• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.846-855
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• 2020

A loose part monitoring system is used to detect unexpected loose parts in a reactor coolant system in a nuclear power plant. It is still necessary to develop a new methodology for the localization and mass estimation of loose parts owing to the high estimation error of conventional methods. In addition, model-based diagnostics recently emphasized the importance of a model describing the behavior of a mechanical system or component. The purpose of this study is to propose a new localization and mass-estimation method based on finite element analysis (FEA) and optimization technique. First, an FEA model to simulate the propagation behavior of the bending wave generated by a metal sphere impact is validated by performing an impact test and a corresponding FEA and optimization for a downsized steam-generator structure. Second, a novel methodology based on FEA and optimization technique was proposed to estimate the impact location and mass of a loose part at the same time. The usefulness of the methodology was then validated through a series of FEAs and some blind tests. A new feature vector, the cross-correlation function, was also proposed to predict the impact location and mass of a loose part, and its usefulness was then validated. It is expected that the proposed methodology can be utilized in model-based diagnostics for the estimation of impact parameters such as the mass, velocity, and impact location of a loose part. In addition, the FEA-based model can be used to optimize the sensor position to improve the collected data quality in the site of nuclear power plants.

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1555-1562
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• 2017

A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.6
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• pp.487-491
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• 2008

Tuning of the speed controller in the linear servo applications needs the accurate information of a mover mass including a load mass. Therefore this paper proposes the mass estimation method of a permanent magnet linear synchronous motor(PMLSM) applied at the vertical axis by using the recursive Least-Squares estimation algorithm. First, this paper derives the deterministic autoregressive moving average(DARMA) model of the mechanical dynamic system used at the vertical axis. The application of the Least-Squares algorithm to the derived DARMA model gives the mass estimation method. Matlab/Simulink-based simulation and experimental results show that the total mover mass of a PMLSM applied at the vertical axis can be accurately estimated at both no-load and load conditions.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.427-429
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• 2005

In order to tune the speed controller in the linear servo applications the accurate information of a mover mass including a load mass is always required. This paper suggests the mass estimation method of a permanent magnet linear synchronous motor(PMLSM) by using the parameter estimation method of Least-Squares algorithm. First, the deterministic autoregressive moving average(DARMA) model of the mechanical dynamic system is derived. The application of the Least-Squares algorithm shows that the mass can be accurately estimated both in the simulation results and in the experimental results.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.2
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• pp.159-163
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• 2006

In order to tune the speed controller in the linear servo applications an accurate information of a mover mass including a load mass is always required. This paper suggests the mass estimation method of a permanent magnet linear synchronous motor(PMLSM) 4y using the parameter estimation method of Least-Squares algorithm. First, the deterministic autoregressive moving average(DARMA) model of the mechanical dynamic system is derived. Then the application of the Least-Squares algorithm shows that the mass can be accurately estimated both in the simulation results and in the experimental results.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.59-64
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• 2011

In this paper, the lumped element model parameter estimation method and its implemented estimation software for fabricated floating mass transducers of IMEHDs have been presented so that the estimated parameter values could be compared with the designed ones and applied to predict the output performance when the transducers were implanted into human ears. The presented method is based on the sequential quadratic programming (SQP) for estimating parameters in the transducer's lumped model and has been implemented by the use of LabVIEW graphical language. Using the implemented estimation software, the accuracy of parameter estimation has been verified and our implemented estimation method has been evaluated by the comparison of the estimated transducer parameter values with the designed ones for a practically fabricated floating mass transducer for IMEHDs.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.5
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• pp.131-139
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• 2001

Highly accurate control of the air-fuel ratio is important to reduce exhaust gas emissions of the gaseous-fuel engines. In order to achieve this purpose, inlet air mass flow must be measured exactly, and precise engine models are necessary to design engine control systems. In this paper, the effects of water vapor and gaseous fuel that change the air mass flow are studied. The effective air mass ratio is defined as the air mass flow divided by the mixture mass flow, and also it is applied to the estimation of the inlet air mass flow. The presence of the gaseous fuel and the water vapor in the mixture reduces the air partial pressure and the effective air mass ratio of the gaseous-fuel engines. The Experimental results for an LPG engine show that the estimation of the inlet ai mass flow based upon the effective air mass ratio is more accurate than that of the normal air mass flow.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.5
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• pp.80-87
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• 2003

Air partial pressure ratio and inlet air mass flow are influenced by water vapor and gaseous fuel in mixture on Compressed Natural Gas (CNG) engines. In this paper, the effects of the water vapor and the gaseous fuel that change the air mass flow and the air-fuel ratio are studied. Effective air mass ratio is defined as the air mass flow divided by mixture mass flow, and also it is applied to the estimation of the inlet air mass flow and the air-fuel ratio. The presence of the gaseous fuel and the water vapor in the mixture reduces the air partial pressure and the effective air mass ratio of the CNG engines. The experimental results for the CNG engine show that estimation of the air-fuel ratio based upon the effective air mass ratio is more accurate than that of a normal mode.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.663-671
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• 2008

This paper presents a real-time haptic rendering method for multi-contact interaction with virtual environments. Haptic systems often employ physics-based deformation models such as finite-element models and mass-spring models which demand heavy computational overhead. The haptic system can be designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. A multi-rate output-estimation with an exponential forgetting factor is proposed to implement real-time haptic rendering for the haptic systems with two sampling rates. The computational burden of the output-estimation increases rapidly as the number of contact points increases. To reduce the computation of the estimation, the multi-rate output-estimation with reduced parameters is developed in this paper. Performance of the new output-estimation with reduced parameters is compared with the original output-estimation with full parameters and an exponential forgetting factor. Estimated outputs are computed from the estimated input-output model at a high rate, and trace the analytical outputs computed from the deformation model. The performance is demonstrated by simulation with a linear tensor-mass model.

• KSBB Journal
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• v.4 no.2
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• pp.118-122
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• 1989

From the on-line mass spectrometric analyese of the exhaust gaseous composition of fermentor and the material balance equations for oxygen and carbon dioxide, oxygen uptake rate (OUR) and carbon dioxide evolution rate (CER) were calculate using a personal computer (IBM PC-AT) interfaced to a quadrupole mass spectromter. The calculate OUR and CER were used for the indirect estimation of cell and substrate concentrations during the batch culture of Candida utilis. For the estimation of sustrate concentration, the yield model of Pirt was applied. It was found that the cell and substrate (glucose) concentration could be ssatisfactorily estimataed and the results showed the more accurate estimations of both fermentation state variables when OUR data were used than CER data.