Evidence map›Paper›PMID 30754697›Full record

ArticleSensors (Basel, Switzerland)2019

High-Sensitivity Real-Time Tracking System for High-Speed Pipeline Inspection Gauge.

Guanyu Piao, Jingbo Guo, Tiehua Hu, Yiming Deng

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Guanyu PiaoDepartment of Electrical Engineering, Tsinghua University, Beijing, 100084, China. pgy14@mails.tsinghua.edu.cn.
Jingbo GuoDepartment of Electrical Engineering, Tsinghua University, Beijing, 100084, China. guojb@tsinghua.edu.cn.
Tiehua HuDepartment of Electrical Engineering, Tsinghua University, Beijing, 100084, China. huthjk@sina.com.
Yiming DengDepartment of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA. dengyimi@egr.msu.edu.

Funding

National Key Research and Development Program of China 2016YFE0202600U.S. Department of Transportation, Pipeline and Hazardous Materials Safety Administration 693JK31850007CAAP and 693JK31810001
6 · The paper itself

Abstract

Real-time tracking of pipeline inspection gauges (PIGs) is an important aspect of ensuring the safety of oil and gas pipeline inline inspections (ILIs). Transmitting and receiving extremely low frequency (ELF) magnetic signals is one of the preferred methods of tracking. Due to the increase in physical parameters of the pipeline including transportation speed, wall thickness and burial depth, the ELF magnetic signals received are short transient (1-second duration) and very weak (10 pT), making the existing above-ground-marker (AGM) systems difficult to operate correctly. Based on the short transient very weak characteristics of ELF signals studied with a 2-D finite-element method (FEM) simulation, a data fusion model was derived to fuse the envelope decay rates of ELF signals by a least square (LS) criterion. Then, a fast-decision-tree (FDT) method is proposed to estimate the fused envelope decay rate to output the maximized orthogonal signal power for the signal detection through a determined topology and a fast calculation process, which was demonstrated to have excellent real-time detection performance. We show that simulation and experimental results validated the effectiveness of the proposed FDT method, and describe the high-sensitivity detection and real-time implementation of a high-speed PIG tracking system, including a transmitter, a receiver, and a pair of orthogonal search coil sensors.

Indexed as

high-sensitivity detection, above ground marker, pipeline inspection gauge, data fusion model, search coil sensor, ELF tracking

Identifiers

PMID30754697
PMCPMC6387012

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.