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Any single machine rotary component in the process could result in downtime costs. It is necessary to monitor the overall machine health while it is in use. Bearing failure is one of the primary causes of machine breakdown in industry at high and low speeds. A vibration signature evaluation has historically determined misalignments in shafting systems. These misalignments are also responsible for the bearing increase in temperature. The purpose of this work is to undertake a comparative study to obtain the reliability of the effect of the amount of misalignment on bearing by using thermography measurement. An experimental study was performed in this paper to indicate the existence of machine misalignment at an early stage by measuring the bearing temperature using a thermal imaging camera. The effects of load, velocity, and misalignment on the bearings and their temperature increase have been investigated. The test bench's rolling-element bearing is an NTN UCP213-208 pillow block bearing. It has been observed that by tracking the change of temperature in bearings could lead to misalignment detection and the effect of the amount of misalignment on it.

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References

  1. Malla C, Panigrahi I. Review of condition monitoring of rolling element bearing using vibration analysis and other techniques. Journal of Vibration Engineering & Technologies. 2019 Aug;7(4):407-14.
     Google Scholar
  2. Verma AK, Sarangi S, Kolekar MH. Experimental investigation of misalignment effects on rotor shaft vibration and on stator current signature. Journal of Failure Analysis and Prevention. 2014 Apr;14(2):125-38.
     Google Scholar
  3. YILMAZ Ö, Aksoy M, Kesilmiş Z. Misalignment fault detection by wavelet analysis of vibration signals. International Advanced Researches and Engineering Journal. 2019;3(3):156-63.
     Google Scholar
  4. Fatima S, Mohanty AR, Naikan VA. A misalignment detection methodology by measuring rate of temperature rise of shaft coupling using thermal imaging. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. 2015 Jun;229(3):209-19.
     Google Scholar
  5. Nabhan A, Ghazaly N, Samy A, Mousa MO. Bearing fault detection techniques-a review. Turkish Journal of Engineering, Sciences and Technology. 2015 Jan;3(2).
     Google Scholar
  6. Gárdonyi P, Nagy D, Gergely Z and Bercesi G. Developing test equipment suitable for testing torque transfer systems used in agriculture. Poljoprivredna tehnika. 2017 42 27-36.
     Google Scholar
  7. Gupta P, Pradhan MK. Fault detection analysis in rolling element bearing: A review. Materials Today: Proceedings. 2017 Jan 1;4(2):2085-94.
     Google Scholar
  8. Ali JB, Chebel-Morello B, Saidi L, Malinowski S, Fnaiech F. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network. Mechanical Systems and Signal Processing. 2015 May 1;56:150-72.
     Google Scholar