Qi et al., 2025 - Google Patents

Vibrating screen fault detection based on video frame prediction

Qi et al., 2025

Document ID
10600576447785722457
Author
Qi J
Wu W
Li H
Publication year
Publication venue
International Journal of Coal Preparation and Utilization

External Links

Snippet

As a key technical equipment for improving coal quality, efficiency and promoting clean and efficient utilization, it is important for vibrating screens to detect their faults quickly and accurately. Traditional vibrating screen fault detection methods usually rely on the vibration …
Continue reading at www.tandfonline.com (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • 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
    • G06F17/30861Retrieval from the Internet, e.g. browsers
    • 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
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01Social networking
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation

Similar Documents

Publication Publication Date Title
Wang et al. An intelligent belt wear fault diagnosis method based on deep learning
Chen et al. Efficient visual content analysis for social media advertising performance assessment
Jeon et al. CutPaste-based anomaly detection model using multi scale feature extraction in time series streaming data
Wang et al. Research on steel surface defect detection system based on YOLOv5s-SE-CA model and BEMD image enhancement
Yu et al. Dynamic convolutional gated recurrent unit attention auto-encoder for feature learning and fault detection in dynamic industrial processes
Chen et al. Generative adversarial synthetic neighbors-based unsupervised anomaly detection
Yang et al. Transformer assisted by DSC and BiLSTM for bearing fault pattern recognition under strong noise interference
Hong et al. TAD-Net: An approach for real-time action detection based on temporal convolution network and graph convolution network in digital twin shop-floor: [version 1; peer review: 2 approved]
Sun et al. A neural network-based control chart for monitoring and interpreting autocorrelated multivariate processes using layer-wise relevance propagation
Sasikumar et al. Investigating explainability of deep learning models for sequential data on stock price prediction
Villegas-Ch et al. Application of deep learning techniques for the optimization of industrial processes through the fusion of sensory data
Jiang et al. Adaptive forecasting of stochastic crack growth using empirical mode decomposition: Gaussian process regression for structural health monitoring
Wei et al. Remaining useful life prediction of rolling bearings using a residual attention network with multi-scale feature extraction and temporal dependency enhancement
Wen et al. Enhanced dual-channel feature fusion approach for rolling bearing fault diagnosis
Mathieu et al. Nonparametric monitoring of sunspot number observations
Mo et al. A lightweight and precision dual track 1D and 2D feature fusion convolutional network for machinery equipment fault diagnosis
Chen et al. A novel few-shot deep regression domain adaptation method with wavelet scattering attention mechanism for fault prognostics
Qi et al. Vibrating screen fault detection based on video frame prediction
Chen et al. A deep integration model of temporal and spatial information for condition monitoring of steam turbine generator sets
Jiang et al. Classification of power quality disturbances in microgrids using a multi-level global convolutional neural network and SDTransformer approach
Xie et al. Multi-scale deep neural network for fault diagnosis method of rotating machinery
Liu RETRACTED ARTICLE: Application of facial expression recognition based on domain-adapted convolutional neural network in English smart teaching system: L. Liu
Goklani Real-Time Plant Disease Detection Using Mobile Device with TensorFlow Lite and Flutter
Rajkamal et al. Hybrid deep learning based vanished object detection and tracking in underwater image processing
Wang et al. Cross-modal deep learning enhanced mixed reality accelerates construction skill transfer from experts to students