• International Journal of Precision Engineering and Manufacturing
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• v.2 no.2
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• pp.65-72
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• 2001

The design of multi-stage gear drives is a time-consuming process, since on includes more complicated problems, which are not considered in the design of single-stage gear drives. The designer has th determine the number of reduction stages and the gear ratios of each reduction state. In addition, the design problems include not only the dimensional design but also the configuration design of gear drive elements. There is no definite rule and principle for these types of design problems. Thus the design practices largely depend on the sense and the experiences of the designer , and consequently result in undesirable design solution. We propose a new generalized design algorithm to support the designer at the preliminary design phase of multi-stage gear drives. The proposed design algorithm automates the design process by integrating the dimensional design and the configuration design process. The algorithm consists of four steps. In the first step, a designer determines the number of reduction stage. In the second step. gear ratios se chosen by using the random search method. In the third step, the values of basic design parameter are chosen by using the generate and test method. Then, the values of other dimension, such ad pitch diameter, outer diameter, and face width, are calculated for the configuration design in the final step. The strength and durability of a gear is guaranteed by the bending strength and the pitting resistance rating practices by using the AGMA rating formulas. In the final step, the configuration design is carried out b using the simulated annealing algorithm. The positions of gears and shafts are determined to minimize the geometrical volume(size) of a gearbox, while satisfying spatial constraints between them. These steps are carried out iteratively until a desirable solution is acquired. The propose design algorithm has been applied to the preliminary design of four-stage gear drives in order to validate the availability. The design solution have shown considerably good results in both aspects of the dimensional and the configuration design.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.10
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• pp.192-199
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• 2000

The design of multi-stage gear drives is a time-consuming process because it includes more complicated problems, which are not considered in the design of single-stage gear drives. The designer has no determine the number of reduction stages and the gear ratios of each reduction stage. In addition, the design problems include not only dimensional design but also configuration design of gear drive elements. There is no definite rule or principle for these types of design problems. Thus the design practices largely depend on the sense and the experiences of the designer, and consequently result in undesirable design solution. A new and generalized design algorithm has been proposed to support the designer at the preliminary phase of the design of multi-stage gear drives. The proposed design algorithm automates the design process by integrating the dimensional design and the configuration design process. The algorithm consists of four steps. In the first step, the user determines the number of reduction stages. In the second step, gear ratios of every stage are chosen using the random search method. The values of the basic design parameters of a gear are chose in the third step by using the generate and test method. Then the values of the dimensions, such as pitch diameter, outer diameter and face width, are calculated for the configuration design in the next step. The strength and durability of each gear is guaranteed by the bending strength and the pitting resistance rating practices by using AGMA rating formulas. In the final step, the configuration design is carried out using simulated annealing algorithm. The positions of gears and shafts are determined to minimize the geometrical volume (size) of a gearbox while avoiding interferences between them. These steps are carried out iteratively until a desirable solution is acquired. The proposed design algorithm is applied to the preliminary design of four-stage gear drives in order to validate the availability. The design solution has considerably good results in both aspects of the dimensional and the configuration design.

• Korean Journal of Computational Design and Engineering
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• v.10 no.4
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• pp.284-292
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• 2005

This paper presents a new framework of kinematic tolerance synthesis and describes the implemented algorithm for planar mechanical systems comprised of higher kinematic pairs. Input to the synthesis algorithm is a parametric model of the mechanical system with allowed parameter ranges (tolerance ranges). The model is specified as the part profiles consisting of line and arc segments and the motion axes along which each part moves. The algorithm analyzes tolerance in generalized configuration space, called contact zones bounding the worst-case variations, and identifies bad system variations. The bad system variations then are removed out of the parameter ranges by adjusting the nominal parameter values if possible and then shrinking the ranges otherwise. This cycle is repeated until no more bad variations we found. I show the effectiveness of the algorithm by case studies on several mechanisms.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.422-427
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• 1994

