• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.603-608
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• 2001

In order to distinguish fault electric motors automatically in real time. an intelligent diagnosis technique may be required. This paper presents an automatic fault detection system for electric motors by using their acoustic noises. Time signals of each candidate motor were measured in an anechoic chamber for further analysis. Spectral analysis was first carried out and they showed that two typical types of fault motors could be successfully distinguished in the frequency domain; bearing faults and scratches. Unlike the trend of normal motors that shows only a single dominant peak at around 2000 ㎐, several peaks are bunched together in bearing fault motors. On the other hand, large frequency noises at around 6500 ㎐ are newly arisen in scratchy fault motors. However, the processing time for spectral analysis was rather long for a real time application in production lines. Thus, a number of band-pass filters were used in the time domain instead for a real time application. Before applying filters, the bands of filters were set from the information of spectral analysis. By applying a set of band-pass filters, the RMS values of each filtered signal were calculated, and thus the normal and damaged motors could be successfully distinguished.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.55-59
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• 2007

It is known that the adhesive interface testing of the rocket motor which using the ultrasonic wave iS superior to the other testing methods about the economically detectable abiliη of the defects. But, the signal analysis of the ultrasonic wave takes too much time and effort that the time interval of the transmitted pulse and the received pulse is too short to be separated the reflected signals because the structure of the rocket motor is multi-layers. The ultrasonic testing of rocket motor have been only applied with automatic system about extremely limited area like the debond in adhesive interface between the motor case and insulator. In this study the new technique to detect the debond between the liner and the propellant using the property of the resonance and Lamb waves was described as comparing the existence ultrasonic testing.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.3
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• pp.243-251
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• 2016

Autonomous Underwater Vehicles (AUVs) generally work in complex marine environments. Any fault in AUVs may cause significant losses. Thus, system reliability and automatic fault diagnosis are important. To address the actuator failure of AUVs, a fault diagnosis method based on the Gaussian particle filter is proposed in this study. Six free-space motion equation mathematical models are established in accordance with the actuator configuration of AUVs. The value of the control (moment) loss parameter is adopted on the basis of these models to represent underwater vehicle malfunction, and an actuator failure model is established. An improved Gaussian particle filtering algorithm is proposed and is used to estimate the AUV failure model and motion state. Bayes algorithm is employed to perform robot fault detection. The sliding window method is adopted for fault magnitude estimation. The feasibility and validity of the proposed method are verified through simulation experiments and experimental data.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1408-1415
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• 2007

To operate Platform Screen Door (PSD) automatically, the operational data of PSD and the train must be interfaced properly. PSD and train are operated together by the signaling system in Automatic Train Operation (ATO) signaling system zone where interfaces are provided between PSD and train. However, the additional PSD interface system with train is required in train operating zone without the interface between PSD and train. For the PSD interface, the wireless communication system or the train status (train correct stop status / train door status) detection system has been used. Seoul Metro line No.2. has the PSD wireless communication system using 447MHz band RF. For the safety of PSD operation, it is required to prevent RF interference in the subway environment where many frequencies exist. In this paper, the PSD wireless communication system is developed using 2.4GHz band RF to prevent the interference of the wireless communication and increase the traffic of the PSD interface. Furthermore, the improved system can store, manage and display the PSD and train operational data using Human Machine Interface (HMI) in the train's driver cab.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1104-1120
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• 2020

The chest X-rays are a common way to diagnose lung cancer or pneumonia. In particular, the finding of a lung nodule is the most important problem in the early detection of lung cancer. Recently, a lot of automatic diagnosis algorithms have been studied to find the lung nodules missed by doctors. The algorithms are typically based on segmentation network like U-Net. However, the occurrence of false positives that similar to lung nodules present outside the lungs can severely degrade performance. In this study, we propose a multi-task learning method that simultaneously learns the lung region and nodule-labeled data based on the prior knowledge that lung nodules exist only in the lung. The proposed method significantly reduces false positives outside the lung and improves the recognition rate of lung nodules to 83.8 F1 score compared to 66.6 F1 score of single task learning with U-net model. The experimental results on the JSRT public dataset demonstrate the effectiveness of the proposed method compared with other baseline methods.

• Journal of the Korean Society of Visualization
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• v.13 no.3
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• pp.15-19
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• 2015

We developed a high-throughput microscopy (HTM) method which enabled us to replace a conventional phase contrast microscopy (PCM) method that has been used as a standard analytical method for airborne asbestos. We could obtain the concentration of airborne asbestos fibers under detection limit by automated image processing and analysis using HTM method. Here we propose an improved image processing algorithm with variable parameters to enhance the accuracy of the HTM analysis. Since the variable parameters that compensate the difference of the brightness are applied to the individual images in our new image processing method, it is possible to enhance the accuracy of the automatic image analysis method for sample slides with low asbestos concentration that caused errors in binary image processing. We demonstrated that enumeration of fibers by improved image processing algorithm remarkably enhanced the accuracy of HTM analysis in comparison with PCM. The improved HTM method can be a potential alternative to conventional PCM.

• Journal of Welding and Joining
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• v.18 no.4
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• pp.70-75
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• 2000

The weld seam tracking system for arc welding process uses various kinds of sensors such as arc sensor, vision sensor, laser displacement and so on. Among the variety of sensors available, electro-magnetic sensor is one of the most useful methods especially in sheet metal butt-joint arc welding, primarily because it is hardly affected by the intense arc light and fume generated during the welding process, and also by the surface condition of weldments. In this study, a dual-electromagnetic sensor, which utilizes the induced current variation in the sensing coil due to the eddy current variation of the metal near the sensor, was developed for arc welding of sheet metal butt-joints. The dual-electromagnetic sensor thus detects the offset displacement of weld line from the center of sensor head even though there's no clearance in the joint. A set of design variables of the sensor were determined for the maximum sensing capability through the repeated experiments. Seam tracking is performed by correcting the position of sensor to the amount of offset displacement every sampling period. From the experimental results, the developed sensor showed the excellent capability of weld seam detection when the sensor to workpiece distance is near less than 5 mm, and it was revealed that the system has excellent seam tracking ability for the butt-joint of sheet metal.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.23-29
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• 2003

This study is the empirical research about application and evaluation of AVI that is an essential technology for calculating and providing the travel time. Travel time calculation and provision is one of the technique for information collecting and providing in the ITS. Through the field test on a national highway, we proposed the travel time calculation technique from the data by non-contact vehicle detecting method and validated field application performance with field data. We proposed the technique of evaluating field application performance, then using this, analyzed recognition rate, detection rate and travel time with field data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.929-932
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• 2007

The integrated prevention of disaster management system is collected prevention of disaster data from prevention of disaster relation other systems and smart sensor in USN. This system manages fire fighting facility effectively. The relation equipment which is used in existing and network using "Open Protocols" about under using the support system which is integrated effectively as the destroyer. It connects CCTV, the sensitivity environmental sensor, automatic fire detection equipment and security equipment and air flow equipment system using Internet. The System Server was collected monitoring data at the each equipment and processing by operational scenario. It will verified the effectiveness of operational scenario and integrated prevention of disaster management system

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.705-710
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• 2003

Recent years, as a rapid development of multimedia technology, video database system to retrieve video data efficiently seems to core technology in the oriented society. This thesis describes an efficient automatic frame detection and location method for content based retrieval of video. Frame extraction part is consist of incoming / outgoing car frame extraction and car number frame extraction stage. We gain star/end time of car video also car number frames. Frames are selected at fixed time interval from video and key frames are selected by color scale histogram and edge operation method. Car frame recognized can be searched by content based retrieval method.