The theoretical model of a Galfenol cantilever energy harvester is investigated for vibration harvesting. Compared with the numerical solution, analytical solution can better capture intrinsic effects physical parameters on performance harvester. In this work, an electromechanical coupled distributed-parameter established based Hamilton's principle, linear constitutive equations magnetostrictive material, and Faraday's law electromagnetic induction. definitions expressions electric damping...

Volatility is an inherent characteristic of wind power. The normal, Weibull, and other distributions are commonly used to describe the characteristics However, many these single distribution models not suitable characterize power, particularly those converging from multiple farm groups. In this study, maximum entropy model utilized as probability density function fit power fluctuations. To evaluate effectiveness performance model, we compared curve cumulative fitting with mixed Gaussian,...

The shape control of probability density function (PDF) is an important subject in stochastic systems. PDF-shaping study has ranged from linear systems to non-linear In this paper we present a technique which useful for class Controlling the PDF requires designing controller make state follow goal PDF; it actually determine gains controller. As know, stationary variable equivalent solution Fokker–Planck–Kolmogorov (FPK) equation arising system driven with Gaussian white noise. After...

Abstract The digitalization enhances nuclear power plant (NPP) instrumentation and control (I&C) system performance, while simultaneously introducing safety reliability challenges. To enhance the stability of distributed (DCS), minimize dangerous failure rate safe system, signal quality bits (SQBs) are widely used in NPP DCS to identify validity important signals. However, past decade or so, numerous unscheduled turbine shutdowns and/or reactor trips have resulted from incorrect SQB...

A novel strategy of probability density function (PDF) shape control is proposed in stochastic systems. The controller designed whose parameters are optimally obtained through the improved particle swarm optimization algorithm. viewed as space position a algorithm and updated continually until makes PDF state variable close possible to expected PDF. technique compared with equivalent linearization simulation experiments. results show superiority effectiveness method. excellent making follow...

This study introduces and analyses existing models of wind speed frequency distribution in farms, such as the Weibull model, Rayleigh lognormal model. Inspired by shortcomings these models, we propose a model based on an exponential polynomial, which can describe actual distribution. The fitting error other common is too large at zero or low speeds. proposed solve this problem. polynomial fit multimodal data well unimodal data. We used linear-least-squares method to acquire parameters for...

The curriculum is the basic basis and carrier of educational teaching activities, it core digital transformation education. With continuous deep integration technology in teaching, how to effectively deal with impact influence innovation breakthrough on better promote students’ inquiry personalized learning has become an urgent problem front us. This paper focuses background issues, aviation maintenance management course as example carry out analysis research, which can provide reference reference..

Existing commercial central air conditioning control systems only the indoor temperature, and setting temperature value depends on experience of operators or managers, cannot be intelligently controlled through demand feedback service objectives. This paper will introduce an intelligent system based human heat radiation automatic adjustment wind field distribution, this applies convolutional neural network analysis for images, according to actual sensory state body distribution personnel, by...

Abstract Traditional distribution models generally have large fitting errors at low wind speeds and poor effects multi-peak speed distributions. In this paper, a novel approach is proposed to fit different distributions, introducing Gumbel into common hybrid models. The model parameters are solved by combination of snake optimizer nonlinear least squares (SO-NLS), using the optimal values obtained method as set initial input vectors for optimizer. Simulation experiments were conducted...

Abstract Wind energy is known for its uncertainty and volatility, necessitating accurate wind speed prediction stable farm operations. To enhance accuracy, this study proposes a BP neural network (BPNN) short-term model based on the Improved Dung Beetle Optimization (IDBO) algorithm. Addressing issue of local optimization reduced accuracy in BPNN optimized by (DBO) algorithm, circle chaotic mapping utilized population initialization to achieve more uniform initial distribution. The improved...

<bold>Purpose:</bold> This study aimed to investigate the relationship between physical activity and mental health of Chinese high school students its mediating mechanism. It provide relevant empirical evidence for improving this group. <bold>Method:</bold> A cross-sectional survey 2,345 in Jiangsu, China, was conducted using International Physical Activity Questionnaire-Short-Chinese Version, Mental Health Scale Secondary School Students Adaptation High Students. After screening...

A method of dynamic fuzzy clustering analysis based on ant colony algorithm for SAR image segmentation is proposed. The confirms dynamically the number and center by stronger ability algorithm. Texture feature calculated according to gray level co-occurrence matrix (GLCM), proper vector selected through statistic analysis. measurement experiment indicates that can segment target fast exactly, an effective

The total variation (TV) regularization-based methods are proven to be effective in removing random noise. However, these solutions usually have staircase effects. This paper proposes a new image reconstruction method based on TV regularization with Lp-quasinorm and group gradient sparsity. In this method, the term of sparsity can retrieve neighborhood information an gradient, constraint characterize gradient. effectively deblur images remove impulse noise well preserve edge reduce effect....