• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.06a
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• pp.109-115
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• 2000

The spindle unit is core parts in high precision machine tools. Diverse static, dynamic and thermal charateristics of spindle unit are needed for special purpose of machine tools. Compromise between those charateristics will be done in concept design phase. High static stiffness at spindle nose may be very important performance for heavy cutting work. High dynamic stiffness is also useful to high precision and high speed machine tools. Improvement of thermal charateristics in spindle lead to high reliability of positioning accuracy. For high speed spindle structure, the design parameter such as, bearing span, diameter, bearing type and arrangement, preload, cooling and lubrication method should be in harmony.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.3
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• pp.117-121
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• 1992

There have been many studies on chatter vibration in machining but there seems to be no regulations to decide the commencing point of chatter objectively. The development of an objective method which can estimate and detect chatter commencement is very much in need for automatic manufacturing systems, dynamic performance tests for machine tools, and so on. In this study, an approach for in-process monitoring and for deciding commencing point of the chatter vibration using the frequency band-energy method was proposed. From this method, in-process monitoring system for detection the chatter vibration was developed, and investigated its practical possibility. As a result, it is shown by experiments that the chatter vibtation can be detected accurately. Since the changing pattern of the signal energy in certain frequency band during chattering is seldom affected by the variation of cutting conditions, if adequate pre-measures are taken, this method can be widely used in most machining processes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.94-96
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• 2014

Press machine has advantage over other manufacturing machine which can produce large quantities of products in short time so it is widely used in lots of industrial sectors. However, vibration problems may occur when operating a high pressure. It has been subjected to the condition monitoring vibration sensors attached to the main point. We perform the maintenance before a failure occurs, the system receives a high load. In this paper, in order to determine the structural characteristics for the transport system to conduct the vibaration and shock analysis.

• Journal of the Korean Society for Railway
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• v.18 no.4
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• pp.335-343
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• 2015

The role of the turnouts installed on the points of railway branches and intersections is to safely switch the directions of trains. In case of abnormal forces applied to the turnouts due to extreme operating conditions, it is difficult in the current system to conduct accurate diagnosis and measuring. Moreover, the existing measurement devices for turnout switching power are mostly based on foreign technologies, which provide only limited information on the switching power; this information is insufficient for effective monitoring and maintenance. In this paper, through an analysis of the characteristics of the switching and locking function, the problems in turnout power measurements of current electrical point machines in Korea are examined. And based on the results, a new sensor-based method for measuring switching power is proposed.

• ETRI Journal
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• v.21 no.4
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• pp.52-64
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• 1999

QoS monitoring is a kind of real-time systems which allows each level of the system to track the ongoing QoS levels achieved by the lower network layers. For these systems, real-time communications between corresponding transport protocol objects is essential for their correct behavior. When two or more entities are employed to perform a certain task as in the case of communication protocols, the capability to do so is called interoperability and considered as the essential aspect of correctness of communication systems. This paper describes a formal approach on modeling and interoperability test case generation of a real-time QoS monitoring protocol. For this, we specify the behavior of flow monitoring of transport layer QoS protocol, i.e., METS protocol, which is proposed to address QoS from an end-to-end's point of view, based on QoS architecture model which includes ATM net work in lower layers. We use a real-time Input/Output finite State Machine to model the behavior of real-time flow monitoring over time. From the modeled real-time I/OFSM, we generate interoperability test cases to check the correctness of METS protocol's flow monitoring behaviors for two end systems. A new approach to efficient interoperability testing is described and the method of interoperability test cases generation is shown with the example of METS protocol's flow monitoring. The current TTCN is not appropriate for testing real-time and multimedia systems. Because test events in TTCN are for message-based system and not for stream-based systems, the real-time in TTCN can only be approximated. This paper also proposes the notation of real-time Abstract Test Suite by means of real-time extension of TTCN. This approach gives the advantages that only a few syntactical changes are necessary, and TTCN and real-time TTCN are compatible. This formal approach on interoperability testing can be applied to the real-time protocols related to IMT-2000, B-ISDN and real-time systems.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.1-7
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• 2012

In general, currently developed ECG(electrocardiogram) based biometrics approaches are not suitable for real market applications since they require high cost ECG monitoring device and their measurement methods showed poor usability. In this paper, we developed lead I signal based biometrics system using special purpose ECG measurement hardware. To guarantee signal quality for biometrics from various signal measurement environment in our ordinary life, several filters are applied. In addition, to enhance usability, only two skin on electrodes without reference point are used for measurement. Lead I signals of seventeen candidates are measured from developed hardware and features are extracted. Extracted features are applied to support vector machine (SVM) pattern classifier for biometrics, and the experimental results showed 98.59% of sensitivity (SN) and 97.21% of accuracy (ACC). Compare to conventional ECG biometrics approaches, proposed system showed enhanced usability with low-cost measurement hardware.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.792-799
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• 2022

