Evidence map›Paper›PMID 42076435›Full record

ArticleSensors (Basel, Switzerland)2026

Design of Unattended Rain and Snow Protection Device for Total Station Based on D-S Evidence Fusion.

Liangquan Jia, Yong Liu, Guangzeng Du, Xinxin Li, Zhikang Wang, Yujie Lu, Zhibin Zhang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. 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

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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

7 authors.

Liangquan JiaSchool of Information Engineering, Huzhou University, Huzhou 313000, China.ORCID 0000-0003-3890-8965
Yong LiuSchool of Information Engineering, Huzhou University, Huzhou 313000, China.
Guangzeng DuSchool of Information Engineering, Huzhou University, Huzhou 313000, China.
Xinxin LiSchool of Information Engineering, Huzhou University, Huzhou 313000, China.
Zhikang WangShanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China.
Yujie LuSchool of Information Engineering, Huzhou University, Huzhou 313000, China.ORCID 0009-0001-3350-9992
Zhibin ZhangShanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China.

Funding

the Key Project of Huzhou City under Grant 2021ZD2003the National College Students' Innovation and Entrepreneurship Training Program of 2025 under Grant 202510347048the National Key R&D Program of China under Grant 2022YFE0133700the Public Welfare Application Research Project under Grant 2024GZ14
6 · The paper itself

Abstract

Aiming at the rain protection problem of outdoor precision instruments such as total stations, this paper designs an environmentally adaptive intelligent protection system based on D-S evidence fusion and state machine control. In terms of mechanical structure, the protective cover is designed as a sinking type, which not only improves the safety of the equipment but also avoids the shielding problem of the working surface compared with the traditional upward-lifting structure. The system collects data from multi-source meteorological sensors and uses D-S evidence theory for fusion decision-making. To alleviate decision conflicts in high-conflict scenarios, a conflict-guided dynamic weight adjustment strategy is introduced. Combined with a dual-layer finite state machine, the system realizes coordinated control between environmental perception and protection actions and can activate protection within 30 s under severe weather. Simulation results show that the improved method increases the response speed by 41.9-62.5% compared with traditional D-S fusion in weather transition conditions. In a 28-day field test, the system achieves a daily protection success rate of 96.4% and 100% reliability in critical weather transitions. The proposed system can provide reliable support for the all-weather safe operation of field precision measurement equipment.

Indexed as

D-S evidence theorymulti-source information fusionprotection systemstate machineweight adjustment mechanism

Identifiers

PMID42076435
PMCPMC13119578

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