OpenAlex topic

Engineering Diagnostics and Reliability

This page lists works and academicians tagged with an OpenAlex topic. It is not a YÖKSİS primary or secondary field.

OpenAlex 411 works 8 author topics

Works

411 works

Artificial intelligence systems for tool condition monitoring in machining: analysis and critical review 2023
YÖKSİS SJR Q1 JCR Q1 OpenAlex top 1% OpenAlex 99.9%
No abstract yet.
- MUSTAFA KUNTOĞLU
The experimental application of popular machine learning algorithms on predictive maintenance and the design of IIoT based condition monitoring system 2021
YÖKSİS SJR Q1 JCR Q1 OpenAlex top 10% OpenAlex 99.0%
No abstract yet.
- SELÇUK MISTIKOĞLU
Vibration monitoring for defect diagnosis of rolling element bearings as a predictive maintenance tool: Comprehensive case studies 2005
OpenAlex top 10% OpenAlex 96.3%
No abstract yet.
REQUIRED CHARACTERISTICS OF BLANKET FOR QUALITY IN PRINTING 2015
YÖKSİS
No abstract yet.
- CENGİZ ŞAHİN
Investıgatıng The Refunctıonıng Of Dıyarbakır Cıtadel Museum Area In Terms Of Its Use As An Educatıonal Tool 2015
YÖKSİS
No abstract yet.
- EMİNE EKİNCİ DAĞTEKİN
The reflections of user requirements to living spaces in traditional Diyarbakir houses according to environmental conditions 2015
YÖKSİS
No abstract yet.
- CAN TUNCAY AKIN
Application of failure modes and effects analysis to main engine crankcase explosion failure on board ship 2013
YÖKSİS SJR Q1 JCR Q2 OpenAlex top 10% OpenAlex 97.4%
No abstract yet.
- METİN ÇELİK
Fault Tree Analysis of chemical cargo contamination by using fuzzy approach 2015
OpenAlex top 10% OpenAlex 96.9%
No abstract yet.
A Simple Real Time Fault Signature Monitoring Tool for Motor Drive Embedded Fault Diagnosis Systems 2011
YÖKSİS SJR Q1 JCR Q1 OpenAlex top 1% OpenAlex 99.4%
The reference frame theory constitutes an essential aspect of electric machine analysis and control. In this study, apart from the conventional applications, it is reported that the reference frame theory approach can successfully be applied to real-time fault diagnosis of electric machinery systems as a powerful tool…
- UMUT ORGUNER
Machine learning for fault analysis in rotating machinery: A comprehensive review 2023
YÖKSİS SJR Q1 JCR Q1 OpenAlex top 1% OpenAlex 99.3%
As the concept of Industry 4.0 is introduced, artificial intelligence-based fault analysis is attracted the corresponding community to develop effective intelligent fault diagnosis and prognosis (IFDP) models for rotating machinery. Hence, various challenges arise regarding model assessment, suitability for real-world…
- DERYA BİRANT
Machine learning for fault analysis in rotating machinery: A comprehensive review 2023
YÖKSİS SJR Q1 JCR Q1 OpenAlex top 1% OpenAlex 99.3%
As the concept of Industry 4.0 is introduced, artificial intelligence-based fault analysis is attracted the corresponding community to develop effective intelligent fault diagnosis and prognosis (IFDP) models for rotating machinery. Hence, various challenges arise regarding model assessment, suitability for real-world…
- DUYGU BAĞCI DAŞ
A novel feature extraction method for bearing fault classification with one dimensional ternary patterns 2020
YÖKSİS SJR Q1 JCR Q1 OpenAlex top 10% OpenAlex 97.8%
No abstract yet.
- MELİH KUNCAN

Academicians

8 academicians