• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.233-244
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• 2021

Recently, several ICT-based cat studies have produced some successful results, according to academic and industry sources. However, research on the level of simply identifying the cat's condition, such as the behavior and sound classification of cats based on images and sound signals, has yet to be found. In this paper, based on the veterinary scientific knowledge of cats, a practical and academic cat monitoring and disease diagnosis system is proposed to monitor the health status of the cat 24 hours a day by automatically categorizing and analyzing the behavior of the cat with location information using LSTM with a beacon sensor and a raspberry pie that can be built at low cost. Validity of the proposed system is verified through experimentation with cats in actual custody (the accuracy of the cat behavior classification and location identification was 96.3% and 92.7% on average, respectively). Furthermore, a rule-based disease analysis system based on the veterinary knowledge was designed and implemented so that owners can check whether or not the cats have diseases at home (or can be used as an auxiliary tool for diagnosis by a pet veterinarian).

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3184-3186
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• 2000

This paper describes the remote monitoring & diagnosis system of tower parking facilities. This system consists of central station, monitoring equipments and parking system control panel. The central station is developed under client/server architecture, and the monitoring systems are connected to central station by LAN using RAS constructed PSTN. This system offers real-time fault detection and data acquisition of tower parking system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.4
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• pp.134-140
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• 2016

Main Spindle System has effect on performance of machine tools and working quality as well as is required of high reliability. Especially, it takes great importance in producing automobiles which includes a large number of working processes. However, main spindle unit in Machine tools are often cases where damage occurs do not meet the design life due to driving in harsh environments. This is when excessive maintenance and repair of machine tools or for damage stability has resulted in huge economic losses. Therefore, this studying propose a method of accelerated life test for diagnosing and prognosis the state of life assessment main spindle system. Time status monitoring of diagnostic data - through the analysis of the frequency band signals were carried out inside the main spindle bearing condition monitoring and fault diagnosis.

• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2212-2214
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• 1999

In this paper, a novel Generator On-line Diagnosis System (GODS) is proposed. This system monitors the insulation condition of the stator winding by on-line measurements of partial discharge (PD). Sensor, such as SSC (Stator Slot Coupler) and RFCT (Radio Frequency Current Transformer) are used for PD measurement. PD signals are continuously measured and digitized with a high speed A/D converter to build the database of the generator's insulation condition. Also this system can communicate with the central monitoring system via RS-485. This helps more efficient operation and maintenance of the generator.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.293-297
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• 1992

For the computerized monitoring and diagnosis of the undesirable chip chatter which are major obstacles to FMS, a pattern recognition system based on multi-layer perception neural network is developed and the performance of the system is experimentally evaluated. Experimental results show that recognition of the two class state of normal or abnormal cutting gives satisfactory results with success rate of 81`91%. Therefore, the proposed system has possibility for use in monitoring and diagnosis of automatic manufacturing system

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.347_348
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• 2009

In this paper, we described the integrated monitoring system for low-voltage panel boards. This system consists of three parts, a panel board controller, an integrated monitoring unit and a remote PC. The panel board controller which was made of CT/PT unit, control unit and power supply is able to transmit variable parameter for monitoring and diagnosis of low voltage branch circuits. Also, the integrated monitoring unit was collected monitoring data from panel boards and displayed on the touch panel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2708-2716
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• 2013

This paper presents implementation of embedded remote monitoring diagnosis system which has effective wireless channel structure and communication protocols with user-friendly UI for intelligent digital vessel. Developed system contains integrated vessel monitoring system, server, exclusive mobile terminal and smart phone. We designed an effective dual structure communication channel and simple but effective communication protocol on the monitoring system. Failures of the wireless communication are minimized and the wrong wireless communication channel is immediately replaced. In addition, we developed an effective embedded Linux UI for LCD. The implemented wireless monitoring system was tested and verified on digital vessel.

• Smart Structures and Systems
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• v.19 no.6
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• pp.587-599
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• 2017

This paper introduces an approach to the realization of an ICT-based bridge remote monitoring system that enables real-time monitoring and controlled adjustments for unexpected heavy loads and also for damaging earthquakes or typhoons. In this paper, an integrated bridge remote monitoring system called the "Intelligent Bridge", which consists of a stand-alone monitoring system (SMS) and a web-based Internet monitoring system(IMS), was developed for not only bridge maintenance but also as an application for a para-stressing bridge system. To verify the possibility of controlling the actual structural performance of an "Intelligent Bridge", a model 2-span continuous cable-stayed bridge with adjustable cables was constructed. The experimental results demonstrate that the implemented monitoring system supplies detailed and accurate information about bridge behaviour for further evaluation and diagnosis, and it also opens up prospects for future application of a web-based remote system to actually adjust in-service bridges under field conditions.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.11a
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• pp.380-381
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• 2008

This paper consider the condition monitoring technology of electrical machine in metro substation need for efficient and effective management and diagnosis. Developing management system using condition monitoring system is very competitive field, and still to a great extent seen as an unnecessary cost. There are several approaches to maintenance management in urban transit such as reliability-centered maintenance, availability-target maintenance and preventive maintenance to advanced approaches involving condition monitoring techniques. In this paper we give a brief introduction to condition-based management and diagnosis in metro substation and which management system satisfying various demanding in railway.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1275-1280
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• 2014

In this study, the performance of a real-time micro telescopic monitoring system is evaluated, in which an artificial neural network is adopted for the diagnoses of vibratory bodies, such as solid piping system or machinery. The structural vibration was measured by a non-contact remote sensing method, in which images of a high-speed high-definition camera were used. The structural vibration data that can be obtained by the PIV (particle image velocimetry) technique were used for training the neural network. The structures of the neural network are dynamically changed and their performances are evaluated for the constructed diagnosis system. Optimized structures of the neural network are proposed for real-time diagnosis for the piping system. It was experimentally verified that the performances of the neural network used for real-time monitoring are influenced by the types of the vibration data, such as minimum, maximum and average values of the vibration data. It concludes that the time-mean values are most appropriate for monitoring the piping system.