• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.301-303
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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. Results obtained by the Matlab/Simulink simulation show that the mass of a PMLSM applied at the vertical axis can be accurately estimated both at no-load and at load.

• Nuclear Engineering and Technology
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• v.43 no.4
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• pp.343-354
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• 2011

It is critically important to identify unexpected loose parts in a nuclear reactor pressure vessel, since they may collide with and cause damage to internal structures. Mass estimation can provide key information regarding the kind as well as the location of loose parts. This study proposes a mass estimation method based on an artificial neural network (ANN), which can overcome several unresolved issues involved in other conventional methods. In the ANN model, input parameters are the discrete cosine transform (DCT) coefficients of the auto-power spectrum density (APSD) of the measured impact acceleration signal. The performance of the proposed method is then evaluated through application to a large-sized plate and a 1/8-scaled mockup of a reactor pressure vessel. The results are compared with those obtained using a conventional method, the frequency ratio (FR) method. It is shown that the proposed method is capable of estimating the impact mass with 30% lower relative error than the FR method, thus improving the estimation performance.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.36-45
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• 2014

Model based control methods are widely used to improve the control performance of diesel engine air systems because the control results of the air system significantly affect the emission level and drivability. However, the model based control algorithm requires a lot of unmeasurable states which are hard to be measured in a mass production engine. In this study, an air system model of the diesel engine is proposed to estimate 11 unmeasurable states using only sensors equipped in a mass production engine. In order to improve the estimation performance in the transient condition, dynamic characteristics of the air system are analyzed and implemented as discrete filters. Turbine and compressor efficiency models are also proposed to overcome a limitation of the constant or look-up table based efficiency values. The proposed air system model was validated in steady state and transient conditions by real-time engine experiments. The maximum error of the estimation for 11 physical states was 11.7%.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.4
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• pp.62-72
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• 2013

To operate an automatic picking system in distribution center with high precision and high dynamics, this paper presents a robust control scheme of a linear induction motor (LIM) using the mass estimation and disturbance force observer. The force disturbance which gives a direct influence on the control performance of LIM is estimated in real-time through the disturbance observer and compensated by a feedforward manner. To get a satisfactory performance even under the mass variation by reducing the disturbance force due to the mismatched mass during the speed transient such as the acceleration and deceleration periods, a mass estimation algorithm is proposed. A Simulink model for LIM is developed and the validity of the proposed scheme is verified through the comparative simulation studies using Matlab - Simulink.

• Journal of Auto-vehicle Safety Association
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• v.12 no.2
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• pp.14-20
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• 2020

This paper presents a vehicle mass and road grade estimator for developing an automated bus. To consider the dynamic characteristics of a bus varying with the number of passengers, the longitudinal controller needs the estimation of the vehicle's mass and road grade in real-time and utilizes the information to adjust the control gains. Discrete Kalman filter is applied to estimate the time-varying road grade, and the recursive least squares algorithm is adopted to account for the constant mass estimation. After being implemented in MATLAB/Simulink, the estimators are evaluated with the dynamic model and experimental data of the target bus. The proposed estimators will be applied to complement the algorithm of the longitudinal controller and proceed with algorithm verification.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.4
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• pp.387-396
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• 2003

A field study was conducted during the summer time of 2002 to determine compositions of volatile organic compounds (VOCs) emitted from vehicles and to develop source emission profiles that is applied to CMB model to estimate the source contribution of certain area. Source emission profile is widely used for the estimation of source contribution by the chemical mass balance model and have to be developed applicable for the target area of estimation. This study was aimed to develop source emission profile and estimation of source contribution of VOCs after application of the chemical mass balance (CMB) receptor model. After considering the emission inventory and other research results for the VOCs in Seoul, Korea, the sources like vehicle emission (tunnel), gas station (gasoline, diesel), solvent usage (painting operation, dry cleaning, graphic art), and gas fuels were selected for the major VOCs sources. Furthermore, ambient air samples were simultaneously collected from 09:00 to 11:00 for four days at eight different official air quality monitoring sites as receptors in Seoul during summer of 2001. Source samples were collected by canisters, and then about seventy volatile organic compounds were analyzed by gas chromatography with flame ionization detector (GC/FID). Based on both the developed source profiles and the database of the receptors, CMB model was intensively applied to estimate mass contribution of VOCs sources. Examining the source profile from the vehicle, the portion of alkanes of VOCs was highest, and then the portion of aromatics such toluene, m/p-xylene were followed. In case of gas fuel. they have their own components; the content of butane, propane, ethane was higher than any other component according to the fuel usage. The average of the source apportionment on VOCs for 8 sites showed that the major sources were vehicle emission and gas fuels. The vehicle emission source was revealed as having the highest contribution with an average of 49.6%, and followed by solvent with 21.3%, gas fuel with 16.1%, gasoline with 13.1%.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.8
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• pp.783-790
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• 2010

