Application Of Vibration Analysis Research Articles

Design and Analysis of Optomechanical Micro-Gyroscope for Angular-Vibration Detection

Micro-gyroscopes based on the Coriolis principle are widely employed in inertial navigation, motion control, and vibration analysis applications. Conventional micro-gyroscopes often exhibit limitations, including elevated noise levels and suboptimal performance metrics. Conversely, the advent of cavity optomechanical system technology heralds an innovative approach to micro-gyroscope development. This method enhances the device’s capabilities, offering elevated sensitivity, augmented precision, and superior resolution. This paper presents our main contributions which include a novel dual-frame optomechanical gyroscope, a unique photonic crystal cavity design, and advanced numerical simulation and optimization methods. The proposed design utilizes an optical cavity formed between dual oscillating frames, whereby input rotation induces a measurable phase shift via optomechanical coupling. Actuation of the frames is achieved electrostatically via an interdigitated comb-drive design. Through theoretical modeling based on cavity optomechanics and finite element simulation, the operating principle and performance parameters are evaluated in detail. The results indicate an expected angular rate sensitivity of 22.8 mV/°/s and an angle random walk of 7.1 × 10−5 °/h1/2, representing superior precision to existing micro-electromechanical systems gyroscopes of comparable scale. Detailed analysis of the optomechanical transduction mechanism suggests this dual-frame approach could enable angular vibration detection with resolution exceeding state-of-the-art solutions.

Improved frequency-domain Spectral Element Method for vibration analysis of nonuniform pipe conveying fluid

The well-known Spectral Element Method (SEM) has a broad application in vibration analysis for various configurations, such as flat plates, beams and straight pipes. Considering the fluid–structure coupling effects in variable cross-section, it has one limitation in dealing with the nonuniform pipes conveying fluid. In the present work, an improved frequency-domain SEM (IFSEM) is proposed for the analysis of the nonuniform fluid-conveying pipes by introducing structural wave propagation. In the IFSEM, the wave propagation coefficient plays a critical role to construct the equivalent dynamic stiffness, improving the analysis accuracy and efficiency. And there is a rule that the propagation coefficients are mainly related to the pipe diameter, flow rate and hydrodynamic pressure. A Simplification is put forward to obtain these coefficients in advance, which can significantly facilitate the vibration analysis. Finally, the IFSEM is validated through several numerical examples and the results show that it can analyze the vibration of the liquid-conveying nonuniform pipes efficiently and accurately.

Application of vibration analysis using time-frequency analysis to detect and predict mechanical failure during the nut manufacturing process

The nut manufacturing machine operates almost continuously throughout the day and, consequently, requires frequent maintenance, the duration of which depends on the type of fault. Unpredicted downtime can cause loss of production volume, inability to meet critical timelines, and product quality degradation. Vibration research was conducted on a six-die nut manufacturing machine, which experienced frequent faults on the fourth and sixth dies that exerted the greatest impact on the nut material. The application of several analytical techniques on vibration data – the fast Fourier Transform, Empirical Mode Decomposition, Multiscale Entropy, Shock Response Spectrum, and correlation – enabled the identification of fault indicators, which would be useful for predictive maintenance. These features were detectable up to 8 h 28 min and up to 1 h 9 min prior to failure or deterioration resulting from severe and regular damage, respectively. Faults included quality deterioration and die and non-die breakage, fusion, bending and cracking. This research can optimise machine efficiency through timely upkeep facilitated by predictive maintenance.

