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Understanding the calculations and concepts related to double-collar bearings is essential for engineers and designers to optimize the performance of these components in various applications. By analyzing the bearing under different conditions, one can ensure that it can withstand the forces and moments experienced during operation. This knowledge enables better decision-making when designing and selecting bearings for specific purposes and configurations. Consider a double-collar bearing with...
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Designing a transmission shaft requires a thorough understanding of the stresses induced by bending moments and torques, especially in systems where power is transferred through gears. These forces create force-couple systems at the centers of the shaft's cross-sections, leading to both transverse and torsional loading. Although shearing stresses from transverse loads are typically smaller than those from torques and are often overlooked, the significant normal stresses from these loads...
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In analyzing a thin-walled hollow shaft subjected to torsional loading, a segment with width dx is isolated for examination. Despite its equilibrium state, this segment faces torsional shearing forces at its ends. These forces are quantitatively described by the product of the longitudinal shearing stress on the segment's minor surface and the area of this surface, leading to the concept of shear flow. This shear flow is consistent throughout the structure, indicating a uniform distribution...
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In materials that exhibit elastic and plastic behavior, known as elastoplastic materials, residual stresses can accumulate when these materials experience plastic deformation. This deformation arises from either high levels of shearing stress or significant strains. Residual stresses are internal stresses that persist within a material after removing the external force causing deformation. This phenomenon is demonstrated when observing the behavior of a shaft under torque; notably, the...
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Journal bearings are mechanical components that support and provide lateral stability to rotating shafts and axles. They are crucial in reducing friction, wear, and vibration in machinery such as engines, turbines, and pumps. The principle behind journal bearings is forming a thin lubricant film between the bearing surface and the rotating shaft, which minimizes direct contact and reduces frictional forces.
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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Rolling Bearing Composite Fault Diagnosis Method Based on Enhanced Harmonic Vector Analysis.

Jiantao Lu1, Qitao Yin1, Shunming Li1,2

  • 1College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

Sensors (Basel, Switzerland)
|June 10, 2023
PubMed
Summary

An enhanced harmonic vector analysis (EHVA) method effectively diagnoses composite faults in rolling bearings by separating overlapping fault signals. This technique improves accuracy and efficiency in identifying bearing defects.

Keywords:
convolution blind source separationfault diagnosisharmonic vector analysisrolling bearing

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Area of Science:

  • Mechanical Engineering
  • Signal Processing
  • Condition Monitoring

Background:

  • Composite fault diagnosis in rolling bearings is challenging due to overlapping characteristic frequencies.
  • Accurate identification of individual fault signatures within composite signals is crucial for effective maintenance.

Purpose of the Study:

  • To propose an Enhanced Harmonic Vector Analysis (EHVA) method for composite fault diagnosis in rolling bearings.
  • To improve the accuracy and efficiency of separating and identifying individual fault signals from complex vibration data.

Main Methods:

  • Wavelet Threshold (WT) denoising to reduce noise in vibration signals.
  • Harmonic Vector Analysis (HVA) with cepstrum thresholding and Wiener-like masking for blind signal separation.
  • Backward projection for frequency scale alignment and Kurtogram analysis for fault characteristic enhancement.

Main Results:

  • The EHVA method successfully separated individual fault signals from composite rolling bearing fault signals.
  • EHVA demonstrated improved separation accuracy and enhanced fault characteristics compared to traditional HVA, FICA, and FMBD.
  • Semi-physical simulation experiments validated the effectiveness of the EHVA method.

Conclusions:

  • The proposed EHVA method is effective for composite fault diagnosis in rolling bearings.
  • EHVA offers superior performance in terms of accuracy and efficiency for bearing fault analysis.
  • This method provides a robust solution for complex machinery condition monitoring.