Showing 1 - 20 results of 1,626 for search 'frequency machine (method OR methods)', query time: 0.19s Refine Results
  1. 1

    Frequency Dynamic Characteristic Analysis of Ultra-Low Frequency Oscillation and Multi-Machine GPSS Parameter Tuning Method by ZENG Pijiang, XU Hao, YE Pengju, ZHENG Chao, SAI Xiangyu, CHEN Gang, ZHAO Yong, JIANG Chuyang, GAN Deqiang

    Published 2025-05-01
    “…To improve the analysis of frequency stability and performance of modern power systems, a frequency dynamic characteristic analysis method for ultralow frequency oscillations is proposed, in addition to a multimachine governor power system stabilizer (GPSS) parameter tuning method aimed at enhancing the frequency regulation performance. …”
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    Online High Frequency Impedance Identification Method of Inverter-Fed Electrical Machines for Stator Health Monitoring by Jérémy Creux, Najla Haje Obeid, Thierry Boileau, Farid Meibody-Tabar

    Published 2024-11-01
    “…In this paper, a new characterization method is proposed to monitor the high-frequency stator impedance evolution of voltage source inverter-fed machines. …”
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    Cascaded Detection Method for Ship Targets Using High-Frequency Surface Wave Radar in the Time–Frequency Domain by Zhiqing Yang, Hao Zhou, Yingwei Tian, Gan Liu, Bing Zhang, Yao Qin, Peng Li, Weimin Huang

    Published 2025-07-01
    “…To address this issue, this paper proposes a cascaded detection method in the time–frequency (TF) domain to improve ship detection performance under such conditions. …”
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    Reservoir Fluid Identification Method Based on Multi-Feature Fusion by JIANG Guoqiang, WU Youbin, LAI Fuqiang, HUANG Zhaohui, YI Hongmei, LI Quan, LI Xu, WANG Qi, LUO Rongtao

    Published 2024-12-01
    “…The resistivity of tight sandstone reservoirs in Sulige gas field is greatly affected by the mineralization degree of formation water and siliceous cementation, resulting in the phenomenon of “high resistivity water layer” and difficulty in identifying reservoir fluids. We extract frequency domain information from well logging curves using time-frequency analysis methods, construct a set of time-frequency images, and extract local binary pattern (LBP) and histograms of oriented gradients (HOG) features from time-frequency image data to construct a fused feature matrix of LBP and HOG. …”
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    Studying the frequency spectrum of acoustic emission signals by the infradyne transform method by V.D. Krevchik, A.V. Rudin, V.V. Safonov

    Published 2024-12-01
    “…Conclusions. The use of the method of infradine conversion of acoustic emission signals arising in the elastic deformation mode allowed to significantly reduce the influence of low-frequency external noise signals on the spectrum of recorded acoustic pulses, increase the sensitivity of the acoustic installation and determine the type of micro-defect formed in various machine parts and structures in their operation mode.…”
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    Method of DFIG Cooperating with SVG to Suppress Low-Frequency Oscillation in Power Systems by Lei YANG, Weigong GAN, Shengnan LI, Xin ZHOU, Peng HE, Xin HE, Jie ZHANG, Delin WANG

    Published 2020-11-01
    “…The characteristic root of the system is changed, and the modalities of the oscillating signals are analyzed based on Prony method. The results show that the method can effectively provide positive damping, suppress low-frequency oscillation of the system, accelerate the stabilization of oscillation waveform and improve the small signal stability of the power system.…”
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  12. 12

    Fault Diagnosis Method for Wind Turbine Blades Through the Integration of Mel-Frequency Cepstral Coefficients and Intrinsic Energy Ratio by HE Wei, HUANG Fan, HE Chengqian, HUANG Weihua

    Published 2025-02-01
    “…This paper presents a fault diagnosis method based on Mel-frequency cepstral coefficients (MFCC) and intrinsic energy ratio (IER) to improve efficiency in feature extraction from audio signals for diagnosing faults in wind turbine blades. …”
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    Machine learning methods for spectrally-resolved imaging analysis in neuro-oncology by T. A. Savelieva, I. D. Romanishkin, A. Ospanov, K. G. Linkov, S. A. Goryajnov, G. V. Pavlova, I. N. Pronin, V. B. Loschenov

    Published 2024-12-01
    “…In this paper, we focus on both the physical foundations of such methods and a very important aspect of their application – machine learning (ML) methods for image processing and tissues’ classification.…”
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    Human-Machine Function Allocation Method for Submersible Fault Detection Tasks by Chenyuan Yang, Liping Pang, Wentao Wu, Xiaodong Cao

    Published 2024-11-01
    “…To address this issue, we proposed a human-machine function allocation method based on level of automation (LOA) taxonomy and submersible task complexity (STC), aimed at improving human-machine cooperation in submersible fault detection tasks. …”
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    Evaluating different translation methods: a case study of Chinese graduate students in an MTI program by Tingting Lei, Jeroen van de Weijer

    Published 2025-12-01
    “…This paper compares three approaches to translation: (i) from-scratch human translation (HT), (ii) machine translation combined with post-editing (MTPE), both produced by two independent groups of translation students, and (iii) machine translation (MT), produced by Baidu Chinese-to-English Translation, employing various evaluation methods. …”
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    TF-LIME : Interpretation Method for Time-Series Models Based on Time–Frequency Features by Jiazhan Wang, Ruifeng Zhang, Qiang Li

    Published 2025-04-01
    “…To address this, this paper proposes a time–frequency domain-based time series interpretation method aimed at enhancing the interpretability of models at the time–frequency domain. …”
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    A Case Study of Frequency Analysis of the Contribution of a Single Number Quantity to the Introduction of Rubber Ball Impact Sound and Changes in Assessment Methods by Hee-Mo Goo, Soon-Seong Moon, Jun-Oh Yeon

    Published 2024-12-01
    “…As a result, the pre-approval system showed a high contribution rate mainly in the 63 Hz band, but the post-verification system expanded the contribution rate to the mid-low frequency band of 63–160 Hz. In particular, the evaluation method using the A-weighted maximum floor impact sound level (<i>L</i>′<sub><i>iA</i>,<i>Fmax</i></sub>) of the post-verification system was found to reflect the performance in the mid- and high-frequency band of 125–250 Hz more effectively. …”
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