• 한국지진공학회논문집
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• 제21권6호
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• pp.287-293
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• 2017

Sometimes, it is impossible to install a sensor on a certain location of a structure due to the size of a structure or poor surrounding environments. Even if possible, sensors can be frequently malfunctioned or improperly operated due to lack of adequate maintenance. These kind of problems are solved by the virtual sensing methods in various engineering fields. Virtual sensing technology is a technology that can measure data even though there is no physical sensor. It is expected that this technology can be also applied to the construction field effectively. In this study, a virtual sensing technology based on ARX model is proposed. An ARX model is defined by using the simulated data through a structural analysis rather than by actually measured data. The ARX-based virtual sensing model can be applied to estimate unmeasured response using a transfer function that defines the relationship between two point data. In this study, a simulation and experimental study were carried out to examine the proposed virtual sensing method with a laboratory test on a cable-stayed model bridge. Acceleration measured at a girder is transformed to estimate a cable tension through the ARX model-based virtual sensing.

• 제어로봇시스템학회논문지
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• 제8권10호
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• pp.827-832
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• 2002

We propose a prediction method of the pollutant and a synchronous classification of the current state of SOx emission in the power plant. We use the auto-regressive with exogeneous (ARX) model as a predictor of SOx emission and use a radial basis function network (RBFN) as a pattem classifier. The ARX modeling scheme is implemented using recursive least squares (RLS) method to update the model parameters adaptively. The capability of SOx emission monitoring is utilized with the application of the RBFN classifier. Experimental results show that the ARX model can predict the SOx emission concentration well and ARX modeling parameters can be a good feature for the state monitoring. in addition, its validity has been verified through the power spectrum analysis. Consequently, the RBFN classifier in combination with ARX model is shown to be quite adequate for monitoring the state of SOx emission.

• 한국구조물진단유지관리공학회 논문집
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• 제13권2호통권54호
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• pp.115-121
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• 2009

본 연구에서는 동적 가속도 데이터를 사용하는 신호기반 손상진단 알고리즘으로 ARX 모델을 제시하였다. ARX 모델은 구조물의 두 지점에서 계측된 가속도 데이터를 입력과 출력의 두 세트 신호로 보고, 두 세트 가속도 데이터의 상관관계를 설정한다. 구조물 손상은 계측한 데이터와 전달함수인 ARX 모델로 예측한 데이터의 차이인 시간이력 잔차를 사용하여 통계적으로 탐색하였다. 시간이력 잔차의 정규분포함수를 구하고, 그 통계적 특성치를 계산하여 손상 평가에 사용하였다. 손상 전후의 정규분포함수를 비교하여 손상을 탐색하기 위하여 세 가지 손상지수를 제시하였다. 손상지수의 통계적 평가를 위해 실내실험을 수행하였고, 제안한 알고리즘의 효율성을 검증하고 제한점을 검토하였다.

• 농업과학연구
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• 제45권4호
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• pp.859-870
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• 2018

Dried red peppers are a staple agricultural product used in Korean cuisine and as such, are an important aspect of agricultural producers' income. Correctly forecasting both their supply and demand situations and price is very important in terms of the producers' income and consumer price stability. The primary objective of this study was to compare the performance of time series forecasting models for dried red peppers in Korea. In this study, three models (an autoregressive model with exogenous variables [ARX], AR-exponential generalized autoregressive conditional heteroscedasticity [EGARCH], and ARX-EGARCH) are presented for forecasting the wholesale price of dried red peppers. As a result of the analysis, it was shown that the ARX model and ARX-EGARCH model, each of which adopt both the rolling window and the adding approach and use the agricultural cooperatives price as the exogenous variable, showed a better forecasting performance compared to the autoregressive model (AR)-EGARCH model. Based on the estimation methods and results, there was no significant difference in the accuracy of the estimation between the rolling window and adding approach. In the case of dried red peppers, there is limitation in building the price forecasting models with a market-structured approach. In this regard, estimating a forecasting model using only price data and identifying the forecast performance can be expected to complement the current pricing forecast model which relies on market shipments.

