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Using Clustering Methods for the Identification of Acoustic Emission Signals Generated by the Selected Form of Partial Discharge in Oil-Paper Insulation
Published 2018-01-01“…The article presents the results concerning the use of clustering methods to identify signals of acoustic emission (AE) generated by partial discharge (PD) in oil-paper insulation. …”
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River Channel Microgeomorphic Feature Extraction and Potential Sandstorm Source Identification Method Based on a Convolutional Autoencoder Model
Published 2025-01-01“…Current deep learning methods are predominantly applied to visible objects, rendering them unsuitable for latent objects with unstable spatiotemporal distributions, such as potential sandstorm sources. …”
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Minima-YOLO: A Lightweight Identification Method for Lithium Mineral Components Under a Microscope Based on YOLOv8
Published 2025-03-01“…To enable effective deployment and implementation of rapid mineral sorting for valuable ores on edge computing devices, we propose a lightweight identification method for lithium minerals under visible light microscopy based on YOLOv8, named Minima-YOLO. …”
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Research on Cross-Circuitry Fault Identification Method for AC/DC Transmission System Based on Blind Signal Separation Algorithm
Published 2025-03-01“…The traditional AC/DC transmission detection methods have the characteristics of complex detection processes and low fault line identification rates. …”
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Power Operation Violation Identification Method Based on Point Cloud Data Preprocessing and Deep Learning under the Architecture of IoT
Published 2023-01-01“…Therefore, the proposed method can effectively improve the accuracy of power operation violation identification.…”
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Identification of Abnormal Electricity Consumption Behavior of Low-Voltage Users in New Power Systems Based on a Combined Method
Published 2025-05-01“…To further validate the proposed method, a comparative analysis was conducted against the Long Short-Term Memory Autoencoder (LSTM-AE) model. …”
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An Improved Time-Frequency Identification Method for Pipeline Weld EMAE Aliasing Modes With a Focused Electromagnetic Excitation Device
Published 2025-01-01“…However, the complex nature of EMAE signals, which consist of both guided wave and acoustic emission (AE) components, presents challenges in the design of excitation devices and mode identification. This paper presents an improved time-frequency identification method for pipeline weld EMAE aliasing modes with a focused electromagnetic excitation device. …”
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