• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.464-469
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• 1999

Recently, the need for designing multi-stage gear drive has been increased as the hear drives are used more in the applications with high-speed and small volume. The design of multi-stage gear drives includes not only dimensional design but also configuration design of various machine elements. Until now, however, the researches on the design of gear drives are mainly focused on the single-stage gear drives and the design practices for multi-stage gear drives, especially in configuration design activity, mainly depend on the experiences and 'sense' of the designer by trial and error. We propose a design algorithm to automate the dimension design and the configuration design of multi-stage gear drives. The design process consists of four steps. The number of stage should be determined in the first step. In second step, the gear ratios of each reduction stage are determined using random search, and the ratios are basic input for the dimension design of gears, which is performed by the exhaustive search in third step. The designs of gears are guaranteed by the pitting resistance and bending strength rating practices by AGMA rating formulas. In configuration design, the positions of gears are determined to minimize the volume of gearbox using simulated annealing algorithm. The effectiveness of the algorithm is assured by the design example of a 4-stage gear drive.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3135-3137
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• 1999

We propose two robust blind equalization algorithms based on multi-stage clustering blind equalization algorithm, which are called a complex classification update algorithm(CCUA) and an error compensation algorithm(ECA). The first algorithm is a tap-updating algorithm which each computes classified real and imaginary parts in order to reduce computations and the complexity of implementation as a stage increase. The second one is a algorithm which can achieve faster convergence speed because error of equalizer input make always fixed. Test results confirm that the proposed algorithms with faster convergence and lower complexity outperforms both constant modulus algorithm (CMA) and conventional multi-stage blind clustering algorithm(MSA) in reducing the SER as well as the MSE at the equalizer output.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2451-2458
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• 1997

Adaptive channel equalization complished without resorting to a training sequence is known as blind equalization. In this paper, in order to increase the speed of the convergence and to reduce the steady-state mean squared error simulatneously, we propose the multi-stage DD(decision-direct) algorithm derived from the combination of the Sato algorithm and the decision-directed algorithm. In the starting stage, the multi-stage DD algorithm is identical to the Sato algorithm which guarantees the convergence of the equalizer. As the blind equalizer converges, the number of the level of the quantizers is increased gradally, so that the proposed algorithm operates identical to the decision-directed algorithm which leads to the low error power after the convergence. Therefore, the multi-stage DD algorithm obtains fast convergence rate and low steady state mean squared error.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.53-58
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• 2003

In recent years, the need for multi-stage gear drives, which highly reduce output speed, has been increased. However, the design of multi-stage gear drives have been carried out by a limited number of experts. The consideration for the direction of input and output axes also makes their design very difficult. The purpose of this study is to develop an algorithm for automatically generating complex multi-stage gear drives and to implement a design supporting system for multi-stage gear drives. There are 4 stages in the proposed algorithm, and major design parameters,.such as the direction of input and output axes, reduction ratio, etc. are set up in the first stage. In the second stage, all mechanisms are generated, and various rules are applied to select feasible mechanisms. In the third stage, the gear ratio of each stage is divided from total gear ratio. Next, the specifications of gears for feasible mechanisms are calculated and their bending strength and surface durability are estimated. In the forth stage, appraised indexes are calculated and provided to support the estimation of the generated gear drives.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.4
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• pp.41-48
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• 2005

In recent years, the need for multi-stage gear drives which highly reduce output speed has been increased. However, the design of multi-stage gear drives has been carried out by a limited number of experts. The consideration for the direction of input and output axes also makes their design very difficult. The purpose of this study is to develop an algorithm for automatically generating complex multi-stage gear drives and to implement a design supporting system for multi-stage gear drives. There are 4 stages in the proposed algorithm, and major design parameters, such as the direction of input and output axes, reduction ratio, etc. are set up in the first stage. In the second stage, all mechanisms are generated, and various rules are applied to select feasible mechanisms. In the third stage, the gear ratio of each stage is divided from total gear ratio. Next, the specifications of gears for feasible mechanisms are calculated and their bending strength and surface durability are estimated. In the forth stage, appraised indexes are calculated and provided to support the estimation of the generated gear drives.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.1957-1967
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• 1997

