• Journal of Sensor Science and Technology
• /
• v.9 no.2
• /
• pp.141-145
• /
• 2000

In order to measure the thickness of the slag layer on the molten metal in the melting vessels for steel making foundaries, we manufactured the slag-thickness measuring system consisting of the probe and its driving system, which is based on the principle of detecting the change in the electrical resistivity. Experimental results show that there is a very wide difference of the electrical resistivity by the order of about $10^3$ between the molten metal and the hot slag and, hence, the air/slag and slag/molten metal interface can be exactly detected with the use of the probe which can be moved toward the melt. Therefore, it can be concluded that the proposed scheme of the slag measurement system in this study is Proven to be excellent in its efficiency and accuracy.

• Journal of Power System Engineering
• /
• v.15 no.1
• /
• pp.18-23
• /
• 2011

Image processing has provided powerful techniques to extract from the acoustic signals the desired information on evaluation for leakage existence, leakage rate, and searching for leakage location, etc. The imagery NDE data available can add additional and significant dimension in nondestructive evaluation(NDE) information and thus for exploiting in applications. To extract such information the use of advanced image processing techniques is much needed. In recent years, there has been much increased use of acoustic signal image processing techniques in acoustic NDE. This approach will increase the efficiency of inspection procedures and reduce inspection time. In this paper we are concerned only with This paper is concerned mainly with the use of advanced image processing techniques in valve leakage detection and advanced image restoration and enhancement methods, which attempt to evaluate promptly by a visualization method the acoustic sources while detecting the valve leakage.

• Journal of the Korean Society for Precision Engineering
• /
• v.33 no.6
• /
• pp.517-523
• /
• 2016

Unlike household refrigerators, commercial refrigerators are composed of separate indoor and outdoor units. The outdoor unit of most commercial refrigerators is designed to run at a fixed speed, which results in low energy efficiency and loud fan noise. Moreover, it cannot respond flexibly to changing thermal load in the indoor unit. Inverter type outdoor units can address such problems through speed changes based on information obtained from the indoor unit. However, using two units from different manufacturers is often not a viable solution. If condition changes in the indoor unit can be detected without communication between the two units, it is possible to adjust the speed of the outdoor unit. This paper attempts to analyze the signal from the outdoor unit when the condition of the indoor unit changes by varying the thermal load.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
• /
• 2002.05a
• /
• pp.34-39
• /
• 2002

The surfaces of machine components in sliding contact such as bearing, gears and pistons etc. frequently operate under the condition of mixed lubrication due to high load, high speed and slip. These machine components often undergo the inception of scuffing in practical application. The scuffing failure is a critical problem in modern machine components, especially for the requirement of high efficiency and small size. However, it is difficult to find a universal mechanism to explain all scuffing phenomena because there are so many factors affecting the onset of scuffing. In this study, scuffing experiments are conducted using Acoustic Emission(AE) measurement by an indirect sensing approach to detect scuffing failure. Acoustic Emission(AE) signal has been widely utilized to monitor the interaction at the friction interface. Using AE signals we can get an indication about the state of the friction processes, about the quality of solid and liquid layers eon the contacting surfaces in real time. The FFT(Fast Fourier Transform)analyses of the AE signal are used to understand the interfacial interaction and the relationship between the AE signal and the state of contact is presented

• Journal of Advanced Navigation Technology
• /
• v.14 no.1
• /
• pp.119-126
• /
• 2010

The software reliability growth model(SRGM) has been developed in order to estimate such reliability measures as remaining fault number, failure rate and reliability for the developing stage software. Almost of them assumed that the faults detected during testing were eventually removed. Namely, they have studied SRGM based on the assumption that the faults detected during testing were perfectly removed. The fault removing efficiency, however, is imperfect and it is widely known as so in general. It is very difficult to remove detected fault perfectly because the fault detecting is not easy and new error may be introduced during debugging and correcting. Therefore, We want to study imperfect software testing effort for the logistic testing effort which is thought to be the most adequate in this paper.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.2069-2070
• /
• 2011

