Self-powered fault diagnosis of rolling bearings based on triboelectric effect

2022 ◽  
Vol 166 ◽  
pp. 108382
Author(s):  
Qinkai Han ◽  
Ziyuan Jiang ◽  
Xueping Xu ◽  
Zhuang Ding ◽  
Fulei Chu
Keyword(s):  
Fault Diagnosis ◽  
Rolling Bearings ◽  
Self Powered ◽  
Triboelectric Effect

scholarly journals An Enhanced Intrinsic Time-Scale Decomposition Method Based on Adaptive Lévy Noise and Its Application in Bearing Fault Diagnosis

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 617
Author(s):  
Jianpeng Ma ◽  
Shi Zhuo ◽  
Chengwei Li ◽  
Liwei Zhan ◽  
Guangzhu Zhang
Keyword(s):  
Fault Diagnosis ◽  
Time Scale ◽  
Lévy Noise ◽  
Model Parameters ◽  
Rolling Bearings ◽  
Intrinsic Time ◽  
Time Scale Decomposition ◽  
Weak Fault ◽  
Levy Noise ◽  
The Impact

When early failures in rolling bearings occur, we need to be able to extract weak fault characteristic frequencies under the influence of strong noise and then perform fault diagnosis. Therefore, a new method is proposed: complete ensemble intrinsic time-scale decomposition with adaptive Lévy noise (CEITDALN). This method solves the problem of the traditional complete ensemble intrinsic time-scale decomposition with adaptive noise (CEITDAN) method not being able to filter nonwhite noise in measured vibration signal noise. Therefore, in the method proposed in this paper, a noise model in the form of parameter-adjusted noise is used to replace traditional white noise. We used an optimization algorithm to adaptively adjust the model parameters, reducing the impact of nonwhite noise on the feature frequency extraction. The experimental results for the simulation and vibration signals of rolling bearings showed that the CEITDALN method could extract weak fault features more effectively than traditional methods.

Fault diagnosis method of rolling bearings based on VMD and MDSVM

2021 ◽  
Author(s):  
MeiYing Qiao ◽  
XiaXia Tang ◽  
YuXiang Liu ◽  
ShuHao Yan
Keyword(s):  
Fault Diagnosis ◽  
Rolling Bearings ◽  
Diagnosis Method

scholarly journals Triboelectric Effect Enabled Self-Powered, Point-of-Care Diagnostics: Opportunities for Developing ASSURED and REASSURED Devices

Micromachines ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 337
Author(s):  
Navneet Soin ◽  
Sam J. Fishlock ◽  
Colin Kelsey ◽  
Suzanne Smith
Keyword(s):  
High Efficiency ◽  
Resource Constraints ◽  
Point Of Care ◽  
Wearable Sensors ◽  
Middle Income ◽  
Physiological Signal ◽  
Point Of Care Diagnostics ◽  
Self Powered ◽  
Triboelectric Nanogenerators ◽  
Triboelectric Effect

The use of rapid point-of-care (PoC) diagnostics in conjunction with physiological signal monitoring has seen tremendous progress in their availability and uptake, particularly in low- and middle-income countries (LMICs). However, to truly overcome infrastructural and resource constraints, there is an urgent need for self-powered devices which can enable on-demand and/or continuous monitoring of patients. The past decade has seen the rapid rise of triboelectric nanogenerators (TENGs) as the choice for high-efficiency energy harvesting for developing self-powered systems as well as for use as sensors. This review provides an overview of the current state of the art of such wearable sensors and end-to-end solutions for physiological and biomarker monitoring. We further discuss the current constraints and bottlenecks of these devices and systems and provide an outlook on the development of TENG-enabled PoC/monitoring devices that could eventually meet criteria formulated specifically for use in LMICs.

Self-powered slide tactile sensor with wheel-belt structures based on triboelectric effect and electrostatic induction

2021 ◽  
pp. 113022
Author(s):  
Weiguang Gu ◽  
Jie Cao ◽  
Shengping Dai ◽  
Hongwei Hu ◽  
Yan Zhong ◽  
...  
Keyword(s):  
Tactile Sensor ◽  
Electrostatic Induction ◽  
Self Powered ◽  
Triboelectric Effect

A novel weak fault diagnosis method for rolling bearings based on LSTM considering quasi-periodicity

2021 ◽  
pp. 107413
Author(s):  
Dawei Gao ◽  
Yongsheng Zhu ◽  
Zhijun Ren ◽  
Ke Yan ◽  
Wei Kang
Keyword(s):  
Fault Diagnosis ◽  
Rolling Bearings ◽  
Diagnosis Method ◽  
Weak Fault

Self-Powered RFID Sensor Tag for Fault Diagnosis and Prognosis of Transformer Winding

2017 ◽  
Vol 17 (19) ◽  
pp. 6418-6430 ◽  
Author(s):  
Tao Wang ◽  
Yigang He ◽  
Qiwu Luo ◽  
Fangming Deng ◽  
Chaolong Zhang
Keyword(s):  
Fault Diagnosis ◽  
Diagnosis And Prognosis ◽  
Transformer Winding ◽  
Self Powered ◽  
Fault Diagnosis And Prognosis

Geometric gradient assisted control of the triboelectric effect in a smart brake system for self-powered mechanical abrasion monitoring

Nano Energy ◽  
2021 ◽  
Vol 89 ◽  
pp. 106448
Author(s):  
Minchang Kim ◽  
Yoonsang Ra ◽  
Sumin Cho ◽  
Sunmin Jang ◽  
Dongik Kam ◽  
...  
Keyword(s):  
Brake System ◽  
Mechanical Abrasion ◽  
Self Powered ◽  
Triboelectric Effect
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