亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

CNN-LSTM network-based damage detection approach for copper pipeline using laser ultrasonic scanning

计算机科学 管道(软件) 人工智能 卷积神经网络 信号(编程语言) 超声波传感器 激光扫描 模式识别(心理学) 激光器 特征(语言学) 特征提取 计算机视觉 声学 光学 语言学 哲学 物理 程序设计语言
作者
Liuwei Huang,Xiaobin Hong,Zhijing Yang,Yuan Liu,Bin Zhang
出处
期刊:Ultrasonics [Elsevier BV]
卷期号:121: 106685-106685 被引量:62
标识
DOI:10.1016/j.ultras.2022.106685
摘要

Copper pipeline is a commonly used industrial transmission pipeline. Nondestructive testing of copper pipeline early damage is very important. Laser scanning has attracted extensive attention because it can realize the visualization of guided wave propagation and non-contact on-line detection. However, the damage points detection in laser scanning imaging method rely on the difference between the damage points signals and surrounding normal points signals. This limits the applicability of laser scanning and may lead to inaccurate in large-area detection. Facing with such challenges, a damage detection method based on CNN-LSTM network is proposed for laser ultrasonic guided wave scanning detection in this paper, which can detect each scanning point signal without relying on the surrounding detection points signals. Firstly, the proposed data conversion algorithm is used to preprocess the laser scanning signals. Next, CNN-LSTM network is used to train the damage detection model. Four 1D Conv channels with different convolution kernel sizes and depths are designed in Convolutional Neural Network (CNN) module. The module can extract the signal time domain features. Then the features are input into the Long Short-Term Memory Network (LSTM) for feature extraction and classification. Finally, the CNN-LSTM is trained using the laser scanning detection data collected on the copper pipeline with crack and corrosion damages, and applied to detect the copper pipeline damage signal. At the same time, the state-of-the-art methods is compared with proposed method. The experimental results show that the detection accuracy of the method is 99.9%, 99.9%, 99.8% and 99.8% for copper pipeline 0.5 mm deep crack damage, penetrating crack damage, corrosion damage and inside crack damage, respectively. The damage location and size can be accurately detected by the proposed 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
传奇3应助科研通管家采纳,获得10
6秒前
我是老大应助闫雪采纳,获得10
6秒前
17秒前
hongtao完成签到 ,获得积分10
22秒前
1分钟前
Jasper应助科研通管家采纳,获得10
2分钟前
2分钟前
2分钟前
璐璐侠完成签到,获得积分10
2分钟前
3分钟前
AJ完成签到 ,获得积分10
3分钟前
xiaozou55完成签到 ,获得积分10
3分钟前
binyao2024完成签到,获得积分10
4分钟前
光亮静槐完成签到 ,获得积分10
4分钟前
lrl350495627发布了新的文献求助10
5分钟前
lrl350495627完成签到,获得积分10
6分钟前
GingerF应助科研通管家采纳,获得50
6分钟前
FashionBoy应助andrele采纳,获得10
6分钟前
7分钟前
自然芷文发布了新的文献求助10
7分钟前
7分钟前
我是老大应助自然芷文采纳,获得10
7分钟前
iNk应助吗喽采纳,获得20
7分钟前
研友_VZG7GZ应助科研通管家采纳,获得10
8分钟前
打打应助科研通管家采纳,获得10
8分钟前
Charlie完成签到 ,获得积分10
8分钟前
CodeCraft应助Benhnhk21采纳,获得30
8分钟前
9分钟前
Benhnhk21发布了新的文献求助30
9分钟前
科研通AI2S应助科研通管家采纳,获得10
10分钟前
村口的帅老头完成签到 ,获得积分0
10分钟前
10分钟前
gincle完成签到 ,获得积分10
10分钟前
10分钟前
andrele发布了新的文献求助10
10分钟前
11分钟前
11分钟前
积极的台灯完成签到,获得积分10
11分钟前
紫荆完成签到,获得积分10
11分钟前
Johnson完成签到 ,获得积分10
11分钟前
高分求助中
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
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 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3990181
求助须知:如何正确求助?哪些是违规求助? 3532136
关于积分的说明 11256472
捐赠科研通 3271042
什么是DOI,文献DOI怎么找? 1805190
邀请新用户注册赠送积分活动 882302
科研通“疑难数据库(出版商)”最低求助积分说明 809234