MEMS Acceleration Sensor Vibration Detection System with LoRa Communication

2021 ◽  
Author(s):  
Jian-liang Wang ◽  
Yan-jun Zhang ◽  
Bo He ◽  
Jiang-yan Xu ◽  
Ye Wei ◽  
...  
2020 ◽  
Vol 1601 ◽  
pp. 032041
Author(s):  
Ji-Yuan Guo ◽  
Fu-Sheng Zhang ◽  
Xuefei Liu ◽  
Jia-Kun An ◽  
Yang Zhao

2013 ◽  
Vol 7 (5) ◽  
pp. 550-557 ◽  
Author(s):  
Nobuhiko Henmi ◽  
◽  
Shingo Takeuchi

An acceleration sensor is usually used to examine for roller bearing damage. It is difficult, however, to detect abnormal vibration and examine for roller bearing damage when rotation speed is low. The final target of this study is to establish a bearing damage diagnosis system based on the piezoelectric jerk sensor we developed, which can be used for both low- and highspeed rotations. For this purpose, this paper aims to identify the features of an abnormal vibration detection signal at a low rotation speed, propose a new roller bearing damage diagnosis method that uses the features, and clarify the validity of the method. Experiments are conducted to analyze a scratch purposely made on the outer ring of a conical roller bearing that rotates at the low speeds of 10 or 40 rpm. The results verify the advantages of using the jerk sensor for the bearing damage diagnosis and the validity of the method proposed in this paper.


2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Carlos Morón ◽  
Alfonso García ◽  
Daniel Ferrández ◽  
Víctor Blanco

The present work exposes an alternative system for detecting vibrations generated by impact on concrete and mortar sheets. In order to carry out the tests it is necessary to implement a system of measurement different than the one proposed by the current UNE EN 140-7. This system consists of an amplifier and a striking device that is also able to measure the deformation of the material once the impact has been produced. This system is able to detect variations in transmission of vibration at the same frequency between the various building materials employed, after establishing a relationship between the theoretical predictions and the experimental results. Thus, this system could be used as a vibration detection system and as an alternative method of standardization of materials against their acoustic characteristics.


2005 ◽  
Vol 123-124 ◽  
pp. 63-72 ◽  
Author(s):  
D. Scheibner ◽  
J. Mehner ◽  
D. Reuter ◽  
T. Gessner ◽  
W. Dötzel

Synthesiology ◽  
2013 ◽  
Vol 6 (1) ◽  
pp. 45-54 ◽  
Author(s):  
Hiroshi TSUDA ◽  
Eiichi SATO ◽  
Tomio NAKAJIMA ◽  
Akiyoshi SATO

Author(s):  
Huageng Luo ◽  
Hector Rodriguez ◽  
Darren Hallman ◽  
Dennis Corbly

This paper presents a methodology of detecting rotor imbalances, such as mass imbalance and crack-induced imbalance, using shaft synchronous vibrations. A vibration detection algorithm is derived based on the first order nonresonant synchronous vibration response. A detection system is integrated by using state-of-the-art commercial analysis equipment. A laboratory rotor test rig with controlled mass imbalances was used to verify the integrated system. The system is then deployed to an engine sub-assembly test setup. Four specimens were used in the subassembly test and the test results are reported in the final section.


2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Nuttun Virojboonkiate ◽  
Adsadawut Chanakitkarnchok ◽  
Peerapon Vateekul ◽  
Kultida Rojviboonchai

This paper introduces a driver identification system architecture for public transport which utilizes only acceleration sensor data. The system architecture consists of three main modules which are the data collection, data preprocessing, and driver identification module. Data were collected from real operation of campus shuttle buses. In the data preprocessing module, a filtering module is proposed to remove the inactive period of the public transport data. To extract the unique behavior of the driver, a histogram of acceleration sensor data is proposed as a main feature of driver identification. The performance of our system is evaluated in many important aspects, considering axis of acceleration, sliding window size, number of drivers, classifier algorithms, and driving period. Additionally, the case study of impostor detection is implemented by modifying the driver identification module to identify a car thief or carjacking. Our driver identification system can achieve up to 99% accuracy and the impostor detection system can achieve the F1 score of 0.87. As a result, our system architecture can be used as a guideline for implementing the real driver identification system and further driver identification researches.


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