In Situ Monitoring of Dynamic Loads on Shafting via Nanogenerators

Abstract Dynamic loads are inevitably generated during the operation of rotating machinery. In situ monitoring the dynamic loads is of great significance for assessing shafting health. Triboelectric nanogenerator (TENG) is sensitive to motion but not suitable for load monitoring, while piezoelectric nanogenerator (PENG) is just the opposite. Therefore, the combination of the two can complement each other. From this, a dynamic load monitoring smart bearing (DLMSB) integrated with TENG and PENG is proposed. The specially designed TENG can produce an “M‐waveform”, which can be used to extract rotation frequency and distinguish the quadrant of the rotor. Meanwhile, applying PENG to capture the load condition of the bearing, and referring to the main frequency of M‐waveform, it is convenient to obtain the dynamic loads of shafting. Furthermore, a real‐time monitoring system is developed, which can realize not only real‐time monitoring of the rotation speed and dynamic loads magnitude but also the quadrant discriminating of dynamic loads. The results have shown that the monitoring error for dynamic loads is 3 N or 5.5%, and the accuracy rate for determining the quadrant of the dynamic loads can reach 93%. This study provides a novel approach for the in situ monitoring of mechanical operating status via nanogenerators.

Authors

Institutions

Publication Details

Journal
Advanced Functional Materials
Published
2024-09-13
DOI
https://doi.org/10.1002/adfm.202411635
Citations
14
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
2.58
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In Situ Monitoring of Dynamic Loads on Shafting via Nanogenerators

Xiaojun Cheng, Ruoshui Liu, Zheng Yang, Zhaobing Cai et al.
14 citations
Advanced Functional Materials
Advanced Sensor and Energy Harvesting Materials
2.58
article

In Situ Monitoring of Dynamic Loads on Shafting via Nanogenerators

Xiaojun Cheng, Ruoshui Liu, Zheng Yang, Zhaobing Cai, Le Gu, Hengyu Li, Xiaosong Zhang, Jianyang Zhu, Tinghai Cheng, Pengfei Wang
article en
14 citations

Abstract

Abstract Dynamic loads are inevitably generated during the operation of rotating machinery. In situ monitoring the dynamic loads is of great significance for assessing shafting health. Triboelectric nanogenerator (TENG) is sensitive to motion but not suitable for load monitoring, while piezoelectric nanogenerator (PENG) is just the opposite. Therefore, the combination of the two can complement each other. From this, a dynamic load monitoring smart bearing (DLMSB) integrated with TENG and PENG is proposed. The specially designed TENG can produce an “M‐waveform”, which can be used to extract rotation frequency and distinguish the quadrant of the rotor. Meanwhile, applying PENG to capture the load condition of the bearing, and referring to the main frequency of M‐waveform, it is convenient to obtain the dynamic loads of shafting. Furthermore, a real‐time monitoring system is developed, which can realize not only real‐time monitoring of the rotation speed and dynamic loads magnitude but also the quadrant discriminating of dynamic loads. The results have shown that the monitoring error for dynamic loads is 3 N or 5.5%, and the accuracy rate for determining the quadrant of the dynamic loads can reach 93%. This study provides a novel approach for the in situ monitoring of mechanical operating status via nanogenerators.

Advanced Functional MaterialsVol. 34(51)
Chinese Academy of Sciences (CN), Beijing Zhongke Science and Technology (China) (CN), Beijing Institute of Nanoenergy and Nanosystems (CN), Wuhan University of Science and Technology (CN)
Openalex Percentile: Top 10%
Advanced Sensor and Energy Harvesting Materials
2.58
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.