In this paper, the fault diagnosis for a gearbox of BLDC motor. The stator of BLDC motor consists of coil winding so it is easy to cool down and it also has a high reliability. In addition, it doesn't have a brush so it is less trouble and good in maintenance. Coupling with the motor which is the power sources, the gear has a high power transfer efficiency and various rotation speed. The gear gets a high driving force through deceleration. Thus it has been widely used. The gearbox fault detection area has not attracted much attention from electrical engineering community. A few papers describe gearbox fault based on vibration. Gearbox fault is diagnosed through FFT analysis of current and voltage. Fault characteristic frequency side band detected by calculating fault frequency. A threshold value is suggested by comparing normal peak value with fault peak value using detected fault characteristic frequency side band. Experimental results demonstrate that motor current and voltage signal analysis are viable tools in detecting these gear faults. Lower side band(LSB) is bigger than upper side band(USB) in current FFT. LSB and USB are similar in voltage FFT. Finally, fault diagnosis system that can easily detect flaws is developted for gearbox of BLDC motor.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.4
• /
• pp.1899-1909
• /
• 2015

Glaucoma is one of the most common causes of blindness which is caused by increase of fluid pressure in the eye which damages the optic nerve and eventually causing vision loss. An automated technique to diagnose glaucoma disease can reduce the physicians’ effort in screening of Glaucoma in a person through the fundal retinal images. In this paper, optimal hyper analytic wavelet transform for Glaucoma detection technique from fundal retinal images is proposed. The optimal coefficients for transformation process are found out using the hybrid GSO-Cuckoo search algorithm. This technique consists of pre-processing module, optimal transformation module, feature extraction module and classification module. The implementation is carried out with MATLAB and the evaluation metrics employed are accuracy, sensitivity and specificity. Comparative analysis is carried out by comparing the hybrid GSO with the conventional GSO. The results reported in our paper show that the proposed technique has performed well and has achieved good evaluation metric values. Two 10- fold cross validated test runs are performed, yielding an average fitness of 91.13% and 96.2% accuracy with CGD-BPN (Conjugate Gradient Descent- Back Propagation Network) and Support Vector Machines (SVM) respectively. The techniques also gives high sensitivity and specificity values. The attained high evaluation metric values show the efficiency of detecting Glaucoma by the proposed technique.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.6
• /
• pp.2178-2186
• /
• 2018

Online identification of load parameters is the premise of establishing a stable and highly-efficient ICPT (Inductive Coupled Power Transfer) system. However, compared with pure resistive load, precise identification of composite load, such as resistor-inductance load and resistance-capacitance load, is more difficult. This paper proposes a method for detecting the composite load parameters of ICPT system utilizing harmonics. In this system, the fundamental and harmonic wave channel are connected to the high frequency inverter jointly. The load parameter values can be obtained by setting the load equation based on the induced voltage of secondary-side network, the fundamental wave current, as well as the third harmonic current effective value received by the secondary-side current via Fourier decomposition. This method can achieve precise identification of all kinds of load types without interfering the normal energy transmission and it can not only increase the output power, but also obtain higher efficiency compared with the fundamental wave channel alone. The experimental results with the full-bridge LCCL-S type voltage-fed ICPT system have shown that this method is accurate and reliable.

• Journal of Broadcast Engineering
• /
• v.4 no.1
• /
• pp.22-31
• /
• 1999

Moving object tracking improves the efficiency and qualification for observation system, broadcasting system, video conference, etc. This paper propcses an improved Bayes decision method for detecting and tracking moving objects in active camera environment. The Bayes decision based tracking approach finds the region of moving objects by analyzing the image sequences statistically. The propcsed algorithm regenerates the probability density function to accord with moving objects and background for active camera. Experimental results show that the algorithm is accurate. reliable and noise resistant. The result is compared with those of the conventional methods.

• Smart Structures and Systems
• /
• v.14 no.5
• /
• pp.917-942
• /
• 2014

Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.