• Journal of the Korean Society for Precision Engineering
• /
• v.9 no.4
• /
• pp.22-35
• /
• 1992

In highly automated machining centers, intelligent sensor fddeback systems are indispensable on order to monitor their operations, to ensure efficient metal removal, and to initate remedial action in the event of accident. In this study, an on-line tool wear detection system for thrning operations is developed, and experimentally evaluated. The system employs multiple sensors and the signals from these sensors are processed using a multichannel autoegressive (AR) series model. The resulting output from the signal processing block is then fed to a previously tranied artificial neural network (multiayered perceptron) to make a final decision on the state of the cutting tool. To learn the necessary input/output mapping for tool wear detection, the weithts and thresholds of the network are adjusted according to the back propagation (BP) method during off-line training. The results of experimental evaluation show that the system works well over a wide range of cutting conditions, and the ability of the system to detect tool wear is improved due to the generalization, fault-tolearant and self-ofganizing properties of the neural network.

• Proceedings of the KSR Conference
• /
• 2009.05a
• /
• pp.457-465
• /
• 2009

Subway system including light-rail transit system is the representative public urban transportation. Accordingly, Nothing is more important than the safety operation as well as passengers' convenience. Due to the fire disaster of Daegu subway on 2003, more strict regulations of detecting fire and of conducting on emergency circumstances. However, regardless of this improved management, it was reported that installations of lots of fire-detection facilities may be harm than good to operate subway system due to frequent malfunction of some fire-detection facilities. It may cause mis-alarm for fire and induces abnormal operation of subway due to the strict regulation; the train shall be stopped on emergency circumstances. Therefore, in this paper, new scheme on surveiling breaking-out-of fire in the station is suggested with new IT technologies, Wireless Sensor Network(WSN) and CCTVs. which were integrated with an intelligent software. This intelligent system enables to surveil breaking-out-of fire in real time through sensor network technology and watch the emergency site on CCTV as well. Through this system, subway organizers could cope with the emergency circumstance rapidly as well as judge precisely whether fire breaks out or not.

• Proceedings of the KSR Conference
• /
• 2008.06a
• /
• pp.653-658
• /
• 2008

Service areas in the urban transit need to construct the intelligent integrated surveillance system, because they are the public places that many people get together at one time. In past, analogue, closed-circuit televisions and analogue video recorders are used to construct the surveillance system. Now, a lot parts of the analogue systems that depend on the images have been changed to the complicated system, which consists of sensors and images and also, to be digitalized. In past, the surveillance system was used as an inspection devices to examine the spots after happening some events. But, with a high level of the computer and communication technologies, it is possible that the digitalized data leads the intelligence systems to prevent some accidents by using the various analysis techniques. And the data could be used to decide surveillance policies and provide some information on the safety and management policies as well as surveillance policies. In this paper, we define the intelligent surveillance system and suggest the major functions of the system. Also, we suggest the fundamental functions that every part should get and describe the way to develop the system.

• Proceedings of the KIEE Conference
• /
• 2007.10a
• /
• pp.399-400
• /
• 2007

The one of the necessary technologies to live in the ubiquitous society that we can exchange some informations whenever it is and wherever we are, is the technology of context-awareness. The technology of context-awareness can be used various fields-medical science, national defense, national security and etc. and the technology can affect our society by and large. The technology of context-awareness is also applicable to many fields in the urban transit. In this paper, we describe the present condition of the technology of context-awareness and the examples of practical application of it and suggest some plans that are applicable to build an intelligent surveillance system for urban transit. We can connect the operating officer who is in the nearest to the place where the some events happened within the urban transit service area through the intelligent surveillance system for urban transit and we can eel a foothold in perceiving automatically various events within urban transit service area. So, the technology of context-awareness is the basic technology to realize an intelligent surveillance for urban transit, for the security of passengers and the protection of facilities in urban transit.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.18 no.8
• /
• pp.2062-2072
• /
• 1994

This paper presents the development of a fuzzy controller for driving camera pan/tilt device so that the camera's viewing direction can automatically track a moving object. To achieve computational efficiency a non-contact type displacement follower is used as a feedback sensor instead of a vision camera. The displacement follower, however, is extremely sensitive to object's lighting condition and results in unstable response at high speed. To this end, a fuzzy controller is developed in such a way to provide stable tracking performance at high speed where the sensory signal is subjected to intermittant disturbances of large magnitude. The test result shows stable tracking response even for high speed and non-uniform lighting condition. The resulting camera autotracking system can be adopted as an effective tool for visual transfer in the context of teleoperation and autonomous robotics.

