A Model-Driven Scheme to Compensate the Strain-Based Non-Intrusive Dynamic Pressure Measurement for Hydraulic Pipe

补偿(心理学) 灵敏度(控制系统) 残余物 校准 压力测量 控制理论(社会学) 动压 机械 结构工程 工程类 计算机科学 机械工程 电子工程 数学 物理 算法 统计 精神分析 人工智能 心理学 控制(管理)
作者
Zechao Wang,Mingyao Liu,Wang‐Ji Yan,Han Song,Zude Zhou,Ka‐Veng Yuen,Qin Wei,Shing Shin Cheng
出处
期刊:IEEE Transactions on Instrumentation and Measurement [Institute of Electrical and Electronics Engineers]
卷期号:70: 1-12 被引量:424
标识
DOI:10.1109/tim.2021.3123218
摘要

Strain-based non-intrusive approaches for measuring the pressure of pipes have attracted widespread attention due to their great convenience and ability to avoid destroying the integrity of structures. However, the mentioned method usually measures the dynamic pressure based only on the static strain-pressure sensitivity coefficients (SSSCs) instead of the dynamic strain-pressure sensitivity coefficients (DSSCs) due to its complicated calibration, which will inevitably affect the accuracy significantly. To address this issue, a model-driven scheme with dual stages is proposed in the present study to compensate the dynamic pressure measurement. The DSSCs are analytically derived for the first time from the axial governing equations of the pipe, considering the general boundary conditions for the thin-wall pipe and thick-wall pipe simultaneously. In the first stage, the physical parameters involved in the DSSCs are calibrated by minimizing the residual of the experimental results and the theoretical counterparts. In the second stage, the DSSCs calculated from the calibrated analytical model are utilized to compensate the dynamic pressure based on the relationship between the DSSCs and the SSSCs. The proposed method is applied to an industrial hydraulic pipe system, and the experimental results show that the relative error is reduced greatly after the compensation is implemented, demonstrating the validity of the proposed compensation method.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
安诺完成签到,获得积分10
刚刚
达鸟啊发布了新的文献求助10
1秒前
huyang发布了新的文献求助10
1秒前
1秒前
小二郎应助面向阳光采纳,获得10
1秒前
11发布了新的文献求助10
2秒前
woaikeyan发布了新的文献求助10
3秒前
ACMI发布了新的文献求助10
3秒前
4秒前
derherzog发布了新的文献求助10
4秒前
zyw发布了新的文献求助20
4秒前
5秒前
加浓咖啡豆完成签到,获得积分10
5秒前
慕青应助ln1111采纳,获得10
5秒前
haha发布了新的文献求助10
5秒前
panyd发布了新的文献求助10
5秒前
华仔应助wei采纳,获得10
5秒前
6秒前
7秒前
7秒前
充电宝应助xiaozhou采纳,获得10
7秒前
7秒前
科研通AI2S应助幸福的向彤采纳,获得10
8秒前
VAE发布了新的文献求助30
9秒前
小马甲应助Danboard采纳,获得10
9秒前
坦率灵槐发布了新的文献求助10
9秒前
10秒前
10秒前
英俊的铭应助胖虎采纳,获得10
11秒前
dong发布了新的文献求助10
11秒前
超级的三问完成签到,获得积分10
11秒前
糖小白发布了新的文献求助30
12秒前
67发布了新的文献求助10
12秒前
lixuegang2023发布了新的文献求助10
12秒前
小鱼完成签到,获得积分10
12秒前
derherzog完成签到,获得积分10
12秒前
tang发布了新的文献求助10
12秒前
zhounan发布了新的文献求助10
13秒前
不安鱼发布了新的文献求助10
13秒前
大冰发布了新的文献求助50
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1001
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Haematolymphoid Tumours (Part A and Part B, WHO Classification of Tumours, 5th Edition, Volume 11) 400
Virus-like particles empower RNAi for effective control of a Coleopteran pest 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5468557
求助须知:如何正确求助?哪些是违规求助? 4571954
关于积分的说明 14332897
捐赠科研通 4498650
什么是DOI,文献DOI怎么找? 2464664
邀请新用户注册赠送积分活动 1453302
关于科研通互助平台的介绍 1427914