Showing papers in "Shock and Vibration in 2019"
TL;DR: A novel hierarchical algorithm based on stacked LSTM (long short-term memory) is proposed in this text, which can not only achieve up to 99% accuracy but also outperform some state-of-the-art intelligent fault diagnosis methods.
Abstract: Faced with severe operating conditions, rolling bearings tend to be one of the most vulnerable components in mechanical systems. Due to the requirements of economic efficiency and reliability, effective fault diagnosis methods for rolling bearings have long been a hot research topic of rotary machinery fields. However, traditional methods such as support vector machine (SVM) and backpropagation neural network (BP-NN) which are composed of shallow structures trap into a dilemma when further improving their accuracies. Aiming to overcome shortcomings of shallow structures, a novel hierarchical algorithm based on stacked LSTM (long short-term memory) is proposed in this text. Without any preprocessing operation or manual feature extraction, the proposed method constructs a framework of end-to-end fault diagnosis system for rolling bearings. Beneficial from the memorize-forget mechanism of LSTM, features inherent in raw temporal signals are extracted hierarchically and automatically by stacking LSTM. A series of experiments demonstrate that the proposed model can not only achieve up to 99% accuracy but also outperform some state-of-the-art intelligent fault diagnosis methods.
76 citations
TL;DR: In this paper, a vibration test bench was established to examine the vibration and stability of a cantilever multistage centrifugal pump under different flow rates, and the vibration spectrum diagrams for the inlet and outlet sections and the pump body were evaluated under varied flow conditions.
Abstract: Multistage pumps are intended to improve designs with low-vibration and -noise features as the industry applications increase the technical requirements. In this frame, it becomes really important to fully understand the vibration patterns of these kinds of complex machines. In this study, a vibration test bench was established to examine the vibration and stability of a cantilever multistage centrifugal pump under different flow rates. The vibration spectrum diagrams for the inlet and outlet sections and the pump body were evaluated under varied flow conditions. Results showed the effects of operational conditions on the vibration of the cantilever multistage centrifugal pump. Vibration velocity was primarily caused by mass unbalance at the shut-off flow rate point. Under different flow conditions, the blade passing frequency (BPF) and two times the blade passing frequency (2BPF) were the main excitation frequencies. The vibration frequency of the final pump body remained at the BPF under different flow conditions due to the contact with the outlet section. The major type of vibration frequency for the inlet and outlet was high frequency.
64 citations
TL;DR: In this paper, the authors applied loess samples to analyze controlling effects of residual deformation on pore pressure based on three kinds of laboratory tests and obtained the similarity and difference of mechanical behaviors of soil samples under different water contents and loading.
Abstract: What the role of each phase medium plays and how their interactions do work should be essential problems to understand dynamic behaviours of soils. In order to disclose interactions between solid, water, and air phases of soils, we applied loess samples to analyse controlling effects of residual deformation on pore pressure based on three kinds of laboratory tests. We obtained the similarity and difference of mechanical behaviors of soil samples under different water contents and loading. Both process and cause of pore air/water pressures are independent of initial stress conditions or loadings. However, absolute values of pore water pressure depend on the confining pressure, whereas the pore air pressure is contrary. The uniformity of responding process and cause of pore pressure depend upon the interaction mechanism between solid particles and air/water media, but the different absolute values depend upon the permeability and compressibility of air/water.
47 citations
TL;DR: A novel deep CNN-based approach for structural damage location and quantification, which operates on images generated from the structure's transmissibility functions to exploit the CNNs’ image processing capabilities and to automatically extract and select relevant features to the structure’s degradation process.
Abstract: Damage diagnosis has become a valuable tool for asset management, enhanced by advances in sensor technologies that allows for system monitoring and providing massive amount of data for use in health state diagnosis. However, when dealing with massive data, manual feature extraction is not always a suitable approach as it is labor intensive requiring the intervention of domain experts with knowledge about the relevant variables that govern the system and their impact on its degradation process. To address these challenges, convolutional neural networks (CNNs) have been recently proposed to automatically extract features that best represent a system’s degradation behavior and are a promising and powerful technique for supervised learning with recent studies having shown their advantages for feature identification, extraction, and damage quantification in machine health assessment. Here, we propose a novel deep CNN-based approach for structural damage location and quantification, which operates on images generated from the structure’s transmissibility functions to exploit the CNNs’ image processing capabilities and to automatically extract and select relevant features to the structure’s degradation process. These feature maps are fed into a multilayer perceptron to achieve damage localization and quantification. The approach is validated and exemplified by means of two case studies involving a mass-spring system and a structural beam where training data are generated from finite element models that have been calibrated on experimental data. For each case study, the models are also validated using experimental data, where results indicate that the proposed approach delivers satisfactory performance and thus being an appropriate tool for damage diagnosis.
