• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.363-368
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• 2004

In this paper, the robustness property of 2nd-order iterative learning control(ILC) method for a class of linear and nonlinear discrete-time dynamic systems is studied. 2nd-order ILC method has the PD-type learning algorithm based on both time-domain performance and iteration-domain performance. It is proved that the 2nd-order ILC method has robustness in the presence of state disturbances, measurement noise and initial state error. In the absence of state disturbances, measurement noise and initialization error, the convergence of the 2nd-order ILC algorithm is guaranteed. A numerical example is given to show the robustness and convergence property according to the learning parameters.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.474-480
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• 2002

Aspheric optical lenses and mirrors are widely used in recent. It is more difficult to manufacture and measure the aspherical optics compared to conventional spherical ones. The interferometric optical test is common for the measurement of spherical optical surface. But the application of the interferometry to the measurement of aspheric surface is difficult because it needs a precise null corrector and very careful environmental conditions such as keeping constant temperature, humidity, atmospheric pressure and vibrations. To enhance productivity of optics manufacturing on-machine measurement and correction has been developed in this study. For practical applications, robustness of the measurement method to environments is more important. For the purpose an optical OMM(On-Machine Measurement) system has been developed using Shack-Hartmann test which has robustness to the environment. The wavefront has been reconstructed from the measured data using the primary aberration polynomial function by least square fitting. The measured result of the developed only system gives the maximum deviation only in 200 nm from the result measured by a commercial Fizeau interferometer Wyko 6000.

• Journal of Mechanical Science and Technology
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• v.19 no.5
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• pp.1131-1137
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• 2005

Methods for measuring surface roughness based on light reflectivity have advantages over methods based on light interference or diffraction, especially in in-situ, on-the-machine and in-process applications. However, measurement inconsistencies caused by changes in the specimen are still a drawback for field applications. In this study, we propose a new feedback-based algorithm to enhance the consistency against changes in the specimen. The algorithm is deduced from simulations based on light reflectance theory with typical modeled surfaces. The proposed method is similar to a digital controller and regulates the power of reflected light. Experiments varying heights and materials, verified the improvements in robustness of the method against measurement disturbances caused by specimen changes.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.418-427
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• 2020

The measurement of meat freshness at meat markets is important for the health of consumers. Currently a variety of sensors have been studied for the measurement of the meat freshness. Therefore, the analysis of sensor data is needed for the reduction of measurement errors. In this paper, we analyze the freshness measurement data of ten sensors based on deep learning. The measured data are composed of beef, pork and chicken, whose reliability and noise-robustness are examined by a deep neural network. Further, to search for multiple sensors better than a torrymeter, PCA (principle component analysis) is carried. Then, we validated that the performance of the three sensors outperforms the torrymeter in the experiment.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.1355-1357
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• 2008

Reflection measurements are critical to the evaluation of display performance under ambient illumination conditions. Various hemispherical reflection methods are evaluated for their suitability and robustness across display technologies. The standard integrating sphere method is compared to a sampling sphere apparatus.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.6
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• pp.102-108
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• 2001

This paper addresses an analytical approach to the mechanical error analysis of gear train and tolerance design and manufacture of gear train in restricted space considering motor driving torque, driving system inertia, motor acceleration, motor rotor inertia and friction torque. The gear train is designed to have optimum gear ratio in restricted space and each gear is manufactured to have the lowest weight and each gear tooth is heat-treated to have robustness. Based on the small difference between the mechanical error analysis and measurement, gear train design with optimum gear ratio and restricted space and robustness is proposed.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.1
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• pp.132-138
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• 1999

This paper addresses an analytical approach to the mechanical error analysis of gear train and tolerance design and manufacture of gear train in restricted space considering motor driving torque, driving system inertia, motor acceleration, motor rotor inertia and friction torque. The gear train is designed to have optimum gear ratio in restricted space and each gear is manufactured to have the lowest weight and each gear tooth is heat-treated to have robustness. Based on the small difference between the mechanical error analysis and measurement, gear train design with optimum gear ratio and restricted space and robustness is proposed

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.974-978
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• 2013

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on the same defect with some variations on position or rotation mainly because different images are provided. This is caused by possible variations from the image acquisition process including optical factors, nonuniform illumination, random noises, and so on. For this reason, conventional area based defect measuring methods have problems of robustness and consistency. In this paper, we propose a new defect size measuring method to overcome this problem, utilizing volume information that is completely ignored in the area based defect measuring method. The results show that our proposed method dramatically improves the robustness and consistency of defect size measurement.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.122-139
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• 2008

With the proliferation of in-process measurement technology, autocorrelated data are increasingly common in industrial SPC applications. A number of high performance control charting techniques that take into account the specific characteristics of the autocorrelation through time series modeling have been proposed over the past decade. We present a survey of such methods and analyze and compare their performances for a range of typical autocorrelated process models. One practical concern with these methods is that their performances are often strongly affected by errors in the time series models used to represent the autocorrelation. We also provide some analytical results comparing the robustness of the various methods with respect to time series modeling errors.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.717-720
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• 2000

The sensorless scheme for Switched Reluctance Motor(SRM) dives must have the robustness and reliability because the noise and error are sensitive. These elements make electrically noisy environments due to the proximity of high current power circuits with small signal electronic circuits when SRM drives. Also the leakage inductances and finite coupling capacitances these can cause the noise on any low voltage current and voltage measurement. the error can occur because the current and voltage including the noise are used as the input of sensorless algorithm In this paper the high robustness and resistance of input noise are described and the fuzzy logic based rotor estimation algorithm is used to reduce the tolerance of input data.