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

作　　者：Aaron K. Adik[1] Wilson Wang[1] 

出　　处：《Intelligent Control and Automation》2019年第4期155-167,共13页智能控制与自动化（英文）

摘　　要：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.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.

关 键 词：Adaptive NEURO-FUZZY Systems MACHINE Learning DIAGNOSTICS PATTERN Classification TOWER CRANES Smart Sensors 

分 类 号：TP1[自动化与计算机技术—控制理论与控制工程]