%0 Journal Article
%T An Intelligent System for Real-Time Condition Monitoring of Tower Cranes
%A Aaron K. Adik
%A Wilson Wang
%J Intelligent Control and Automation
%P 155-167
%@ 2153-0661
%D 2019
%I Scientific Research Publishing
%R 10.4236/ica.2019.104011
%X 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.
%K Adaptive Neuro-Fuzzy Systems
%K Machine Learning
%K Diagnostics
%K Pattern Classification
%K Tower Cranes
%K Smart Sensors
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=96572