Building Information Modeling (BIM) technology is a key component of modern construction engineering and project management workflows. As-is BIM models that represent the spatial reality of a project site can offer crucial information to stakeholders for construction progress monitoring, error checking, and building maintenance purposes. Geometric methods for automatically converting raw scan data into BIM models (Scan-to-BIM) often fail to make use of higher-level semantic information in the data. Whereas, semantic segmentation methods only output labels at the point level without creating object level models that is necessary for BIM. To address these issues, this research proposes a hybrid semantic-geometric approach for clutter-resistant floorplan generation from laser-scanned building point clouds. The input point clouds are first pre-processed by normalizing the coordinate system and removing outliers. Then, a semantic segmentation network based on PointNet++ is used to label each point as ceiling, floor, wall, door, stair, and clutter. The clutter points are removed whereas the wall, door, and stair points are used for 2D floorplan generation. A region-growing segmentation algorithm paired with geometric reasoning rules is applied to group the points together into individual building elements. Finally, a 2-fold Random Sample Consensus (RANSAC) algorithm is applied to parameterize the building elements into 2D lines which are used to create the output floorplan. The proposed method is evaluated using the metrics of precision, recall, Intersection-over-Union (IOU), Betti error, and warping error.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.772-775
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• 2004

Generally, arterial pulse waves are measured at the radial arterial of wrist or carotid arterial of neck using a sensor such as pressure sensor, piezoelectric sensor or optic sensor. But in this paper, arterial pulse wave is measured at the temple using PZT piezo sensor which is attached on the temple in form of a hair-band. Arterial Pulse waves are generally measured when a reagent is in a static state. But in this paper, we implemented the arterial pulse wave measurement system, as a previous stage of the arterial pulse wave measurement system for running at outdoors or on a running machine, that measures arterial pulse waves at the temple, which is the least moving part when running. Thorough the continuous study, if the motion artifact when running is possible to be removed, the system will be able to perform monitoring of running men's states and especially emergency signals such as serious pulse waves of an/old and feeble persons and handicapped persons.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.869-875
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• 2009

Safety is a big issue in the construction sites. For safe and secure management, tracking locations of construction resources such as labors, materials, machineries, vehicles and so on is important. The materials, machineries and vehicles could be controlled by computer, whereas the movement of labors does not have fixed pattern. So, the location and movement of labors need to be monitored continuously for safety. In general, Global Positioning System(GPS) is an opt solution to obtain the location information in outside environments. But it cannot be used for indoor locations as it requires a clear Line-Of-Sight(LOS) to satellites Therefore, indoor location monitoring system could be a convenient alternative for environments such as tunnel and indoor building construction sites. This paper presents a case study to investigate feasibility of Wi-Fi based indoor location monitoring system in construction site. The system is developed by using fingerprint map of gathering Received Signal Strength Indication(RSSI) from each Access Point(AP). The signal information is gathered by Radio Frequency Identification (RFID) tags, which are attached on a helmet of labors to track their locations, and is sent to server computer. Experiments were conducted in a shield tunnel construction site at Guangzhou, China. This study consists of three phases as follows: First, we have a tracking test in entrance area of tunnel construction site. This experiment was performed to find the effective geometry of APs installation. The geometry of APs installation was changed for finding effective locations, and the experiment was performed using one and more tags. Second, APs were separated into two groups, and they were connected with LAN cable in tunnel construction site. The purpose of this experiment was to check the validity of group separating strategy. One group was installed around the entrance and the other one was installed inside the tunnel. Finally, we installed the system inner area of tunnel, boring machine area, and checked the performance with varying conditions (the presence of obstacles such as train, worker, and so on). Accuracy of this study was calculated from the data, which was collected at some known points. Experimental results showed that WiFi-based indoor location system has a level of accuracy of a few meters in tunnel construction site. From the results, it is inferred that the location tracking system can track the approximate location of labors in the construction site. It is able to alert the labors when they are closer to dangerous zones like poisonous region or cave-in..

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.4
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• pp.436-442
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• 2016

An electroencephalogram (EEG)-connectome processor to monitor and diagnose mental health is proposed. From 19-channel EEG signals, the proposed processor determines whether the mental state is healthy or unhealthy by extracting significant features from EEG signals and classifying them. Connectome approach is adopted for the best diagnosis accuracy, and synchronization likelihood (SL) is chosen as the connectome feature. Before computing SL, reconstruction optimizer (ReOpt) block compensates some parameters, resulting in improved accuracy. During SL calculation, a sparse matrix inscription (SMI) scheme is proposed to reduce the memory size to 1/24. From the calculated SL information, a small world feature extractor (SWFE) reduces the memory size to 1/29. Finally, using SLs or small word features, radial basis function (RBF) kernel-based support vector machine (SVM) diagnoses user's mental health condition. For RBF kernels, look-up-tables (LUTs) are used to replace the floating-point operations, decreasing the required operation by 54%. Consequently, The EEG-connectome processor improves the diagnosis accuracy from 89% to 95% in Alzheimer's disease case. The proposed processor occupies $3.8mm^2$ and consumes 1.71 mW with $0.18{\mu}m$ CMOS technology.