The health condition of rolling bearing possesses a significant impact on the safety and efficiency rotating machinery. Accordingly, to diagnose faults in bearings effectively accurately, novel hybrid approach coupling variational mode decomposition (VMD), composite multiscale fine-sorted dispersion entropy (CMFSDE) support vector machine (SVM) optimized by mutation sine cosine algorithm Harris hawks optimization (MSCAHHO) is proposed paper. Firstly, VMD employed decompose raw vibration...

In this article, a hypersensitive multispectral partial discharge (PD) optical sensor array was developed, by which the pulses in seven independent bands can be acquired simultaneously. By using array, for three typical PDs gas insulated system were obtained experimentally and analyzed with phase-based (phase-resolved) nonphase-based (spectral-ratio-based) characteristics, respectively. It indicates that characteristics produced specific defect provide unique spectral signatures mode as well...

A hydropower generator (HPG) is the key equipment for power grid peaking and frequency modulation, whose faults are usually in form of vibration. Hence, it great significance to measure vibration trend an HPG which can contribute achieving advanced management predictive maintenance, thus improving stability system enhancing economic efficiency. For this purpose, a novel measuring model vibrational based on optimal variational mode decomposition (OVMD) least squares support vector machine...

Accurate vibrational trend measuring for hydroelectric unit (HEU) is of great significance safe and economic operation unit. For this purpose, a novel hybrid approach based on variational mode decomposition (VMD), singular value (SVD)-based phase space reconstruction (PSR) least squares support vector machine (LSSVM) improved with adaptive sine cosine algorithm optimization (ASCA) proposed. Firstly, the raw vibration signal preprocessed into several components different scales by VMD, while...

As a crucial and widely used component in industrial fields with great complexity, the health condition of rotating machinery is directly related to production efficiency safety. Consequently, recognizing diagnosing machine faults remain be one main concerns preventing failures mechanical systems, which can enhance reliability systems. In this paper, novel approach based on blind parameter identification MAR model mutation hybrid GWO‐SCA optimization proposed diagnose for machinery. Signals...

Space charge injection in polypropylene (PP) significantly weakens the stability of HVDC cables. Impact copolymer (IPC) is often used as insulation material for AC cables, but DC field, IPC has problem space accumulation. This because there a multi-phase structure inside to which ethylene monomer was added production process, and difference physicochemical properties each phase an important reason accumulation material. In this work, vinyl phases propenyl two types were separated. The film...

Accurate wind speed prediction plays a significant role in reasonable scheduling and the safe operation of power system. However, due to non-linear non-stationary traits time series, construction an accuracy forecasting model is difficult achieve. To this end, novel synchronous optimization strategy-based hybrid combining multi-scale dominant ingredient chaotic analysis kernel extreme learning machine (KELM) proposed, for which integrates variational mode decomposition (VMD), singular...

Accurate vibrational tendency forecasting of hydropower generator unit (HGU) is great significance to guarantee the safe and economic operation station. For this purpose, a novel hybrid approach combined with multiscale dominant ingredient chaotic analysis, kernel extreme learning machine (KELM), adaptive mutation grey wolf optimizer (AMGWO) proposed. Among methods, variational mode decomposition (VMD), phase space reconstruction (PSR), singular spectrum analysis (SSA) are suitably...

Rolling bearing is of great importance in modern industrial products, the failure which may result accidents and economic losses. Therefore, fault diagnosis rolling significant necessary can enhance reliability efficiency mechanical systems. a novel method for based on semi-supervised clustering support vector data description (SVDD) with adaptive parameter optimization improved decision strategy proposed this study. First, variational mode decomposition (VMD) was applied to decompose...

Rolling bearings are a vital and widely used component in modern industry, relating to the production efficiency remaining life of device. An effective robust fault diagnosis method for rolling can reduce downtime caused by unexpected failures. Thus, novel fine-sorted dispersion entropy mutation sine cosine algorithm particle swarm optimization (SCA-PSO) optimized support vector machine (SVM) is presented diagnose various sizes, locations motor loads. Vibration signals collected from...

In this paper, we extend the work by Sato devoted to development of economic growth models within framework Lie group theory. We propose a new model based on assumption logistic in factors and derive corresponding production functions, as well compatible notion wage share. process, it is shown that functions compare reasonably against relevant data. The problem maximisation profit under conditions perfect competition solved with aid one these functions. addition, explained rigorous...

This paper presents a modified Bidirectional Reflectance Distribution Function (BRDF) model based on the Cauchy–Lorentz distribution that accurately characterizes reflected energy of typical materials, such as metals and coatings in hemispherical space. The proposed overcomes problem large errors classical models when detecting angles far away from specular reflection angle by dividing light into reflection, directional diffuse ideal components. newly added component is represented...

Cycle slip determination plays an important role in high-precision data processing and application of global navigation satellite systems (GNSS). The TurboEdit method consists the Melbourne-Wubbena (MW) geometry-free phase (GF) combination. It can correctly detect repair cycle most cases. detection (CSD) with GF is disturbed by severe ionospheric delay variations; moreover, CSD or (CSR) MW faces risk disturbance from large pseudorange errors. Hence, would be difficult under some extreme...