Intelligent Control and Automation

Volume 10, Issue 4 (November 2019)

ISSN Print: 2153-0653   ISSN Online: 2153-0661

Google-based Impact Factor: 1.12  Citations  h5-index & Ranking

An Intelligent System for Real-Time Condition Monitoring of Tower Cranes

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DOI: 10.4236/ica.2019.104011    216 Downloads   439 Views  


Reliability and safety are major issues in tower crane applications. A new adaptive neurofuzzy system is developed in this work for real-time health condition monitoring of tower cranes, especially for hoist gearboxes. Vibration signals are measured using a wireless smart sensor system. Fault detection is performed gear-by-gear in the gearbox. A new diagnostic classifier is proposed to integrate strengths of several signal processing techniques for fault detection. A hybrid machine learning method is proposed to facilitate implementation and improve training convergence. The effectiveness of the developed monitoring system is verified by experimental tests.

Cite this paper

Adik, A. and Wang, W. (2019) An Intelligent System for Real-Time Condition Monitoring of Tower Cranes. Intelligent Control and Automation, 10, 155-167. doi: 10.4236/ica.2019.104011.

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