Triboelectric Rotary Motion Sensor for Industrial-Grade Speed and Angle Monitoring

Mechanical motion sensing and monitoring is an important component in the field of industrial automation. Rotary motion is one of the most basic forms of mechanical motion, so it is of great significance for the development of the entire industry to realize rotary motion state monitoring. In this paper, a triboelectric rotary motion sensor (TRMS) with variable amplitude differential hybrid electrodes is proposed, and an integrated monitoring system (IMS) is designed to realize real-time monitoring of industrial-grade rotary motion state. First, the operating principle and monitoring characteristics are studied. The experiment results indicate that the TRMS can achieve rotation speed measurement in the range of 10–1000 rpm with good linearity, and the error rate of rotation speed is less than 0.8%. Besides, the TRMS has an angle monitoring range of 360° and its resolution is 1.5° in bidirectional rotation. Finally, the applications of the designed TRMS and IMS prove the feasibility of self-powered rotary motion monitoring. This work further promotes the development of triboelectric sensors (TESs) in industrial application.

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A self-powered electronic-skin for real-time perspiration analysis and application in motion state monitoring

Journal of Materials Chemistry C ◽

10.1039/c8tc03296c ◽

2018 ◽

Vol 6 (36) ◽

pp. 9624-9630 ◽

Cited By ~ 18

Author(s):

Haoxuan He ◽

Hui Zeng ◽

Yongming Fu ◽

Wuxiao Han ◽

Yitong Dai ◽

...

Keyword(s):

Uric Acid ◽

Real Time ◽

Acid Concentration ◽

Uric Acid Concentration ◽

State Monitoring ◽

Electronic Skin ◽

Motion State ◽

Self Powered

A self-powered electronic-skin has been fabricated for real-time perspiration analysis of lactate, glucose, Na+, K+, urea and uric acid concentration.

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Reverse Electrowetting-on-Dielectric Energy Harvesting Integrated With Charge Amplifier and Rectifier for Self-Powered Motion Sensors

Volume 8: Energy ◽

10.1115/imece2020-24189 ◽

2020 ◽

Author(s):

Pashupati R. Adhikari ◽

Nishat T. Tasneem ◽

Dipon K. Biswas ◽

Russell C. Reid ◽

Ifana Mahbub

Keyword(s):

Energy Harvester ◽

Schottky Diodes ◽

Boost Converter ◽

Motion Sensor ◽

Motion Sensors ◽

Frequency Range ◽

Charge Amplifier ◽

Electrowetting On Dielectric ◽

Dc Voltage ◽

Self Powered

Abstract This paper presents a reverse electrowetting-on-dielectric (REWOD) energy harvester integrated with rectifier, boost converter, and charge amplifier that is, without bias voltage, capable of powering wearable sensors for monitoring human health in real-time. REWOD has been demonstrated to effectively generate electrical current at a low frequency range (< 3 Hz), which is the frequency range for various human activities such as walking, running, etc. However, the current generated from the REWOD without external bias source is insufficient to power such motion sensors. In this work, to eventually implement a fully self-powered motion sensor, we demonstrate a novel bias-free REWOD AC generation and then rectify, boost, and amplify the signal using commercial components. The unconditioned REWOD output of 95–240 mV AC is generated using a 50 μL droplet of 0.5M NaCl electrolyte and 2.5 mm of electrode displacement from an oscillation frequency range of 1–3 Hz. A seven-stage rectifier using Schottky diodes having a forward voltage drop of 135–240 mV and a forward current of 1 mA converts the generated AC signal to DC voltage. ∼3 V DC is measured at the boost converter output, proving the system could function as a self-powered motion sensor. Additionally, a linear relationship of output DC voltage with respect to frequency and displacement demonstrates the potential of this REWOD energy harvester to function as a self-powered wearable motion sensor.

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Solution-synthesized chiral piezoelectric selenium nanowires for wearable self-powered human-integrated monitoring

Nano Energy ◽

10.1016/j.nanoen.2018.12.003 ◽

2019 ◽

Vol 56 ◽

pp. 693-699 ◽

Cited By ~ 24

Author(s):

Min Wu ◽

Yixiu Wang ◽

Shengjie Gao ◽

Ruoxing Wang ◽

Chenxiang Ma ◽

...

Keyword(s):

Integrated Monitoring ◽

Selenium Nanowires ◽

Self Powered

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All-fiber rotation speed measurement based on dual-beam speckle interference

Applied Optics ◽

10.1364/ao.418233 ◽

2021 ◽

Vol 60 (14) ◽

pp. 4064

Author(s):

Peng Chen ◽

Tao Huang ◽

Zhen Huang ◽

YuTing Dang ◽

Biao Gao

Keyword(s):

Rotation Speed ◽

Speed Measurement ◽

Dual Beam

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A Hierarchical Deep Fusion Framework for Egocentric Activity Recognition Using a Wearable Hybrid Sensor System

Sensors ◽

10.3390/s19030546 ◽

2019 ◽

Vol 19 (3) ◽

pp. 546 ◽

Cited By ~ 5

Author(s):

Haibin Yu ◽

Guoxiong Pan ◽

Mian Pan ◽

Chong Li ◽

Wenyan Jia ◽

...

Keyword(s):

Activity Recognition ◽

Short Term Memory ◽

Specific Activity ◽

Negative Influence ◽

Sensor System ◽

Sensor Data ◽

Motion Sensor ◽

Motion Sensors ◽

Motion State ◽

Fusion Framework

Recently, egocentric activity recognition has attracted considerable attention in the pattern recognition and artificial intelligence communities because of its wide applicability in medical care, smart homes, and security monitoring. In this study, we developed and implemented a deep-learning-based hierarchical fusion framework for the recognition of egocentric activities of daily living (ADLs) in a wearable hybrid sensor system comprising motion sensors and cameras. Long short-term memory (LSTM) and a convolutional neural network are used to perform egocentric ADL recognition based on motion sensor data and photo streaming in different layers, respectively. The motion sensor data are used solely for activity classification according to motion state, while the photo stream is used for further specific activity recognition in the motion state groups. Thus, both motion sensor data and photo stream work in their most suitable classification mode to significantly reduce the negative influence of sensor differences on the fusion results. Experimental results show that the proposed method not only is more accurate than the existing direct fusion method (by up to 6%) but also avoids the time-consuming computation of optical flow in the existing method, which makes the proposed algorithm less complex and more suitable for practical application.

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