High sensitivity strain sensor based on cascaded cladding mode resonant double-clad fiber and simple mode fiber

2018 ◽  
Author(s):  
Dong Wang ◽  
Fan Liu ◽  
Jing Wen ◽  
Guangwei Fu ◽  
Weihong Bi ◽  
...  
Keyword(s):  
Strain Sensor ◽  
High Sensitivity ◽  
Simple Mode ◽  
Cladding Mode

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.

Superhydrophobic gradient wrinkle strain sensor with ultra-high sensitivity and broad strain range for motion monitoring

2021 ◽  
Vol 9 (15) ◽  
pp. 9634-9643
Author(s):  
Zhenming Chu ◽  
Weicheng Jiao ◽  
Yifan Huang ◽  
Yongting Zheng ◽  
Rongguo Wang ◽  
...  
Keyword(s):  
Human Body ◽  
Full Range ◽  
Strain Sensor ◽  
Strain Range ◽  
High Sensitivity

A graphene-based gradient wrinkle strain sensor with a broad range and ultra-high sensitivity was fabricated by a simple pre-stretching method. It can be applied to the detection of full-range human body motions.

scholarly journals Design of a Sensitive Balloon Sensor for Safe Human–Robot Interaction

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2163
Author(s):  
Dongjin Kim ◽  
Seungyong Han ◽  
Taewi Kim ◽  
Changhwan Kim ◽  
Doohoe Lee ◽  
...  
Keyword(s):  
High Performance ◽  
Strain Sensor ◽  
High Sensitivity ◽  
Human Robot Interaction ◽  
Large Area ◽  
Tactile Sensors ◽  
Robot Interaction ◽  
Mechanical Crack ◽  
Flexible Strain Sensor ◽  
Contact Sensing

As the safety of a human body is the main priority while interacting with robots, the field of tactile sensors has expanded for acquiring tactile information and ensuring safe human–robot interaction (HRI). Existing lightweight and thin tactile sensors exhibit high performance in detecting their surroundings. However, unexpected collisions caused by malfunctions or sudden external collisions can still cause injuries to rigid robots with thin tactile sensors. In this study, we present a sensitive balloon sensor for contact sensing and alleviating physical collisions over a large area of rigid robots. The balloon sensor is a pressure sensor composed of an inflatable body of low-density polyethylene (LDPE), and a highly sensitive and flexible strain sensor laminated onto it. The mechanical crack-based strain sensor with high sensitivity enables the detection of extremely small changes in the strain of the balloon. Adjusting the geometric parameters of the balloon allows for a large and easily customizable sensing area. The weight of the balloon sensor was approximately 2 g. The sensor is employed with a servo motor and detects a finger or a sheet of rolled paper gently touching it, without being damaged.

High-sensitivity strain sensor implemented by hybrid cascaded interferometers and the Vernier-effect

2019 ◽  
Vol 119 ◽  
pp. 105591 ◽  
Author(s):  
Ling Liu ◽  
Tigang Ning ◽  
Jingjing Zheng ◽  
Li Pei ◽  
Jing Li ◽  
...  
Keyword(s):  
Strain Sensor ◽  
High Sensitivity ◽  
Vernier Effect

Area-Arrayed Graphene Nano-Ribbon-Base Strain Sensor

2018 ◽  
Author(s):  
Ryohei Nakagawa ◽  
Zhi Wang ◽  
Ken Suzuki
Keyword(s):  
Chemical Vapor Deposition ◽  
Stress Concentration ◽  
Health Monitoring ◽  
Vapor Deposition ◽  
Strain Sensor ◽  
Chemical Vapor ◽  
High Sensitivity ◽  
Strain Sensors ◽  
Chemical Vapor Deposition Method ◽  
High Quality

Health monitoring devices using a strain sensor, which shows high sensitivity and large deformability, are strongly demanded due to further aging of society with fewer children. Conventional strain sensors, such as metallic strain gauges and semiconductive strain sensors, however, aren’t applicable to health monitoring because of their low sensitivity and deformability. In this study, fundamental design of area-arrayed graphene nano-ribbon (GNR) strain senor was proposed in order to fabricate next-generation strain sensor. The sensor was consisted of two sections, which are stress concentration section and stress detecting section. This structure can take full advantage of GNR’s properties. Moreover, high quality GNR fabrication process, which is one of the important process in the sensor, was developed by applying CVD (Chemical Vapor Deposition) method. Top-down approach was applied to fabricate the GNR. At first, in order to synthesize a high-quality graphene sheet, acetylene-based LPCVD (low pressure chemical vapor deposition) using a closed Cu foil was employed. After that, graphene was transferred silicon substrate and the quality was evaluated. The high quality graphene was transferred on the soft PDMS substrate and metallic electrodes were fabricated by applying MEMS technology. Area-arrayed fine pin structure was fabricated by using hard PDMS as a stress-concentration section. Finally, both sections were integrated to form a highly sensitive and large deformable pressure sensor. The strain sensitivity of the GNR-base sensor was also evaluated.

A strain sensor based on cladding mode resonance of optical double-cladding fiber

2010 ◽  
Author(s):  
Jian Zhang ◽  
Fufei Pang ◽  
Hairun Guo ◽  
Zhenyi Chen ◽  
Tingyun Wang
Keyword(s):  
Strain Sensor ◽  
Cladding Mode

scholarly journals Understanding the Impact of Machine Learning Models on the Performance of Different Flexible Strain Sensor Modalities

2021 ◽  
Vol 8 ◽  
Author(s):  
Brett C. Hannigan ◽  
Tyler J. Cuthbert ◽  
Wanhaoyi Geng ◽  
Mohammad Tavassolian ◽  
Carlo Menon
Keyword(s):  
Machine Learning ◽  
Mean Squared Error ◽  
Strain Sensor ◽  
High Sensitivity ◽  
Signal Amplitude ◽  
Electrical Signal ◽  
Gauge Factor ◽  
Piezoresistive Sensor ◽  
Fibre Strain ◽  
The Impact

Fibre strain sensors commonly use three major modalities to transduce strain—piezoresistance, capacitance, and inductance. The electrical signal in response to strain differs between these sensing technologies, having varying sensitivity, maximum measurable loading rate, and susceptibility to deleterious effects like hysteresis and drift. The wide variety of sensor materials and strain tracking applications makes it difficult to choose the best sensor modality for a wearable device when considering signal quality, cost, and difficulty of manufacture. Fibre strain sensor samples employing the three sensing mechanisms are fabricated and subjected to strain using a tensile tester. Their mechanical and electrical properties are measured in response to strain profiles designed to exhibit particular shortcomings of sensor behaviour. Using these data, the sensors are compared to identify materials and sensing technologies well suited for different textile motion tracking applications. Several regression models are trained and validated on random strain pattern data, providing guidance for pairing each sensor with a model architecture that compensates for non-ideal effects. A thermoplastic elastomer-core piezoresistive sensor had the highest sensitivity (average gauge factor: 12.6) and a piezoresistive sensor of similar construction with a polyether urethane-urea core had the largest bandwidth, capable of resolving strain rates above 300% s−1 with 36% signal amplitude attenuation. However, both piezoresistve sensors suffered from larger hysteresis and drift than a coaxial polymer sensor using the capacitive strain sensing mechanism. Machine learning improved the piezoresistive sensors’ root-mean-squared error when tracking a random strain signal by up to 58% while maintaining their high sensitivity, bandwidth, and ease of interfacing electronically.

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