Study on Micro Force Sensor and its Signal Acquisition System Based on Android and Arduino

2020 ◽  
Vol 15 (9) ◽  
pp. 1384-1389
Author(s):  
Shaopeng Yu ◽  
Bowen Wang ◽  
Liyuan Dong
2011 ◽  
Vol 105-107 ◽  
pp. 2179-2182
Author(s):  
Wei Min Zhang ◽  
Shu Xuan Liu ◽  
Yong Qiu ◽  
Cheng Feng Chen

Crack propagation is the main reason which leads to the invalidity of the metal components. A set of detecting equipment based on the acoustic emission method was designed, and it was mainly composed of acoustic emission sensor, signal operating circuits and signal acquisition system. Specimens of 16MnR material were manufactured and the static axial tension test of them was carried on. Acoustic emission signals from the specimen were detected by acoustic emission equipment by using piezoelectric ceramic sensor. Signal datum were acquired and operated by the acquisition system, as well as the acquisition program written for it. The final results has demonstrated that acoustic emission equipment designed for the test performed well in acquiring the signals induced by the metal crack propagation.


2014 ◽  
Vol 599-601 ◽  
pp. 1135-1138
Author(s):  
Chao Zhe Ma ◽  
Jin Song Du ◽  
Yi Yang Liu

At present, sub-micro-Newton (sub-μN) micro-force in micro-assembly and micro-manipulation is not able to be measured reliably. The piezoelectric micro-force sensors offer a lot of advantages for MEMS applications such as low power dissipation, high sensitivity, and easily integrated with piezoelectric micro-actuators. In spite of many advantages above, the research efforts are relatively limited compared to piezoresistive micro-force sensors. In this paper, Sensitive component is polyvinylidene fluoride (PVDF) and the research object is micro-force sensor based on PVDF film. Moreover, the model of micro-force and sensor’s output voltage is built up, signal processing circuit is designed, and a novel calibration method of micro-force sensor is designed to reliably measure force in the range of sub-μN. The experimental results show the PVDF sensor is designed in this paper with sub-μN resolution.


Micromachines ◽  
2017 ◽  
Vol 8 (10) ◽  
pp. 304
Author(s):  
Huan Liu ◽  
Zhongliang Yu ◽  
Yan Liu ◽  
Xudong Fang

2013 ◽  
Vol 462-463 ◽  
pp. 1001-1004
Author(s):  
Xue Wang ◽  
Wen Liang Niu ◽  
Yuan Sheng Liu

In order to more accurate detection of ECG signal and cost savings, this paper designed a set of ECG signal acquisition system based on Matlab. The system is composed of hardware and software. Hardware is made up of signal acquisition processing circuit and MPC82G516 microcontroller for AD conversion. The software mainly contains configuring Matlab serial to realize communication with MPC82G516 and uses abundant filter resources of Matlab to remove noise by differential, absolute value, smoothing and threshold selection algorithm of R wave detection, R wave peak provides the basis for calculating the heart rate. This paper uses Matlab friendly user interface for displaying received data to make the data more intuitive and read more easily.


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yidong Zeng ◽  
Jun Ji ◽  
Jinghua Wang ◽  
Jiasuo Gao ◽  
Jie Hu ◽  
...  

In this paper, the pulse wave feature alertness detection system based on computer software technology is researched. First, the computer software technology designs the alertness detection system and then conducts the system alertness test experiment using a system that can not affect the subjects’ alertness, a portable multichannel physiological signal acquisition system that measures the subjects’ ECG signal, skin resistance, blood oxygen saturation, and other physiological signals in the case of a degree task experiment. The multichannel physiological signal acquisition system collects the signals during the vigilance task experiment. At the same time, before, during, and after the experiment, subjects are required to fill in the Stanford Sleepiness Scale (SSS) and evaluate the level of individual alertness through subjective self-evaluation. The relevant experimental data show that, 10 minutes before the experiment, the pulse amplitude increased rapidly, then slowly decreased at the beginning, reached a peak in about 25 minutes, and then began to rise.


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