Abstract
As a key component of rotating machinery power transmission system, rolling bearings in gas turbines are often required to serve in complex working conditions such as the high speed, the heavy load, the variable load, the variable rotational speed, and so on. The signals of bearing failures are easily drowned out by strong background noise and disturbances of related components. In the mechanical transmission system, the signals of bearing failures are easily submerged by the strong background noise and the disturbance of related components, especially for the composite bearing failures, which seriously hinders the effective identification of the vibration characteristics of the bearing operating state and increases the difficulty of fault diagnosis. In order to investigate the impact of interference on the bearing, through the establishment of rolling bearing composite fault vibration model, analyze the relationship between the vibration signals caused by different types of bearing failures and the corresponding vibration characteristics, to reveal the transmission system of the parts of the perturbation of the main multi-interference factors on the bearing fault signal influence law. The experimental verification shows that disturbance yp(t) caused by the sum of gear meshing frequency, and installation errors of the shaft, and coupling in the transmission system and background noise ni(t), which makes the fault frequency relatively weak and difficult to observe, and makes it difficult to accurately separate the fault information of the bearing. It provides a theoretical basis to solve the problem of damage identification and fault diagnosis of rolling bearings under multi-interference state.
Funder
the National Natural Science Foundation of China
Natural Science Foundation of Heilongjiang Province
Publisher
Public Library of Science (PLoS)
Reference34 articles.
1. Where to go and where to go in the basic research of mechanical fault diagnosis[J];G Wang;Journal of Mechanical Engineering,2013
2. Y. Multidimensional denoising of rotating machine based on tensor factorization[J];WANG HU C;Mechanical Systems and Signal Processing,2019
3. Research Advances of Fault Diagnosis Technique for Planetary Gearboxes [J];Yaguo Lei;Journal of mechanical Engineering,2011
4. Research on an Adaptive Variational Mode Decomposition with Double Thresholds for Feature Extraction[J];Deng Wu;Symmetry,2018
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献