Simulation evaluation of dynamic characteristic identification accuracy of sliding bearing considering test error

被引：2

作者：

Chen, Runlin ^{[1
]}

Du, Chen ^{[1
]}

Wang, Xiaotuan ^{[1
]}

Zhang, Yanchao ^{[1
]}

Liu, Kai ^{[1
]}

机构：

[1] Xian Univ Technol, Sch Mech & Precis Instrument Engn, 5 South Jinhua Rd, Xian 710048, Peoples R China

来源：

ADVANCES IN MECHANICAL ENGINEERING | 2021年 / 13卷 / 12期

基金：

国家重点研发计划; 中国国家自然科学基金; 中国博士后科学基金;

关键词：

Sliding bearing; test bench; dynamic characteristic identification; test error; excitation frequency; TILTING-PAD; JOURNAL BEARING; COEFFICIENTS; SYSTEM; MODEL;

D O I：

10.1177/16878140211066846

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

Aiming at the dynamic characteristics test bench of sliding bearings, the dynamic model is established. Based on the forward and inverse dynamic problems of the bearing, a simulation evaluation method for the identification accuracy of the sliding bearing dynamic characteristics is proposed and the algorithm is verified. The identification errors of dynamic characteristic coefficients under different excitation frequencies are analyzed, the sensitivities of single frequency excitation method and dual-frequency excitation method to test error are contrastively analyzed, and the influence laws of dynamic characteristic identification accuracy of sliding bearing are evaluated. Based on which the traditional single frequency excitation method has been improved. The dynamic characteristic test should be carried out respectively in the low frequency range and the high frequency range. The main stiffness and cross damping are the average of two tests, the main damping is the identification value in the high frequency, and the cross stiffness is the identification value in the low frequency. That will effectively reduce the impact of test error. The obtained data and laws could support the improvement of the dynamic characteristics test method of sliding bearings and the confirmation of test parameters, thereby the accuracy of dynamic characteristics identification is improved.

引用

页数：13

共 27 条

[11] Guo W., 2014, SHIP ENG, V36, P62
[12] Jiang GD., 2000, MECH SCI TECHNOL, V19, P123
[13] Jiang GD., 1998, LUBR ENG, V01, P18
[14] Machine learning based anomaly detection and classification of acoustic emission events for wear monitoring in sliding bearing systems
Koenig, F.
Sous, C.
Chaib, A. Ouald
Jacobs, G.
[J]. TRIBOLOGY INTERNATIONAL, 2021, 155
[15] A high-speed rolling bearing test rig supported by sliding bearing
Li, Hui
Liu, Heng
Qi, Shemiao
Liu, Yi
[J]. INDUSTRIAL LUBRICATION AND TRIBOLOGY, 2020, 72 (07) : 955 - 959
[16] Bearing dynamic parameters identification for a sliding bearing-rotor system with uncertainty
Mao, Wengui
Li, Jianhua
Huang, Zhonghua
Liu, Jie
[J]. INVERSE PROBLEMS IN SCIENCE AND ENGINEERING, 2018, 26 (08) : 1094 - 1108
[17] Rotordynamic Force Prediction of Centrifugal Compressor Impellers Using Computational Fluid Dynamics
Moore, J. Jeffrey
Ransom, David L.
Viana, Flavia
[J]. JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME, 2011, 133 (04):
[18] Simulated identification on dynamic characteristics of large heavy-load bearing
Ouyang, Wu
Peng, Lin
Chen, Runlin
Yuan, Xiaoyang
[J]. JOURNAL OF VIBROENGINEERING, 2017, 19 (05) : 3230 - 3242
[19] TURBULENT-FLOW HYDROSTATIC BEARINGS - ANALYSIS AND EXPERIMENTAL RESULTS
SANANDRES, L
CHILDS, D
YANG, Z
[J]. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES, 1995, 37 (08) : 815 - 829
[20] Wang J., 2019, IND LUBR TRIBOL, V72, P93

← 1 2 3 →