41 citations
TL;DR: In this article, the Dizong blasting scheme was optimized by reducing the maximum single-segment charge and a variety of damping measures such as multistage duplex wedge groove, adding damping hole, and millisecond blasting.
Abstract: According to the on-site vibration velocity monitoring and peak vibration velocity prediction, it is found that the maximum vibration velocity generated by the existing Dizong blasting scheme does not meet the requirements of the maximum allowable vibration velocity of houses. Therefore, the existing blasting scheme is optimized by reducing the maximum single-segment charge and a variety of damping measures such as multistage duplex wedge groove, adding damping hole, and millisecond blasting. In addition, the blasting data before and after optimization are analyzed and compared by wavelet (packet) technology. The results show that the optimized blasting main frequency domain is increased to 50∼150 Hz and the maximum vibration intensity value is reduced by 79.8%. Based on the time-energy analysis, the maximum energy value is reduced by 67.75% compared with the original scheme, and the dominant energy of the original scheme is reduced by 97.81%, 71.49%, 82.44%, 95.93%, and 93.03%, respectively, after optimization. The maximum vibration velocity generated by the optimized blasting scheme construction is 1.12 cm/s, which is less than the maximum allowable vibration velocity of the building of 1.2 cm/s, which meets the maximum allowable vibration velocity requirements of the building. The optimized blasting scheme realizes the safe and rapid construction of the two steps of the Dizong tunnel, which can provide a reference for similar engineering construction in the future.
39 citations
TL;DR: A novel fault diagnosis framework is proposed for three-phase induction motors with a hybrid feature learning method, which combines empirical statistical parameters, recurrence quantification analysis (RQA) and long short-term memory (LSTM) neural network, which achieves the highest diagnostic accuracy in both the original dataset and the noised dataset.
Abstract: Motor fault diagnosis has gained much attention from academic research and industry to guarantee motor reliability. Generally, there exist two major approaches in the feature engineering for motor fault diagnosis: (1) traditional feature learning, which heavily depends on manual feature extraction, is often unable to discover the important underlying representations of faulty motors; (2) state-of-the-art deep learning techniques, which have somewhat improved diagnostic performance, while the intrinsic characteristics of black box and the lack of domain expertise have limited the further improvement. To cover those shortcomings, in this paper, two manual feature learning approaches are embedded into a deep learning algorithm, and thus, a novel fault diagnosis framework is proposed for three-phase induction motors with a hybrid feature learning method, which combines empirical statistical parameters, recurrence quantification analysis (RQA) and long short-term memory (LSTM) neural network. In addition, weighted batch normalization (BN), a modification of BN, is designed to evaluate the contributions of the three feature learning approaches. The proposed method was experimentally demonstrated by carrying out the tests of 8 induction motors with 8 different faulty types. Results show that compared with other popular intelligent diagnosis methods, the proposed method achieves the highest diagnostic accuracy in both the original dataset and the noised dataset. It also verifies that RQA can play a bigger role in real-world applications for its excellent performance in dealing with the noised signals.
37 citations
TL;DR: Reflecting through this review, structures including a novel flow mode and miniature bypass valves have represented the currently structural and technical features of MR dampers.
Abstract: Owing to unique advantages, magnetorheological fluid (MRF) dampers have been widely adopted in different fields of vibration control. Significant differences of structures occur in diverse fields due to the respective requirements, thus obtaining a large number of MR dampers. Having a good understanding of types, technical characteristics, comprehensive performance, and developing trend and their dependencies on structures are extremely conducive to innovative developments and a market selection. While the fundamental and partial structures are summarized in an existing review, the classification, latest technologies, and developing trend are not involved clearly. Therefore, the current survey aims at a comprehensive supplement in such aspects. The review begins with an introduction of the development, application, and classification. Then, details of three technical routes are revealed, and the development of each type is roughly analyzed. Finally, reflecting through this review, structures including a novel flow mode and miniature bypass valves have represented the currently structural and technical features. Fully considering the latest technologies and future requirements, the developing trend and a variety of applications will be anticipated.
37 citations
TL;DR: In this paper, a short cantilever beam by roof cutting method was proposed to solve the problem of roadway deformation based on the theory of "short cantilevers beam-by-roof cutting" in the adjacent roadway.
