Research on an Online Intelligent Monitoring System for Resistance Spot Welding Based on Wireless Communication.

Shuwan Cui, Xuan Zhou, Baoyan Zhang, Leigang Han, Bin Xue, Feiyang Liu

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2025. 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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Shuwan CuiSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China.

Xuan ZhouSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China.

Baoyan ZhangSchool of Mechanical Engineering, Jiamusi University, Jiamusi 154007, China.

Leigang HanSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China.

Bin XueSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China.

Feiyang LiuSchool of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China.

Funding

Special Project for Central Government Guiding Local Science and Technology Development 2022JRJ0102

6 · The paper itself

Abstract

Resistance spot welding (RSW) faces critical monitoring challenges in industrial applications due to nonlinear coupling characteristics and production line disturbances. This study developed a Zigbee-enabled real-time monitoring system to address the precision limitations of conventional methods in tracking RSW parameters. Using DP780/DP590 dual-phase steel specimens with thickness variations, we implemented a dedicated data acquisition system capturing welding current, voltage, and barometric pressure dynamics. The experimental results demonstrated measurement accuracies within ±0.49% for current, ±0.25% for voltage, and 3.72% average relative error for barometric pressure with stable operational deviations (0.017-0.024 MPa).

Indexed as

intelligent monitoringresistance spot weldingwelding parameterswireless communicationZigbee wireless communication

Identifiers

PMID40363097

DOI10.3390/s25092658

PMCPMC12073806

What OpenQuestion holds

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LicenceCC BY

Read underepoch 390

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.