Evidence map›Paper›PMID 37420856›Full record

ArticleSensors (Basel, Switzerland)2023

Research on the Health Assessment Method of the Safety Retaining Wall in a Dump Based on UAV Point-Cloud Data.

Yachun Mao, Xin Zhang, Wang Cao, Shuo Fan, Hui Wang, Zhexi Yang, Bo Ding, Yu Bai

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Yachun MaoSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China.
Xin ZhangSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China.
Wang CaoSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China.
Shuo FanSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China.
Hui WangSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China.
Zhexi YangSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China.
Bo DingSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China.
Yu BaiSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China.

Funding

National key research and development program 2016YFCO801602National Natural Science Foundation of China 41974028 (Yanhua Fu)
6 · The paper itself

Abstract

The safety retaining wall is a critical infrastructure in ensuring the safety of both rock removal vehicles and personnel. However, factors such as precipitation infiltration, tire impact from rock removal vehicles, and rolling rocks can cause local damage to the safety retaining wall of the dump, rendering it ineffective in preventing rock removal vehicles from rolling down and posing a huge safety hazard. To address these issues, this study proposed a safety retaining wall health assessment method based on modeling and analysis of UAV point-cloud data of the safety retaining wall of a dump, which enables hazard warning for the safety retaining wall. The point-cloud data used in this study were obtained from the Qidashan Iron Mine Dump in Anshan City, Liaoning Province, China. Firstly, the point-cloud data of the dump platform and slope were extracted separately using elevation gradient filtering. Then, the point-cloud data of the unloading rock boundary was obtained via the ordered crisscrossed scanning algorithm. Subsequently, the point-cloud data of the safety retaining wall were extracted using the range constraint algorithm, and surface reconstruction was conducted to construct the Mesh model. The safety retaining wall mesh model was isometrically profiled to extract cross-sectional feature information and to compare the standard parameters of the safety retaining wall. Finally, the health assessment of the safety retaining wall was carried out. This innovative method allows for unmanned and rapid inspection of all areas of the safety retaining wall, ensuring the safety of rock removal vehicles and personnel.

Indexed as

AlgorithmsIronChinaCross-Sectional StudiesIronelevation gradient filteringhealth assessmentordered criss-crossed scanning algorithmsafety retaining wallsurface reconstructionUAV point-cloud data

Identifiers

PMID37420856
PMCPMC10303201

What OpenQuestion holds

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LicenceCC BY
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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.