Evidence map›Paper›PMID 40572322›Full record

ArticleMicromachines2025

Energy Harvesting Microelectromechanical System for Condition Monitoring Based on Piezoelectric Transducer Ring.

Kaixuan Wang, Hao Long, Di Song, Hasan Shariar

Abstract read
In one paragraph

Article in Micromachines, 2025. 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. Article
  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.

Kaixuan WangSchool of Information Engineering, Xuzhou College of Industrial Technology, Xuzhou 221140, China.
Hao LongSchool of Information Engineering, Xuzhou College of Industrial Technology, Xuzhou 221140, China.
Di SongSchool of Mechatronic Engineering, Jiangsu Normal University, Xuzhou 221116, China.
Hasan ShariarDepartment of Mechanical Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.

Funding

Key Project of Xuzhou College of Industrial Technology XGY2024ZXZD02National Natural Science Foundation of China 52305589
6 · The paper itself

Abstract

For complex mechanical transmission equipment, shaft bearings are usually enclosed together with the shaft in the internal space of the housing to maintain good sealing and reliability. However, it is difficult to monitor the status of the shaft bearing through external sensors on the housing, while internal sensors face challenges in energy supply and data transmission. Therefore, a piezoelectric transducer ring-based energy harvesting microelectromechanical system (PTR-EH-MEMS) is proposed for the condition monitoring of shaft bearings. Specifically, the piezoelectric transducer ring is designed to convert mechanical vibrations into electrical energy, which simultaneously acts as a self-powered monitoring sensor through energy harvesting. In addition, the MEMS is embedded for piezoelectric data processing and condition monitoring of the shaft bearings. To verify the proposed PTR-EH-MEMS, an experimental investigation is implemented under different conditions. The experimental results demonstrate that the system can achieve the maximum DC output of 0.8 V and the root mean square power of 43.979 μW within 128 s, which can effectively identify early-stage bearing faults frequency through a self-powered mode. By combining energy harvesting with condition monitoring capability, the PTR-EH-MEMS offers a compact and sustainable approach for predictive maintenance in rotating machinery, reducing the reliance on external power sources and enhancing the reliability of industrial systems.

Indexed as

condition monitoringenergy harvestingMEMSpiezoelectric transducershaft bearing

Identifiers

PMID40572322
PMCPMC12194851

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.