In this paper, we propose a turbine mass flow rate model for a variable geometry turbocharger (VGT) using an artificial neural network (ANN). The model predicts the turbine mass flow rate using the VGT vane position, engine rotational speed, exhaust manifold pressure, exhaust manifold temperature, and turbine outlet pressure. The ANN is used for the estimation of the effective flow area. In order to validate the results estimated by the proposed model, we have compared estimation results with engine experimental results. The results, in addition, represent improved estimation accuracy when compared with the performance using the turbine map.

• Korean Journal of Exercise Nutrition
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• v.24 no.1
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• pp.9-13
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• 2020

[Purpose] This preliminary study aimed to develop a regression model to estimate the resting metabolic rate (RMR) of young and middle-aged Koreans using various easy-to-measure dependent variables. [Methods] The RMR and the dependent variables for its estimation (e.g. age, height, body mass index, fat-free mass; FFM, fat mass, % body fat, systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, and resting heart rate) were measured in 53 young (male n = 18, female n = 16) and middle-aged (male n = 5, female n = 14) healthy adults. Statistical analysis was performed to develop an RMR estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and age were important variables in both the regression models based on the regression coefficients. Mean explanatory power of RMR₁ regression models estimated only by FFM was 66.7% (R²) and 66.0% (adjusted R²), while mean standard errors of estimates (SEE) was 219.85 kcal/day. Additionally, mean explanatory power of RMR₂ regression models developed by FFM and age were 70.0% (R²) and 68.8% (adjusted R²), while the mean SEE was 210.64 kcal/day. There was no significant difference between the measured RMR by the canopy method using a metabolic gas analyzer and the predicted RMR by RMR₁ and RMR₂ equations. [Conclusion] This preliminary study developed a regression model to estimate the RMR of young and middle-age healthy Koreans. The regression model was as follows: RMR₁ = 24.383 × FFM + 634.310, RMR₂ = 23.691 × FFM - 5.745 × age + 852.341.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.5
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• pp.701-711
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• 2006

Sewage treatment plants located near to large cities emit extremely higher concentration of odorous materials. This study evaluated flux profiles of ammonia emitted from the water surface of sewage treatment plants using a dynamic flux chamber. Also, an ammonia overall mass transfer coefficient and a mass transfer model was developed in order to estimate fluxes of ammonia using environment parameters and the flux from the sewage treatment plants. The developed mass transfer model was evaluated through a fitness analysis. Comparison modeled flux applying empirical overall mass transfer coefficients of ammonia and measured ammonia flux show a high linearity with 0.977. The flux ratio of 1.282 demonstrated highly statistical fitness, also. Modeled flux using the mass transfer model was compared with measured flux. In result, it indicated that empirical overall mass transfer coefficients were similar to measured flux. The mass transfer model using the empirical overall mass transfer coefficient developed in this study was proved to be an easy and effective method to make accurate and precise predictions for ammonia flux discharged from sewage treatment plants.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.228-234
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• 2000

The aim of the work is to present a new method of estimating the existence of a mass unbalance and mass unbalance under a crack on a rotating shaft. This is an advanced new method for the detection of a mass unbalance and a new way to estimate the position of it under crack influence. As the first step, the shaft is physically modelled with a finite element method and the dynamic mathematical model is derived by using the Hamilton principle; thus, the system is represented by various subsystems. The equation of motion of the shaft with a mass unbalance and a crack are established by adapting the local mass unbalance and the stiffness change. this is a reference system for the given system. Based on a model for transient behavior induced from vabrations measured at the bearings, an elementary Estimator is designed to detect mass unblance on the shaft. Using the Estimator, a bank of the Estimator is established to estimate the estimate the position of the mass unbalance and arranged at a certain location on the shaft. The informations for the given system are the measurements of bearing displacements and velocity.