• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.5
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• pp.45-50
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• 2011

Compression pressure of individual cylinder and valve timing have big influence on combustion pressure, indicated mean effective pressure (IMEP), emission, vibration, combustion noise and many other combustion parameters. Conventional method, however, to check compression pressure uniformity is done by mechanical pressure gage and valve timing is checked manually. This conventional method causes inaccuracy of cylinder pressure measurement because of different cranking speed results from battery status and temperature. Also to check valve timing, related FEAD parts should be disassembled and timing mark should be checked. This study describes and suggests new methodology to measure compression pressure by analysis of start motor current and to check valve timing by cylinder pressure with high accuracy. Results, it is found that detection of bulky as well as small leaky cylinder is possible by cranking motor current analysis and wrong valve timing can be detected by cylinder pressure analysis and cam and crank sensor signal.

• Nuclear Engineering and Technology
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• v.36 no.6
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• pp.540-548
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• 2004

Check valve failure is one of the worst problems in nuclear power plants. Recently, many researches have been based on new technology using accelerometers and ultrasonic and magnetic flux detection have been carried out. Here, we have suggested a method that uses acoustic emission sensors for detecting the failures of check valves through measuring and analyzing backward leakage flow, a system that works without disassembling the check valve. For validating the suggested acoustic emission sensor methodology, we designed a hydraulic test loop with a check valve. We have assumed in this study that check valve failure is caused by disk wear or by the insertion of a foreign object. In addition, we have developed diagnostic algorithms by using a neural network model to identify the type and size of the failure in the check valve. Our results show that the proposed diagnostic algorithm with acoustic emission sensors is a good solution for identifying check valve failure without necessitating any disassembly work.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.429-438
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• 1997

Mechanical valve is one of the most widely used implantable artificial organs of which the reliability is so important that its failure means the death of patient. Therefore early noninvasive detection is essentially required, though mechanical valve failure with thrombosis is the most common. The objective of this paper is to detect the thrombosis formation by spectral analysis and neural network. Using microphone and amplifier, we measured the sound from the mechanical valve which is attached to the pneumatic ventricular assist device. The sound was sampled by A/D converter(DaqBook 100) and the periodogram is the main algorithm for obtaining spectrum. We made the thrombosis models using pellethane and silicon and they are thrombosis model on the valvular disk, around the sewing ring and fibrous tissue growth across the orifice of valve. The performance of the measurment system was tested firstly using 1 KHz sinusoidal wave. The measurement system detected well 1KHz spectrum as expected. The spectrum of normal and 5 kinds of thrombotic valve were obtained and primary and secondary peak appeared in each spectrum waveform. We find that the secondary peak changes according to the thrombosis model. So to distinguish the secondary peak of normal and thrombotic valve quantatively, 3 layer back propagation neural network, which contains 7, 000 input node, 20 hidden layer and 1 output was employed The trained neural network can distinguish normal and valve with more than 90% probability. As a conclusion, the noninvasive monitoring of implanted mechanical valve is possible by analysing the acoustical spectrum using neural network algorithm and this method will be applied to the performance evaluation of other implantable artificial organs.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.421-430
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• 2004

Clinically, it is almost impossible for a physician to distinguish subtle changes of frequency spectrum by using a stethoscope alone especially in the early stage of thrombus formation. Considering that reliability of mechanical valve is paramount because the failure might end up with patient death, early detection of valve thrombus using noninvasive technique is important. Thus the study was designed to provide a tool for early noninvasive detection of valve thrombus by observing shift of frequency spectrum of acoustic signals with computer aid diagnosis system. A thrombus model was constructed on commercialized mechanical valves using polyurethane or silicon. Polyurethane coating was made on the valve surface, and silicon coating on the sewing ring of the valve. To simulate pannus formation, which is fibrous tissue overgrowth obstructing the valve orifice, the degree of silicone coating on the sewing ring varied from 20％, 40％, 60％ of orifice obstruction. In experiment system, acoustic signals from the valve were measured using microphone and amplifier. The microphone was attached to a coupler to remove environmental noise. Acoustic signals were sampled by an AID converter, frequency spectrum was obtained by the algorithm of spectral analysis. To quantitatively distinguish the frequency peak of the normal valve from that of the thrombosed valves, analysis using a neural network was employed. A return map was applied to evaluate continuous monitoring of valve motion cycle. The in-vivo data also obtained from animals with mechanical valves in circulatory devices as well as patients with mechanical valve replacement for 1 year or longer before. Each spectrum wave showed a primary and secondary peak. The secondary peak showed changes according to the thrombus model. In the mock as well as the animal study, both spectral analysis and 3-layer neural network could differentiate the normal valves from thrombosed valves. In the human study, one of 10 patients showed shift of frequency spectrum, however the presence of valve thrombus was yet to be determined. Conclusively, acoustic signal measurement can be of suggestive as a noninvasive diagnostic tool in early detection of mechanical valve thrombosis.

