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储罐状况评估的当前方法与技术:全面综述

Current Methods and Technologies for Storage Tank Condition Assessment: A Comprehensive Review.

作者信息

Stoicescu Alexandru-Adrian, Ripeanu Razvan George, Tănase Maria, Toader Liviu

机构信息

Mechanical Engineering Department, Petroleum-Gas University of Ploiesti, 100680 Ploiesti, Romania.

Technical Lead & Development Srl, 107063 Corlatesti, Romania.

出版信息

Materials (Basel). 2025 Feb 27;18(5):1074. doi: 10.3390/ma18051074.

DOI:10.3390/ma18051074
PMID:40077299
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11901327/
Abstract

This study investigates the current industry practices for storage tank assessment and the possibilities for improving inspection methods using the latest technologies on the market. This article presents the main methods and technologies for non-destructive testing (NDT), along with new methods that make them more efficient and economical. To further analyze the state of a tank and determine its lifetime expectancy, analysis methods are presented based on NDT results. The key aspects that can be improved and made more efficient are NDT procedures using robots/drones and autonomous devices; automated inspection procedures, like remote video inspection combined with local thickness measurement or 3D scanning of the tank elements for deformations; advanced analysis methods using the input from the NDT and inspection data collected using analytical calculations according to applicable standards; Finite Element Analysis (FEA); and digitalized models of equipment (Digital Twin) accompanied by artificial intelligence for data processing. The best way to make the process more efficient is to develop and use dedicated standardized software for tank condition assessment.

摘要

本研究调查了储油罐评估的当前行业实践,以及使用市场上最新技术改进检测方法的可能性。本文介绍了无损检测(NDT)的主要方法和技术,以及使其更高效、更经济的新方法。为了进一步分析罐体状态并确定其预期寿命,基于无损检测结果提出了分析方法。可以改进并提高效率的关键方面包括使用机器人/无人机和自主设备的无损检测程序;自动化检测程序,如远程视频检测结合局部厚度测量或对罐体元件进行三维扫描以检测变形;利用无损检测输入和根据适用标准通过分析计算收集的检测数据的先进分析方法;有限元分析(FEA);以及配备人工智能进行数据处理的设备数字化模型(数字孪生)。使该过程更高效的最佳方法是开发和使用用于罐体状况评估的专用标准化软件。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/8dad4653928d/materials-18-01074-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/603f251adaac/materials-18-01074-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/d809dac74d88/materials-18-01074-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/5a2e2457d836/materials-18-01074-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/8dad4653928d/materials-18-01074-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/603f251adaac/materials-18-01074-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/cd40fcd5a96a/materials-18-01074-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/15fb14d7a73b/materials-18-01074-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/8a12bb0c0c24/materials-18-01074-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/3d8e932102e3/materials-18-01074-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/3d8b1dba1659/materials-18-01074-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/2fc58c0977c8/materials-18-01074-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/d809dac74d88/materials-18-01074-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/5a2e2457d836/materials-18-01074-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cca/11901327/8dad4653928d/materials-18-01074-g010.jpg

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