Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

停工期 管道(软件) 计算机科学 管道运输 工程类 风险分析(工程) 系统工程 可靠性工程 医学 环境工程 程序设计语言
作者
Boon Wong,Julie A. McCann
出处
期刊:Sensors [Multidisciplinary Digital Publishing Institute]
卷期号:21 (15): 4959-4959 被引量:13
标识
DOI:10.3390/s21154959
摘要

Pipeline networks have been widely utilised in the transportation of water, natural gases, oil and waste materials efficiently and safely over varying distances with minimal human intervention. In order to optimise the spatial use of the pipeline infrastructure, pipelines are either buried underground, or located in submarine environments. Due to the continuous expansion of pipeline networks in locations that are inaccessible to maintenance personnel, research efforts have been ongoing to introduce and develop reliable detection methods for pipeline failures, such as blockages, leakages, cracks, corrosion and weld defects. In this paper, a taxonomy of existing pipeline failure detection techniques and technologies was created to comparatively analyse their respective advantages, drawbacks and limitations. This effort has effectively illuminated various unaddressed research challenges that are still present among a wide array of the state-of-the-art detection methods that have been employed in various pipeline domains. These challenges include the extension of the lifetime of a pipeline network for the reduction of maintenance costs, and the prevention of disruptive pipeline failures for the minimisation of downtime. Our taxonomy of various pipeline failure detection methods is also presented in the form of a look-up table to illustrate the suitability, key aspects and data or signal processing techniques of each individual method. We have also quantitatively evaluated the industrial relevance and practicality of each of the methods in the taxonomy in terms of their respective deployability, generality and computational cost. The outcome of the evaluation made in the taxonomy will contribute to our future works involving the utilisation of sensor fusion and data-centric frameworks to develop efficient, accurate and reliable failure detection solutions.
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
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
刚刚
不吃香菜完成签到 ,获得积分10
刚刚
黄瓜双耳拌腐竹完成签到,获得积分10
1秒前
研友_VZG7GZ应助年轻的听露采纳,获得10
1秒前
六点一横完成签到,获得积分10
1秒前
pizza发布了新的文献求助10
3秒前
zyz完成签到,获得积分10
3秒前
一顿吃不饱完成签到,获得积分0
3秒前
周周完成签到,获得积分10
3秒前
xin发布了新的文献求助10
4秒前
单薄树叶完成签到,获得积分10
4秒前
啊七飞完成签到,获得积分10
5秒前
mawenxing完成签到,获得积分10
5秒前
称心的问薇完成签到,获得积分10
5秒前
逗逗完成签到,获得积分10
5秒前
Dr_Stars完成签到,获得积分10
6秒前
6秒前
若雨凌风完成签到,获得积分10
7秒前
三千港完成签到,获得积分10
7秒前
坚强小蚂蚁完成签到,获得积分10
7秒前
小朱完成签到,获得积分10
7秒前
刘若鑫完成签到,获得积分10
7秒前
csu_zs完成签到,获得积分10
8秒前
Lak完成签到 ,获得积分10
8秒前
nz完成签到,获得积分10
9秒前
爆米花应助南风采纳,获得10
9秒前
酷酷伟宸完成签到,获得积分10
9秒前
moyacheung完成签到,获得积分10
10秒前
hyf完成签到 ,获得积分10
10秒前
Fe2O3完成签到,获得积分10
10秒前
啊哦完成签到 ,获得积分10
10秒前
xin完成签到,获得积分10
10秒前
中科院饲养员完成签到,获得积分10
10秒前
易方完成签到,获得积分10
11秒前
昏睡的蟠桃给求助的求助进行了留言
11秒前
Illich完成签到,获得积分10
11秒前
一剑温柔完成签到 ,获得积分10
12秒前
王Hope完成签到,获得积分10
12秒前
12秒前
13秒前
高分求助中
Les Mantodea de Guyane Insecta, Polyneoptera 2500
Technologies supporting mass customization of apparel: A pilot project 450
A Field Guide to the Amphibians and Reptiles of Madagascar - Frank Glaw and Miguel Vences - 3rd Edition 400
Brain and Heart The Triumphs and Struggles of a Pediatric Neurosurgeon 400
Cybersecurity Blueprint – Transitioning to Tech 400
Mixing the elements of mass customisation 400
Периодизация спортивной тренировки. Общая теория и её практическое применение 310
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 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3784938
求助须知:如何正确求助?哪些是违规求助? 3330274
关于积分的说明 10245276
捐赠科研通 3045590
什么是DOI,文献DOI怎么找? 1671719
邀请新用户注册赠送积分活动 800686
科研通“疑难数据库(出版商)”最低求助积分说明 759609