• Journal of Mechanical Science and Technology
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• 제17권2호
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• pp.215-220
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• 2003

Trepan prevents the wear of the inside part of a bearing when the initial shaft rotates. It continuously contacts with the eccentric part of the shaft in rotation and is loaded repeatedly. Therefore, even if an early crack of a trepan part is small, the crack may progress by the repeated load. If the crack progresses, very small chips come out. This Is put in the rotor and prevents the rotation of the compressor, There can be leaks in a microgroove and extreme wear can occur due to lack of oil on the surface contact part. Therefore, this study was carried out to compare and investigate the trepan strength and deflection characteristics between trepan locations and dimension changes using the finite element method and search a motor bearing for a model with bigger stiffness of a trepan part and the same deflection.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.950-953
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• 2002

Trepan prevents wear of an inside part of a bearing when the initial shaft rotates. It continuously contacts with the eccentric part of the shaft in rotation and is loaded repeatedly. Therefore, even if an early crack of a trepan part is small, a crack progresses by a repeated load. If a crack progresses, very small chips come out. This is pill in the rotor and prevents rotation of the compressor. There can be leaks in a microgroove and extreme wear can occur due to lack of oil on the surface contact pan. Therefore, this study was carried out to compare and investigate trepan strength and deflection characteristics between trepan locations and dimension changes using a finite element method and search a motor bearing for a model with bigger stiffness of a trepan part and the same deflection. And then. five different types of the oil groove model were chosen to prevent small crack and considered also machining ability and the analysis was carried out on oil feeding flow.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.128-132
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• 2001

In this paper, we evaluate and contrast four neural network rule extraction approaches for credit scoring. Experiments are carried our on three real life credit scoring data sets. Both the continuous and the discretised versions of all data sets are analysed The rule extraction algorithms, Neurolonear, Neurorule. Trepan and Nefclass, have different characteristics, with respect to their perception of the neural network and their way of representing the generated rules or knowledge. It is shown that Neurolinear, Neurorule and Trepan are able to extract very concise rule sets or trees with a high predictive accuracy when compared to classical decision tree(rule) induction algorithms like C4.5(rules). Especially Neurorule extracted easy to understand and powerful propositional if -then rules for all discretised data sets. Hence, the Neurorule algorithm may offer a viable alternative for rule generation and knowledge discovery in the domain of credit scoring.