Author(s)

Chunhua Feng ¹, Binbin Deng ¹

Affiliation(s)

¹ School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

Corresponding Author

Chunhua Feng

ABSTRACT

The course of mechanical testing technology occupies a very important position in the mechanical major, and signal processing technology is its main teaching content. This paper introduces a fault diagnosis case based on vibration sensor to deepen students' understanding of signal processing process. Taking a certain mechanical equipment as the research object, a vibration sensor is arranged to monitor the vibration of the equipment during operation. Then, the vibration data of the equipment under different working conditions are collected and analyzed. Based on the feature extraction of vibration data in time and frequency domain, principal component analysis is used as the feature selection method. Finally, the fault analysis is carried out with support vector machine. Through this case, the students could better understand how to use vibration data for fault diagnosis analysis.

KEYWORDS

Vibration sensor, Signal processing, Feature selection, Mechanical measurement technology

CITE THIS PAPER

Chunhua Feng, Binbin Deng, Case Study Analysis of Equipment Fault Diagnosis for Course of Mechanical Measurement Technology. Journal of Electrotechnology, Electrical Engineering and Management (2024) Vol. 7: 131-136. DOI: http://dx.doi.org/10.23977/jeeem.2024.070117.

REFERENCES

[1] Wen B., Shimizu Y., Matsukuma H., Tohyama K., Gao W. (2020). A differential strategy for measurement of a static force in a single point diamond cutting by a force-controlled fast tool servo. Measurement Science and Technology, 31(7).
[2] Marziani C.D., Urena J., Hernandez Garcia J.J., Alvarez F. J., Jimenez A., et al. (2012). Simultaneous round-trip time-of-flight measurements with encoded acoustic signals. IEEE Sensors Journal, 12(10), 2931-2940.
[3] Niessner S., Liewald M. (2020). Identification of methods for the in-situ measurement of cutting forces in a tool-bound punching machine. IOP Conference Series Materials Science and Engineering, 967, 012025.
[4] Patil R.A., Gombi S. L. (2020). Operational cutting force identification in end milling using inverse technique to predict the fatigue tool life. Iranian Journal of Science and Technology: Transactions of Mechanical Engineering, 46, 31–41.

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