• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.751-760
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• 2017

In recent years, multifractal-based analysis methods have been widely applied in engineering. Among these methods, multifractal detrended cross-correlation analysis (MFDXA), a branch of fractal analysis, has been successfully applied in the fields of finance and biomedicine. For its great potential in reflecting the subtle characteristic among signals, a structural health monitoring (SHM) system based on MFDXA is proposed. In this system, damage assessment is conducted by exploiting the concept of multifractal theory to quantify the complexity of the vibration signal measured from a structure. According to the proposed algorithm, the damage condition is first distinguished by multifractal detrended fluctuation analysis. Subsequently, the relationship between the q-order, q-order detrended covariance, and length of segment is further explored. The dissimilarity between damaged and undamaged cases is visualized on contour diagrams, and the damage location can thus be detected using signals measured from different floors. Moreover, a damage index is proposed to efficiently enhance the SHM process. A seven-story benchmark structure, located at the National Center for Research on Earthquake Engineering (NCREE), was employed for an experimental verification to demonstrate the performance of the proposed SHM algorithm. According to the results, the damage condition and orientation could be correctly identified using the MFDXA algorithm and the proposed damage index. Since only the ambient vibration signal is required along with a set of initial reference measurements, the proposed SHM system can provide a lower cost, efficient, and reliable monitoring process.

• Journal of Power System Engineering
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• v.12 no.6
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• pp.18-23
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• 2008

This paper describes development of real-time condition monitoring system to observe state of a container crane in a port. To analyze the state of a crane, the strength and the direction of wind are measured with sensors along with the load resulted a crane at the moment. The measured signals are processed by especially developed conditioning board and converted into digital data. Measured data are analyzed to define the state of the crane at an indicator. For transmission of these data to the indicator, we implemented wireless sensor network based on IEEE 802.15.4 MAC(Media Access Control) protocol and Bluetooth network protocol. To extend the networking distance between the indicator and sensor nodes, the shortest path routing algorithm was applied for WSN(Wireless Sensor Network) networks. The indicator sends the state information of the crane to monitoring server through IEEE 802.11 b wireless LAN(Local Area Network). Monitoring server decides whether alarm should be issued or not. The performance of developed WSN and Bluetooth network were evaluated and analyzed in terms of communication delay and throughput.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1713-1720
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• 2009

An local area weather condition monitoring system to minimize many disasters from the sudden change of weather condition in local and mountain ales is proposed. Firstly, the comparison of present state of the related monitoring systems and the possibility of realization with some merits are investigated. Moreover, this paper present direction of local area weather condition monitoring system based on integration of wireless sensor network and CDMA network following some case study. The sensor node for wireless sensor network and an interface dongle are fabricated for the system. The stand-alone software in cellular phone is also developed. Through the efficient integration of both networks, the measured weather condition data from sensors can be transmitted to the server or mobile to monitor with high reliability. The proposed monitoring system will guide new type of project in wireless sensor network and support alarm service of the sudden change of weather condition to mobile user from central official regulations.

• Corrosion Science and Technology
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• v.7 no.4
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• pp.208-211
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• 2008

Safety operation of main pipelines is primarily provided by anticorrosive monitoring. Anticorrosive monitoring of oil pipeline transportation objects is based on results of complex corrosion inspections, analysis of basic data including design data, definition of a corrosion residual rate and diagnostic of general equipment's technical condition. All the abovementioned arrangements are regulated by normative documents. For diagnostics of corrosion-technical condition of oil pipeline transportation objects one presently uses different methods such as in-line inspection using devices with ultrasonic, magnetic or another detector, acoustic-emission diagnostics, electrometric survey, general external corrosion diagnostics and cameral processing of obtained data. Results of a complex of diagnostics give a possibility: $\cdot$ to arrange a pipeline's sectors according to a degree of corrosion danger; $\cdot$ to check up true condition of pipeline's metal; $\cdot$ to estimate technical condition and working ability of a system of anticorrosive protection. However such a control of corrosion technical condition of a main pipeline creates the appearance of estimation of a true degree of protection of an object if values of protective potential with resistive component are taken into consideration only. So in addition to corrosive technical diagnostics one must define a true residual corrosion rate taking into account protective action of electrochemical protection and true protection of a pipeline one must at times. Realized anticorrosive monitoring enables to take a reasonable decision about further operation of objects according to objects' residual life, variation of operation parameters, repair and dismantlement of objects.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.211-214
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• 2002