Probabilistic learning for modeling and quantifying model‐form uncertainties in nonlinear computational mechanics

SummaryRecently, a novel nonparametric probabilistic method for modeling and quantifying model‐form uncertainties in nonlinear computational mechanics was proposed. Its potential was demonstrated through several uncertainty quantification (UQ) applications in vibration analysis and nonlinear computational structural dynamics. This method, which relies on projection‐based model order reduction to achieve computational feasibility, exhibits a vector‐valued hyperparameter in the probability model of the random reduced‐order basis and associated stochastic projection‐based reduced‐order model. It identifies this hyperparameter by formulating a statistical inverse problem, grounded in target quantities of interest, and solving the corresponding nonconvex optimization problem. For many practical applications, however, this identification approach is computationally intensive. For this reason, this paper presents a faster predictor‐corrector approach for determining the appropriate value of the vector‐valued hyperparameter that is based on a probabilistic learning on manifolds. It also demonstrates the computational advantages of this alternative identification approach through the UQ of two three‐dimensional nonlinear structural dynamics problems associated with two different configurations of a microelectromechanical systems device.

Vibration Analysis for Monitoring of Ancient Tie-Rods

This paper presents an application of vibration analysis to the monitoring of tie-rods. An algorithm for the axial load estimation based on experimentally measured natural frequencies is introduced and its application to a case study is reported. The proposed model of a tie-rod incorporates elastic bed-type boundary conditions that represent the contact between stonework and the tie-rod. The weighed differences between experimentally and numerically determined frequencies are minimized with respect to the parameters of the model, the main being the axial load and the stiffness at the tie-rod/wall interface. Thus, the multidimensional optimization problem is solved. Results are analysed in comparison to a model with simple fixed-end boundary conditions. In addition, the analytical formulation of the problem is delivered.

The contact mode of a joint interface based on improved deep neural networks and its application in vibration analysis

The precision of the contact model for a joint interface strongly depends on the fractal dimension and fractal roughness coefficient. In this paper, an improved deep neural network method was adopted to predict the surface appearance parameters. In order to meet the high accuracy requirements for the prediction results of the contact model, a novel surface appearance prediction model was established utilizing a regularized deep belief network. The Bayesian regularization strategy was used to reduce the network weights during unsupervised training, which can effectively restrain the contribution of unimportant neurons. This allows to limit the occurrence of overfitting, and the layer-by-layer training was performed for each hidden layer based on a continuous transfer function. Meanwhile, the surface appearance parameters of the joint interface could be obtained by plugging arbitrary machining parameters into the training model. The specific contact model was then established based on fractal theory by applying the above-mentioned prediction results. The parameters of the joint interface were used to simulate the frequencies and vibration modes of frame-shaped structural parts. The contact model was validated by comparing the simulation results with experimental data. The proposed model is expected to provide a theoretical basis for optimizing the structure and improving the accuracy of computerized numerical control machines.

Quantitative evaluation on the performance and feature enhancement of stochastic resonance for bearing fault diagnosis

Stochastic resonance (SR) has been widely applied in the field of weak signal detection by virtue of its characteristic of utilizing noise to amplify useful signal instead of eliminating noise in nonlinear dynamical systems. How to quantitatively evaluate the performance of SR, including the enhancement effect and the degree of waveform distortion, and how to accurately extract signal amplitude have become two important issues in the research on SR. In this paper, the signal-to-noise ratio (SNR) of the main component to the residual in the SR output is constructed to quantitatively measure the enhancement effect of the SR method. And two indices are constructed to quantitatively measure the degree of waveform distortion of the SR output, including the correlation coefficient between the main component in the SR output and the original signal, and the zero-crossing ratio. These quantitative indices are combined to provide a comprehensive quantitative index for adaptive parameter selection of the SR method, and eventually the adaptive SR method can be effective in enhancing the weak component hidden in the original signal. Fast Fourier Transform and Fourier Transform (FFT+FT) spectrum correction technology can extract the signal amplitude from the original signal and effectively reduce the difficulty of extracting signal amplitude from the distorted resonance output. The application in vibration analysis for bearing fault diagnosis verifies that the proposed quantitative evaluation method for adaptive SR can effectively detect weak fault feature of the vibration signal during the incipient stage of bearing fault.

