scholarly journals A New Stochastic Model Updating Method Based on Improved Cross-Model Cross-Mode Technique

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3290
Author(s):  
Hui Chen ◽  
Bin Huang ◽  
Kong Fah Tee ◽  
Bo Lu
Keyword(s):  
Stochastic Model ◽  
Galerkin Method ◽  
Measurement Errors ◽  
Model Updating ◽  
Measurement Data ◽  
New Method ◽  
Statistical Characteristics ◽  
Practical Significance ◽  
Cross Model ◽  
Coefficient Vector

This paper proposes a new stochastic model updating method to update structural models based on the improved cross-model cross-mode (ICMCM) technique. This new method combines the stochastic hybrid perturbation-Galerkin method with the ICMCM method to solve the model updating problems with limited measurement data and uncertain measurement errors. First, using the ICMCM technique, a new stochastic model updating equation with an updated coefficient vector is established by considering the uncertain measured modal data. Then, the stochastic model updating equation is solved by the stochastic hybrid perturbation-Galerkin method so as to obtain the random updated coefficient vector. Following that, the statistical characteristics of the updated coefficients can be determined. Numerical results of a continuous beam show that the proposed method can effectively cope with relatively large uncertainty in measured data, and the computational efficiency of this new method is several orders of magnitude higher than that of the Monte Carlo simulation method. When considering the rank deficiency, the proposed stochastic ICMCM method can achieve more accurate updating results compared with the cross-model cross-mode (CMCM) method. An experimental example shows that the new method can effectively update the structural stiffness and mass, and the statistics of the frequencies of the updated model are consistent with the measured results, which ensures that the updated coefficients are of practical significance.

scholarly journals Stochastic Model Updating of Bolt-Jointed Structure for Structural Dynamics Applications

2021 ◽  
Vol 18 (2) ◽  
Author(s):  
M.A.S. Aziz Syah ◽  
M. A. Yunus ◽  
M.N. Abdul Rani ◽  
R. Omar ◽  
Akhil Mora
Keyword(s):  
Stochastic Model ◽  
Dynamic Behaviour ◽  
Model Updating ◽  
Stochastic Modelling ◽  
Latin Hypercube Sampling ◽  
Bolted Joints ◽  
Statistical Characteristics ◽  
Experimental Result ◽  
Predicted Model ◽  
Rigid Element

Structural stiffness exerts from joint connections and contact interfaces are significantly affect the dynamic behaviour of the bolt-jointed structure. Randomness in the joint connections due to the manufacturing variability in the identical bolted joints and uncertainty in contact interfaces due to the assambled and reassambled of the joint structure make sets of the dynamic behaviour of the bolt-jointed structure always inconsistent. On this account, a stochastic analytical model needs to be developed for the bolt-jointed structure to be used for uncertain parameters quantification. Hence, this paper is intended to propose an accurate and efficient stochastic analytical modelling of bolt-jointed structure in predicting the dynamic behaviour of the structure due to the randomness in the joint connections and uncertainty in contact interfaces. The aim of the study was accomplished by investigating four different finite element (FE) models of bolt-jointed structure with different element connectors to represent the bolted joints connections, namely rigid element (RBE), beam element (CBEAM), and 2 types of spring elements namely CELAS and CBUSH. Stochastic modelling was conducted by coupled the appropriate FE models with Latin Hypercube Sampling (LHS) algorithm to provide variability sampling due to the randomness in the bolted joints. The experimental modal analysis was performed by reassembled and disassembled the bolted joints to extract the variability in the dynamic behaviour, and the results were compared with LHS using statistical characteristics. Stochastic model updating then was used to minimise the discrepancies between experimental result and predicted model. The result has shown that the CBUSH is the most appropriate connector to accurately predict the dynamic behaviour of the bolt-jointed structure under variability conditions using the stochastic model updating method.

Incorporating concepts from physical theory into stochastic modelling of urban runoff pollution

1998 ◽  
Vol 37 (1) ◽  
pp. 179-185
Author(s):  
Morten Grum
Keyword(s):  
Stochastic Model ◽  
Continuous Time ◽  
Measurement Errors ◽  
Physical Theory ◽  
Oxygen Demand ◽  
Stochastic Modelling ◽  
Urban Runoff ◽  
Primary Input ◽  
Deterministic Modelling ◽  
Runoff Pollution

On evaluating the present or future state of integrated urban water systems, sewer drainage models, with rainfall as primary input, are often used to calculate the expected return periods of given detrimental acute pollution events and the uncertainty thereof. The model studied in the present paper incorporates notions of physical theory in a stochastic model of water level and particulate chemical oxygen demand (COD) at the overflow point of a Dutch combined sewer system. A stochastic model based on physical mechanisms has been formulated in continuous time. The extended Kalman filter has been used in conjunction with a maximum likelihood criteria and a non-linear state space formulation to decompose the error term into system noise terms and measurement errors. The bias generally obtained in deterministic modelling, by invariably and often inappropriately assuming all error to result from measurement inaccuracies, is thus avoided. Continuous time stochastic modelling incorporating physical, chemical and biological theory presents a possible modelling alternative. These preliminary results suggest that further work is needed in order to fully appreciate the method's potential and limitations in the field of urban runoff pollution modelling.