The detection of tool wear is very important in an automated manufacturing system. This paper presents a tool condition monitoring system based on the wavelet transform analysis of the AC servo motor current in a milling process. The current measurement is relatively simple and does not affect machining operations. The discrete wavelet transform was used to decompose the current of a spindle AC servo motor in the time and frequency domain. The feature vectors were extracted from the decomposed signals and compared to clarity normal and wear conditions. The results show the feasibility of the wavelet transform analysis for the tool condition monitoring.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.366-372
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• 2007

Self-sensing measurement of piezo inkjet and its application are discussed. The pressure wave inside the inkjet dispenser was measured by current measurement due to self-sensing capability of PZT. The pressure wave measured from current was verified by commercially available laser vibrometer. Here, two applications using self-sensing signal were discussed: waveform design for high speed jetting and condition monitoring. For waveform design, two pulse waveform was designed based on self-sensing signal such that the pressure wave after droplet formation can be minimized. For condition monitoring, self-sensing signal was shown to be effective in detecting air bubble trapped in inkjet printhead.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.243-245
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• 2005

Condition monitoring is desirable for increasing machinery availability, reducing consequential damage, and improving operational efficiency. In this paper, a model-based method using neural network modeling of induction noter in vibration spectra is proposed for machine fault detection and diagnosis. The short-time Fourier transform (STFT) is used to process the quasi-steady vibration signals to continuous spectra so that the neural network model can be trained with vibration spectra. And the faults are detected from changes in the expectation of vibration spectra modeling error. The effectiveness of the proposed method is demonstrated through experimental results.

• Tribology and Lubricants
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• v.10 no.4
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• pp.51-58
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• 1994

Condition monitoring technology has recently been received much attention in the light of its significance on the maintenance of complex machineries such as turbines in power plants. Currently, turbines in power plants are maintained by scheduled overhaul based on the manufacturer's recommendations and the utility's experience. Although this preventive maintenance is known to be very effective, operators have less access to identify failure of elements when it happens between overhaul period. Therefore, in this study, a development of a on-line condition monitoring system through wear debris analysis of lubricating oils is aimed with a view to detecting abnormal wear behaviour of bearings and other wet-components at an early stage, allowing better outage scheduling and minimizing forced outages. For field application purposes, the on-line system developed was installed on the turbine of the No.4 unit at Ulsan Power Plant and its performance has been evaluated on site.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.10a
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• pp.36-39
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• 2000

This paper presents the technology of condition diagnosis & life estimation on insulation system of the traction motor. In the non-destructive methods for diagnosis of coil insulation state, residual dielectric strength is estimated by the D-map which consist of the partial discharge quantity Q and average degradation degree $\Delta$. In the operating history of machine, the N-Y life estimation method is based on the stop-starting numbers and operating times with considering each degradation factor by the thermal, electrical and heat-cycle stress. With the on-line conditioning monitoring on the currents of traction motors, detecting the abnormal operating state due to bearing faults, stator or armature faults, eccentricity related faults and broken rotor bars can be performed.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.617-620
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• 2017

The periodic monitoring of crop conditions and timely estimation of crop yield are of great importance for supporting agricultural decision-makings, as well as for effectively coping with food security issues. Remote sensing has been regarded as one of effective tools for crop condition monitoring and crop type classification. Since 2010, RDA (Rural Development Administration) has been developing technology for monitoring on crop condition using remote sensing and model. These special papers address recent state-of-the-art of remote sensing and geospatial technologies for providing operational agricultural information, such as, crop yield estimation methods using remote sensing data and process-oriented model, crop classification algorithm, monitoring and prediction of weather and climate based on remote sensing data,system design and architecture of crop monitoring system, history on rice yield forecasting method.