Operational modal analysis on a pump operating at varying speeds: an industrial history case

Industrial hydraulic pumps are complex structures on which vibrations can be harmful for reliability, fatigue of components and productivity. The application of vibration analysis and diagnosis on a huge water treatment pump at the City of Montreal’s facility is presented in this paper. By using a Short Time Auto-Regressive (STAR) method combined with a modal test, it is seen that the dynamic properties and behavior of the pump included both rotating and fixed structures can be evaluated from the experimental analysis on the vibration measurement signal during its normal working condition. Natural frequencies, damping ratios and rotating speed can be clearly identified and monitored. It is shown that the analysis and diagnosis from operational vibration measurement is a very effective technique for the assessment of the huge machines in real working condition.

Application of vibration analysis of mining shovels for diggability assessment in open-pit operations

Over the past decades, technological advances and mining requirements have led to larger, more complex and more costly equipment. This trend in mining equipment has resulted in changing maintenance strategies from unplanned and scheduled maintenance to a condition-based maintenance (CBM) strategy. However, condition monitoring techniques used in CBM programmes are more than a maintenance management tool; they can provide the means to improve machine performance, production capacity and overall mine production. Vibration monitoring is usually the dominant technique of CBM programmes for critical machines such as electric rope shovels. It has been demonstrated that abnormal machine behaviour can be diagnosed using vibration monitoring techniques. However, this article aims to show the applicability of vibration monitoring of electric rope shovels for post-blast assessment rather than maintenance management. As a result, an electric rope shovel’s vibrations experienced by its boom during different operating conditions are measured by a tri-axial accelerometer mounted inside an enclosure on the side of shovel’s boom. The results show that the amount of apparent energy experienced by the tri-axial accelerometer can be used as an indirect measure of muck-pile digging conditions. Additionally, instantaneous and/or averaged vibration can be used as part of a system to monitor operator performance which potentially leads towards a machine with higher reliability, availability and maintainability and with higher productivity.

Research on Fault Diagnosis of Ship Stern Bearing Based on Vibration Analysis

The application of vibration analysis in fault diagnosis of rotary machine becomes more and more popular. Aiming at an abnormal high frequency vibration of a stern bearing, this paper proposed a method of fault diagnosis based on the analysis of vibration characteristics and the spectral analysis. From the gathered vibration data of a stern shaft bench through Pulse Vibration Analysis Platform, using the speed spectrum array to determine the characteristics of vibration source, with the analysis of vibration characteristics of the bench, it concluded that the abnormal high frequency vibration source of the stern bearing is a weak rigidity part of bench─ tacho-torque meter. The vibration data of again test after strengthening the part illustrated the validity of this diagnostic mode.

Adaptive harmonic wavelet transform with applications in vibration analysis

An adaptive harmonic wavelet transform is developed by taking advantage of the flexibility of the generalized harmonic wavelets. It first constructs a partition tree, which contains a great number of disjoint partitions of the frequency axis of a signal with each corresponding to an orthogonal harmonic wavelet basis. Then it searches the tree for the partition to represent the signal most sparsely. Since the corresponding basis is adapted to the composition of the signal, the transform can well reveal its characteristics. This is demonstrated with analysis examples of some simulated and vibration signals as well as comparisons with the conventional orthogonal harmonic wavelet transforms and wavelet packet transform.

A COMPARATIVE STUDY OF HIGH-ACCURACY FREQUENCY ESTIMATION METHODS

This paper presents a comparative study of three high-accuracy frequency estimation methods for application in vibration analysis of rotating machinery. The first two techniques are non-parametric methods based on the fast Fourier transform (FFT) : the interpolated fast Fourier transform (IFFT) and the iterative weighted phase averager (IWPA). The third method is a parametric high-resolution technique known as ESPRIT. The FFT-based methods combine techniques to reduce the effects of windowing with an iterative procedure which, at each iteration, detects the strongest peak and subtracts its effect (to reduce the interference resulting from spectral leakage). The paper compares their variance, resolution and computational requirements by means of simulation examples and also using end winding vibration data taken from a hydroelectric turbogenerator. It is found that, in situations with a moderate or high level of spectral interference, the IWPA method outperforms the IFFT and is even competitive with ESPRIT. Moreover, the IWPA has the ability to separate sinusoids more closely spaced than the periodogram's resolution limit. The IFFT method, on the other hand, has the lowest computational cost.

