A novel remote pipeline inspection gauge positioning scheme using dynamic iterative time warping

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement Pub Date : 2025-04-03 DOI:10.1016/j.measurement.2025.117488

Yan Chen , Weiwei Zhang , Zeyu Wang , Jinglin Zhou

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引用次数: 0

Abstract

Cleaning long-distance pipelines is crucial to ensuring smooth operation. Since the position of the pipeline inspection gauge (PIG) has critical importance for the operational safety of the pipeline, real-time online tracking is essential. This study introduces a two-stage real-time remote tracking framework of PIG specifically constructed for liquid pipelines. A fast expectation difference (FED) algorithm is first proposed to dynamically normalize the pressure signals, while further improvements in the signal-to-noise ratio (SNR) are achieved by coefficient adjustment. A dynamic iterative time series warping (DITW) algorithm is subsequently introduced to adapt to the real-time positioning calculation. By integrating historical data with the algorithm’s boundary conditions, a new class of real-time remote position-tracking algorithms is developed. Tests using actual pigging data tests confirm that the proposed remote positioning scheme accurately represents the PIG’s real-time position during the cleaning operation, with the maximum tracking error remaining within the actual demand.

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一种新的基于动态迭代时间翘曲的远程管道检测仪表定位方案

长输管道的清洁是保证管道顺利运行的关键。由于管道检测仪表（PIG）的位置对管道的运行安全至关重要，因此对其进行实时在线跟踪至关重要。本文介绍了一种专门针对液体管道构建的两阶段实时远程跟踪PIG框架。首先提出了一种快速期望差（FED）算法对压力信号进行动态归一化，并通过系数调整进一步提高了信噪比。为了适应实时定位计算，引入了动态迭代时间序列翘曲（DITW）算法。将历史数据与算法边界条件相结合，提出了一种新的实时远程位置跟踪算法。使用实际清管数据测试的测试证实，所提出的远程定位方案准确地代表了清管器在清洗作业中的实时位置，最大跟踪误差保持在实际需求范围内。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Measurement 工程技术-工程：综合

CiteScore

10.20

自引率

12.50%

发文量

1589

审稿时长

12.1 months

期刊介绍： Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.