An innovative method of fault detection in power transformers

The Bayesian classifier is a priori the optimal solution for minimizing the total error in problems of statistical pattern recognition. The article suggests using the classifier as a regular tool to increase the reliability of defect recognition in power oil-filled transformers based on the results of the analysis of gases dissolved in oil. The wide application of the Bayesian method for solving tasks of technical diagnostics of electrical equipment is limited by the problem of the multidimensional distribution of random parameters (features) and the nonlinearity of classification. The application of a generalized feature of a defect in the form of a nonlinear function of the transformer state parameters is proposed. This simultaneously reduces the dimension of the initial space of the controlled parameters and significantly improves the stochastic properties of the random distribution of the generalized feature. A special algorithm has been developed to perform statistical calculations and the procedure for recognizing the current technical condition of the transformer using the generated decision rule. The presented research results illustrate the possibility of the practical application of the developed method in the conditions of real operation of power transformers.

Solutions for a category of singular nonlinear fractional differential equations subject to integral boundary conditions

We concentrate on a category of singular boundary value problems of fractional differential equations with integral boundary conditions, in which the nonlinear function f is singular at $t=0$ t = 0 , 1. We use Banach’s fixed-point theorem and Hölder’s inequality to verify the existence and uniqueness of a solution. Moreover, also we prove the existence of solutions by Krasnoselskii’s and Schaefer’s fixed point theorems.

Design and FPGA implementation of a memristor-based multi-scroll hyperchaotic system

In this paper, a novel memristor-based multi-scroll hyperchaotic system is proposed. Based on a voltage-controlled memristor and a modulating sine nonlinear function, a novel method is proposed to generate the multi-scroll hyperchaotic attractors. First, a multi-scroll chaotic system is constructed from a three-dimensional chaotic system by designing a modulating sine nonlinear function. Then, a voltage-controlled memristor is introduced into the above-designed multi-scroll chaotic system. Thus, a memristor-based multi-scroll hyperchaotic system is generated, and this hyperchaotic system can produce various coexisting hyperchaotic attractors with different topological structures. Moreover, different number of scrolls and different topological attractors can be obtained by varying the initial conditions of this system without changing the system parameters. The Lyapunov exponents, bifurcation diagrams and basins of attraction are given to analyze the dynamical characteristics of the multi-scroll hyperchaotic system. Besides, the FPGA-based digital implementation of the memristor-based multi-scroll hyperchaotic system is carried out. The experimental results of the FPGA-based digital circuit are displayed on the oscilloscope.

Composite Observer-Based Adaptive Dynamic Surface Control for Fractional-Order Nonlinear Systems with Input Saturation

This article proposes an adaptive neural output feedback control scheme in combination with state and disturbance observers for uncertain fractional-order nonlinear systems containing unknown external disturbance, input saturation and immeasurable state. The radial basis function neural network (RBFNN) approximation is used to estimate unknown nonlinear function, and a state observer as well as a fractional-order disturbance observer is developed simultaneously by using the approximation output of the RBFNN to estimate immeasurable states and unknown compounded disturbances, respectively. Then, a fractional-order auxiliary system is constructed to compensate the effects caused by the saturated input. In addition, by introducing a dynamic surface control strategy, the tedious analytic computation of time derivatives of virtual control laws in the conventional backstepping method is avoided. The proposed method guarantees that the boundness of all signals in the closed loop system and the tracking errors converge to a small neighbourhood around the origin. Finally, two examples are provided to verify the effectiveness of the proposed control method.

Finite-time fuzzy dynamic surface control for permanent magnet synchronous motor stochastic systems with input constraint and load disturbance

In this paper, a finite-time adaptive fuzzy dynamic surface control (DSC) method is proposed for the position tracking control of permanent magnet synchronous motors (PMSMs) stochastic nonlinear system with input constraint and load disturbance. First, the stochastic disturbance of PMSMs is considered in operation, and the fuzzy control method is applied to cope with the stochastic nonlinear function in the motor model. Second, the DSC technique is applied to avoid the “explosion of complexity” in the backstepping design. Moreover, the finite-time control is applied to the stochastic nonlinear system of PMSMs to improve the convergence speed of the system, tracking accuracy, and anti-interference ability. Conclusive, simulation results are given to verify the method that can achieve fast tracking of the desired signal.

