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Journals / Istanbul University Journal of Electrical and Electronics Engineering / 2001 / Cilt: 1 - Sayı: 1

Condition monitoring and predictive maintenance technologies in industrial processes

Endüstriyel süreçlerde durum izleme ve öngörülü bakım teknolojileri

Serhat ŞEKER
Emine AYAZ
Pages
140–142
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In this sense, this paper presents the importance of condition monitoring and predictive maintenance technologies in industrial processes.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Induction motors are the most widely used electrical drives in industry.
📊
Key Findings & Data:The increased need for monitoring and prognosis of process equipment in industrial systems has increased the efforts towards developing new and reliable maintenace techniques.
💡
Conclusion & Impact:In this sense, this paper presents the importance of condition monitoring and predictive maintenance technologies in industrial processes.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Induction motors are the most widely used electrical drives in industry. The early detection of anomalies in the electrical or mechanical parts of electric motors is important to the safe and economic operation of an industrial process. The increased need for monitoring and prognosis of process equipment in industrial systems has increased the efforts towards developing new and reliable maintenace techniques. In this sense, this paper presents the importance of condition monitoring and predictive maintenance technologies in industrial processes.

Özet

Asenkron motorlar endüstride en fazla kullanılan elektrik makinası tipidir. Elektrik motorlarındaki anormal durumun erken tanısı ise endüstriyel süreçlerin ekonomik ve güvenli işletimi bakımından son derece önemlidir. Son senelerde endüstriyel sistemlerdeki izleme ve tanı çalışmaları, yeni ve güvenilir bakım teknolojilerini geliştirme yönünde artmaktadır. Bu nedenle bu çalışma endüstriyel süreçlerdeki durum izleme ve önörülü bakım teknolojilerini tanıtmaktadır.

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Cite This Article

ŞEKER, S., AYAZ, E. (2022). Condition monitoring and predictive maintenance technologies in industrial processes. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 1 - Sayı: 1, 140–142. https://ajindex.com/articles/543980

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References (10)

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