Preliminary investigation on the development of low-cost vibration based condition monitoring DAQ system in industry 4.0

Authors

  • Setti Suresh Central Manufacturing Technology Institute, Bengaluru, Karnataka, India
  • S. Yaswant Central Manufacturing Technology Institute, Bengaluru, Karnataka, India
  • T. Narendra Reddy Central Manufacturing Technology Institute, Bengaluru, Karnataka, India
  • Prakash Vinod Central Manufacturing Technology Institute, Bengaluru, Karnataka, India

DOI:

https://doi.org/10.58368/MTT.23.5-6.2024.1-7

Keywords:

MEMS Sensor, Vibration Analysis, DAQ, Condition Monitoring

Abstract

This paper presents a preliminary investigation into the development of a low-cost, vibration-based data acquisition (DAQ) system for condition monitoring in the context of Industry 4.0. The system utilizes a single-axis MEMS accelerometer with a sensitivity of 40 mV/g and a frequency response range of DC to 11 kHz (3 dB) to capture vibration data. This data is processed in real-time at the edge using an ST microcontroller to compute the FFT spectrum. The accuracy of the preliminary vibration data was validated against a reference setup comprising a vibration exciter and an OROS vibration analyzer. When the prototype DAQ module, equipped with the MEMS sensor, was tested on a three-phase induction motor alongside a reference piezoelectric accelerometer, the computed FFT spectra from both setups demonstrated strong similarity. Beyond conventional analysis, the raw data from the DAQ system is integrated into a live dashboard for real-time signal interpretation. Further optimization of this low-cost DAQ system aims to address the condition monitoring needs of micro, small, and medium enterprises (MSMEs), enabling in-situ asset monitoring at an affordable price point.

Metrics

Metrics Loading ...

References

Ali, M. Y., Mohamed, A. R., Asfana, B., Lutfi, M., & Fahmi, M. I. (2012). Investigation of vibration and surface roughness in micro milling of PMMA. Applied Mechanics and Materials, 217-219, 2187-2193. https://doi.org/10.4028/ WWW.SCIENTIFIC.NET/AMM.217-219.2187

Dalpiaz, G., & Rivola, A. (1997). Condition monitoring and diagnostics in automatic machines: comparison of vibration analysis techniques. Mechanical Systems and Signal Processing, 11(1), 53-73. https://doi. org/10.1006/MSSP.1996.0067

Ebersbach, S., & Peng, Z. (2008). Expert system development for vibration analysis in machine condition monitoring. Expert Systems with Applications, 34(1), 291-299. https://doi. org/10.1016/J.ESWA.2006.09.029

Ghosh, D., Roy, H., Saha, A., & Subramanian, C. (2022). Failure analysis of boiler water wall tube: A case study from thermal power plant. Journal of Failure Analysis and Prevention, 22(1), 203-208. https://doi.org/10.1007/S11668- 021-01271-Y/FIGURES/8

Hsieh, W. H., Lu, M. C., & Chiou, S. J. (2012). Application of backpropagation neural network for spindle vibration-based tool wear monitoring in micro-milling. International Journal of Advanced Manufacturing Technology, 61(1-4), 53-61. https://doi.org/10.1007/S00170- 011-3703-X/METRICS

Krishnakumar, P., Rameshkumar, K., & Rama-chandran, K. I. (2015). Tool wear condition prediction using vibration signals in high speed machining (HSM) of titanium (Ti-6Al-4 V) alloy. Procedia Computer Science, 50, 270-275. https://doi.org/10.1016/J.PROCS.2015.04.049

Mohamed, A. R., Atiqah, N., Ali, M. Y., & Chowdhury, M. S. H. (2013). Tool Vibration due to High Speed Micro End Milling Parameters. Applied Mechanics and Materials, 372, 364–368. https://doi.org/10.4028/WWW.SCIENTIFIC.NET/ AMM.372.364

Rossi, A., Bocchetta, G., Botta, F., & Scorza, A. (2023). Accuracy characterization of a mems accelerometer for vibration monitoring in a rotating framework. Applied Sciences 2023, 13(8), 5070. https://doi.org/10.3390/ APP13085070

Sridhar, A. V., Prasad, B. S., & Mouli, K. V. V. N. R. C. (2021). Evaluation of tool performance and wear through vibration signature analysis in drilling of IS3048 steel. Journal of Engineering and Applied Science, 68(1), 1-12. https://doi. org/10.1186/S44147-021-00036-6/FIGURES/11

Xie, Z., Li, J., & Lu, Y. (2018). An integrated wireless vibration sensing tool holder for milling tool condition monitoring. International Journal of Advanced Manufacturing Technology, 95(5-8), 2885-2896. https://doi.org/10.1007/S00170- 017-1391-X/METRICS

Zhang, J. Z., & Chen, J. C. (2008). Tool condition monitoring in an end-milling operation based on the vibration signal collected through a microcontroller-based data acquisition system. International Journal of Advanced Manufacturing Technology, 39(1-2), 118-128. https://doi.org/10.1007/S00170-007-1186-6/ METRICS

Downloads

Published

01-05-2024

How to Cite

Suresh, S., Yaswant, S., Narendra Reddy, T., & Vinod, P. (2024). Preliminary investigation on the development of low-cost vibration based condition monitoring DAQ system in industry 4.0. Manufacturing Technology Today, 23(5-6), 1–7. https://doi.org/10.58368/MTT.23.5-6.2024.1-7