A new method for finite element model updating in structural dynamics

2010 ◽  
Vol 24 (7) ◽  
pp. 2137-2159 ◽  
Author(s):  
J.L. Zapico-Valle ◽  
R. Alonso-Camblor ◽  
M.P. González-Martínez ◽  
M. García-Diéguez
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Structural Dynamics ◽  
Model Updating ◽  
Element Model ◽  
New Method ◽  
Finite Element Model Updating

Dynamic Measurement of Spatial Attitude at Bottom Rotating Drillstring: Simulation, Experimental, and Field Test

2015 ◽  
Vol 138 (2) ◽  
Author(s):  
Qilong Xue ◽  
Ruihe Wang ◽  
Baolin Liu ◽  
Leilei Huang
Keyword(s):  
Real Time ◽  
Measurement Errors ◽  
Time Window ◽  
Measurement Data ◽  
Movement Patterns ◽  
Dynamic Measurement ◽  
Drilling Process ◽  
Stick Slip ◽  
Actual Measurement ◽  
Gas Drilling

In the oil and gas drilling engineering, measurement-while-drilling (MWD) system is usually used to provide real-time monitoring of the position and orientation of the bottom hole. Particularly in the rotary steerable drilling technology and application, it is a challenge to measure the spatial attitude of the bottom drillstring accurately in real time while the drillstring is rotating. A set of “strap-down” measurement system was developed in this paper. The triaxial accelerometer and triaxial fluxgate were installed near the bit, and real-time inclination and azimuth can be measured while the drillstring is rotating. Furthermore, the mathematical model of the continuous measurement was established during drilling. The real-time signals of the accelerometer and the fluxgate sensors are processed and analyzed in a time window, and the movement patterns of the drilling bit will be observed, such as stationary, uniform rotation, and stick–slip. Different signal processing methods will be used for different movement patterns. Additionally, a scientific approach was put forward to improve the solver accuracy benefit from the use of stick–slip vibration phenomenon. We also developed the Kalman filter (KF) to improve the solver accuracy. The actual measurement data through drilling process verify that the algorithm proposed in this paper is reliable and effective and the dynamic measurement errors of inclination and azimuth are effectively reduced.

scholarly journals Diagnostic Procedures for Jet Engines

1985 ◽  
Author(s):  
R. Lunderstädt ◽  
K. Fiedler
Keyword(s):  
Mathematical Model ◽  
Path Analysis ◽  
Working Conditions ◽  
Measurement Data ◽  
Diagnostic Procedures ◽  
Practical Significance ◽  
Jet Engines ◽  
Actual Measurement ◽  
Jet Engine ◽  
The Mathematical Model

In the paper to be presented diagnostic procedures on the basis of a gas path analysis are applied on a two-shaft jet engine. Starting from the mathematical model of the engine a filter-algorithm is used which delivers from actual measurement data the state of the engine for different working conditions. The procedure is proven for some examples and discussed in regard of its practical significance.

scholarly journals Effective plots to assess bias and precision in method comparison studies

2016 ◽  
Vol 27 (6) ◽  
pp. 1650-1660 ◽  
Author(s):  
Patrick Taffé
Keyword(s):  
Measurement Errors ◽  
Regression Line ◽  
Latent Trait ◽  
Method Comparison ◽  
Estimation Procedure ◽  
New Method ◽  
Reference Standard ◽  
Limits Of Agreement ◽  
Modeling Framework ◽  
Methods Of Measurement

Bland and Altman’s limits of agreement have traditionally been used in clinical research to assess the agreement between different methods of measurement for quantitative variables. However, when the variances of the measurement errors of the two methods are different, Bland and Altman’s plot may be misleading; there are settings where the regression line shows an upward or a downward trend but there is no bias or a zero slope and there is a bias. Therefore, the goal of this paper is to clearly illustrate why and when does a bias arise, particularly when heteroscedastic measurement errors are expected, and propose two new plots, the “bias plot” and the “precision plot,” to help the investigator visually and clinically appraise the performance of the new method. These plots do not have the above-mentioned defect and still are easy to interpret, in the spirit of Bland and Altman’s limits of agreement. To achieve this goal, we rely on the modeling framework recently developed by Nawarathna and Choudhary, which allows the measurement errors to be heteroscedastic and depend on the underlying latent trait. Their estimation procedure, however, is complex and rather daunting to implement. We have, therefore, developed a new estimation procedure, which is much simpler to implement and, yet, performs very well, as illustrated by our simulations. The methodology requires several measurements with the reference standard and possibly only one with the new method for each individual.

A Sensitivity-Enhancing Control Approach for Structural Model Updating

2007 ◽  
Author(s):  
L. J. Jiang ◽  
K. W. Wang ◽  
J. Tang
Keyword(s):  
Closed Loop ◽  
Structural Model ◽  
Natural Frequencies ◽  
Model Updating ◽  
Measurement Data ◽  
Frequency Measurement ◽  
Physical Parameters ◽  
Fe Model ◽  
Initial Model ◽  
Closed Loop Systems

Model updating plays an important role in structural design and dynamic analysis. The process of model updating aims to produce an improved mathematical model by correlating the initial model with the experimentally measured data. There are a variety of techniques available for model updating using dynamic and static measurements of the structure’s behavior. This paper focuses on the model updating methods using the measured natural frequencies of the structure. The practice of model updating using only the natural frequencies encounters two well-known limitations: deficiency of frequency measurement data, and low sensitivity of measured natural frequencies with respect to the physical parameters that need to be updated. To overcome these limitations, a novel model updating method is presented in this paper. First, closed-loop control is applied to the structure to enhance the sensitivity of natural frequencies to the updating parameters. Second, by including the natural frequencies based on a series of sensitivity-enhanced closed-loop systems, we can significantly enrich the frequency measurement data available for model updating. Using the natural frequencies of these sensitivity-enhanced closed-loop systems, an iterative process is utilized to update the physical parameters in the initial model. To demonstrate and verify the proposed method, case studies are carried out using a cantilevered beam structure. The natural frequencies of a series of sensitivity-enhanced closed-loop systems are utilized to update the mass and stiffness parameters in the initial FE model. Results show that the modeling errors in the mass and stiffness parameters can be accurately identified by using the proposed model updating method.

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