• Journal of the Korean Society for Precision Engineering
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• v.12 no.10
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• pp.50-56
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• 1995

Chatter Vibration is an unwanted phenomenon in metal cutting and it always affects surface finish, tool life, machine life and the productivity of machining process. The real-time detection of the chatter vibration is is necessarily required to automation system. In this study, we constructed the multi-sensing system using Tool Dynamometer, Accelermeter and AE sensor. Especially, Acoustic Emission(AE) generated during turning was investigated the possibility for real-time detection of chatter vibration. Turning experiments were performed using carbide insert tip under realistic cutting conditions and tapered workpiece of SM45C. Consquently, the real-time detection using multi-sensing system can be used for Inprocess monitoring of chatter vibration.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.4
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• pp.167-174
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• 2018

Presently, the exploration of an unknown environment is an important task for the development of mobile robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, In mobile robotics, multi-sensor data fusion(MSDF) became useful method for navigation and collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within indoor environments. Simulation results with a mobile robot will demonstrate the effectiveness of the discussed methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2213-2231
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• 2013

Compressed sensing is a novel technology used in the field of wireless communication and sensor networks for channel estimation, signal detection, data gathering, network monitoring, and other applications. It plays a significant role in highly secure, real-time, well organized, and cost-effective data communication in smart-grid (SG) systems, which consist of multi-tier network standards that make it challenging to synchronize in power management communication. In this paper, we present a multi-layer communication model for SG systems and propose compressed-sensing based data transmission at every layer of the SG system to improve data transmission performance. Our approach is to utilize the compressed-sensing procedure at every layer in a controlled manner. Simulation results demonstrate that the proposed monitoring devices need less transmission power than conventional systems. Additionally, secure, reliable, and real-time data transmission is possible with the compressed-sensing technique.

• Broadcasting and Media Magazine
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• v.11 no.1
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• pp.68-77
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• 2006

The Cognitive Radio (CR) technology is a promising solution for exploiting the limited spectrum resources and providing flexibility of spectrum usage. Future interactive broadcasting service can be realized by utilizing CR concept, since the up-link return channel can be found by the spectrum sensing method, which is core functional block of the CR system. In this paper, the spectrum sensing technologies of CR system is presented. First the system architecture of the CR with spectrum sensing block is presented. The suggested spectrum sensing technique consists of the coarse and the fine spectrum sensing. The coarse spectrum sensing technique adopted the wavelet transform to provide the multi-resolution sensing feature - Multi-Resolution Spectrum Sensing (MRSS). The fine spectrum sensing technique uses the beneficial properties of the autocorrelation function Analog Auto-Correlation (AAC). The simulation results for the proposed sensing technologies are presented for various incumbent signals.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.170-173
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• 2004

When the data from the artificial satellite is analyzed, recent years it is perceived to vegetation index using BRF(Bi-directional Reflectance Factor) of the observation target. To make the BRF models, it is important to measure the 3D structure of the observation target actually. In this study, it is proposed to the observation technique by using multi-angle stereo pair image, and shown the observation result in grassland area. Also, our team has been operating the radio controlled helicopter which can fly over the tall forest canopy and it can be equipped the measurement system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1090-1105
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• 2012

A multi-modal sensing M2M healthcare monitoring system for the continuous monitoring of patients under their natural physiological states or elderly persons with chronic diseases is summarized. The system is designed for homecare or the monitoring of the elderly who live in country side or small rest home without enough support from caregivers or doctors, instead of patient monitoring in big hospital environment. Further insights into the natural cause and progression of diseases are afforded by context-aware sensing, which includes the use of accelerometers to monitor patient activities, or by location-aware indoor tracking based on ultrasonic and RF sensing. Moreover, indoor location tracking provides information about the location of patients in their physical environment and helps the caregiver in the provision of appropriate support.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.2
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• pp.95-103
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• 1993

In the manufacturing field, some traditional manufacturing and machining methods become weakened the productivity, the external competitive power, and accuracies of the products. In these point of view, the unmanned and intelligent manufacturing systems are proposed by some manufacturing companies. The real-time monitoring technology of the cutting tool conditions i.e. tool wear, tool breakage, crack, and chipping anre necessarily reauired to realize those system, especially. In this study, we constructed the multi- sensing system using the acceleration sensor, the current sensor, and the loadmeter of a machine tool. Also, we analyzed the nose breakage, the massive signal, and some monitoring features by means of the developed system.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.721-730
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• 2010

In satellite remote sensing, irregular temporal sampling is a common feature of geophysical and biological process on the earth's surface. Lee (2008) proposed a feed-back system using a harmonic model of single period to adaptively reconstruct observation image series contaminated by noises resulted from mechanical problems or environmental conditions. However, the simple sinusoidal model of single period may not be appropriate for temporal physical processes of land surface. A complex model of multiple periods would be more proper to represent inter-annual and inner-annual variations of surface parameters. This study extended to use a multi-periodic harmonic model, which is expressed as the sum of a series of sine waves, for the adaptive system. For the system assessment, simulation data were generated from a model of negative errors, based on the fact that the observation is mainly suppressed by bad weather. The experimental results of this simulation study show the potentiality of the proposed system for real-time monitoring on the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.20-25
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• 2014

In this paper, we provide efficient spectrum sensing technology for smooth use of frequency and energy charge of multi-copter. The proposed structures focus on improving performance of spectrum sensing that is based on Ad-hoc network. First, we explain basic principles and disadvantages of cooperative spectrum sensing and ad-hoc based spectrum sensing. To solve these problems, in this paper, we employ the beamforming technology that guarantees higher transmit primary users' signal power to secondary users in ad-hoc network. The performance of proposed algorithm is analyzed in terms of detection probabilities, and the results of this paper can be applied to the various ad-hoc based Cognitive Radio system.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.2
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• pp.93-100
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• 2022

In this paper, we propose a machine learning-based method for supporting resource management of IoT software platforms in a multi-modal sensing scenario. We assume that an IoT device installed with a oneM2M-compatible software platform is connected with various sensors such as PIR, sound, dust, ambient light, ultrasonic, accelerometer, through different embedded system interfaces such as general purpose input output (GPIO), I2C, SPI, USB. Based on a collected dataset including CPU usage and user-defined priority, a machine learning model is trained to estimate the level of nice value required to adjust according to the resource usage patterns. The proposed method is validated by comparing with a rule-based control strategy, showing its practical capability in a multi-modal sensing scenario of IoT devices.