1.4k citations · 1.6k across the 10 of their papers we have counts for
11 papers
Exploring Sound vs Vibration for Robust Fault Detection on Rotating Machinery
Serkan Kiranyaz, Ozer Can Devecioglu, Amir Alhams +4
Robust and real-time detection of faults on rotating machinery has become an ultimate objective for predictive maintenance in various industries. Vibration-based Deep Learning (DL)…
Sound-to-Vibration Transformation for Sensorless Motor Health Monitoring
Ozer Can Devecioglu, Serkan Kiranyaz, Amer Elhmes +6
Automatic sensor-based detection of motor failures such as bearing faults is crucial for predictive maintenance in various industries. Numerous methodologies have been developed ov…
Zero-Shot Motor Health Monitoring by Blind Domain Transition
Serkan Kiranyaz, Ozer Can Devecioglu, Amir Alhams +5
Continuous long-term monitoring of motor health is crucial for the early detection of abnormalities such as bearing faults (up to 51% of motor failures are attributed to bearing fa…
Zero-Shot Transfer Learning for Structural Health Monitoring using Generative Adversarial Networks and Spectral Mapping
Mohammad Hesam Soleimani-Babakamali, Roksana Soleimani-Babakamali, Kourosh Nasrollahzadeh +3
Gathering properly labelled, adequately rich, and case-specific data for successfully training a data-driven or hybrid model for structural health monitoring (SHM) applications is…
CycleGAN for Undamaged-to-Damaged Domain Translation for Structural Health Monitoring and Damage Detection
Furkan Luleci, F. Necati Catbas, Onur Avci
The recent advances in the data science field in the last few decades have benefitted many other fields including Structural Health Monitoring (SHM). Particularly, Artificial Intel…
Generative Adversarial Networks for Labelled Vibration Data Generation
Furkan Luleci, F. Necati Catbas, Onur Avci
As Structural Health Monitoring (SHM) being implemented more over the years, the use of operational modal analysis of civil structures has become more significant for the assessmen…
Generative Adversarial Networks for Data Generation in Structural Health Monitoring
Furkan Luleci, F. Necati Catbas, Onur Avci
Structural Health Monitoring (SHM) has been continuously benefiting from the advancements in the field of data science. Various types of Artificial Intelligence (AI) methods have b…
Generative Adversarial Networks for Labeled Acceleration Data Augmentation for Structural Damage Detection
Furkan Luleci, F. Necati Catbas, Onur Avci
There has been a major advance in the field of Data Science in the last few decades, and these have been utilized for different engineering disciplines and applications. Artificial…
Early Bearing Fault Diagnosis of Rotating Machinery by 1D Self-Organized Operational Neural Networks
Turker Ince, Junaid Malik, Ozer Can Devecioglu +4
Preventive maintenance of modern electric rotating machinery (RM) is critical for ensuring reliable operation, preventing unpredicted breakdowns and avoiding costly repairs. Recent…
A Review of Vibration-Based Damage Detection in Civil Structures: From Traditional Methods to Machine Learning and Deep Learning Applications
Onur Avci, Osama Abdeljaber, Serkan Kiranyaz +3
Monitoring structural damage is extremely important for sustaining and preserving the service life of civil structures. While successful monitoring provides resolute and staunch in…
1D Convolutional Neural Networks and Applications: A Survey
Serkan Kiranyaz, Onur Avci, Osama Abdeljaber +3
During the last decade, Convolutional Neural Networks (CNNs) have become the de facto standard for various Computer Vision and Machine Learning operations. CNNs are feed-forward Ar…