In this paper, we propose a new design approach of a two-degrees-of-freedom compensator which assures the robust stability. First of all, we clarify the internal structure of the generalized two-degrees-of-freedom compensator. By adopting this structure, we can make a bridge between the generalized controller and the disturbance observer based controller, Secondly, based on the clarified structure we derive a robust stability condition, and propose a design algorithm of free parameter taking the condition into account. The proposed design algorithm is easy to implement and, as a result, we obtain lower order free parameter then that of the conventional design algorithm.. Thirdly, we show by adopting an appropriate coprime factorization that the clarified structure can also be regarded as an extended version of the conventional PID compensator. Finally, we apply the proposed algorithm to a three-degrees-of freedom direct drive robot, and show some experimental results to verify the effectiveness of the proposed algorithm.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.81-89
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• 1999

Image obtained by incomplete communication always include noise, blur and distortion, etc. In this paper, we propose and apply the new spatial filter algorithm, called an optimal adaptive generalized stack filter(AGSF), which optimizes adaptive generalized stack filter(AGSF) using neural network weight learning algorithm of back-propagation learning algorithm for improving noise removal and edge preservation rate. AGSF divides into two parts: generalized stack filter(GSF) and adaptive multistage median filter(AMMF), GSF improves the ability of stack filter algorithm and AMMF proposes the improved algorithm for reserving the sharp edge. Applied to neural network theory, the proposed algorithm improves the performance of the AGSF using two weight learning algorithms, such as the least mean absolute(LAM) and least mean square (LMS) algorithms. Simulation results of the proposed filter algorithm are presented and discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.123-128
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• 1995

The grouping of parts into families and machines into cells poses an important problem in the design and planning of the flexible manufacturing system(FMS). This paper proposes a new optimal algorithm of forming machine-part groups to maximize the similarity, based on branching from seed machine and bounding on a completed part. This algorithm is illustrated with numerical example. This algorithm could be applied to the generalized machine-part grouping problem.

• Journal of Power Electronics
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• v.9 no.2
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• pp.198-206
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• 2009

An algorithm is developed that enables a single-phase matrix converter (SPMC) to perform functions of a generalized single phase power electronics converter such as acting as a frequency changer, rectifier, inverter, and chopper. This reduces the need for new converter hardware. The algorithm is implemented first on computer simulation software Orcad Capture CIS version 9.1. Simulation results are presented for five types of converters with a control input variable that decides the 1) type of converter and 2) type of output waveform. The simulated results verify the working and operation of a generalized converter based on SPMC. Simulated results are verified with experimental results. Hardware design is obtained using readily available ICs and other components. The trigger circuit has been tested qualitatively by observing waveforms on CRO. The operation of the proposed system has been found to be satisfactory.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.608-613
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• 2004

This paper is concerned with the design of a predictive PID controller, which has similar features to the model-based predictive controller. A PID type control structure is defined which includes prediction of the outputs and the recalculation of new set points using the future set point data. The optimal values of the PID gains are pre-calculated using the values of gains calculated from an unconstrained generalized predictive control algorithm. Simulation studies demonstrate the performance of the proposed controller and the results are compared with generalized predictive controller and the results are compared with generalized predictive control solutions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.69-75
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• 2005

This paper is concerned with the design of a predictive PID controller, which has similar features to the model-based predictive controller. A PID type control structure is defined which includes prediction of the outputs and the recalculation of new set points using the future set point data. The optimal values of the PID gains are pre-calculated using the values of gains calculated from an unconstrained generalized predictive control algorithm. Simulation studies demonstrate the performance of the proposed controller and the results are compared with generalized predictive controller and the results are compared with generalized predictive control solutions.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.142-147
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• 2018

We present a practical design algorithm for quantizers at nodes in distributed systems in which each local measurement is quantized without communication between nodes and transmitted to a fusion node that conducts estimation of the parameter of interest. The benefits of vector quantization (VQ) motivate us to incorporate the VQ strategy into our design and we propose a low-complexity design technique that seeks to assign vector codewords into sets such that each codeword in the sets should be closest to its associated local codeword. In doing so, we introduce new distance metrics to measure the distance between vector codewords and local ones and construct the sets of vector codewords at each node to minimize the average distance, resulting in an efficient and independent encoding of the vector codewords. Through extensive experiments, we show that the proposed algorithm can maintain comparable performance with a substantially reduced design complexity.