Literature DB >> 33353160

Vibration-Based Diagnostics of Radial Clearances and Bolts Loosening in the Bearing Supports of the Heavy-Duty Gearboxes.

Pavlo Krot1, Volodymyr Korennoi2, Radoslaw Zimroz1.   

Abstract

The problem solved in this research is the diagnosis of the radial clearances in bearing supports and the loosening of fastening bolts due to their plastic elongation (creep) or weak tightening using vibration signals. This is an important issue for the maintenance of the heavy-duty gearboxes of powerful mining machines and rolling mills working in non-stationary regimes. Based on a comprehensive overview of bolted joint diagnostic methods, a solution to this problem based on a developed nonlinear dynamical model of bearing supports is proposed. Diagnostic rules are developed by comparing the changes of natural frequency and its harmonics, the amplitudes and phases of shaft transient oscillations. Then, the vibration signals are measured on real gearboxes while the torque is increasing in the transmission during several series of industrial trials under changing bearings and bolts conditions. In parallel, dynamical torque is measured and its interrelation with vibration is determined. It is concluded that the radial clearances are the most influencing factors among the failure parameters in heavy-duty gearboxes of industrial machines working under impulsive and step-like loading. The developed diagnostics algorithm allows condition monitoring of bearings and fastening bolts, allowing one to undertake timely maintenance actions to prevent failures.

Entities:  

Keywords:  bearings; bolts loosening; condition monitoring; nonlinear model; radial clearance; transient vibration

Year:  2020        PMID: 33353160      PMCID: PMC7766838          DOI: 10.3390/s20247284

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Integrating the IoT and Blockchain Technology for the Next Generation of Mining Inspection Systems.

Authors:  Miguel Pincheira; Mattia Antonini; Massimo Vecchio
Journal:  Sensors (Basel)       Date:  2022-01-25       Impact factor: 3.576

  1 in total

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