A review on machinery diagnostics and prognostics implementing condition-based maintenance

Artificial intelligence for fault diagnosis of rotating machinery: A review

Vibration of cracked structures: A state of the art review

Recent advances in time–frequency analysis methods for machinery fault diagnosis: A review with application examples

Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods

In the dynamic analysis of rotors supported on journal bearings, Reynolds equation is solved at each time step. In the present work, Reynolds equation is solved using pseudospectral method to estimate fluid film forces. Fluid pressure is approximated by a finite number of Chebyshev polynomials along the bearing length and Fourier series along the bearing circumference. Fluid domain is reduced to a finite set of algebraic equations with pressure at specific grid points as variables using collocation method. Unlike in finite element method (FEM), spectral method uses higher order global basis functions which guarantee high accuracy and lower computational time. A comparison study of fluid film forces for a bearing geometry with an L/D ratio of 0.25 with short bearing theory, solution of Reynolds equation using FEM and pseudospectral method (PSM) is presented. Two different elements are studied in FEM: 3 node triangular element and 9 node quadrilateral element. Computational time taken for one time pressure calculation is also compared. Pseudospectral method is found to be efficient than FEM for a converged solution.

Dynamic Analysis of Rotors Supported on Journal Bearings by Solving Reynolds Equation Using Pseudospectral Method


 Rotating machinery components like shafts subjected to continuous fluctuating loads are prone to fatigue cracks. Fatigue cracks are severe threat to the integrity of rotating machinery. Therefore it is indispensable for early diagnostics of fatigue cracks in shaft to avoid catastrophic failures. From the literature, it is evident that the spectral kurtosis (SK) and fast kurtogram were used to detect the faults in bearings and gears. The present study illustrates the use of SK and fast kurtogram for early fatigue crack detection in the shaft using vibration data. To perform this study, experiments are conducted on a rotor test rig which is designed and developed according to the function specification proposed by ASTM E468-11 standard. Fatigue crack is developed, on three shaft specimens, each seeded with the same circumferential V-Notch configuration, by continuous application of stochastic loads on the shaft using electrodynamic shaker in addition to the unbalance forces that arise in normal operating conditions. Vibration data is acquired from various locations of the rotor, using different sensors like miniature accelerometers, laser vibrometer and wireless telemetry strain gauge, till the shaft specimen develops fatigue crack. The analysis results show that the combination of SK and fast kurtogram is an effective signal processing technique for detecting the fatigue crack in the shaft.

Diagnostics of Fatigue Crack in the Shaft Using Spectral Kurtosis

Rotating shafts operating under complex loading conditions are susceptible to develop fatigue cracks at the localized stress concentration points. Fatigue cracks are the prime sources for catastrophic failures. Therefore, it is vital and challenging for the early fatigue crack detection to prevent costly machinery breakdowns. A rotor test rig with a facility of introducing stochastic loads on to the rotating shaft is designed and developed to induce fatigue crack on the shaft is utilized for this study. Accelerated fatigue tests are performed, along by introducing stochastic loads, on a shaft specimen seeded with circumferential V-notch configuration. The methodology for early crack detection is based on analyzing the steady-state vibration data acquired, till the shaft specimen develops fatigue crack, from various locations of the test rig using different sensors like miniature accelerometers, wireless telemetry strain gauge, and laser vibrometer. In the present study, signal processing tools like continuous wavelet transforms (CWT), Hilbert–Huang transform (HHT), and short-time Fourier transform (STFT) are employed for the early fatigue crack detection. Wavelet packet (WP) analysis is used to decompose the experimental vibration response data into narrow frequency band signals before the processing of CWT, HHT, and STFT analyses. In addition, these techniques are compared to evaluate their detection performance when employed directly on raw data and preprocessed data using WP analysis. Finally, this paper provides a detailed description and comprehensive selection of time-frequency techniques for the early fatigue crack detection.

Detection of Fatigue Crack in the Shaft Using Time-Frequency Analysis

This paper studies the dynamic analysis and characterization of two-stage planetary gear transmission system for wind turbine drive train under random loads. Rigid multi body dynamics with discrete flexibility is used for modeling the wind turbine drive train. Variable gear mesh stiffness, bearings and shaft stiffness are accounted in this model. The derivation of the system governing equation by Lagrange approach requires the formulation of kinetic and potential energies. The coupled torsional and bending model of 22 degrees of freedom is solved for vibration responses in time domain using Newmark time algorithm. Applying the Fast Fourier Transformation (FFT) on a time signal, vibration responses in frequency domain are obtained and further studied for wind turbine drive train characteristics. To identify the wind characteristics at low frequencies, wavelet decomposition is used.

Dynamic analysis and characterization of two stage epicyclic gear box in wind turbine drive train

Active magnetic bearings (AMB’s) are used to support rotors using magnetic forces, without any solid to solid contact. The AMB system has four main components: power amplifier, electromagnetic actuator, sensor and controller. In this work, the characterization of power amplifier for the AMB system is undertaken. The gain and phase lag of the power amplifiers over the operating frequency is obtained experimentally. Equivalent circuit models are made for the power amplifier. These characteristics of the amplifiers are used in developing the control algorithm for the AMB. The experimental results of these characterizations will help in understanding the gain of the power amplifier and also the lag between the signal input and the output signal over the desired frequency range.

A. S. Sekhar

Papers

Dynamic Analysis of Rotors Supported on Journal Bearings by Solving Reynolds Equation Using Pseudospectral Method

Diagnostics of Fatigue Crack in the Shaft Using Spectral Kurtosis

Detection of Fatigue Crack in the Shaft Using Time-Frequency Analysis

Dynamic analysis and characterization of two stage epicyclic gear box in wind turbine drive train

Characterization of Digital Power Amplifier-Based Active Magnetic Bearings