The Intelligent Monitoring And Fault Diagnosis System Of Tower Cranes

Tower cranes are major hoisting apparatus of the industrial or civil construction with traits of high working efficiency, wide range of uses, easy manipulation and convenient installation or dismantlement. With the development of the architecture industry in recent years, tower cranes are offered the best opportunities for developing which they have never met. But when the number of tower cranes increases rapidly, the number of the tower- cranes accidents also increases in large quantity. Therefore it is urgent that the safety of tower cranes should be improved and the rate of tower-crane accidents should be reduced .To realize the goal this paper presents a sort of intelligent monitoring system of tower cranes, which is developed on the basis of sensor technology, computers, measuring technology and automation control technology. The system can ensure that cranes work more safely, more smoothly and more efficiently.In this paper, not only is the intelligent monitoring system of tower cranes analyzed and studied, but also the hardware and software design is performed. The industrial control computer is selected as the core of the intelligent monitoring system and through video monitoring technology both the pictures of the crane work status and the dynamic information of tower cranes are live displayed on the CRT in order that drivers can know the status and the trend of the crane easily without looking out of the window of the operator cabin. At the same time, considering the defects of mechanical impacts and low efficiency that exist when the tower-crane hoist winch works, the thesis introduces the fuzzy control technology to regulate the speed of the hook by changing the power frequency of hoist-winch electromotor with frequency-converter, so that the aim of prolonging the service life of the tower crane and raising work efficiency can be attained by increasing or reducing the speed of the hook smoothly and conquering the bad mechanical impacts. In addition, fault diagnosis system is needed to check out the faulty component or trouble unit, so that they can be replaced in time. Therefore in the paper the diagnostic system of electrical equipment malfunction based on BP neural network has been set up to diagnose the fault cause according to the fault phenomena and point out the trouble part at once, cutting down the time of maintenance and repair.The subsequent experiment verified that the above-mentioned intelligent monitoring system of tower cranes is feasible and effective. But if the system is put into practice, the hardware and software of it must be further perfected and debugged.