Numerical Investigation of the Influence of Precooling on the Thermal Performance of a Borehole Heat Exchanger

Ground source heat pumps (GSHPs), a high-efficiency and energy-saving air-conditioning technology that utilizes shallow geothermal resources for both heating and cooling, are a vital green energy system for residential and commercial buildings. Improving the performance of such a system was the focus of the current research. As soil temperature and thermal radius are two important aspects that affect the performance of ground source heat pump systems, we conducted a new numerical simulation to capture the changes in sensitive factors and propose the optimized paths. The numerical simulation analyzed the thermal characteristics of a borefield under different pre-cooling times and soil types. The results indicated the following: (1) The rate of the ground temperature change with pre-cooling during the discharging period had a faster rise than in the case without pre-cooling. The longer the precooling time was, the smaller the thermal radius became. In particular, when the precooling time was longer than 14 days, the decrease in the thermal radius rate percentages was less than 4%. (2) Among the three kinds of soils compared, the soils with lower thermal conductivity and thermal diffusivity best suppressed the thermal interference effects. (3) Using a multivariate nonlinear function regression model, a simulation formula was proposed to predict- the thermal radius, which considered the factors of thermal diffusivity, precooling time, and discharging time. The prediction deviation was within 14.8%.

Model of normal cracks level formation and opening in stretched reinforced concrete elements

The article highlights the most important studies results of the mechanism of normalcracks formation and opening in stretched reinforced concrete elements during their deformation. Acritical analysis of the existing methods and ways for calculating normal cracks level formation andopening, in which the reinforcement to concrete adhesion is taken into account directly or indirectly,is carried out. The main advantages and disadvantages of each of these methods are indicated. It hasbeen experimentally confirmed that the crack formation process is generally leveled. The mainfeatures and patterns of cracking in stretched reinforced concrete elements and structures arerevealed. The main characteristics of the prototypes are given, according to the test results of whichit was established that in practical calculations of the reinforced concrete elements crack resistance,it is usually possible to restrict oneself to two levels of normal cracking. For the indicated crackinglevels, the corresponding load level, step and crack opening width are established. The expediencyof using in practical calculations the nonlinear function of the reinforcement with concrete averageadhesion stresses is also substantiated. Based on the studies results carried out, the existing methodsfor calculating the normal cracks formation and opening in reinforced concrete elements andstructures were evaluated from the standpoint of local disadvantage of the reinforcement to concreteadhesion.General and simplified methods for calculating normal cracks level formation and opening inreinforced concrete elements have been developed. In them, the direct integration of the expressionfor the concrete and reinforcement mutual displacements is proposed to be replaced not by thenumerical integration of the indicated expression, but by the successive accumulation of the indicateddisplacements. Corresponding statistical comparisons of the calculations results by these methodswith experimental data are carried out. The effectiveness of the developed methods for calculatingnormal cracks level formation and opening by comparing them with existing methods is estimated.

Absolute Stability of Neutral Systems with Lurie Type Nonlinearity

The paper studies absolute stability of neutral differential nonlinear systems x ˙ ( t ) = A x t + B x t − τ + D x ˙ t − τ + b f ( σ ( t ) ) , σ ( t ) = c T x ( t ) , t ⩾ 0 $$ \begin{align}\dot x(t)=Ax\left ( t \right )+Bx\left ( {t-\tau} \right ) +D\dot x\left ( {t-\tau} \right ) +bf({\sigma (t)}),\,\, \sigma (t)=c^Tx(t), \,\, t\geqslant 0 \end{align} $$ where x is an unknown vector, A, B and D are constant matrices, b and c are column constant vectors, 𝜏 > 0 is a constant delay and f is a Lurie-type nonlinear function satisfying Lipschitz condition. Absolute stability is analyzed by a general Lyapunov-Krasovskii functional with the results compared with those previously known.

Effective Emotion Recognition Technique in NLP Task over Nonlinear Big Data Cluster

Human-to-human communication can be achieved not only by body language but also by high-level language. Moreover, information can be conveyed in writing. In particular, the high-level and specific process of logical thinking can be expressed in writing. Text is data that we encounter daily, and there are hidden patterns in it. A person’s cognitive activity, that is, text data, contains the author’s emotions. In the existing text analysis method, simply using the frequency of words has limited interpretability. The model proposed in this paper is a nonlinear emotion system based on emotion to increase document diversity. The purpose is to effectively converge features by assigning weights to a nonlinear function with existing training and learning methods. Our study used the confusion matrix, an area under the receiver operating characteristic curve, and F1-score as evaluation methods. This research created a new error function and measured emotions. The accuracy was 0.9447, and the model’s receiver operating curve peak was 0.9845, which is somewhat similar to that of TF-IDF in the evaluation.