Intelligent Fault Diagnosis

Intelligent fault diagnosis (IFD) aims to automatically identify malfunctions in complex systems using data-driven methods, primarily to improve efficiency and safety. Current research emphasizes robust model development, focusing on techniques like federated and transfer learning to address data scarcity and heterogeneity across diverse industrial settings, as well as incorporating interpretability and resilience to adversarial attacks. These advancements are crucial for improving the reliability and maintainability of industrial equipment and processes, impacting various sectors from manufacturing to power generation.

Papers

November 15, 2024

Domain Adaptation-based Edge Computing for Cross-Conditions Fault Diagnosis
Yanzhi Wang, Chu Wang, Jinhong Wu, Ziyang Yu, Qi Zhou
Edge Computing Medical Diagnosis Internet Service Domain Fault Diagnosis Post Fault Trajectory Fault Diagnosis Method Rapid Diagnosis Intelligent Fault Diagnosis

November 11, 2024

Research on an intelligent fault diagnosis method for nuclear power plants based on ETCN-SSA combined algorithm
Jiayan Fang, Siwei Li, Yichun Wu
Practical Algorithm Deep Convolutional Neural Network DH Research Temporal Convolutional Network Fault Diagnosis Nuclear Reactor Fault Diagnosis Method Intelligent Fault Diagnosis Sparrow Search Algorithm

November 9, 2024

Intelligent Fault Diagnosis of Type and Severity in Low-Frequency, Low Bit-Depth Signals
Tito Spadini, Kenji Nose-Filho, Ricardo Suyama
Fine Tuning High Frequency Imbalanced Datasets Audio Datasets Severity Prediction Intelligent Fault Diagnosis Face Normalization Bit Depth

July 30, 2024

Industrial-Grade Smart Troubleshooting through Causal Technical Language Processing: a Proof of Concept
Alexandre Trilla, Ossee Yiboe, Nenad Mijatovic, Jordi Vitrià
Causal Relationship High Impact Concept Causal Learning Predictive Maintenance Causal Approach Partial Proof Causal Explanation Causal Machine Intelligent Fault Diagnosis

December 29, 2023

FedLED: Label-Free Equipment Fault Diagnosis with Vertical Federated Transfer Learning
Jie Shen, Shusen Yang, Cong Zhao, Xuebin Ren, Peng Zhao, Yuqian Yang, Qing Han, Shuaijun Wu
Vertical Federated Learning Label Free Fault Diagnosis Federated Transfer Learning Intelligent Fault Diagnosis

December 5, 2023

Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis
Florent Forest, Olga Fink
Unsupervised Domain Adaptation Adaptive Teaching Intelligent Fault Diagnosis

October 7, 2023

EdgeFD: An Edge-Friendly Drift-Aware Fault Diagnosis System for Industrial IoT
Chen Jiao, Mao Fengjian, Lv Zuohong, Tang Jianhua
Extreme Edge Drift Detection Weight Update Data Drift Intelligent Fault Diagnosis

February 12, 2023

SCLIFD:Supervised Contrastive Knowledge Distillation for Incremental Fault Diagnosis under Limited Fault Data
Peng Peng, Hanrong Zhang, Mengxuan Li, Gongzhuang Peng, Hongwei Wang, Weiming Shen
Class Incremental Learning Fault Detection Long Tailed Fault Diagnosis Intelligent Fault Diagnosis Limited Fault

November 17, 2022

Personalized Federated Learning for Multi-task Fault Diagnosis of Rotating Machinery
Sheng Guo, Zengxiang Li, Hui Liu, Shubao Zhao, Cheng Hao Jin
Data Heterogeneity Personalized Federated Learning Robot Team Fault Diagnosis Industrial Machine Intelligent Fault Diagnosis

September 26, 2022

Review for AI-based Open-Circuit Faults Diagnosis Methods in Power Electronics Converters
Chuang Liu, Lei Kou, Guowei Cai, Zihan Zhao, Zhe Zhang
Narrative Review Intelligent Fault Diagnosis Power Electronics Converter Open Circuit Fault

September 5, 2022

TFN: An Interpretable Neural Network with Time-Frequency Transform Embedded for Intelligent Fault Diagnosis
Qian Chen, Xingjian Dong, Guowei Tu, Dong Wang, Baoxuan Zhao, Zhike Peng
Multi Scale Time Frequency Interpretable Neural Network Intelligent Fault Diagnosis Time Frequency Information

March 14, 2022

RES-HD: Resilient Intelligent Fault Diagnosis Against Adversarial Attacks Using Hyper-Dimensional Computing
Onat Gungor, Tajana Rosing, Baris Aksanli
Adversarial Attack Hyperdimensional Computing IOT Technology Intelligent Fault Diagnosis

December 11, 2021

Technical Language Supervision for Intelligent Fault Diagnosis in Process Industry
Karl Löwenmark, Cees Taal, Stephan Schnabel, Marcus Liwicki, Fredrik Sandin
Language Supervision Text Supervision Fault Diagnosis Method Intelligent Fault Diagnosis Natural Language Annotation

November 12, 2021

Guided Sampling-based Evolutionary Deep Neural Network for Intelligent Fault Diagnosis
Arun K. Sharma, Nishchal K. Verma
Deep Learning Model Policy Gradient DNN Architecture Evolutionary Approach Intelligent Fault Diagnosis Evolutionary Deep Learning

Intelligent Fault Diagnosis

Papers

Domain Adaptation-based Edge Computing for Cross-Conditions Fault Diagnosis

Research on an intelligent fault diagnosis method for nuclear power plants based on ETCN-SSA combined algorithm

Intelligent Fault Diagnosis of Type and Severity in Low-Frequency, Low Bit-Depth Signals

Industrial-Grade Smart Troubleshooting through Causal Technical Language Processing: a Proof of Concept

FedLED: Label-Free Equipment Fault Diagnosis with Vertical Federated Transfer Learning

Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis

EdgeFD: An Edge-Friendly Drift-Aware Fault Diagnosis System for Industrial IoT

SCLIFD:Supervised Contrastive Knowledge Distillation for Incremental Fault Diagnosis under Limited Fault Data

Personalized Federated Learning for Multi-task Fault Diagnosis of Rotating Machinery

Review for AI-based Open-Circuit Faults Diagnosis Methods in Power Electronics Converters

TFN: An Interpretable Neural Network with Time-Frequency Transform Embedded for Intelligent Fault Diagnosis

RES-HD: Resilient Intelligent Fault Diagnosis Against Adversarial Attacks Using Hyper-Dimensional Computing

Technical Language Supervision for Intelligent Fault Diagnosis in Process Industry

Guided Sampling-based Evolutionary Deep Neural Network for Intelligent Fault Diagnosis