A Selective-Response Bioinspired Strain Sensor Using Viscoelastic Material as Middle Layer

ACS Nano ◽  
2021 ◽  
Author(s):  
Dakai Wang ◽  
Junqiu Zhang ◽  
Guoliang Ma ◽  
Yuqiang Fang ◽  
Linpeng Liu ◽  
...  
Keyword(s):  
Viscoelastic Material ◽  
Strain Sensor ◽  
Middle Layer

Development of Flexible Piezoelectric Strain Sensor Array

2017 ◽  
Vol 137 (12) ◽  
pp. 438-443
Author(s):  
Takahiro Yamashita ◽  
Seiichi Takamatsu ◽  
Hironao Okada ◽  
Toshihiro Itoh ◽  
Takeshi Kobayashi
Keyword(s):  
Sensor Array ◽  
Strain Sensor ◽  
Piezoelectric Strain ◽  
Strain Sensor Array

A Consistent Implementation of Inelastic Material Models into Steady State Rolling

2016 ◽  
Vol 44 (3) ◽  
pp. 174-190 ◽  
Author(s):  
Mario A. Garcia ◽  
Michael Kaliske ◽  
Jin Wang ◽  
Grama Bhashyam
Keyword(s):  
Steady State ◽  
Numerical Simulations ◽  
Viscoelastic Material ◽  
Rolling Contact ◽  
Arbitrary Lagrangian Eulerian ◽  
Ale Formulation ◽  
Inelastic Material ◽  
Material Formulation ◽  
Steady State Rolling ◽  
Efficient Alternative

ABSTRACT Rolling contact is an important aspect in tire design, and reliable numerical simulations are required in order to improve the tire layout, performance, and safety. This includes the consideration of as many significant characteristics of the materials as possible. An example is found in the nonlinear and inelastic properties of the rubber compounds. For numerical simulations of tires, steady state rolling is an efficient alternative to standard transient analyses, and this work makes use of an Arbitrary Lagrangian Eulerian (ALE) formulation for the computation of the inertia contribution. Since the reference configuration is neither attached to the material nor fixed in space, handling history variables of inelastic materials becomes a complex task. A standard viscoelastic material approach is implemented. In the inelastic steady state rolling case, one location in the cross-section depends on all material locations on its circumferential ring. A consistent linearization is formulated taking into account the contribution of all finite elements connected in the hoop direction. As an outcome of this approach, the number of nonzero values in the general stiffness matrix increases, producing a more populated matrix that has to be solved. This implementation is done in the commercial finite element code ANSYS. Numerical results confirm the reliability and capabilities of the linearization for the steady state viscoelastic material formulation. A discussion on the results obtained, important remarks, and an outlook on further research conclude this work.

Development of a smart timber bridge (phase III): moisture and strain sensor investigation for historic covered bridges

2019 ◽  
Author(s):  
Brent M. Phares ◽  
Trevor L. Pence ◽  
James P. Wacker ◽  
Travis K. Hosteng
Keyword(s):  
Strain Sensor ◽  
Phase Iii

Effect of CeO2 Modified MAS Middle Layer on the Joint of C/C-LAS

2013 ◽  
Vol 28 (12) ◽  
pp. 1345-1348
Author(s):  
Huan-Xia ZHU ◽  
Ke-Zhi LI ◽  
Jin-Hua LU ◽  
He-Jun LI ◽  
Jian-Yang WANG
Keyword(s):  
Middle Layer

Improved Environment-Aware–Based Noise Reduction System for Cochlear Implant Users Based on Knowledge Transfer Approach (Preprint)

2020 ◽  
Author(s):  
Lieber Po-Hung Li ◽  
Ji-Yan Han ◽  
Wei-Zhong Zheng ◽  
Ren-Jie Huang ◽  
Ying-Hui Lai
Keyword(s):  
Knowledge Transfer ◽  
Cochlear Implant ◽  
Noise Reduction ◽  
Speech Intelligibility ◽  
Middle Layer ◽  
Successful Implementation ◽  
Perceptual Evaluation ◽  
Reduction System ◽  
Listening Tests ◽  
Implementation Costs

