[go: up one dir, main page]

Hu et al., 2020 - Google Patents

Voltage sag/swell waveform analysis method based on multi‐dimension characterisation

Hu et al., 2020

View PDF @Full View
Document ID
6748920366402654411
Author
Hu W
Xiao X
Zheng Z
Publication year
Publication venue
IET Generation, Transmission & Distribution

External Links

Snippet

Voltage magnitude and sag duration are known as acknowledged basic voltage sag characteristics in the last decades. However, these values cannot meet the demands of waveform analysis in the modern smart grid. Therefore, voltage sag multi‐dimension …
Continue reading at ietresearch.onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image

Similar Documents

Publication Publication Date Title
Hu et al. Voltage sag/swell waveform analysis method based on multi‐dimension characterisation
Xiao et al. Maximal overlap discrete wavelet transform and deep learning for robust denoising and detection of power quality disturbance
Li et al. A power system disturbance classification method robust to PMU data quality issues
Chakravorti et al. Detection and classification of islanding and power quality disturbances in microgrid using hybrid signal processing and data mining techniques
Su et al. Power harmonic and interharmonic detection method in renewable power based on Nuttall double‐window all‐phase FFT algorithm
Hasheminejad et al. Traveling‐wave‐based protection of parallel transmission lines using Teager energy operator and fuzzy systems
Salehi et al. Fault classification and faulted phase selection for transmission line using morphological edge detection filter
Hossam‐Eldin et al. Artificial intelligence‐based short‐circuit fault identifier for MT‐HVDC systems
Ghanbari Autocorrelation function‐based technique for stator turn‐fault detection of induction motor
De et al. Real‐time cross‐correlation‐based technique for detection and classification of power quality disturbances
Ghosh et al. Improved non‐intrusive identification technique of electrical appliances for a smart residential system
Babu et al. A new fast discrete S‐transform and decision tree for the classification and monitoring of power quality disturbance waveforms
Abdelsalam et al. Categorisation of power quality problems using long short‐term memory networks
Biswal et al. Fault‐swing discrimination using Hilbert–Huang transform integrated discrete teager energy operator
Almounajjed et al. Fault diagnosis and investigation techniques for induction motor
Ravindran et al. Interharmonics in PV systems: a review of analysis and estimation methods; considerations for selection of an apt method
Wang et al. Faulty feeder detection based on mixed atom dictionary and energy spectrum energy for distribution network
Wang et al. Transient stability evaluation model based on SSDAE with imbalanced correction
Xi et al. Double‐ended travelling‐wave fault location based on residual analysis using an adaptive EKF
CN118332424B (en) A small sample cross-domain classification prediction method for electromagnetic compatibility defects in battery simulators
Mahmud et al. A robust transmission line fault classification scheme using class-dependent feature and 2-Tier multilayer perceptron network
Jafari et al. Fault detection and isolation based on fuzzy‐integral fusion approach
Samal et al. New signal subspace approach to estimate the inter‐area oscillatory modes in power system using TLS‐ESPRIT algorithm
Li et al. Research on power quality disturbance identification and classification technology in high noise background
Petrović et al. Computational effective modified Newton–Raphson algorithm for power harmonics parameters estimation