• 유체기계공업학회:학술대회논문집
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• 2005.12a
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• pp.607-612
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• 2005

Check valves playa vital role in the operation and protection of nuclear power plants. Check valves failure in nuclear power plants often lead to a plant transient or trip. An overview of the failure history of check valves needs to identify key area where resources can be best applied to further improve their reliability, and provide cost effective means for failure reduction. The analysis of historical failure data gives information on the populations of various types of check valves, the systems they are installed in, failure modes, effects, methods of detection, and the mechanisms of the failures. The results presented are based on information derived from operating records, nuclear industry reports, manufacturer supplied information. A majority of check valve failures are caused by improper application. Failure modes are identified for swing and lift check valves. Failures involving improper seating and valve disc stuck comprised the largest percentage of failures.

• Transactions of The Korea Fluid Power Systems Society
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• v.4 no.4
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• pp.1-7
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• 2007

Flow rate is one of the important variables for precise motion control and detection of the faults and fluid loss in many hydraulic components and systems. But in many cases, it is not easy to measure it directly. The orifice area of a servo valve by which the fluid flows is one of key factors to monitor the flow rate. In this paper, we have constructed an estimation algorithm for the effective orifice area by using the model of a servo valve cylinder control system and Kalman filter algorithm. Without geometry information about the servo valve, it is shown that the effective orifice area can be estimated by using only displacement and pressure data corrupted with noise. And the effect of the biased sensor data and system parameter errors on the estimation results are discussed. The paper reveals that sensor calibration is important in accurate estimation and plausible parameter data such as oil bulk modulus and actuator volume are acceptable for the estimation without any error. The estimation algorithm can be used as an useful tool for detecting leakage, monitoring malfunction and/or degradation of the system performance.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.5
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• pp.662-673
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• 2012

This study introduces a condition diagnosis technique for a turbine governor system. The governor system is an important control system to handle turbine speed in a nuclear power plant. The turbine governor system includes turbine valves and stop valves which have their own functions in the system. Because a turbine governor system is operated by high oil pressure, it is very difficult to maintain under stable operating conditions. Turbine valves supply oil pressure to the governor system for proper operation. Using the pressure variation of turbine and governor valves, operating conditions of the turbine governor control system are detected and identified. To achieve automatic detection of valve status, time-based and frequency-based analysis is employed. In this study, a new approach, wavelet decomposition, was used to extract specific features from the pressure signals of the governor and stop valves. The extracted features, which represent the operating conditions of the turbine governor system, include important information to control and diagnose the valves. After extracting the specific features, decision rules were used to classify the valve conditions. The rules were generated by a decision tree algorithm (a typical simple method for data-based rule generation). The results given by the wavelet-based analysis were compared to detection results using time- and frequency-based approaches. Compared with the several related studies, the wavelet transform-based analysis, the proposed in this study has the advantage of easier application without auxiliary features.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2975-2981
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• 2014

Micro-magnetic detection system is used to detect small particles in an automatic transmission valve body, which signal noise and time-delay may occurs in process of signal transmitting and filtering. In this paper, we present the design and implement of a micro-magnetic detection system based on wireless sensor networks in conveyer belt. Micro-magnetic detection system consists of five modules which are magnetic sensor detector, signal processing unit, wireless sensor networks, system control unit and system monitoring unit. Our experimental results show that the proposed wireless micro-magnetic detection system improves both accuracy and time delay compared to the wired system; therefore, it may apply for wireless micro-magnetic detection system by analysis of packet reception rate.

• Journal of Biosystems Engineering
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• v.23 no.5
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• pp.427-438
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• 1998

In Korea, rotary implements are mainly utilized in the tillage operation. The attitude control system for rolling phenominon of tractors, which in caused due to uneven ground surfaces and sinkage of tractor wheels, is one of the most important control systems in agricultural tractors. The attitude control system of a rotary implement, attached on tractors, was designed and fabricated in this study. The control system was largely composed of four main units; a setting unit, a detection unit, a controller and a hydraulic unit. The implement was controlled by control signals from a computer proportional to controlled errors, on/off action of two directional solenoide valve and lift cylinder on the right lift rod. Response characteristic experiments for the control system fabricated in this study were carried out indoors and outdoors. The results of experiments showed the response characteristics sufficient to use as the attitude control system of rotary implements for agricultural tractors.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2004.11a
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• pp.237-240
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• 2004

Sulfur Hexafluoride, SF6 is widely used for leak detection and as a gaseous dielectric in transformers, condensers and circuit breakers. SF6 gas is also effective as a cleanser in the semiconductor industry. This paper presents a numerical study of the sealing force of disk type seal in SF6 gas safety valve. The sealing force on the disk seal is analyzed by the FEM method based on the Taguch's experimental design technique. Disk seals in SF6 gas safety valve are designed with 9 design models based on 3 different contact length, compressive ratio and gas pressure. The calculated results of Cauchy stress and strain showed that the sealing characteristics of Teflon PTFE is more effective compared to that of FKM(Viton), which is related to the stiffness of the materials. And also, the contact length of the disk seal is important design parameter for sealing the SF6 gas leakage in the safety valve.