• Journal of Power System Engineering
• /
• v.4 no.2
• /
• pp.25-30
• /
• 2000

The grinding process is very complex and relates many parameters to control the process. As this reason, a theoretical analysis and a quantitative estimation of the grinding process has not been well established. In this study, the in-process monitoring system was suggested by applying the neural network for monitoring and shooting the malfunction of cylindrical plunge grinding process. This system used the power signals from the electric power meter. This neural network was composed of processing elements [4-(5-5)-3] with 4 identified power parameters. Because sensitivity is blunted some minute vibration components, the simulation result of this system has appeared about 10% erroneous recognition in the uncertain pattern and the average success rate of the trouble recognition was about 90%. Consequently, the developed system, which applied to the power signals, can be recognize enough to monitor the grinding process as in-process.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.2
• /
• pp.23-29
• /
• 2014

The advanced traffic management system of intelligent transport systems automates the related traffic tasks such as vehicle speed, traffic volume and traffic incidents through the improved infrastructures like high definition cameras, high-performance radar sensors. For the safety of road users, especially, the automated incident detection and secondary accident prevention system is required. Normally, CCTV based image object detection and radar based object detection is used in this system. In this paper, we proposed the algorithm for real time highway incident detection system using multi surveillance cameras to mosaic video and track accurately the moving object that taken from different angles by background modeling. We confirmed through experiments that the video detection can supplement the short-range shaded area and the long-range detection limit of radar. In addition, the video detection has better classification features in daytime detection excluding the bad weather condition.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.6
• /
• pp.1449-1454
• /
• 2015

Virtualization lacks capabilities for enabling the application to scale efficiently because of new applications components which are raised to be configured on demand. In this paper, we propose an architecture that affords mobile app based on nomadic smartphone using not only mobile cloud computing-cloudlet architecture but also a dedicated platform that relies on using virtual private mobile networks to provide reliable connectivity through LTE(Long Term Evolution) wireless communication. The design architecture lies with how the cloudlet host discovers service and sends out the cloudlet IP and port while locating the user mobile device. We demonstrate the effectiveness of the proposed architecture by implementing an android application responsible of real time analysis by using a vehicle to applications smartphone interface approach that considers the smartphone to act as a remote users which passes driver inputs and delivers outputs from external applications.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.21 no.1
• /
• pp.75-81
• /
• 2007

This paper dealt with the design and implementation of an expert system to monitor and diagnose the lightning arresters in GIS substations. The expert system consists of a data acquisition module(DAM) based on microprocessor and diagnostic algorithms. The DAM measures and analyzes several parameters necessary for the arrester diagnosis such as system voltages, leakage current components, and temperatures. Also, it includes an intelligent surge counter which can record the date and tin, the polarity, and the amplitude of surge currents. All the data acquired is transmitted to a remote computer by a low rate wireless network specified in IEEE 802.15.4 to avoid electromagnetic intereference under high voltage and large current environments. The decision-making for the arrester diagnosis completes with a Java Expert System Shell(JESS) which is composed of a knowledge base, an inference engine and a graphic user interface(GUI).

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.3
• /
• pp.607-612
• /
• 2015

As the amount of vehicle's diagnostics data increases, the actors in automotive ecosystem will encounter difficulties to perform a real time analysis in order to simulate or to design new services according to the data gathered from the connected cars. In this paper, we have conducted a study of a Big Data solution that expresses the essential deep analytics to process and analyze vast quantities of vehicles on board diagnostics data generated by cars. Hadoop and its ecosystems have been deployed to process a large data and delivered useful outcomes that may be used by actors in automotive ecosystem to deliver new services to car owners. As the Intelligent transport system is involved to guarantee safety, reduce rate of crash and injured in the accident due to speed, addressing big data solution based on vehicle diagnostics data is upcoming to monitor real time outcome from it and making collection of data from several connected cars, facilitating reliable processing and easier storage of data collected.