• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.33 no.3
• /
• pp.219-224
• /
• 2010

Depreciation accounting has as its main objective, the recovery of the original cost of plant investment less net salvage, over the estimated useful life of that plant. Accuracy of the whole life technique in meeting this objective depends entirely on the original estimates of service life and net salvages for an account. Where the whole life technique has been used and original estimates prove inaccurate, excessive or deficient accumulations in the depreciation reserve frequently occur. To overcome this, the remaining life technique is suggested to better match the challenges of accelerated technology and competition within the regulated environment. The flexibility of the remaining life technique will allow an even chance to provide a complete recovery of the original cost.

• Structural Engineering and Mechanics
• /
• v.53 no.4
• /
• pp.681-702
• /
• 2015

Fracture analysis and remaining life prediction has been carried out for aluminium alloy (Al 2014A) plate panels with concentric stiffener by varying sizes and positions under fatigue loading. Tension coupon tests and compact tension tests on 2014A have been carried out to evaluate mechanical properties and crack growth constants. Domain integral technique has been used to compute the Stress intensity factor (SIF) for various cases. Generalized empirical expressions for SIF have been derived for various positions of stiffener and size. From the study, it can be concluded that the remaining life for stiffened panel for particular size and position can be estimated by knowing the remaining life of corresponding unstiffened panel.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.27 no.1
• /
• pp.48-55
• /
• 2022

This paper proposes a battery remaining useful life (RUL) prediction method using a deep learning-based EMD-CNN-LSTM hybrid method. The proposed method pre-processes capacity data by applying empirical mode decomposition (EMD) and predicts the remaining useful life using CNN-LSTM. CNN-LSTM is a hybrid method that combines convolution neural network (CNN), which analyzes spatial features, and long short term memory (LSTM), which is a deep learning technique that processes time series data analysis. The performance of the proposed remaining useful life prediction method is verified using the battery aging experiment data provided by the NASA Ames Prognostics Center of Excellence and shows higher accuracy than does the conventional method.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.6
• /
• pp.100-107
• /
• 1999

This paper describes a probabilistic remaining life assessment program for the creep crack growth. The probabilistic life assessment program is developed to increase the reliability of life assessment. The probabilistic life assessment involves some uncertainties, such as, initial crack size, material properties, and loading condition, and a triangle distribution function is used for random variable generation. The resulting information provides the engineer with an assessment of the probability of structural failure as a function of operating time given the uncertainties in the input data. This study forms basis of the probabilistic life assessment technique and will be extended to other damage mechanisms.

• Nuclear Engineering and Technology
• /
• v.52 no.9
• /
• pp.1998-2008
• /
• 2020

Solenoid operated valves (SOV) play important roles in industrial process to control the flow of fluids. Solenoid valves can be found in so many industries as well as the nuclear plant. The ability to be able to detect the presence of faults and predicting the remaining useful life (RUL) of the SOV is important in maintenance planning and also prevent unexpected interruptions in the flow of process fluids. This paper proposes a fault diagnosis method for the alternating current (AC) powered SOV. Previous research work have been focused on direct current (DC) powered SOV where the current waveform or vibrations are monitored. There are many features hidden in the AC waveform that require further signal analysis. The analysis of the AC powered SOV waveform was done in the time and frequency domain. A total of sixteen features were obtained and these were used to classify the different operating modes of the SOV by applying a machine learning technique for classification. Also, a deep neural network (DNN) was developed for the prediction of RUL based on the failure modes of the SOV. The results of this paper can be used to improve on the condition based monitoring of the SOV.

• Journal of Korean Society of Water and Wastewater
• /
• v.30 no.2
• /
• pp.155-165
• /
• 2016

Pipe Deterioration Prediction (PDP) and Pipe Failure Risk Prediction (PFRP) models were developed in an attempt to predict the deterioration and failure risk in water mains using fuzzy technique and the markov process. These two models were used to determine the priority in repair and replacement, by predicting the deterioration degree, deterioration rate, failure possibility and remaining life in a study sample comprising 32 water mains. From an analysis approach based on conservative risk with a medium policy risk, the remaining life for 30 of the 32 water mains was less than 5 years for 2 mains (7%), 5-10 years for 8 (27%), 10-15 years for 7 (23%), 15-20 years for 5 (17%), 20-25 years for 5 (17%), and 25 years or more for 2 (7%).

• Journal of Welding and Joining
• /
• v.13 no.2
• /
• pp.12-24
• /
• 1995

Recently, more researches have been actively performed for the assessment of material degradation and residual-life of elevated temperature plant components, as some of domestic fossil power plants become older than 30 years. In this paper, results of on_site residual life assessment are reported for main steam pipes of Youngwol power station #2 which have operated since 1965. For critical weld locations such as butt welds branch welds, Y_sections and a T-section, replication technique and hardness measurement technique were employed for life_assessment. When cracks were detected by conventional NDT tests, crack growth life was calculated using a computer code. On the other hand, for matrix of pipes, residual life was quantitatively estimated by an analytic method and material degradation was estimated qualitatively using diameter measurement data and grain-boundary etching method. Also, direction in further improvement of on-site life assessment techniques are proposed.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.14 no.5
• /
• pp.119-127
• /
• 2010

This paper provides a new approach for durability prediction of reinforced concrete structures exposed to carbonation. In this method, the prediction can be updated successively by a Bayes' theorem when additional data are available. The stochastic properties of model parameters are explicitly taken into account in the model. To simplify the procedure of the model, the probability of the durability limit is determined based on the samples obtained from the Latin Hypercube Sampling(LHS) technique. The new method may be very useful in design of important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored. For using the new method, in which the prior distribution is developed to represent the uncertainties of the carbonation velocity using data of concrete structures(3700 specimens) in Korea and the likelihood function is used to monitor in-situ data. The posterior distribution is obtained by combining a prior distribution and a likelihood function. Efficiency of the LHS technique for simulation was confirmed through a comparison between the LHS and the Monte Calro Simulation(MCS) technique.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.10 s.181
• /
• pp.2597-2602
• /
• 2000

The most effective means of evaluating remaining life is through the creep testing of samples removed from the component. But sampling of large specimen from in-service component is actually impossible. So, sampling device and small-specimen creep tester have been applied. Sampling device has been devised to extract mechanically small samples by hemispherical, diamond -coated cutter from the surface of turbine rotor bores and thick-walled pipes without subsequent weld repairs requiring post weld heat treatment. A method of manufacturing small creep specimen, 2min gage diameter and 10min gage length, using electron beam welding to attach grip section, has been proven. Small-specimen creep tester has been designed to control atmosphere to prevent stress increment by oxidation during experiment. To determine whether the small specimens successfully reproduce the behavior of large specimens, creep rupture tests for small and large specimens have been performed at identical conditions. Creep rupture times based on small specimens have closely agreed within 5% error compared with that of large specimen. The errors in rupture time have decreased at longer test period. This comparison validates the procedure for fabricating and testing on small specimen. This technique offers potential as an efficient method for remaining life assessment by direct sampling from in -service high temperature components.

• Proceedings of the KSME Conference
• /
• 2000.04a
• /
• pp.914-919
• /
• 2000

In most case high temperature components in fossil power plant are damaged by fatigue, creep and degradation. Design of power plant components is based on ideal loading such as temperature, pressure and so on. But in many cases unexpected loadings are applied at components. A key ingredient in plant life extension is the preventive diagnosis technology and remaining-life-assessment technology. This paper describes diagnosis technology and life-assessment technology for power plant boiler. It helps in setting up proper inspection schedules, maintenance procedures, and operating procedure.