Article

Welding fault detection and diagnosis using One-Class SVM with distance substitution kernels and random convolutional kernel transform

2023-03-07

Abstract excerpt

<title>Abstract</title> <p>Welding defect detection is still often performed by the human visual inspection or with non destructive tests. These quality inspections methods can be time consuming and can have an important error rate. In this paper, we propose an approach for the detection of welding faults through the detection of abnormal subsequences of the welding voltage signal. The approach is based on the On...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 6f53de37-1474-54ec-b5b2-ff3d1c7f65ed
DOI: 10.21203/rs.3.rs-2378527/v3

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Welding fault detection and diagnosis using One-Class SVM with distance substitution kernels and random convolutional kernel transformDOI 10.21203/rs.3.rs-2378527/v3Read

Research on Few-Shot Fault Diagnosis and Feature Extraction Mechanism Based on ADPCW-ELCNNSemantic proximity Read

Research on Mechanical Fault Diagnosis under Complex Working Conditions Based on Improved YOLOv8Semantic proximity Read

Adaptive Graph Construction and Feature-Enhanced Graph Neural Network for Few-Shot Bearing Fault Diagnosis under Variable ConditionsSemantic proximity Read

ETNeXt: Integrated feature engineering and classification framework for BLDC motor fault detectionSemantic proximity Read

A novel meta-learning method based on relation network for train bearing fault diagnosisSemantic proximity Read

Research on Fault Diagnosis of Water-Based Dynamic Rodless Oil Pumping Machine Based on Manifold Learning and Genetic AlgorithmSemantic proximity Read

A Comprehensive Methodology for CNN Based Fault Identification in Induction Motors – A Case Study for EV’sSemantic proximity Read

Intelligent Diagnosis Model for Rolling Bearing Faults Based on Multi-Modal Data FusionSemantic proximity Read

An Intelligent diagnosis method for rolling bearings based on Ghost module and adaptive weighting moduleSemantic proximity Read

A Robust Deep Learning-Based Fault Diagnosis Method for Rotating MachinerySemantic proximity Read

Rolling bearing fault detection of rotary machine using a novel adaptive sparse representationSemantic proximity Read

A Functional Deep Learning Framework for Rotary Machines Fault DetectionSemantic proximity Read