Abstract: In order to solve the problem of roadway deformation based on the theory of “short cantilever beam by roof cutting,” the method of “pressure relief by roof cutting in the adjacent roadway” is proposed. Through presplitting blasting the roadway hard rock layer, the stress propagation path is cut off, and the surrounding rock stress environment of the roadway is improved, to achieve the purpose of controlling the deformation of the roadway caused by stress. Through theoretical analysis, it is determined that the depth of the presplitting blasthole is 17 m, and the angle with the vertical direction is 10°. Based on in situ measurements and tests, by presplitting blasting the roof strata of the adjacent roadway, the maximal value of the working resistance of the hydraulic support in the presplitting blasting side of the working face decreased by 24.9%, and the average volumes of the maximum floor heave, the maximum roof subsidence, and the maximum ribs displacement were reduced by 50.1%, 34.9%, and 41.7%, respectively. This method completely changes the traditional thought patterns of “reinforcing support” to control roadway deformation from “strong support” to “pressure relief.” It provides a new idea for controlling the roadway deformation.
34 citations
TL;DR: In this paper, the authors presented an experimental methodology that is capable of sensitively detecting the cavitation inception in a centrifugal pump by measuring the bubble pattern distribution at impeller inlet, and the vibration and noise were synchronously measured at different flow conditions with several cavitation coefficients.
Abstract: This paper presents an experimental methodology that is capable of sensitively detecting the cavitation inception in a centrifugal pump. Firstly, with a centrifugal pump of as research object, the cavitation performance, the bubble pattern distribution at impeller inlet, and the vibration and noise were synchronously measured at different flow conditions each with several cavitation coefficients. The change laws of total level of vibration and noise signals throughout the cavitation process were emphatically investigated. After comparing the sensitivity and reliability of different detection methods, the method based on overall sound pressure level of liquid-borne noise is found to present high sensitivity to cavitation. Secondly, by comparing the affected 1/3 octave spectrum by changing flow and cavitation coefficients, the highly sensitive frequency band to cavitation was obtained. Then, a new inception cavitation detection method was proposed based on Pauta principle. Finally, the method was verified through an ultra-low-specific speed pump ( ). The results show that the total pressure level of liquid-borne noise increases firstly and then decreases with the development of cavitation. The broadband SPL of liquid-borne noise between 2000 and 3000 Hz can be used to detect the inception cavitation, and the cavitation detection threshold is determined as 1.0%.
29 citations
TL;DR: In this paper, the authors proposed an optimal fuzzy-PID control method for semi-active cab's hydraulic mounts based on an off-road vehicle roller dynamic model to analyze the low-frequency performance of semiactive cab hydraulic mounts under the different operating conditions.
Abstract: To improve the ride comfort of the off-road vibratory roller, the cab’s hydraulic mounts were analyzed to prevent vibration sources transmitting to the cab. However, the cab’s low-frequency shaking in the vertical direction and the direction of forward motion is still great. This study proposes an optimal fuzzy-PID control method for semi-active cab’s hydraulic mounts based on an off-road vehicle roller dynamic model to analyze the low-frequency performance of semi-active cab’s hydraulic mounts under the different operating conditions. In order to evaluate the ride comfort of the off-road vibratory roller with semi-active cab’s hydraulic mounts, the power spectral density (PSD) and the weighted root mean square (RMS) of acceleration responses of the vertical driver’s seat, cab’s pitch, and roll vibrations in the low-frequency range are chosen as objective functions. Contrastive analysis of low-frequency vibration characteristics of the off-road vibratory roller with passive cab’s hydraulic mounts, semi-active cab’s hydraulic mounts without optimization, and semi-active cab’s hydraulic mounts with optimization is, respectively, carried out. The research results show that the semi-active cab’s hydraulic mounts with optimization have an obvious effect on mitigating the cab shaking and improving the ride comfort in comparison with passive cab’s hydraulic mounts and semi-active cab’s hydraulic mounts without optimization.
29 citations
TL;DR: A new methodology for simultaneous optimization of parameters and positions of multiple tuned mass dampers (MTMDs) in buildings subjected to earthquakes is proposed and it is believed that the proposed methodology can be used as a promising tool for MTMD design.
Abstract: Passive energy devices are well known due to their performance for vibration control in buildings subjected to dynamic excitations. Tuned mass damper (TMD) is one of the oldest passive devices, and it has been very much used for vibration control in buildings around the world. However, the best parameters in terms of stiffness and damping and the best position of the TMD to be installed in the structure are an area that has been studied in recent years, seeking optimal designs of such device for attenuation of structural dynamic response. Thus, in this work, a new methodology for simultaneous optimization of parameters and positions of multiple tuned mass dampers (MTMDs) in buildings subjected to earthquakes is proposed. It is important to highlight that the proposed optimization methodology considers uncertainties present in the structural parameters, in the dynamic load, and also in the MTMD design with the aim of obtaining a robust design; that is, a MTMD design that is not sensitive to the variations of the parameters involved in the dynamic behavior of the structure. For illustration purposes, the proposed methodology is applied in a 10-story building, confirming its effectiveness. Thus, it is believed that the proposed methodology can be used as a promising tool for MTMD design.
