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Slewing bearing

About: Slewing bearing is a research topic. Over the lifetime, 1498 publications have been published within this topic receiving 5309 citations.


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Patent
25 May 2011
TL;DR: The utility model as discussed by the authors provides a large-aperture deep-pile long-auger drilling rig, which comprises a drill rod bracket, an auger stem and a hydraulic power head.
Abstract: The utility model provides a large-aperture deep-pile long-auger drilling rig, which comprises a drill rod bracket, an auger stem and a hydraulic power head, wherein a slewing bearing is arranged on the hydraulic power head; an external gear ring of the slewing bearing is meshed with a planetary gear, and a hydraulic power head assembling seat is rotationally matched with the external gear ring. The utility model adopts the technical scheme that a long auger pile driver has the large power torque-induced precession construction capability, the purpose of completing the large aperture and deep pile foundation construction technique by use of a long auger pile driver is realized, the construction technology of pile foundations of viaducts, high-speed railways, high-rise buildings and the like is simplified, and construction efficiency and quality are greatly improved.

5 citations

Patent
14 Sep 2011
TL;DR: In this article, a vehicular rotary drilling rig with a steel crawler belt chassis and a slewing bearing connecting the lower frame assembly with the upper frame assembly is presented.
Abstract: The utility model discloses a vehicular rotary drilling rig which comprises an automobile chassis, a lower frame assembly, an upper frame assembly, and a slewing bearing connecting the lower frame assembly with the upper frame assembly. The automobile chassis is fixedly connected with the lower frame assembly, thus playing a role of enhancing an automobile chassis frame; and the whole vehicular rotary drilling rig has two cabs, the cab of the upper frame assembly is separated from the automobile cab, and the two cabs are operated independently. A travelling control system is separated from an operating control system, and a hydraulic landing leg is adopted for supporting during operation, thereby eliminating the load of an automobile tire, and improving the operation stability. The vehicular rotary drilling rig overcomes the defects of a rotary drilling rig with a steel crawler belt chassis, and solves the problems of poor on-site maneuvering capability and low movement speed of the rotary drilling rigs.

5 citations

Journal ArticleDOI
Weigang Bao1, Xiaodong Miao1, Hua Wang1, Guichao Yang1, Zhang Hao1 
TL;DR: Experimental results verify that the proposed RUL prediction model can well estimate the RUL of slewing bearings and its performance is superior to some existing methods.
Abstract: Slewing bearing is one of key components in the large size machinery and its remaining useful life (RUL) prediction is required to schedule a future action to avoid catastrophic events, extend life cycles, etc. The vibration-based method has been widely used in the RUL prediction. However, the spurious fluctuation usually exists in the vibration signal when the machines are operated under complex conditions. In order to enhance performance of RUL prediction model, two kinds of new health indicators are constructed by the spatial-temporal (ST) information firstly. One is the temporal indicators, which are derived by using the smoothing mean values of positive and negative vibration signal. Another is the spatial indicator, which is defined by fusing the multi-features extracted from the balance position information of vibration signal. During this process, a new data processing method proposed in this paper improves the quality of the vibration data and increases the number of samples. And then, the RUL prediction model is presented by combing the ST indicators and long-short-term memory network (LSTM) to establish the relationship between the ST indicators and the RUL of slewing bearings and overcome the sparsity of data. Moreover, in order to accelerate the adjustment of ST-LSTM model, a fine-tuning ST-LSTM model is further proposed by incorporating the generative adversarial networks (GAN) into the ST-LSTM. Experimental results verify that the proposed RUL prediction model can well estimate the RUL of slewing bearings and its performance is superior to some existing methods.

5 citations

Patent
29 Aug 2017
TL;DR: The steel ladle full-course covering and uncovering device has low requirements for clearance above a steamer and is low in equipment failure rate, small in maintenance quantity and smooth in production as discussed by the authors.
Abstract: The invention provides a steel ladle full-course covering and uncovering device and a molten steel carrying device. The steel ladle full-course covering and uncovering device comprises a fixed stand column, a lifting hydraulic cylinder, a lifting stand column, a rotation driving motor, a slewing bearing, a rotary frame, a transverse moving hydraulic cylinder and a transverse moving trolley. The fixed stand column is fixed on a platform; the lifting stand column is connected onto the fixed stand column in a sleeving manner; the lifting hydraulic cylinder drives the lifting stand column to go up and down along the fixed stand column; the rotary frame comprises a vertical rod and a horizontal rod connected with the vertical rod; the bottom of the vertical rod and the top of the lifting stand column are connected through the slewing bearing; the rotation driving motor is fixed on the lifting stand column and drives the slewing bearing to rotate so as to drive the rotary frame to rotate; the transverse moving trolley is positioned on the horizontal rod; and the transverse moving hydraulic cylinder drives the transverse moving trolley to move along the horizontal rod. The steel ladle full-course covering and uncovering device has low requirements for clearance above a steel ladle, is free of impact during covering and uncovering, and is low in equipment failure rate, small in maintenance quantity and smooth in production.

5 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202115
202055
201982
2018124
2017134
2016175