Applications of machine learning to machine fault diagnosis: A review and roadmap

A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings

Intelligent fault diagnosis of rolling bearing using hierarchical convolutional network based health state classification

A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions

Since the early 1980s, wind power technology has experienced an immense growth with respect to both the turbine size and market share. As the demand for large-scale wind turbines and lor operation & maintenance cost continues to raise, the interest on condition monitoring system has increased rapidly. The main components of wind turbines are the focus of all CMS since they frequently cause high repair costs and equipment downtime. However, vast quantities of their failures are caused due to a bearing failure. Therefore, bearing condition monitoring becomes crucial. This paper aims at providing a state-of-the-art review on wind turbine bearing condition monitoring techniques such as acoustic measurement, electrical effects monitoring, power quality, temperature monitoring, wear debris analysis and vibration analysis. Furthermore, this paper will present a literature review and discuss several technical, financial and operational challenges from the purchase of the CMS to the wind farm monitoring stage.

A review of wind turbine bearing condition monitoring: State of the art and challenges

/pdf/fault-diagnosis-and-detection-4yp697yjy3.pdf

Fault Diagnosis and Detection

Modelling of the Effect of Concentration and Temperature on Reaction Time By Means of Artificial Neural Networks

Recent progress on computer technologies is focused on mobility and size reduction rather than functionality. That provided us researchers and commercial manufacturers with low-cost, compact and high-capability electronic hardware. Visual sensors are no exception. Hereby in the light of recent technological advance it is possible to organize sensors with a two dimension array hierarchy and build very-capable systems which are not enormous. These systems can be used and is being used in variety of needs like surveillance, virtual environment applications and robotic vision. Nature is a step ahead of us in this subject.

http://ieeexplore.ieee.org/iel7/7383115/7394429/07394526.pdf

A survey of insect eye inspired visual sensors

Bu çalışmada, hasar tespiti ve yapısal durum izleme için Alüminyum 2024 T-3 plakası üzerinde oluşturulan 2 ile 5 cm arası kesikler Lamb dalgaları ile incelenmiş ve Lamb dalgalarının simetrik ve asimetrik modlarının karşılaştırılması yapılmıştır. Toplanan yüzey frekans cevaplarının zarfları Hilbert dönüşümü ile elde edilmiş ve her bir hasarın zayıflama miktarı yüzdelik olarak gösterilmiştir. Elde edilen sonuçlar, her iki Lamb dalga modunun Alüminyum 2024 T-3 plakada oluşturulan kesik boyutlarının araştırılmasında kullanılabileceğini göstermektedir. In this study, cuts between 2 and 5 cm formed on Aluminum 2024 T-3 plate for damage detection and structural health monitoring were examined with Lamb waves and the symmetric and asymmetric modes of Lamb waves were compared. The envelopes of the acquired surface frequency responses are obtained by Hilbert transform and the amount of attenuation of each damage is shown as a percentage. The results show that both Lamb wave modes can be used to investigate the cut dimensions created in the Aluminum 2024 T-3 plate.

/pdf/determination-of-damage-length-in-aluminum-2024-t-3-plate-by-32qdh4379h.pdf

Muhammet Unal

Papers

Fault Diagnosis and Detection

Modelling of the Effect of Concentration and Temperature on Reaction Time By Means of Artificial Neural Networks

A survey of insect eye inspired visual sensors

Determination of damage length in aluminum 2024 T-3 plate by lamb wave

Performance-Aware Data Management for Remote Sensing Big Data