TL;DR: The decision-level sensor fusion based on the Sugeno fuzzy integral was proposed to integrate the vibration and current information to improve the accuracy of the diagnosis of induction machines.
Abstract: Induction machines are widely used in the industry as one of the major actuators, such as water pumps, air compressors, and fans. It is necessary to monitor and diagnose these induction motors to prevent any sudden shut downs caused by premature failures. Numerous fault detection and isolation techniques for the diagnosis of induction machines have been proposed over the past few decades. Among these techniques, motor current signature analysis (MCSA) and vibration analysis are two of the most common signal-based condition monitoring methods. They are often adopted independently, but each method has its strengths and weaknesses. This research proposed a systemic method to integrate the information received from the vibration and current measurements. We applied the wavelet packet decomposition to extract the time-frequency features of the vibration and current measurements and used the support vector machines as classifiers for the initial decision-making. The significant features were identified, and the performances of several classifiers were compared. As a result, the decision-level sensor fusion based on the Sugeno fuzzy integral was proposed to integrate the vibration and current information to improve the accuracy of the diagnosis.
TL;DR: In this paper, the effects of several stone pebble layer parameters (the layer thickness, the fraction of pebbles, the peak ground acceleration (PGA), the pebblite compaction, the pebbble moisture, the vertical contact stress below the foundation, and the effect of repeated excitations) on layer aseismic efficiency were investigated using a shake table.
Abstract: Using a shake-table, the effects of several stone pebble layer parameters (the layer thickness, the fraction of pebbles, the pebble compaction, the pebble moisture, the vertical contact stress below the foundation, and the effect of repeated excitations) on layer aseismic efficiency were investigated. For each considered parameter, a model of a rigid building on an aseismic layer was exposed to four different accelerograms, with three levels of peak ground acceleration (PGA), while all other layer parameters were kept constant. For each test, the characteristic displacements and accelerations were measured. Based on the test results, the main conclusions regarding the effect of the considered parameters on the effectiveness of the adopted aseismic layer are given.
TL;DR: In this paper, the authors discuss the development of the methods in microseismic/acoustic emission (AE) source localization and detail the principles of the mainly developed methods.
Abstract: The purpose of this review is to discuss the development of the methods in microseismic/acoustic emission (AE) source localization and detail the principles of the mainly developed methods. The important applications of the microseismic/AE in engineering practice and the history of the source localization (from the initial Geiger method of localization to the later double-difference method) are introduced briefly in the beginning of the review. The factors that influence the accuracy of source locating are discussed in Section 2 to provide references on how to improve the accuracy of the localization methods. Then, the main localization methods in the history of the source and AE research have been classified into four parts (i.e., the localization methods for single event, the joint inversion methods, the relative localization methods, and the localization methods in spatial domain); each part is extended and systematically reviewed, respectively, from Sections 3 to 6, where the merit and demerit of the methods are discussed. Finally, a brief summary and some aspects of prospective research are presented.
TL;DR: A new method for automatic classification of microseismic signals based on the Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) by using only Mel-frequency cepstral coefficient (MFCC) features extracted from the waveform is presented.
Abstract: In order to mitigate economic and safety risks during mine life, a microseismic monitoring system is installed in a number of underground mines. The basic step for successfully analyzing those microseismic data is the correct detection of various event types, especially the rock mass rupture events. The visual scanning process is a time-consuming task and requires experience. Therefore, here we present a new method for automatic classification of microseismic signals based on the Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) by using only Mel-frequency cepstral coefficient (MFCC) features extracted from the waveform. The detailed implementation of our proposed method is described. The performance of this method is tested by its application to microseismic events selected from the Dongguashan Copper Mine (China). A dataset that contains a representative set of different microseismic events including rock mass rupture, blasting vibration, mechanical drilling, and electromagnetic noise is collected for training and testing. The results show that our proposed method obtains an accuracy of 92.46%, which demonstrates the effectiveness of the method for automatic classification of microseismic data in underground mines.
TL;DR: Based on the traditional energy-regenerative efficiency calculation, a novel self-supply energy efficiency concept is proposed to evaluate the utilization effect of the recycled energy for this dual-functional suspension.
Abstract: In this paper, an electromagnetic energy-regenerative suspension system is proposed to achieve active control and vibration energy harvesting. For this system, a PID controller based on BP neural network algorithm is designed and vehicle dynamic performances are studied. Based on the traditional energy-regenerative efficiency calculation, a novel self-supply energy efficiency concept is proposed to evaluate the utilization effect of the recycled energy for this dual-functional suspension. Simulations are carried out, and the results show that the vehicle dynamic performances are effectively improved under different input conditions, including road surfaces and vehicle speeds. Furthermore, the energy-regenerative suspension can recover part of vibration energy, where the self-supply energy efficiency is about 55% and the energy-regenerative efficiency is about 16%. Meanwhile, the BP-PID algorithm also enables the suspension system’s self-adaptability and stability characteristics on its energy recovery capability.
