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Fault Detection For Low Speed Heavy Duty Crane Slewing Bearing Based On Acoustic Emission

Posted on:2015-02-15Degree:MasterType:Thesis
Country:ChinaCandidate:C ChenFull Text:PDF
GTID:2252330425486974Subject:Circuits and Systems
Abstract/Summary:PDF Full Text Request
The slewing mechanism is the key part to connect the crane base and upper movableparts, crane’s slewing mechanism is an important part of the crane. Some slewingmechanism’s parts which are connecting bolts, raceways, rolling elements and ring gearare very sensitive to failures. The crane operation state will be affected seriously, andcasualties will be caused. So study on slewing mechanism detection technology has greatsignificance for national economy and staff safety. In this paper, acoustic emissiontechnology is applied to detect crane slewing mechanism. The slewing mechanismdetection system had been built and a large amount of experiment study had been done.The crane slewing mechanism detection system had been built. The system consists ofcrane model, AE sensor, preamplifier, acquisition cards, computers and signal processingform. This system can simulate crane’s operation which slewing mechanism with nodefect and with three kinds of defects under different operation conditions. In addition, thepreamplifier and filter circuit had been designed and simulated.By use of the experimental platform, the acoustic emission detection for the slewingmechanism with no defect and the slewing mechanism with rolling defect, inner rollingdefect and outer rolling defect had been accomplished under all kinds of conditions (atdifferent load, at different speed, at different rotation direction). A large amount ofexperiment data had been acquired. By use of the parameter analysis method and thewaveform analysis method, experiment data had been analyzed and the defect signalfeatures had been gained.Acoustic emission detection for many cranes on the project site had been completed. Alarge amount of field data had been acquired. The field data were analyzed according tothe research methods and results from the experiment platform. The detection conclusionfor all cranes had been given.
Keywords/Search Tags:The slewing mechanism, Crane, Acoustic emission technique, Parameteranalysis, Waveform analysis
PDF Full Text Request
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