Explainable AI Algorithms for Vibration Data-Based Fault Detection: Use Case-Adadpted Methods and Critical Evaluation

Vibration analysis process based on spectrogram using gradient class activation map with selection process of CNN model and feature layer

(2022) Youngjun Yoo et al.   DISPLAYS

Vibration-based gear continuous generating grinding fault classification and interpretation with deep convolutional neural network

(2022) Chenyu Liu et al.   Journal of Manufacturing Processes

Explainable AI for Bearing Fault Prognosis Using Deep Learning Techniques

(2022) Deva Chaitanya Sanakkayala et al.   Micromachines

An Explainable AI-Based Fault Diagnosis Model for Bearings

(2021) Md Junayed Hasan et al.   SENSORS

Condition Monitoring of Drive Trains by Data Fusion of Acoustic Emission and Vibration Sensors

(2021) Oliver Mey et al.   Processes

Bearing Fault Diagnosis Using a Grad-CAM-Based Convolutional Neuro-Fuzzy Network

(2021) Cheng-Jian Lin et al.   Mathematics

Bearing Fault Diagnosis Using Grad-CAM and Acoustic Emission Signals

(2020) JaeYoung Kim et al.   Applied Sciences-Basel

Review of tool condition monitoring in machining and opportunities for deep learning

(2020) G. Serin et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Role of artificial intelligence in rotor fault diagnosis: a comprehensive review

(2020) Aneesh G. Nath et al.   ARTIFICIAL INTELLIGENCE REVIEW

Stable and explainable deep learning damage prediction for prismatic cantilever steel beam

(2020) Darian M. Onchis et al.   COMPUTERS IN INDUSTRY

An Explainable Convolutional Neural Network for Fault Diagnosis in Linear Motion Guide

(2020) Min Su Kim et al.   IEEE Transactions on Industrial Informatics

Understanding and Improving Deep Learning-Based Rolling Bearing Fault Diagnosis with Attention Mechanism

(2019) Xiang Li et al.   SIGNAL PROCESSING

Order spectrogram visualization for rolling bearing fault detection under speed variation conditions

(2019) Yi Wang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Data-Driven Methods for Predictive Maintenance of Industrial Equipment: A Survey

(2019) Weiting Zhang et al.   IEEE Systems Journal

A new dynamic predictive maintenance framework using deep learning for failure prognostics

(2019) Khanh T.P. Nguyen et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Understanding and Learning Discriminant Features based on Multiattention 1DCNN for Wheelset Bearing Fault Diagnosis

(2019) Huan Wang et al.   IEEE Transactions on Industrial Informatics

Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning

(2018) Jiedi Sun et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Artificial intelligence for fault diagnosis of rotating machinery: A review

(2018) Ruonan Liu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Visual interpretability for deep learning: a survey

(2018) Quan-shi Zhang et al.   Frontiers of Information Technology & Electronic Engineering

Peeking inside the black-box: A survey on Explainable Artificial Intelligence (XAI)

(2018) Amina Adadi et al.   IEEE Access

Deep learning and its applications to machine health monitoring

(2018) Rui Zhao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Convolutional Neural Network Based Fault Detection for Rotating Machinery

(2016) Olivier Janssens et al.   JOURNAL OF SOUND AND VIBRATION

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

(2015) Sebastian Bach et al.   PLoS One

A machine learning approach for the condition monitoring of rotating machinery

(2014) Dimitrios Kateris et al.   Journal of Mechanical Science and Technology

State-of-the-Art Predictive Maintenance Techniques

(2010) H. M. Hashemian   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Rolling element bearing diagnostics—A tutorial

(2010) Robert B. Randall et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING