Embedded piezoelectric sensor-based real-time strength monitoring during curing process of concrete

Author(s):  
Dong-Jin Kim ◽  
Changgil Lee ◽  
Hajoo Chang ◽  
Seunghee Park
Author(s):  
Isna Fatimatuz Zahra ◽  
I Dewa Gede Hari Wisana ◽  
Priyambada Cahya Nugraha ◽  
Hayder J Hassaballah

Acute myocardial infarction, commonly referred to as a heart attack, is the most common cause of sudden death where a monitoring tool is needed that is equipped with a system that can notify doctors to take immediate action. The purpose of this study was to design a heart attack detection device through indicators of vital human signs. The contribution of this research is that the system works in real-time, has more parameters, uses wireless, and is equipped with a system to detect indications of a heart attack. In order for wireless monitoring to be carried out in real-time and supported by a detection system, this design uses a radio frequency module as data transmission and uses a warning system that is used for detection. Respiration rate was measured using the piezoelectric sensor, and body temperature was measured using the DS18B20 temperature sensor. Processing of sensor data is done with ESP32, which is displayed wirelessly by the HC-12 module on the PC. If an indication of a heart attack is detected in the parameter value, the tool will activate a notification on the PC. In every indication of a heart attack, it was found that this design can provide notification properly. The results showed that the largest respiratory error value was 4%, and the largest body temperature error value was 0.55%. The results of this study can be implemented in patients who have been diagnosed with heart attack disease so that it can facilitate monitoring the patient's condition.


2014 ◽  
Vol 711 ◽  
pp. 329-332
Author(s):  
Lin Zhao

The main research direction of Numerical control lathe cutting force signal on-line monitoring is to process real-time monitoring, using the sensor, charge amplifier, video acquisition card and computer to collect data and signal. Signal acquisition makes use of the piezoelectric sensor signals and send them to the computer in order to acquire the real-time data and display the dynamic signal so that monitor the process. Signal processing is the course that data will be collected for subsequent processing and analyzing. It includes display, filtering, correlation analysis, spectral analysis, etc. We can conclude the signal’s characteristics after the time domain and frequency domain analysis of signals.


2021 ◽  
Vol 52 (1) ◽  
pp. 795-798
Author(s):  
Ying Qian ◽  
Huimin Li ◽  
Anqi Li ◽  
Xinghui Liu ◽  
Guoxian Wu ◽  
...  

2021 ◽  
Vol 31 (1) ◽  
pp. 015039
Author(s):  
Jianjian Zhu ◽  
Jinshan Wen ◽  
Chunyang Chen ◽  
Xiao Liu ◽  
Zifeng Lan ◽  
...  

Abstract As one of cost-effective maintenance methods, bonded composite patch repair has been receiving more and more attention in the engineering community since past decades. However, realizing real-time monitoring for curing process of bonded repair patch is difficult for most current techniques. In our work, a method based on electromechanical impedance and system parameters evaluation for structural health monitoring issues was developed, which could implement the online monitoring throughout whole curing process. Compared with the dynamic thermomechanical analysis results, the experiment data matches well. It demonstrates that the proposed approach can effectively monitor the curing process of composite repair patch at a constant temperature of 120 °C. Hence, the presented approach in this paper is expected to be a novel, robust, and real-time monitoring method for structural maintenance with the composite patch.


Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3241 ◽  
Author(s):  
Ahmed Rasheed ◽  
Emad Iranmanesh ◽  
Weiwei Li ◽  
Yangbing Xu ◽  
Qi Zhou ◽  
...  

In this work, we report an active respiration monitoring sensor based on a piezoelectric-transducer-gated thin-film transistor (PTGTFT) aiming to measure respiration-induced dynamic force in real time with high sensitivity and robustness. It differs from passive piezoelectric sensors in that the piezoelectric transducer signal is rectified and amplified by the PTGTFT. Thus, a detailed and easy-to-analyze respiration rhythm waveform can be collected with a sufficient time resolution. The respiration rate, three phases of respiration cycle, as well as phase patterns can be further extracted for prognosis and caution of potential apnea and other respiratory abnormalities, making the PTGTFT a great promise for application in long-term real-time respiration monitoring.


2018 ◽  
Vol 8 (1) ◽  
pp. 75 ◽  
Author(s):  
Sang-Ki Choi ◽  
Najeebullah Tareen ◽  
Junkyeong Kim ◽  
Seunghee Park ◽  
Innjoon Park

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