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온도변화에 따른 냉장고 발포시스템용 에어믹싱가스 농도검출기술에 관한 연구
구영목(Yeong-Mok Koo),양준석(Jun-Suk Yang),조상영(Sang-Young Jo),김민성(Min-Seong Kim),노춘수(Chun-Su Noh) 한국산업융합학회 2016 한국산업융합학회 논문집 Vol.19 No.2
This study proposes the temperature compensation algorithm using thermopile detector for non-dispersive infrared Nitrogen gas sensor. From the output voltage of thermistor that is attached onto the infrared detector, the ambient temperature was extracted. The effects of temperatures on the properties of sensor module characteristics of narrow bandpass filter, optical cavity and infrared lamp, and air mixing gas have been introduced in order to implement the temperature compensation algorithm.
900L 냉장고 진공발포시스템 유압노즐의 최적 압력제어에 관한 연구
조상영(Sang-Young Jo),김민성(Min-Seong Kim),구영목(Yeong-Mok Koo),양준석(Jun-Suk Yang),신행봉(Haeng-Bong Shin),한성현(Sung-Hyun Han) 한국산업융합학회 2016 한국산업융합학회 논문집 Vol.19 No.2
This study proposes a new approach to control the nozzle pressure of homogenizer in refrigerator foam system in the 900L class. Generally, dynamic characteristics of the hydraulic nozzle system is highly nonlinear due to uncertain parameters, and it is very difficult to control of hydraulic dynamics. Firstly, it has been performed to derive a real-time control algorithm based on the mathematical model of hydraulic cylinder, and to estimate the values of the unknown parameter in the hydraulic system. Secondly, the feedback controller was designed to implement the optimal pressure control of the hydraulic nozzle system. Finally the control performance was illustrated by simulation.
음성명령기반 26관절 보행로봇 실시간 작업동작제어에 관한 연구
조상영(Sang Young Jo),김민성(Min Sung Kim),양준석(Jun Suk Yang),구영목(Young Mok Koo),정양근(Yang Geun Jung),한성현(Sung Hyun Han) 제어로봇시스템학회 2016 제어·로봇·시스템학회 논문지 Vol.22 No.4
The Voice recognition is one of convenient methods to communicate between human and robots. This study proposes a speech recognition method using speech recognizers based on Hidden Markov Model (HMM) with a combination of techniques to enhance a biped robot control. In the past, Artificial Neural Networks (ANN) and Dynamic Time Wrapping (DTW) were used, however, currently they are less commonly applied to speech recognition systems. This Research confirms that the HMM, an accepted high-performance technique, can be successfully employed to model speech signals. High recognition accuracy can be obtained by using HMMs. Apart from speech modeling techniques, multiple feature extraction methods have been studied to find speech stresses caused by emotions and the environment to improve speech recognition rates. The procedure consisted of 2 parts: one is recognizing robot commands using multiple HMM recognizers, and the other is sending recognized commands to control a robot. In this paper, a practical voice recognition system which can recognize a lot of task commands is proposed. The proposed system consists of a general purpose microprocessor and a useful voice recognition processor which can recognize a limited number of voice patterns. By simulation and experiment, it was illustrated the reliability of voice recognition rates for application of the manufacturing process.