TL;DR: Wang et al. as discussed by the authors explored the key factors influencing the roof-coal caving and recovery characteristics, which indicated the strength of the coal and gangue will directly affect the roof coal recovery.
Abstract: With mining technology and mechanization degree being improving, fully mechanized caving mining technology (FCM) has become a main method for thick coal seam extraction in China. However, roof-coal caving characteristics in turn restrict its recovery efficiency, especially for the coal seam with complicated structure (CCS), that is, the coal seam comprises hard or soft coal and gangue. In order to explore the key factors influencing the roof-coal caving and recovery characteristics, related research work has been conducted as follows: firstly, a mechanical model of CCS has been established, which indicates the strength of the coal and gangue will directly affect the roof-coal recovery. Meanwhile, based on the geological settings of Qinyuan coal mine, numerical simulation on roof-coal caving law under different thicknesses of hard or soft coal and gangue has been performed using UDEC software. The results show that the maximum principal stress will increase with the increase of mining depth, making the roof-coal to break easily. Furthermore, the range of the plastic zone of the top coal and the damage degree of the top coal increase with the increase of mining depth. Physical modeling results show that when an extraction-caving ratio is 1, the number of times the coal arch forms is 0.43 at every caving, up to a maximum of 3; the number of times coal arch forms with an extraction-caving ratio of 2 is 4.65 times larger than that with an extraction-caving ratio of 1. The probability of coal arch formation with an extraction-caving ratio of 3 is minimal, about 0.4, which is due to that the arch span is large and the curvature is small, so it is difficult to form a stable arch structure. According to the mechanical characteristics of roof-coal in Qinyuan coal mine, deep-hole blasting technique has been used to reduce the fragments of roof-coal crushed. The results show that this technique can effectively improve the recovery of roof-coal.
TL;DR: This study proposes a symmetrized dot pattern characteristic information fusion-based convolutional neural network (CNN) fault diagnosis method to resolve issues of high complexity, nonlinearity, and instability in original rotor vibration signals.
Abstract: This study proposes a symmetrized dot pattern (SDP) characteristic information fusion-based convolutional neural network (CNN) fault diagnosis method to resolve issues of high complexity, nonlinearity, and instability in original rotor vibration signals. The method was used to conduct information fusion of real modal components of vibration signals and SDP image identification using CNN in order to achieve vibration fault diagnosis. Compared with other graphic processing methods, the proposed method more fully expressed the characteristics of different vibration signals and thus presented variations between different vibration states in a simpler and more intuitive way. The proposed method was experimentally investigated using simulation signals and rotor test-rig signals, and its validity and advancements were demonstrated using experimental analysis. By using CNN through deep learning to adaptively extract SDP characteristic information, vibration fault identification was ultimately realized.
TL;DR: In this paper, a numerical vehicle-track coupling dynamic model based on multibody dynamics and finite element theories is established by using a self-compiling program to find the relationship between long-wavelength irregularities and vehicle dynamic responses.
Abstract: Long-wavelength track irregularities have obvious influence on ride comfort and running stability of high-speed trains. Meanwhile, it brings risk to the inspection of track irregularities since ordinary inspection equipment has difficulties in covering long wavelengths. Previous research on the effect of long-wavelength track irregularities is rare. In order to find the relationship between long-wavelength irregularities and vehicle dynamic responses, a numerical vehicle-track coupling dynamic model based on multibody dynamics and finite element theories is established by using a self-compiling program. One case study is given as an example to show the methodology of determining the sensitive long wavelength and management amplitude of track longitudinal-level irregularities in high-speed railway. The simulation results show that the sensitive long wavelength has a strong correlation with train speed and natural frequency. The simulation and field test results are in good agreement.
TL;DR: In this article, the effects of tunnel blast excavation on the adjacent existing highvoltage tower are comprehensively studied for the Chashan highway tunnel project as a case study, and a guideline for the blast safety zone is proposed based on vibration velocity, main frequency, and the quantity of explosive.
