1,720,969 research outputs found
The analysis of the effects of surface roughness of shafts on journal bearings using recurrent hybrid neural network
No full textThis paper presents an investigation for analysing the load carrying capacity of journal bearing in a variety of conditions using a proposed neural network (NN). The NN structure is very suitable for this kind of system. The network is capable of predicting the pressures of the experimental system. The network has parallel structure and fast learning capacity. It can be outlined from the results for both approaches, NN could be used to model journal bearing systems in real time applications
Design of neural model for analysing journal bearings considering effects of transverse and longitudinal profile
No full textPurpose - The purpose of this paper is to study the effects of shaft surface profiles on the load carriage capacity of journal bearings using an experimental and neural network approach. The paper aims to inspect the performance characteristics of journal bearing systems; the presence of transverse and longitudinal roughness on journal-shaft surfaces is studied using the proposed neural network
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A neural predictor to analyse the effects of metal matrix composite structure (6063 Al/SiCp MMC) on journal bearing
No full textPurpose - To discuss the effects of metal matrix composite (MMC) journal structure on the pressure distribution and, consequently, on the load-carrying capacity of the bearing are predicted using feed forward architecture of neurons
Design of An Artificial Neural Network for Assembly Sequence Planning System
No full textThe problem of assembly sequence generation is complex and has proven to be difficult to solve. Various method have been used in attempting to solve the problem, including mathematical modeling and search techniques. This paper presents an investigation for analyzing assembly sequences of assembly systems with a proposed neural network predictor. The proposed neural network has three layers with recurrent structure. A fast learning algorithm Backpropagation (BP) algorithm is employed for updating the weight parameters of the proposed network
The analysis of the effects of surface texture on the capability of load carriage of journal bearings using neural network
No full textPurpose - This paper investigates the load carrying capacity of the journal bearings with steel shafts with varying surface texture in varying revolutions using experimental and neural network (NN) approach
Design of An Artificial Neural Network for Assembly Sequence Planning System
Get PDFThe problem of assembly sequence generation is complex and has proven to be difficult to solve. Various method have been used in attempting to solve the problem, including mathematical modeling and search techniques. This paper presents an investigation for analyzing assembly sequences of assembly systems with a proposed neural network predictor. The proposed neural network has three layers with recurrent structure. A fast learning algorithm Backpropagation (BP) algorithm is employed for updating the weight parameters of the proposed network
The analysis of effects of shaft surface porosity on journal bearing using experimental and neural network approach
No full textPurpose - The purpose of this paper is to investigate pressure distribution of the journal bearings with aluminium shafts with varying surface porosity in varying revolutions using experimental and neural network approach
Investigation of load carriage capacity of journal bearings by surface texturing
No full textPurpose - The purpose of this paper is to investigate and discuss the influence of the pattern, size and orientation of textures on journal bearing load carriage capacity. An important development in load carriage capacity of journal bearings can be obtained by forming regular surface structure in the form of threaded on their shaft surfaces. This is performed both theoretically and experimentally using shafts with textured (threaded) and untextured surfaces. Each screw thread can serve either as a micro-hydrodynamic bearing in cases of full or mixed lubrication or as a micro reservoir for lubricant in cases of starved lubrication conditions
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