• Korean Chemical Engineering Research
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• 제45권1호
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• pp.67-72
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• 2007

부분 최소자승회귀, 균형 잡힌 realization, 균형 잡힌 truncation을 결합함으로써, MIMO 상태공간 모델의 모델인식을 위한 효과적인 방법이 개발되었다. 개발된 방법에서 MIMO 시스템은 고차 ARX 모델로 표현되는 다중 MISO 시스템으로 분해된다. 이 때, ARX 모델의 파라미터는 부분 최소자승회귀에 의해 추정된다. 그 후, realization을 통해 각각의 MISO ARX 전달함수에 대한 MISO 상태공간 모델이 만들어지며, MIMO 상태공간 모델로 결합된다. 최종적으로, 균형 잡힌 realization과 균형 잡힌 truncation을 통해 최소의 균형 잡힌 MIMO 상태공간 모델이 얻어진다. 제안된 방법은 고압 $CO_2$ 용해도 측정 실험 장치의 온도제어를 위한 모델 예측 제어의 설계에 적용되었다.

• Earthquakes and Structures
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• 제7권6호
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• pp.1093-1118
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• 2014

A sophisticated story-wise stiffness identification method for a shear building structure is applied to the case where the shear building is subjected to an actual micro-tremor. While the building responses to earthquake ground motions are necessary in the previous method, it is shown that micro-tremors can be used for identification within the same framework. This enhances the extended usability and practicality of the previously proposed identification method. The difficulty arising in the limit manipulation at zero frequency in the previous method is overcome by introducing an ARX model. The weakness of small SN ratios in the low frequency range is avoided by using the ARX model together with filtering and introducing new constraints on the ARX parameters.

• 제어로봇시스템학회논문지
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• 제8권7호
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• pp.556-562
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• 2002

This paper studies the identification of a combustion model, which is used to design a linear controller of a steam generation quantity and harmful exhaust gases of a Refuse Incineration Plant(RIP). Even though the RIP has strong nonlinearities and complexities, it is identified as a MIMO parametric ARX model from experimental input-output data sets. Unknown model parameters are decided from experimental input-output data sets, using system identification algorithm based on Instrumental Variables(IV) method. It is shown that the identified model well approximates the input-output combustion characteristics.

• Advances in robotics research
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• 제2권1호
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• pp.99-112
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• 2018

The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.

• 한국수자원학회논문집
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• 제53권7호
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• pp.481-491
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• 2020

새만금 농업단지가 조성됨에 따라 농업용수 공급이 요구되며, 농업적 측면에서 염분은 작물 재배시 생육에 영향을 미치는 항목으로 농업용수 공급시 철저한 관리가 요구된다. 따라서 농작물에 영향을 미치지 않는 농업용수 공급을 위해 염분계측을 통한 체계적인 농업용수 관리가 필요하다. 본 연구에서는 새만금호내에 관측되는 염분 시계열 자료를 모의하기 위해서 자기회귀모형을 기반으로 한 Two-Stage ARX 모형을 개발하였다. 층별로 나눠진 염분자료를 계층적 Bayesian기법을 활용하여 매개변수를 확률분포형으로 추정하였으며 염분모의의 불확실성을 제시하였다. 최적 모형을 선정하기 위해서 통계적 지표인 BIC값을 이용하였으며, 최종적으로 선정된 모형을 통해 양수장 인근 수역의 염분 모의 결과를 제시하였다.

• 한국항공우주학회지
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• 제40권10호
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• pp.840-845
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• 2012

본 논문에서는 후향계단(Backward Facing Step) 유동장의 유동운동에 대한 ARX(Auto Regressive eXogenous) 모델링 기법을 제시한다. BFS 유동장 모델링을 위해 밀도를 모드분석을 통해 고유 공간모드와 시간계수를 추출한다. 입력 차수와 상태변수 차수는 각각 유동장 스팩트럼 분석과 시간계수 분석을 통해 결정한다. 또한, 유동장의 속도 분석을 통해 ARX의 입력 지연 차수를 결정한다. 한편, ARX 모델의 계수는 신경망을 이용하여 설계한다.