Establishment of an antifouling performance index derived from the assessment of biofouling on typical marine sensor materials

生物污染 背景(考古学) 环境科学 海洋工程 计算机科学 工艺工程 工程类 遗传学 生物 古生物学
作者
Adrián Delgado,Séan Power,Chloe Richards,P. Daly,Ciprian Briciu-Burghina,Yan Delauré,Fiona Regan
出处
期刊:Science of The Total Environment [Elsevier]
卷期号:887: 164059-164059 被引量:16
标识
DOI:10.1016/j.scitotenv.2023.164059
摘要

Marine biofouling, known as the unwanted accumulation of living organisms on submerged surfaces, is one of the main factors affecting the operation, maintenance and data quality of water quality monitoring sensors. This can be a significant challenge for marine deployed infrastructure and sensors in water. When organisms attach to the mooring lines or other submerged surfaces of the sensor, they can interfere with the sensor's operation and accuracy. They can also add weight and drag to the mooring system, making it more difficult to maintain the desired position of the sensor. This increases the cost of ownership to the point where it becomes prohibitively expensive to maintain operational sensor networks and infrastructures. Furthermore, the analysis and quantification of biofouling is extremely complex as it is based on biochemical methods such as the analysis of pigments such as chlorophyll-a as a direct indicator of the biomass of photosynthetic organisms, dry weight, carbohydrate analysis and protein analysis among others. In this context, this study has developed a method to estimate biofouling quickly and accurately on different submerged materials used in the marine industry and specifically in sensor manufacturing like copper, titanium, fiberglass composite, different types of polyoxymethylene (POMC, POMH), polyethylene terephthalate glycol (PETG) and 316L-stainless steel. To do this, in situ images of fouling organisms were collected with a conventional camera and image processing algorithms and machine learning models trained were used to construct a biofouling growth model. The algorithms and models were implemented with Fiji-based Weka Segmentation software. A supervised clustering model was used to identify three types of fouling to quantify fouling on panels of different materials submerged in seawater over time. This method is easy, fast and cost-effective to classify biofouling in a more accessible and holistic way that could be useful for engineering applications.

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
1秒前
1秒前
1秒前
1816013153发布了新的文献求助30
2秒前
量子星尘发布了新的文献求助10
2秒前
jianglidong完成签到,获得积分10
3秒前
3秒前
小青椒应助小李采纳,获得60
3秒前
huntme发布了新的文献求助30
4秒前
interesmazing发布了新的文献求助10
5秒前
风清扬发布了新的文献求助10
5秒前
6秒前
haojiewu发布了新的文献求助10
6秒前
研友_VZG7GZ应助无理采纳,获得10
6秒前
沈蓉完成签到,获得积分10
6秒前
Dreamable发布了新的文献求助10
6秒前
8秒前
9秒前
仇从安完成签到,获得积分10
9秒前
10秒前
忧伤的慕梅完成签到 ,获得积分10
10秒前
斯人完成签到 ,获得积分10
10秒前
JESI完成签到,获得积分10
10秒前
10秒前
昏睡的乌冬面完成签到 ,获得积分10
11秒前
情怀应助jianglidong采纳,获得10
12秒前
稳重的无色完成签到,获得积分10
14秒前
光脚丫给光脚丫的求助进行了留言
14秒前
仇从安发布了新的文献求助10
15秒前
15秒前
JIA发布了新的文献求助10
15秒前
17秒前
17秒前
小秦完成签到 ,获得积分10
17秒前
17秒前
风清扬发布了新的文献求助10
17秒前
小蘑菇应助嘟嘟图图采纳,获得10
18秒前
Ted完成签到,获得积分10
19秒前
19秒前
20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 1581
以液相層析串聯質譜法分析糖漿產品中活性雙羰基化合物 / 吳瑋元[撰] = Analysis of reactive dicarbonyl species in syrup products by LC-MS/MS / Wei-Yuan Wu 1000
Lloyd's Register of Shipping's Approach to the Control of Incidents of Brittle Fracture in Ship Structures 800
Biology of the Reptilia. Volume 21. Morphology I. The Skull and Appendicular Locomotor Apparatus of Lepidosauria 600
The Scope of Slavic Aspect 600
Foregrounding Marking Shift in Sundanese Written Narrative Segments 600
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 5541745
求助须知:如何正确求助?哪些是违规求助? 4628089
关于积分的说明 14606733
捐赠科研通 4569152
什么是DOI,文献DOI怎么找? 2505007
邀请新用户注册赠送积分活动 1482490
关于科研通互助平台的介绍 1454013