Parameter identification of nonlinear rotor-bearing system based on improved kriging surrogate model

2016 ◽  
Vol 23 (5) ◽  
pp. 794-807 ◽  
Author(s):  
Fang Han ◽  
Xinglin Guo ◽  
Changki Mo ◽  
Haiyang Gao ◽  
Peijun Hou
Keyword(s):  
Evolutionary Algorithm ◽  
Surrogate Model ◽  
Computation Time ◽  
Previous Method ◽  
New Method ◽  
Structure Parameters ◽  
Kriging Surrogate Model ◽  
Rotor Bearing ◽  
Robustness To Noise ◽  
Bearing System

This paper presents a new method which can identify the structure parameters (such as the bearing parameters, the nonlinear rub-impact parameters, and so on) of a nonlinear rotor-bearing system. Based on an improved kriging surrogate model and evolutionary algorithm (IKSMEA), the new method can provide more accurate results with less computation time. The initial kriging surrogate model (KSM) is constructed by the samples of varying structure parameters and their response values. According to the identified process, a multi-point addition criterion is proposed and more appropriate predicted points are added to update the KSM. Numerical studies and experimental validation of a nonlinear rotor-bearing system are performed. Comparing to the previous method (KSM and evolutionary algorithm), the new method satisfies the condition of convergence with less updating steps and increased robustness to noise. The identified results indicate that the IKSMEA can identify the nonlinear rotor system more effectively and accurately.

scholarly journals Crack Parameters Identification Based on a Kriging Surrogate Model for Operating Rotors

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Danyang Wang ◽  
Chunrong Hua ◽  
Dawei Dong ◽  
Biao He ◽  
Zhiwen Lu
Keyword(s):  
Surrogate Model ◽  
Parameters Identification ◽  
The Finite Element Method ◽  
Breathing Crack ◽  
Kriging Surrogate Model ◽  
Crack Location ◽  
Rotor Bearing ◽  
Location Depth ◽  
Nondominated Sorting ◽  
Bearing System

Parameters identification of cracked rotors has been gaining importance in recent years, but it is still a great challenge to determine the crack parameters including crack location, depth, and angle for operating rotors. This work proposes a new method to identify crack parameters in a rotor-bearing system based on a Kriging surrogate model and an improved nondominated sorting genetic algorithm-III (NSGA-III). A rotor-bearing system with a breathing crack is established by the finite element method and the superharmonic components are used as index to detect the cracks, the Kriging surrogate model between crack parameters and the superharmonic component amplitudes of the vibration response for rotors are constructed, and an improved NSGA-III is proposed to obtain the optimal crack parameters. Numerical experiments show that the proposed method can identify the crack location, depth, and angle accurately and efficiently for operating rotors.

Evaluation of Q-Values of a Rotor-Bearing System Using a Modal Open Loop Transfer Function

2008 ◽  
Author(s):  
Hiroyuki Fujiwara ◽  
Hirot Oyama ◽  
Norihisa Anegawa ◽  
Osami Matsushita
Keyword(s):  
Transfer Function ◽  
Model Simulation ◽  
Damping Ratio ◽  
Open Loop ◽  
New Method ◽  
Q Value ◽  
Response Measurement ◽  
Loop Transfer Function ◽  
Rotor Bearing ◽  
Bearing System

One of the key features of vibration characteristics (e.g., critical speed, damping ratio, Q-value, instability margin, etc.) of a rotor-bearing system can be described by their eigenvalues. The eigenvalues are conventionally evaluated by feed forward excitations, e.g., hammering test, harmonic sweep excitation, and unbalance response measurement. However it has been difficult to identify their damping ratios under various conditions. In this paper, we introduce a new method using a modal open loop transfer function. This method provides a more accurate Q-value and can help to identify the damping ratio by considering only the mode which we want to measure. We applied this method to a few models and some test rigs: 1) 3DOF model (simulation), 2) A flexible rotor equipped with active magnetic bearings (experiment). As a result, we concluded: 1) As the number of sensors is increased, the accuracy of the measurement also increases. 2) Our new method is more effective in terms of the accuracy of modal damping ratio than the conventional method is.

A new practical modal method for rotor balancing

2001 ◽  
Vol 215 (2) ◽  
pp. 179-189 ◽  
Author(s):  
Xu Bingang ◽  
Qu Liangsheng
Keyword(s):  
Rotational Speed ◽  
New Method ◽  
New Technique ◽  
Critical Speeds ◽  
Rotor Bearing ◽  
First Time ◽  
Rotor Balancing ◽  
Bearing System ◽  
Modal Method

A new practical modal balancing technique, which uses the modal ratio among measurement points (MRMP coefficient), has been developed. This new method is an improvement upon traditional modal balancing when the rotor to be balanced operates at the speed between the first and second critical speeds. The concept of the MRMP coefficient is introduced for the first time in this paper, on the basis of which the rotor-bearing system can be balanced at any one rotational speed between the first and second critical speeds by decomposing the modal components of unbalance and response simultaneously. Moreover, only one test run is required in three of the four balancing schemes provided in this paper to balance the rotor. In the new method, the test weights need not be orthogonal, so prior modal function knowledge is not necessary for calculation of the test weights, as required in the traditional modal balancing method. To verify the validity of the new technique, a balancing experiment using a rotating cantilever rotor is carried out. The results show that the new method can be applied effectively in field balancing.

scholarly journals Updated Kriging-Assisted Shape Optimization of a Gravity Dam

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 87
Author(s):  
Yongqiang Wang ◽  
Ye Liu ◽  
Xiaoyi Ma
Keyword(s):  
Surrogate Model ◽  
Computational Cost ◽  
Region Of Interest ◽  
Optimization Procedure ◽  
Optimal Shape ◽  
Small Sample ◽  
Gravity Dam ◽  
Kriging Surrogate Model ◽  
Gravity Dams ◽  
Sample Set

The numerical simulation of the optimal design of gravity dams is computationally expensive. Therefore, a new optimization procedure is presented in this study to reduce the computational cost for determining the optimal shape of a gravity dam. Optimization was performed using a combination of the genetic algorithm (GA) and an updated Kriging surrogate model (UKSM). First, a Kriging surrogate model (KSM) was constructed with a small sample set. Second, the minimizing the predictor strategy was used to add samples in the region of interest to update the KSM in each updating cycle until the optimization process converged. Third, an existing gravity dam was used to demonstrate the effectiveness of the GA–UKSM. The solution obtained with the GA–UKSM was compared with that obtained using the GA–KSM. The results revealed that the GA–UKSM required only 7.53% of the total number of numerical simulations required by the GA–KSM to achieve similar optimization results. Thus, the GA–UKSM can significantly improve the computational efficiency. The method adopted in this study can be used as a reference for the optimization of the design of gravity dams.

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