Results 31 to 40 of about 136,308 (262)
Research on a bearing early fault features extraction method
Gong-kuang zidonghua, 2020 In view of problems that early fault signals of rolling bearings are submerged by background noise and fault characteristics are not obvious, a bearing early fault feature extraction method based on wavelet packet decomposition and CEEMD was proposed ...
ZHANG Meng, MIAO Changyun, MENG Deju
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Bearing Fault Diagnosis Method Based on Improved Singular Value Decomposition Package
Sensors, 2023 The singular value decomposition package (SVDP) is often used for signal decomposition and feature extraction. At present, the general SVDP has insufficient feature extraction ability due to the two-row structure of the Hankel matrix, which leads to mode
Huibin Zhu +4 more
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Energies, 2021 Short-Term Load Prediction (STLP) is an important part of energy planning. STLP is based on the analysis of historical data such as outdoor temperature, heat load, heat consumer configuration, and the seasons.
Szabolcs Kováč +3 more
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Transient Signal Spaces and Decompositions
CoRR, 2015 In this paper, we study the problem of transient signal analysis. A signal-dependent algorithm is proposed which sequentially identifies the countable sets of decay rates and expansion coefficients present in a given signal. We qualitatively compare our method to existing techniques such as orthogonal exponential transforms generated from orthogonal ...
Tarek A. Lahlou, Anuran Makur
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Self-Similar Decomposition of Digital Signals [PDF]
Cybernetics and Information Technologies, 2019 Abstract Traditionally, the engineers analyze signals in the time domain and in the frequency domain. These signal representations discover different signal characteristics and in many cases, the exploration of a single signal presentation is not sufficient.
Kiril Alexiev +2 more
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Advances in Mechanical Engineering, 2020 Adaptive sparsest narrow-band decomposition is the most sparse solution to search for signals in the over-complete dictionary library containing intrinsic mode functions, which transform the signal decomposition into an optimization problem, but the ...
Yanfeng Peng +7 more
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Dynamic decomposition of spatiotemporal neural signals [PDF]
PLOS Computational Biology, 2017 Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing.
Ambrogioni, L. +4 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 This article characterized the linear trends and interannual signals of terrestrial water storage (TWS) and meteorological variables including precipitation (P) and evapotranspiration (ET) over the arid Northwestern China (NWC). The relative impaction of
Jianguo Yin +3 more
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A fault diagnosis method for coal mine machinery bearing
Gong-kuang zidonghua, 2019 Aiming at the problem that existing adaptive diagnosis methods of coal mine machinery bearing fault were susceptible to the interference of high frequency noise and intermittent noise, which led to the low accuracy of original signal decomposition and ...
XU Qingqing, ZHAO Haifang, LI Shouju
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Parameter-Adaptive TVF-EMD Feature Extraction Method Based on Improved GOA
Sensors, 2022 In order to separate the sub-signals and extract the feature frequency in the signal accurately, we proposed a parameter-adaptive time-varying filtering empirical mode decomposition (TVF-EMD) feature extraction method based on the improved grasshopper ...
Chengjiang Zhou +5 more
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