首页|Parameter Estimation of a Valve-Controlled Cylinder System Model Based on Bench Test and Operating Data Fusion

Parameter Estimation of a Valve-Controlled Cylinder System Model Based on Bench Test and Operating Data Fusion

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system.Bench test data are easily obtained,but it is challenging to emulate actual loads in the research on parameter estimation of valve-controlled cylinder system.Despite the actual load information con-tained in the operating data of the control valve,its acquisition remains challenging.This paper proposes a method that fuses bench test and operating data for parameter estimation to address the aforementioned problems.The proposed method is based on Bayesian theory,and its core is a pool fusion of prior information from bench test and operating data.Firstly,a system model is established,and the parameters in the model are analysed.Secondly,the bench and operating data of the system are collected.Then,the model parameters and weight coefficients are estimated using the data fusion method.Finally,the estimated effects of the data fusion method,Bayesian method,and particle swarm optimisation(PSO)algorithm on system model parameters are compared.The research shows that the weight coefficient represents the contribution of different prior information to the parameter estimation result.The effect of parameter estimation based on the data fusion method is better than that of the Bayesian method and the PSO algorithm.Increasing load complexity leads to a decrease in model accuracy,highlighting the crucial role of the data fusion method in parameter estimation studies.

Valve-controlled cylinder systemParameter estimationThe Bayesian theoryData fusion methodWeight coefficients

Deying Su、Shaojie Wang、Haojing Lin、Xiaosong Xia、Yubing Xu、Liang Hou

展开 >

Pen-Tung Sah Institute of Micro-Nano Science and Technology,Xiamen University,Xiamen 361102,China

Xuzhou XCMG Excavation Machinery Co.,Ltd,Xuzhou 221000,China

国家重点研发计划国家重点研发计划国家自然科学基金国家自然科学基金Guangdong Provincial Basic and Applied Basic Research Foundation of ChinaScience and Technology Plan Project of Fuzhou City of China

2020YFB17099012020YFB170990451975495519054602021-A15150122862022-P-022

2024

10.1186/s10033-024-01022-8

中国机械工程学报
中国机械工程学会

中国机械工程学报

CSTPCD
影响因子：0.765
ISSN：1000-9345
年,卷(期)：2024.37(2)