Multistage noise reduction processing for vibration signal of hydropower units

In actual field testing environments of hydropower units, unit vibration signals are often contaminated with noise. In order to obtain the real vibration signal, a multi-stage vibration signal denoise method SG-SVD-VMD is proposed for the guide bearing nonlinear and non-stationary vibration signals. And the root mean square error (RMSE) and signal to noise ratio (SNR) are used to evaluate the noise reduction ability of eight methods. The results show that the noise-canceling ability of this proposed method has improved to some extent. It can effectively suppress the noise of the hydropower units vibration signals. This method can effectively identify the shaft track and the running state of hydropower units.

Application of multi-layer denoising based on ensemble empirical mode decomposition in extraction of fault feature of rotating machinery

Aiming at the problem that the weak features of non-stationary vibration signals are difficult to extract under strong background noise, a multi-layer noise reduction method based on ensemble empirical mode decomposition (EEMD) is proposed. First, the original vibration signal is decomposed by EEMD, and the main intrinsic modal components (IMF) are selected using comprehensive evaluation indicators; the second layer of filtering uses wavelet threshold denoising (WTD) to process the main IMF components. Finally, the virtual noise channel is introduced, and FastICA is used to de-noise and unmix the IMF components processed by the WTD. Next, perform spectral analysis on the separated useful signals to highlight the fault frequency. The feasibility of the proposed method is verified by simulation, and it is applied to the extraction of weak signals of faulty bearings and worn polycrystalline diamond compact bits. The analysis of vibration signals shows that this method can efficiently extract weak fault characteristic information of rotating machinery.

Dynamic Modelling, Experimental Identification and Computer Simulations of Non-Stationary Vibration in High-Speed Elevators

Modelling the dynamic behaviour of elevators with high lifting velocities (contemporary elevators in building construction and mine elevators) is a complex task and an important step in the design process and creating conditions for safe and reliable exploitation of these machines. Due to high heights and lifting velocities, the standard procedures for dynamic exploitation are not adequate. The study presents the method of forming a dynamic model to analyse nonstationary vibrations of a rope with time-varying length with nonholonomic boundary conditions in the position where the rope is connected with the cabin (cage) and in the upcoming point of its winding onto the pulley (drum). A unique method was applied to identify the basic parameters of the dynamic model (stiffness and damping) based on experimental measures for a concrete elevator. Due to the verification of this procedure, the experiment was conducted on a mine elevator in RTB Bor, Serbia. Using the obtained computer-experimental results, the simulations of the dynamic behaviour of an empty and loaded cage were shown. In addition, the study shows the specific method as the basis for forming a control program that would enable the decrease in vertical vibrations during an elevator starting and braking mode.

Operational Modal Analysis for Vibration Control Following Moving Window Locality Preserving Projections for Linear Slow-Time-Varying Structures

Modal parameters can reflect the dynamic characteristics of the structure and can be used to control vibration. To identify the operational modal parameters of linear slow-time-varying structures only from non-stationary vibration response signals, a method based on moving window locality preserving projections (MWLPP) algorithm is proposed. Based on the theory of “time freeze”, the method selects a fixed length window and takes the displacement response signal in each window as a stationary random sequence. The locality preserving projections algorithm is used to identify the transient modal frequency and modal shape of the structure at this window. The low-dimensional embedding of the displacement response data set calculated by locality preserving projections (LPP) corresponds to the modal coordinate response matrix, and the transformation matrix corresponds to the modal shape matrix. The simulation results of the mass slow-time-varying three degree of freedom (DOF) and the density slow-time-varying cantilever beam show that the new method can effectively identify the modal shape and modal natural frequency of the linear slow-time-varying only from the non-stationary vibration response signal, and the performance is better than the moving window principal component analysis (MWPCA).

Detection of Induction Motor Improper Bearing Lubrication by Discrete Wavelet Transforms (DWT) Decomposition

The present paper deals with healthy and improper bearing lubrication signals analysis using Discrete Wavelet Transform (DWT) enhanced by MATLAB/ Wavelets toolbox analysis. The identification of bearing faults from the time or the frequency domain are difficult due to non stationary vibration signal. Therefore, for more accurate faults information and identification of bearing with lubrication defects (improper or absence of lubrication), the DWT is used. The validation of this procedure is conducted by an experimental setup designed for vibration signal acquisition and the complete analysis is finalized by MATLAB/ Wavelets toolbox. The recorded data used for the validation are the signals of healthy and un-lubricated bearing driven at a rotation speed of 1500 rpm by 0.78 KW three phase induction motor. From the obtained results it can be observed that, for medium speeds DWT decomposition enhanced by MATLAB Wavelets Toolbox procedure is efficient for improper lubricated bearing related faults diagnosis and detection.