An Input Estimation Approach to on-Line Two-Dimensional Inverse Heat Conduction Problems

Tuan, Pan-Chio; Ji, Ching-China; Fong, Li-Wei; Huang, Wen-Tang

doi:10.1080/10407799608914986

Cited by 106 publications

(63 citation statements)

References 15 publications

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“…The estimator then computes the histories of the excitation blast loads by applying the residual innovation sequence to the adaptive weighted recursive least square algorithm. The detailed derivation of this technique can be found in the work by Tuan 14 , et al The equations of the Kalman filter are as follows:…”

Section: Adaptive Weighted Recursive Input Estimation Methodsmentioning

confidence: 99%

Blast Load Input Estimation of the Medium Girder Bridge using Inverse Method

Lee

Chen

2008

DSJ

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Innovative adaptive weighted input estimation inverse methodology for estimating the unknown time-varying blast loads on the truss structure system is presented. This method is based on the Kalman filter and the recursive least square estimator (RLSE). The filter models the system dynamics in a linear set of state equations. The state equations of the truss structure are constructed using the finite element method. The input blast loads of the truss structure system are inverse estimated from the system responses measured at two distinct nodes. This work presents an efficient weighting factor γ applied in the RLSE, which is capable of providing a reasonable estimation results. The results obtained from the simulations show that the method is effective in estimating input blast loads, so has great stability and precision.

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Section: Adaptive Weighted Recursive Input Estimation Methodsmentioning

confidence: 99%

Blast Load Input Estimation of the Medium Girder Bridge using Inverse Method

Lee

Chen

2008

DSJ

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“…The extended Kalman filter will typically converge with long time propagation if un is omitted in Eqn (11). However, a long convergence time is unacceptable for online requirement.…”

Section: Recursive Input Estimationmentioning

confidence: 99%

“…The predicted and updated state vectors of the extended Kalman filter (EKF) with input vector u,, from t = nAt to t = (n+l)At, n = 0,1,2 ,..., are givenI by k+,,n = o"in/n + <pun (11) %+lh+, =R+lln +Kn+l(Zn+l -HR+*,n) (12) where…”

Section: Figure 1 Reentry Vehicle Flight Geometrymentioning

confidence: 99%

Input Estimation Algorithms for Reentry Vehicle Trajectory Estimation

Liu¹,

Wang²,

Tuan³

2005

DSJ

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Fast and accurate estimation of trajectory is important in tracking and intercepting reentry vehicles. Validating model is a real challenge associated with the qverall trajectory estimation problem. Input estimation technique provides a'solution to this challenge. Two input estimation algorithms were introduced based on different assumptions about the input applied to the model. This investigation presents approaches consisting of an extended Kahnan filter and two input estimation algorithms to identify the reentry vehicle trajectory in its terminal phase using data from a single radar source. Numerical simulations with data generated from two models demonstrate superior capabilities as measured by accuracy compared to the extended Kalman filter. Evaluation using real flight data provides the consistent results. The comparison between two input estimation algorithms is also presented. The trajectory estimation approaches based on two algorithms are effective in solving the reentry vehicle tracking problem.

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“…To understand the actual values, one can get 15 : (20) where ( ) to converge to the true constant value. In the time-varying case, however, one likes to prevent K b (k) from reducing to zero.…”

Section: Input-estimation Algorithmmentioning

confidence: 99%

“…The input-estimation method uses the Kalman filter to generate the residual innovation sequence. A recursive least-squares algorithm is derived that uses this residual sequence to compute the value of the heat flux 15 . The proposed method for solving a 2-D gun barrel IHCP is also used for studying the modelling error effect and the temperature containing measurement errors.…”

Section: Introductionmentioning

confidence: 99%

Inverse Estimation of Time-varied Heat Flux and Temperature on 2-D Gun Barrel using Input Estimation Method with Finite-element Scheme

Chen

Liu

2008

DSJ

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When a gun fires, a large amount of heat flux is triggered by the propellant gas acting on the gun barrel inner wall, leading to the rise of temperature, which will cause serious destruction. In this paper, an inverse method based on the input-estimation method including the finite inverse heat conduction problem (IHCP) element scheme to inverse estimate the unknown heat flux on the 2-D gun barrel has been presented. The use of the online accuracy to inversely estimate the unknown heat flux on the chamber has been made using 7.62 mm gun barrel outer wall temperature measurement data. Using simulation uniform and non-uniform heat flux q(z,t) cases involves a gun barrel inner wall that varies with time t and the axial z-location with convection situation in the outer surface. Computational results show that the proposed method exhibits a good estimation performance and highly facilitates practical implementation.

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An Input Estimation Approach to on-Line Two-Dimensional Inverse Heat Conduction Problems

Cited by 106 publications

References 15 publications

Blast Load Input Estimation of the Medium Girder Bridge using Inverse Method

Blast Load Input Estimation of the Medium Girder Bridge using Inverse Method

Input Estimation Algorithms for Reentry Vehicle Trajectory Estimation

Inverse Estimation of Time-varied Heat Flux and Temperature on 2-D Gun Barrel using Input Estimation Method with Finite-element Scheme

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