Adaptive channel equlization accomplished without resorting to a training sequence is known as blind equalization. In this paper, in order to reduce the speed of the convergence and the steady-state mean squared error simultaneously, we propose the multi-stage RD(radius-directed) algorithm derived from the combination of the constant modulus algorithm and the radius-directed algorithm. In the starting stage, multi-stage RD algorithm are identical to the constant modulus algorithm which guarantees the convergence of the equalizer. As the blind identical to the constant modulus algorithm which guarantees the convergence of the equalizer. As the blind equalizer converges, the number of the level of the quantizers is increased gradually, so that the proposed algorithm operate identical to the radius-directed algorithm which leads to the low error power after the covnergence. Therefore, the multi-stage RD algorithm obtains fast convergence rage and low steady stage mean square error.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1256-1275
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• 2014

As one of the new self-organizing and self-configuration broadband networks, wireless mesh networks are being increasingly attractive. In order to solve the load balancing problem in wireless mesh networks, this paper proposes a novel multi-path routing algorithm based on clustering (Cluster_MMesh) for wireless mesh networks. In the clustering stage, on the basis of the maximum connectivity clustering algorithm and k-hop clustering algorithm, according to the idea of maximum connectivity, a new concept of node connectivity degree is proposed in this paper, which can make the selection of cluster head more simple and reasonable. While clustering, the node which has less expected load in the candidate border gateway node set will be selected as the border gateway node. In the multi-path routing establishment stage, we use the intra-clustering multi-path routing algorithm and inter-clustering multi-path routing algorithm to establish multi-path routing from the source node to the destination node. At last, in the traffic allocation stage, we will use the virtual disjoint multi-path model (Vdmp) to allocate the network traffic. Simulation results show that the Cluster_MMesh routing algorithm can help increase the packet delivery rate, reduce the average end to end delay, and improve the network performance.

• Smart Structures and Systems
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• v.25 no.3
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• pp.345-368
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• 2020

The present work proposes a self-controlled multi-stage optimization method for damage identification of structures utilizing standard particle swarm optimization (PSO) algorithm. Damage identification problem is formulated as an inverse optimization problem where damage severity in each element of the structure is considered as optimization variables. An efficient objective function is formed using the first few frequencies and mode shapes of the structure. This objective function is minimized by a self-controlled multi-stage strategy to identify and quantify the damage extent of the structural members. In the first stage, standard PSO is utilized to get an initial solution to the problem. Subsequently, the algorithm identifies the most damage-prone elements of the structure using an adaptable threshold value of damage severity. These identified elements are included in the search space of the standard PSO at the next stage. Thus, the algorithm reduces the dimension of the search space and subsequently increases the accuracy of damage prediction with a considerable reduction in computational cost. The efficiency of the proposed method is investigated and compared with available results through three numerical examples considering both with and without noise. The obtained results demonstrate the accuracy of the present method can accurately estimate the location and severity of multi-damage cases in the structural systems with less computational cost.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.139-144
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• 1997

The objective of this study is to establish an actual optimization strategy for the traditional multi-stage distribution system which consists of factory warehouse, central distribution warehouse, and regional distribution warehouse under the basic assumption of distribution system. A minimization algorithm of total operating cost in a multi-stage distribution system was developed by expanding the previously existing algorithm through consideration of additional transportation environment. Alternative non-linear transportation costs for the same travel distance can be applied for the multi-stage distribution system by estimating the corresponding characteristic values through the collection of the actual data representing the change of transportation circumstances.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.398-403
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• 2000

The design of multi-stage gear drives is a time-consuming process that includes additional design problems, which are not considered in the design of single-stage gear drives. In the previous research works, the authors have proposed a new algorithm to design multi-stage gear drives at the preliminary design phase. The proposed design algorithm automates the design process by integrating the dimensional design and the configuration design process. In the configuration design process, the positions of gears and shafts are determined by minimizing the geometrical volume (size) of a gearbox. However, various types of spatial constraints should be satisfied in practical design situation. To locate input and output shaft in specified positions is the typical example of such problems. In this paper, the authors show the formulations of spatial constraints applied to the design of four-stage gear drives. The design solution shows considerably good results, and the design system is confirmed to be readily applicable to practical design situation.