Abstract: The effects of tunnel blast excavation on the adjacent existing high-voltage tower are comprehensively studied for the Chashan highway tunnel project as a case study. To investigate the effect of blast-induced vibration from the tunnel on the adjacent existing tower, field tests and numerical simulations method were adopted to study the vibration velocity and vibration frequency of the existing tower. Moreover, the relationship between the transverse distance from the detonation center and the peak velocity is discussed in detail. The results showed that the peak velocity of the measuring point in tower foundation increases with the distance between the detonation center and tower foundation approaches, and the maximum velocity is appearing when detonation center is 0 m. Furthermore, the corresponding energy spectrum distributions of the existing tower under the effect of blast induced by vibration is also analyzed, and the main frequency of vertical vibration is generally higher than that of transverse vibration. On combining the peak velocity with the main frequency and the natural frequency of the tower, the safety evaluation of the blasting area is proposed, and the corresponding control measures of blasting vibration are put forward. A guideline for the blast safety zone is proposed based on vibration velocity, main frequency, and the quantity of explosive.
TL;DR: In this paper, a detailed investigation of the mechanism of metro wheel polygonal wear using on-site experiments and numerical simulation is presented, where the authors suggest that the P2 resonance is the main contributor to the high amplitude of wheel/rail contact forces in the 50-70 Hz frequency range.
Abstract: We present a detailed investigation of the mechanism of metro wheel polygonal wear using on-site experiments and numerical simulation. More than 70% of metro wheels exhibit 6th–8th harmonic-order polygonal wear; the excitation frequency of the polygonal wear is located in the 50–70 Hz interval at an operating speed of 65–75 km/h. To determine the root cause of the polygonal wear, a dynamic train behavior test is conducted immediately after wheel reprofiling. The results suggest a natural mode resonance in the vehicle/track system, whose frequency coincides with the passing frequency of the 6th–8th order polygonalization. The magnitude of the resonance increases significantly when the vehicle runs on a monolithic concrete bed with DTVI2 fasteners. Thus, a corresponding coupled vehicle/track dynamic model is established and validated by comparing the calculated frequency response functions (FRFs) of tracks and dynamic responses of axlebox acceleration with the measured values. Using multiple timescales, the dynamic model and Archard wear model are integrated in a closed loop for long-term polygonal wear prediction. The simulated and measured evolution of polygonal wear show good agreement. By combining simulation results and experimental data, we suggest that the P2 resonance is the main contributor to the high amplitude of wheel/rail contact forces in the 50–70 Hz frequency range and the reason for subsequent polygonal wear. Parametric studies show that the dominant order decreases as vehicle speeds increase, representing a “frequency-constant” mechanism. The wheelset flexibility, especially the bending mode, would aggravate the wheel/rail creepage and further accelerate the formation of polygonal wear. Higher rail pad stiffness will increase P2 resonance frequency and shift the dominant wheel to higher polygonal orders.
TL;DR: The experimental result demonstrates that fault diagnosed ability of bearing of VPS-IBPSOKNN is better than that of VS-KNN, and it can be concluded that fault diagnosis of bearing based on VPS -IBPSokNN is effective.
Abstract: Fault diagnosis of bearing based on variational mode decomposition (VMD)-phase space reconstruction (PSR)-singular value decomposition (SVD) and improved binary particle swarm optimization (IBPSO)-K-nearest neighbor (KNN) which is abbreviated as VPS-IBPSOKNN is presented in this study, among which VMD-PSR-SVD (VPS) is presented to obtain the features of the bearing vibration signal (BVS), and IBPSO is presented to select the parameter K of KNN. In IBPSO, the calculation of the next position of each particle is improved to fit the evolution of the particles. The traditional KNN with different parameter K and trained by the training samples with the features based on VMD-SVD (VS-KNN) can be used to compare with the proposed VPS-IBPSOKNN method. The experimental result demonstrates that fault diagnosis ability of bearing of VPS-IBPSOKNN is better than that of VS-KNN, and it can be concluded that fault diagnosis of bearing based on VPS-IBPSOKNN is effective.
TL;DR: In this paper, a shaking table test was performed to study the dynamic response and failure modes of high slope, and the results showed that PGA amplification coefficients increased with increasing elevation and the amplification coefficient of concave slope was slightly larger than that of convex slope.
Abstract: A shaking table test was performed to study the dynamic response and failure modes of high slope. Test results show that PGA amplification coefficients increased with increasing elevation and the PGA amplification coefficient of the concave slope was slightly larger than that of the convex slope. The slope type affected the dynamic response of the slope. The elevation amplification effect of the concave slope under seismic load was more significant than that of the convex slope; thus, the concave slope was more unstable than the convex slope. Additionally, the PGA amplification coefficient measured on the slope surface was always larger than that inside the slope, and the data show an increasing trend with the broken line. The dynamic amplification effect of the high slope was closely related to the natural frequency of the slope. Within a certain range, the higher the frequency, the more significant the amplification effect. The dynamic failure process of concave and convex slopes was studied through tests. Findings indicate that the dynamic failure modes of the concave slope are characterized by shoulder collapse, formation of the sliding surface, and integral sliding above the slope line. Dynamic failure modes of the convex slope are mainly slips in the soil layer and collapse of the slope near the slope line.