EXCITATION OF VIBRO-IMPACT SYSTEMS BY PERIODIC IMPULSES

Linear mechanical systems with periodic impulse excitation are related to the classical area of dynamical analysis. The exact solutions obtained played an important role in mathematics and had numerous applications in vibration analysis and machine dynamics. The introduction of non-linear factors into the excited models makes integration impossible and generally involves the use of various difficult estimated approximations. However, it is shown here that for one important class of strongly non-linear mechanical systems, vibro-impact systems, it is possible to produce an exact steady state solution of the problem of periodic impulse excitation by the use of the periodic Green function method. These solutions can be applied to the analysis of impulse transformations in percussion machines, non-linear mechanical structures and in systems of vibration protection.

Aging Characterization of Adhesives and Bonded Joints by Non-Destructive Damping Measurements

Long term performance of adhesive joints in various environments is the main concern of bonding technology in both military and civil applications. Joint strength can be greatly degraded by aging. Periodic non-destructive strength evaluation of bonded devices is, thus, a critical necessity for quality assurance. Developing a tool for non-destructive testing of joint strength in bonded devices is the long-term goal of the present study. The method revealed here is application of vibration analysis, concentrating on the damping behavior of the tested object. Contrary to other non-destructive evaluation methods, which indicate only the presence of defects, this method is sensitive mainly to the material properties, thus can assess material degradation. In this case, the property of interest is the strength. In stage 1 of this research (Shiloh et al., 1996) it was shown that aging of adhesives and bonded joints can be evaluated non-destructively by vibration analysis, based on the internal friction (damping) effect. Good correlation between the specific damping capacity (SDC) and the shear strength of bonded joints was determined. In stage 2 (Shiloh et al., 1998), an additional step towards the target application was achieved, by broadening the range of the tested specimen. Additional adhesives and adherends as well as various geometries and sizes of the bonded joints were tested. The effect of the following factors was established: adhesive aging or shear strength, adherends, temperature, sample size [up to diameter of 356 mm (14")] and sample shapes (flats and rings). The results show that the method is most promising. For more reliable wide-ranging guidelines, theoretical analysis by numerical simulation of vibrational stresses is required.

Aging Characterization of Adhesives and Bonded Joints by Non-Destructive Damping Measurements

Long term performance of adhesive joints in various environments is the main concern of bonding technology in both military and civil applications. Joint strength can be greatly degraded by aging. Periodic non-destructive strength evaluation of bonded devices is, thus, a critical necessity for quality assurance. Developing a tool for non-destructive testing of joint strength in bonded devices is the long-term goal of the present study.The method revealed here is application of vibration analysis, concentrating on the damping behavior of the tested object. Contrary to other non-destructive evaluation methods, which indicate only the presence of defects, this method is sensitive mainly to the material properties, thus can assess material degradation. In this case, the property of interest is the strength.In stage 1 of this research (Shiloh et al., 1996) it was shown that aging of adhesives and bonded joints can be evaluated non-destructively by vibration analysis, based on the internal friction (damping) effect. Good correlation between the specific damping capacity (SDC) and the shear strength of bonded joints was determined.In stage 2 (Shiloh et al., 1998), an additional step towards the target application was achieved, by broadening the range of the tested specimen. Additional adhesives and adherends as well as various geometries and sizes of the bonded joints were tested. The effect of the following factors was established: adhesive aging or shear strength, adherends, temperature, sample size [up to diameter of 356 mm (14")] and sample shapes (flats and rings).The results show that the method is most promising. For more reliable wide-ranging guidelines, theoretical analysis by numerical simulation of vibrational stresses is required.

Using holographic interferometry in vibration measurements

This paper will review principles of holographic interferometry and provide examples of current applications in vibration analysis. Specific techniques discussed will include double exposure (frozen fringe), real time, and stroboscopic and time‐average holographic interferometry.