사물인터넷 기반 무선 상태 모니터링 시스템 개발
Abstract
With the advancements in sensor technology and open source-based controllers, the development of a condition monitoring system has become relatively easier. However, there is not enough well-organized information to develop condition monitoring system. Therefore, we present a wireless condition monitoring system based on the Internet of Things (IoT) by using an open-source controller. The developed wireless condition monitoring system consists of a sensor module, data processing unit, and condition monitoring program. This system can measure 3-axis accelerations of frequency up to 1.5 kHz, with a frequency resolution of 0.05 Hz to 20 Hz, and temperature. The developed condition monitoring system provides statistical time information and frequency spectrum for advanced condition diagnosis. Furthermore, the condition diagnosis function for low-speed rotating machines was implemented effectively.
Keywords:
Accelerometer, Internet of things, Condition monitoring, Condition diagnosis, Frequency analysisAcknowledgments
이 논문은 안동대학교 기본연구지원사업에 의하여 연구되었음.
References
- Tandon, N., Yadava, G. S. , Ramakrishna, K. M., 2007, A Comparison of Some Condition Monitoring Techniques for the Detection of Defect in Induction Motor Ball Bearings, Mechanical systems and signal processing, 21:1 244-256. [https://doi.org/10.1016/j.ymssp.2005.08.005]
- Sinha, J. K., Elbhbah, K., 2013, A Future Possibility of Vibration Based Condition Monitoring of Rotating Machines, Mechanical systems and signal processing, 34:1-2 231-240. [https://doi.org/10.1016/j.ymssp.2012.07.001]
- Jardine, A. K. S., Lin, D., Banjevic, D., 2006, A Review on Machinery Diagnostics and Prognostics Implementing Condition-based Maintenance, Mechanical systems and signal processing, 20:7 1483-1510. [https://doi.org/10.1016/j.ymssp.2005.09.012]
- Fassois, S. D., Sakerllariou, J. S., 2007, Time-series Methods for Fault Detection and Identification in Vibrating Structures, Philosophical Transactions of the Royal Society A., 365:1851 411-448. [https://doi.org/10.1098/rsta.2006.1929]
- Feng, Z., Liang, M., Chu, F., 2013, Recent Advances in Time-frequency Analysis Methods for Machinery Fault Diagnosis: A Review with Application Examples, Mechanical Systems and Signal Processing, 38:1 165-205. [https://doi.org/10.1016/j.ymssp.2013.01.017]
- Analog Devices, n.d., viewed 18 January 2020, ADXL354, <https://www.analog.com/en/products/adxl354.html, >
- Arduino, n.d., viewed 18 January 2020, Arduino MKR1000 WIFI, <https://store.arduino.cc/usa/arduino-mkr1000, >.
- Korean Standard Association, 1991, Mechanical Vibration of Machines With Operating Speeds from 10 to 200REV/S-Basis for Specifying Evaluation Standards, KS B 0142.
- Shin, K. H., Lee, S. H., 2015, Machinery Fault Diagnosis Using Two-Channel Analysis Method Based on Fictitious System Frequency Response Function, Shock and Vibration, 2015: 561238 1-7. [https://doi.org/10.1155/2015/561238]
- Analog Devices, n.d., viewed 27 July 2020, Taking the Mystery out of the Infamous Formula “SNR = 6.02N + 1.76dB,” and Why You Should Care, <https://www.analog.com/media/en/training-seminars/tutorials/MT-001.pdf, >.
- Texas Instruments, n.d., viewed 27 July 2020, Understanding Signal to Noise Ratio and Noise, <https://training.ti.com/sites/default/files/docs/>.
- Nutaq, n.d., viewed 27 July 2020, From Analog to Digital - Part 6a: ADC Performance, <https://www.nutaq.com/blog/analog-digital-%E2%80%93-part-6a-adc-performance, >.
Professor in the Department of Mechanical & Robotics Engineering, Andong National University.His research interest is the design and control of mechatronics systems.
E-mail: shlee@andong.ac.kr