TL;DR: In this article, the effect of considering soil-structure interaction (SSI) in seismic responses of reinforced concrete (RC) chimneys installed by distributed tuned vibration absorbers vertically (d-MTVAs).
Abstract: This paper investigates the effect of considering soil-structure interaction (SSI) in seismic responses of reinforced concrete (RC) chimneys installed by distributed tuned vibration absorbers vertically (d-MTVAs). A multimode control approach is used to design the d-MTVAs. Two-dimensional (2D) RC chimney is the assembly of beam elements. Frequency-independent constants for the springs and dashpots are used for modeling the raft and the surrounding soil. The equations of motion for nonclassically damped systems are derived and solved using Newmark’s method. The effectiveness of the d-MTVAs is weighed against the case of single tuned vibration absorber (STVA), d-MTVAs suppressing the first modal responses (d-MTVAs-1), and randomly distributed MTVAs (ad-MTVAs). Additionally, parametric studies are conducted for varying mass and damping ratios in the STVA, d-MTVAs-1, ad-MTVAs, and d-MTVAs. In order to show the efficiency in the STVA, d-MTVAs-1, ad-MTVAs, and d-MTVAs cases, responses (displacement and acceleration) at top of the RC chimney while subjected to different real earthquake excitations are computed. It is concluded that the STVA, d-MTVAs-1, ad-MTVAs, and d-MTVAs are effective in response mitigation of the RC chimney; however, d-MTVAs are more efficient while considering equal total mass of the TVA(s). Moreover, the soil type significantly influenced the design parameters of the STVA/d-MTVAs-1/ad-MTVAs/d-MTVAs and seismic response of the RC chimney.
TL;DR: In this article, a novel and simple method for predicting the peak response of RC beams subjected to impact loading is proposed, where the theoretical basis for calculating peak impact force originates from the contact law, the principle of conservation of energy, the impulse-momentum theorem, and the wave theory.
Abstract: In this paper, a novel and simple method for predicting the peak response of RC beams subjected to impact loading is proposed. The theoretical basis for calculating the peak impact force originates from the contact law, the principle of conservation of energy, the impulse-momentum theorem, and the wave theory. Additionally, the conventional beam theory, in conjunction with the well-known layered-section approach, is utilized to obtain the force-deflection relationship of the RC beam. Subsequently, by taking into account the strain rate effect, the maximum midspan deflection of RC beams under impact loading is determined based on the conservation of energy approach. A comparison with 143 impact tests has shown that the proposed method is able to estimate the maximum midspan deflection of RC beams under impact loading with high accuracy. The prediction of the peak impact force is shown to be slightly overestimated, which however can be used in the anti-impact design to preclude the shear failure near the impact point.
TL;DR: In this paper, a single-frame bridge model with adjacent abutments subjected to uniform ground excitations was considered and the pounding behavior was observed using a pair of pounding and measuring heads, which revealed that pounding could indeed influence the responses of skewed bridges in the longitudinal and transverse directions differently and thus affect the development of the girder rotations.
Abstract: Observations from past earthquake events indicate that skewed bridges are seismically vulnerable due to induced horizontal in-plane rotations of the girder. To date, however, very limited experimental research has been done on the pounding behaviour of skewed bridges. In this study, shake table tests were performed on a single-frame bridge model with adjacent abutments subjected to uniform ground excitations. Bridges with different skew angles, i.e., 0°, 30°, and 45°, were considered. The pounding behaviour was observed using a pair of pounding and measuring heads. The results reveal that poundings could indeed influence the responses of skewed bridges in the longitudinal and transverse directions differently and thus affect the development of the girder rotations. Ignoring pounding effects, the 30° skewed bridges could experience more girder rotations than the 45° skewed bridges. With pounding, the bridges with a large skew angle could suffer more opening girder displacements than straight bridges.
TL;DR: In this paper, a multiscale modeling and simulation of destress blasting of rock mass is presented. And the proposed and novel approach combines two separate 3D solutions: the first was obtained for the small-scale problem, face(s) blasting process, and the second for the global scale problem, seismic wave propagation within very large volumes of surrounding rock mass.
Abstract: In this paper, a multiscale modelling and simulation of destress blasting of rock mass is presented. The proposed and novel approach combines two separate 3D solutions: the first was obtained for the small-scale problem, face(s) blasting process, and the second for the global scale problem, seismic wave propagation within very large volumes of surrounding rock mass. Both the approaches were based on explicit dynamic modelling methodology using the central difference method. In the local case, the arbitrary Lagrangian–Eulerian (ALE) procedure with the Jones–Wilkins–Lee (JWL) equation defining an explosive material was used. For this purpose, a selected volume of a rock mass comprising a blasted mining face was modelled in detail. From the numerical simulation, pressure distribution over the modelled rock was obtained, which was the basis for an initial condition for the global 3D FE model. The peak particle velocity (ppv) distribution obtained from finite element analysis was compared with experimental outcomes. A reasonable agreement between both results was achieved; therefore, the adopted multiscale modelling approach confirmed its effectiveness and that it can be successfully implemented in further engineering practice.
