Wear Degree Quantification of Pin Connections Using Parameter-Based Analyses of Acoustic Emissions.

Jingkai Wang, Linsheng Huo, Chunguang Liu, Gangbing Song

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it

0cells of the map it votes in

3citing 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

3 citing papers in PubMed.

Piezoceramic-Based Damage Monitoring of Concrete Structure for Underwater Blasting.Sensors (Basel, Switzerland) · 2020
Article
Bond-Slip Monitoring of Concrete Structures Using Smart Sensors-A Review.Sensors (Basel, Switzerland) · 2019
Review
Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses.Sensors (Basel, Switzerland) · 2019
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.

Jingkai WangState Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China. wjk@mail.dlut.edu.cn.

Linsheng HuoState Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China. lshuo@dlut.edu.cn.ORCID 0000-0002-3044-2630

Chunguang LiuState Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China. liucg@dlut.edu.cn.

Gangbing SongSmart Materials and Structures Laboratory, Department of Mechanical Engineering, University of Houston, Houston, TX 77204, USA. gsong@uh.edu.ORCID 0000-0001-5135-5555

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pin connections are commonly used in many engineering fields, and continuous operation may cause severe wear on the pins and may lead to their eventual fracture, if undetected. However, a reliable nonintrusive real-time method to monitor the wear of pin connections is yet to be developed. In this paper, acoustic emission (AE)-based parametric analysis methods, including the logarithm of the cumulative energy (LAE), the logarithm of the slope of cumulative energy (LSCE), the

Indexed as

acoustic emission (AE)b-value methodquantification of wear degreewear frequency spectrumwear of pin connections

Identifiers

PMID30336608

DOI10.3390/s18103503

PMCPMC6210804

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

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.