attention is paid to a fundamentally new way of women's existence in ethnocultural communities. Their social and cultural status is changing in the modern globalization and information society, in connection with which the issues related to the revision and adjustment of traditional positions and views on gender stereotypes, the distribution of emphasis in the field of gender equality, and ideas about the business activity of women are being actualized. To solve research problems, a structural-functional method, comparative analysis, a socio-gender approach with the use of the principles of consistency, historicism, objectivity have been used, allowing to analyze the nature of modifications in women's business activity. It has been noted that in the region under consideration there is a special transformation of gender stereotypes, a specific delimitation of the space of "masculine" and "feminine", which, on the one hand, are conditioned by the patriarchal nature of traditional culture, the presence of stable religious factors, a special mentality, and on the other hand, by the general desire for the processes of globalization, development of civil society. In this regard, the problem arises of the formation and assimilation of values by women in modern society. It has been revealed that modern representatives of the fairer sex are clearly aware that it is necessary to strive for greater financial independence, to have their own stable income in order to feel confident in the future, despite the ongoing socio-economic changes that have lead to the transformation of family relations and the culture of society. At the same time, a woman's business activity is aimed at controlling time in favor of preserving many traditional views on the position of women in the community of the region and finding a balance between work and family, innovations and traditions.

Leakage Inductances of Transformers at Arbitrarily Located Windings

The article presents the calculation of the leakage inductance in power transformers. As a rule, the leakage flux in the transformer window is represented by the short-circuit inductance, which affects the short-circuit voltage, and this is a very important factor for power transformers. This inductance reflects the typical windings of power transformers well, but is insufficient for special transformers or in any case of the internal asymmetry of windings. This paper presents a methodology for calculations of the self- and mutual-leakage inductances for windings arbitrarily located in the air window. It is based on the 2D approach for analyzing the stray field in the air zone only, using discrete partial differential operators. That methodology is verified with the finite element method tested on real transformer data.

General M-lumps, T -breathers, and hybrid solutions to (2+1)-dimensional generalized KDKK equation* *Project supported by the National Natural Science Foundation of China (Grant No. 11775116) and the Jiangsu Qinglan High-Level Talent Project.

A special transformation is introduced and thereby leads to the N-soliton solution of the (2+1)-dimensional generalized Konopelchenko–Dubrovsky–Kaup–Kupershmidt (KDKK) equation. Then, by employing the long wave limit and imposing complex conjugate constraints to the related solitons, various localized interaction solutions are constructed, including the general M-lumps, T-breathers, and hybrid wave solutions. Dynamical behaviors of these solutions are investigated analytically and graphically. The solutions obtained are very helpful in studying the interaction phenomena of nonlinear localized waves. Therefore, we hope these results can provide some theoretical guidance to the experts in oceanography, atmospheric science, and weather forecasting.

Novel localized wave solutions of the (2+1)-dimensional Boiti–Leon–Manna–Pempinelli equation

Based on a special transformation that we introduce, the N-soliton solution of the (2+1)-dimensional Boiti–Leon–Manna–Pempinelli equation is constructed. By applying the long wave limit and restricting certain conjugation conditions to the related solitons, some novel localized wave solutions are obtained, which contain higher-order breathers and lumps as well as their interactions. In particular, by choosing appropriate parameters involved in the N-solitons, two interaction solutions mixed by a bell-shaped soliton and one breather or by a bell-shaped soliton and one lump are constructed from the 3-soliton solution. Five solutions including two breathers, two lumps, and interaction solutions between one breather and two bell-shaped solitons, one breather and one lump, or one lump and two bell-shaped solitons are constructed from the 4-soliton solution. Five interaction solutions mixed by one breather/lump and three bell-shaped solitons, two breathers/lumps and a bell-shaped soliton, as well as mixing with one lump, one breather and a bell-shaped soliton are constructed from the 5-soliton solution. To study the behaviors that the obtained interaction solutions may have, we present some illustrative numerical simulations, which demonstrate that the choice of the parameters has a great impacts on the types of the solutions and their propagation properties. The method proposed can be effectively used to construct localized interaction solutions of many nonlinear evolution equations. The results obtained may help related experts to understand and study the interaction phenomena of nonlinear localized waves during propagations.

Optimised approach of feature selection based on genetic and binary state transition algorithm in the classification of bearing fault in BLDC motor

This study represents an effective approach for detection and classification of bearing faults in brushless DC (BLDC) motors based on hall-sensor signal analysis. The envelope analysis and Hilbert–Huang transform are used to extract features from the time and frequency domains of each signal. A new feature selection technique is proposed based on the combination of the genetic algorithm strength and the advantage of the binary state transition algorithm. The genetic algorithm explores search space through cross-over operator while the binary state transition algorithm is based on four special transformation operators in the local exploitation capabilities. The artificial neural network and support vector machine are used as the classifier. Each model is separately analysed and compared, leading to a high possibility to distinguish the bearing faults.

SPEED OBSERVER FOR SENSORLESS ENERGY GENERATION SYSTEMS BASED ON FIELD ORIENTED INDUCTION GENERATOR

The paper presents a novel adaptive speed – rotor flux linkage observer for sensorless field oriented control of induction generators. The proposed solution is based on Matsuse observer structure to- gether with specially designed correction terms and utilize current measurement and calculated stator volt- ages for real-time flux and speed reconstruction. A special coordinate transformation is used to avoid non- linear parametrization in the right side of flux linkages differential equations. Adaptive observer is designed in two steps: at the first step nonadaptive flux linkage observer is designed under condition of speed meas- urement; at the second step adaptive to rotor speed version of the flux linkage observer is designed. Infor- mation about rotor speed for adaptive flux observer is calculated by developed speed observer. A second Lyapunov’s method together with adaptive control theory are utilized for observer’s correction terms synthe- sis and stability proof. Designed adaptive observer under persistence of excitation conditions guarantees local exponential estimation of constant rotor speed and flux linkage vector components of induction ma- chine. From the practical point of view persistency excitation conditions are met if rotor flux linkages are nonzero. Proposed solution investigated by simulations. It is shown, that developed adaptive speed observer provides asymptotic estimation of induction motor currents, speed and flux linkage components under con- stant speed conditions. For varying speed proposed observer provides estimation of required variables with a small dynamic error. Proposed observer can be used in energy generation systems based on induction generators as well as in sensorless induction motor-based drive systems with constant or slowly varying ro- tor speed.

Reformulating Special Relativity on a Two-World Background II

The exposition of the two-world background of the special theory of relativity started in the first part of this paper is continued in this second part. The negative sign of mass in the negative universe is derived from the generalized mass expression in special relativity (SR) in the two-world picture. Four-dimensional inversion is shown to be a special Lorentz transformation in the two-world picture. Also by starting with the negativity of spacetime dimensions (that is, negativity of distances in space and of intervals of time) in the negative universe, derived in part one of this paper, and requiring the symmetry of natural laws between the positive and negative universes, the signs of mass and other physical parameters and physical constants in the negative universe are derived and tabulated. The invariance of natural laws, including the fundamental interactions, in the negative universe is demonstrated. The derived negative sign of mass in the negative universe is a conclusion of a century and a score years of efforts toward the incorporation of the concept of negative mass into physics. It is shown that the anti-particles observed in our universe originate from the negative universe, and conversely, but how a particle can make transition across the event horizon separating the universes without hitting singularity in the Lorentz transformation is as yet unexplained. Experimental test of the two-world picture depends on the possibility of exchange of particles between the two universes without hitting the singularity in LT at the point of making transition across the universes.