BACKGROUND The cochlear implant technology is a well-known approach to help deaf patients hear speech again. It can improve speech intelligibility in quiet conditions; however, it still has room for improvement in noisy conditions. More recently, it has been proven that deep learning–based noise reduction (NR), such as noise classification and deep denoising autoencoder (NC+DDAE), can benefit the intelligibility performance of patients with cochlear implants compared to classical noise reduction algorithms. OBJECTIVE Following the successful implementation of the NC+DDAE model in our previous study, this study aimed to (1) propose an advanced noise reduction system using knowledge transfer technology, called NC+DDAE_T, (2) examine the proposed NC+DDAE_T noise reduction system using objective evaluations and subjective listening tests, and (3) investigate which layer substitution of the knowledge transfer technology in the NC+DDAE_T noise reduction system provides the best outcome. METHODS The knowledge transfer technology was adopted to reduce the number of parameters of the NC+DDAE_T compared with the NC+DDAE. We investigated which layer should be substituted using short-time objective intelligibility (STOI) and perceptual evaluation of speech quality (PESQ) scores, as well as t-distributed stochastic neighbor embedding to visualize the features in each model layer. Moreover, we enrolled ten cochlear implant users for listening tests to evaluate the benefits of the newly developed NC+DDAE_T. RESULTS The experimental results showed that substituting the middle layer (ie, the second layer in this study) of the noise-independent DDAE (NI-DDAE) model achieved the best performance gain regarding STOI and PESQ scores. Therefore, the parameters of layer three in the NI-DDAE were chosen to be replaced, thereby establishing the NC+DDAE_T. Both objective and listening test results showed that the proposed NC+DDAE_T noise reduction system achieved similar performances compared with the previous NC+DDAE in several noisy test conditions. However, the proposed NC+DDAE_T only needs a quarter of the number of parameters compared to the NC+DDAE. CONCLUSIONS This study demonstrated that knowledge transfer technology can help to reduce the number of parameters in an NC+DDAE while keeping similar performance rates. This suggests that the proposed NC+DDAE_T model may reduce the implementation costs of this noise reduction system and provide more benefits for cochlear implant users.

SIMULATION OF MIDDLE LAYER TURBIDITY PEAK AND BLUE TIDE

2019 ◽  
Vol 75 (2) ◽  
pp. I_997-I_1002
Author(s):  
Teruhisa OKADA ◽  
Masahiro IMAMURA
Keyword(s):  
Middle Layer

scholarly journals Flexible Metal/Polymer Composite Films Embedded with Silver Nanowires as a Stretchable and Conductive Strain Sensor for Human Motion Monitoring

Micromachines ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 372 ◽  
Author(s):  
Jinjin Luan ◽  
Qing Wang ◽  
Xu Zheng ◽  
Yao Li ◽  
Ning Wang
Keyword(s):  
Polymer Composite ◽  
Silver Nanowires ◽  
Composite Films ◽  
Strain Sensor ◽  
High Sensitivity ◽  
Human Motion ◽  
Applied Strain ◽  
Potential Candidate ◽  
Flexible Metal ◽  
Metal Polymer

To avoid conductive failure due to the cracks of the metal thin film under external loads for the wearable strain sensor, a stretchable metal/polymer composite film embedded with silver nanowires (AgNWs) was examined as a potential candidate. The combination of Ag film and AgNWs enabled the fabrication of a conductive film that was applied as a high sensitivity strain sensor, with gauge factors of 7.1 under the applied strain of 0–10% and 21.1 under the applied strain of 10–30%. Furthermore, the strain sensor was demonstrated to be highly reversible and remained stable after 1000 bending cycles. These results indicated that the AgNWs could act as elastic conductive bridges across cracks in the metal film to maintain high conductivity under tensile and bending loads. As such, the strain sensor engineered herein was successfully applied in the real-time detection and monitoring of large motions of joints and subtle motions of the mouth.

Inductive Strain Sensor With High Repeatability and Ultra-Low Hysteresis Based on Mechanical Spring

2020 ◽  
Vol 20 (24) ◽  
pp. 14670-14675
Author(s):  
Zhiguang Xing ◽  
Jun Lin ◽  
David McCoul ◽  
Dapeng Zhang ◽  
Jianwen Zhao
Keyword(s):  
Strain Sensor ◽  
Mechanical Spring ◽  
High Repeatability
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