TL;DR: A state-of-the-art review has been done highlighting advantages and drawbacks, application fields, and technology readiness level of most recent developments of passive electromagnetic devices for vibration damping and isolation.
Abstract: Passive electromagnetic devices for vibration damping and isolation are becoming a real alternative to traditional mechanical vibration and isolation methods. These types of devices present good damping capacity, lower cost, null power consumption, and higher reliability. In this work, a state-of-the-art review has been done highlighting advantages and drawbacks, application fields, and technology readiness level of most recent developments. In addition, a general introductory section relates presents key considerations that any engineer, electrical or mechanical, needs to know for a deep comprehension and correct design of these types of devices.
TL;DR: A novel fault diagnosis model, which extracts features by combining vibration severity, dyadic wavelet energy time-spectrum, and coefficient power spectrum of the maximum wavelets energy level (VWC) at the feature extraction stage, is proposed.
Abstract: Fault diagnosis of rotating machinery mainly includes fault feature extraction and fault classification. Vibration signal from the operation of machinery usually could help diagnosing the operational state of equipment. Different types of fault usually have different vibrational features, which are actually the basis of fault diagnosis. This paper proposes a novel fault diagnosis model, which extracts features by combining vibration severity, dyadic wavelet energy time-spectrum, and coefficient power spectrum of the maximum wavelet energy level (VWC) at the feature extraction stage. At the stage of fault classification, we design a support vector machine (SVM) based on the modified shuffled frog-leaping algorithm (MSFLA) for the accurate classifying machinery fault method. Specifically, we use the MSFLA method to optimize SVM parameters. MSFLA can avoid getting trapped into local optimum, speeding up convergence, and improving classification accuracy. Finally, we evaluate our model on real rotating machinery platform, which has four different states, i.e., normal state, eccentric axle fault (EAF), bearing pedestal fault (BPF), and sealing ring wear fault (SRWF). As demonstrated by the results, the VWC method is efficient in extracting vibration signal features of rotating machinery. Based on the extracted features, we further compare our classification method with other three fault classification methods, i.e., backpropagation neural network (BPNN), artificial chemical reaction optimization algorithm (ACROA-SVM), and SFLA-SVM. The experiment results show that MSFLA-SVM achieves a much higher fault classification rate than BPNN, ACROA-SVM, and SFLA-SVM.
TL;DR: In this paper, a simulation experiment of a coal and gas outburst with a ground stress of 16 MPa and a gas pressure of 0.5µm was carried out using a self-developed large-scale coal-and gas outburst simulation experimental system.
Abstract: With mining depths increasing, coal and gas outburst disasters are becoming more and more serious and complicated, which directly restricts the production efficiency of coal mines. In order to study the rules of energy dissipation during the occurrence of a coal and gas outburst based on the occurrence mechanisms, a simulation experiment of a coal and gas outburst with a ground stress of 16 MPa and a gas pressure of 0.5 MPa was carried out using a self-developed large-scale coal and gas outburst simulation experimental system. A quantitative analysis was given based on the energy model. The results showed the following: (1) In the process of the coal and gas outburst, the main energy source originated from the elastic potential energy of the coal body and the gas internal energy. The main energy loss was used for coal crushing and throwing. (2) The outburst coal sample in this experiment had a mass of 18.094 kg, and the relative outburst intensity was 1.21%. Additionally, the farthest throwing distance of the outburst coal samples was 3.3 m away from the outburst hole wall. The distribution of the outburst coal sample decreased along the roadway, and the proportion of the coal sample grain size in each area first decreased and then increased with the decrease of the grain size. The coal samples with a grain size less than 0.2 mm after the outburst accounted for 6.34% of the mass of the total coal samples. (3) The elastic potential energy of the coal body accounted for 0.34% of the total outburst energy, while the gas internal energy accounted for 99.66%. It was verified that gas internal energy was the key energy source for the coal and gas outburst, and this internal energy was two orders of magnitude more than the elastic potential energy, playing a leading role in the outburst process. After the outburst initiation, most of the energy was consumed in coal crushing, which was in the same order of magnitude as the gas internal energy. Moreover, the energy losses due to friction, vibration, and sound during the outburst process comprised no more than 10% of the total energy. The research results can provide certain guidance for clarifying the mechanism of a coal and gas outburst and the quantitative analysis of outburst energy.