Showing papers in "Shock and Vibration in 2014"

Fault Diagnosis of Rotating Machinery Based on Multisensor Information Fusion Using SVM and Time-Domain Features

Abstract: Multisensor information fusion, when applied to fault diagnosis, the time-space scope, and the quantity of information are expanded compared to what could be acquired by a single sensor, so the diagnostic object can be described more comprehensively. This paper presents a methodology of fault diagnosis in rotating machinery using multisensor information fusion that all the features are calculated using vibration data in time domain to constitute fusional vector and the support vector machine (SVM) is used for classification. The effectiveness of the presented methodology is tested by three case studies: diagnostic of faulty gear, rolling bearing, and identification of rotor crack. For each case study, the sensibilities of the features are analyzed. The results indicate that the peak factor is the most sensitive feature in the twelve time-domain features for identifying gear defect, and the mean, amplitude square, root mean square, root amplitude, and standard deviation are all sensitive for identifying gear, rolling bearing, and rotor crack defect comparatively.

Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis

Abstract: A new rolling bearing fault diagnosis approach based on multiscale permutation entropy (MPE), Laplacian score (LS), and support vector machines (SVMs) is proposed in this paper. Permutation entropy (PE) was recently proposed and defined to measure the randomicity and detect dynamical changes of time series. However, for the complexity of mechanical systems, the randomicity and dynamic changes of the vibration signal will exist in different scales. Thus, the definition of MPE is introduced and employed to extract the nonlinear fault characteristics from the bearing vibration signal in different scales. Besides, the SVM is utilized to accomplish the fault feature classification to fulfill diagnostic procedure automatically. Meanwhile, in order to avoid a high dimension of features, the Laplacian score (LS) is used to refine the feature vector by ranking the features according to their importance and correlations with the main fault information. Finally, the rolling bearing fault diagnosis method based on MPE, LS, and SVM is proposed and applied to the experimental data. The experimental data analysis results indicate that the proposed method could identify the fault categories effectively.

Structural Health Monitoring under Nonlinear Environmental or Operational Influences

Abstract: Vibration-based structural health monitoring is based on detecting changes in the dynamic characteristics of the structure. It is well known that environmental or operational variations can also have an influence on the vibration properties. If these effects are not taken into account, they can result in false indications of damage. If the environmental or operational variations cause nonlinear effects, they can be compensated using a Gaussian mixture model (GMM) without the measurement of the underlying variables. The number of Gaussian components can also be estimated. For the local linear components, minimum mean square error (MMSE) estimation is applied to eliminate the environmental or operational influences. Damage is detected from the residuals after applying principal component analysis (PCA). Control charts are used for novelty detection. The proposed approach is validated using simulated data and the identified lowest natural frequencies of the Z24 Bridge under temperature variation. Nonlinear models are most effective if the data dimensionality is low. On the other hand, linear models often outperform nonlinear models for high-dimensional data.

Monitoring of Rotor-Stator Interaction in Pump-Turbine Using Vibrations Measured with On-Board Sensors Rotating with Shaft

Abstract: Current trends in design of pump-turbines have led into higher rotor-stator interaction (RSI) loads over impeller-runner. These dynamic loads are of special interest having produced catastrophic failures in pump-turbines. Determining RSI characteristics facilitates the proposal of actions that will prevent these failures. Pressure measurements all around the perimeter of the impeller-runner are appropriate to monitor and detect RSI characteristics. Unfortunately most installed pump-turbines are not manufactured with in-built pressure sensors in appropriate positions to monitor RSI. For this reason, vibration measurements are the preferred method to monitor RSI in industry. Usually vibrations are measured in two perpendicular radial directions in bearings where valuable information could be lost due to bearing response. In this work, in order to avoid the effect of bearing response on measurement, two vibration sensors are installed rotating with the shaft. The RSI characteristics obtained with pressure measurements were compared to those determined using vibration measurements. The RSI characteristics obtained with pressure measurements were also determined using vibrations measured rotating with shaft. These RSI characteristics were not possible to be determined using the vibrations measured in guide bearing. Finally, it is recommended to measure vibrations rotating with shaft to detect RSI characteristics in installed pump-turbines as a more practical and reliable method to monitor RSI characteristics.

Localization of transversal cracks in sandwich beams and evaluation of their severity

Abstract: An algorithm to assess transversal cracks in composite structures based on natural frequency changes due to damage is proposed. The damage assessment is performed in two steps; first the crack location is found, and afterwards an evaluation of its severity is performed. The technique is based on a mathematical relation that provides the exact solution for the frequency changes of bending vibration modes, considering two terms. The first term is related to the strain energy stored in the beam, while the second term considers the increase of flexibility due to damage. Thus, it is possible to separate the problems of localization and severity assessment, which makes the localization process independent of the beams cross-section shape and boundary conditions. In fact, the process consists of comparing vectors representing the measured frequency shifts with patterns constructed using the mode shape curvatures of the undamaged beam. Once the damage is localized, the evaluation of its severity is made taking into account the global rigidity reduction. The damage identification algorithm was validated by experiments performed on numerous sandwich panel specimens.

A Roller Bearing Fault Diagnosis Method Based on LCD Energy Entropy and ACROA-SVM

Abstract: This study investigates a novel method for roller bearing fault diagnosis based on local characteristic-scale decomposition (LCD) energy entropy, together with a support vector machine designed using an Artificial Chemical Reaction Optimisation Algorithm, referred to as an ACROA-SVM. First, the original acceleration vibration signals are decomposed into intrinsic scale components (ISCs). Second, the concept of LCD energy entropy is introduced. Third, the energy features extracted from a number of ISCs that contain the most dominant fault information serve as input vectors for the support vector machine classifier. Finally, the ACROA-SVM classifier is proposed to recognize the faulty roller bearing pattern. The analysis of roller bearing signals with inner-race and outer-race faults shows that the diagnostic approach based on the ACROA-SVM and using LCD to extract the energy levels of the various frequency bands as features can identify roller bearing fault patterns accurately and effectively. The proposed method is superior to approaches based on Empirical Mode Decomposition method and requires less time.

Numerical Simulation of Rock Fragmentation under the Impact Load of Water Jet

Abstract: To investigate the rock fragmentation and its influence factors under the impact load of water jet, a numerical method which coupled finite element method (FEM) with smoothed particle hydrodynamics (SPH) was adopted to simulate the rock fragmentation process by water jet. Linear and shock equations of state were applied to describe the dynamic characteristics of rock and water, respectively, while the maximum principal stress criterion was used for the rock failure detection. The dynamic stresses at the selected element containing points in rock are computed as a function of time under the impact load of water jet. The influences of the factors of boundary condition, impact velocity, confining pressure, and structure plane on rock dynamic fragmentation are discussed.

Three-dimensional exact free vibration analysis of spherical, cylindrical, and flat one-layered panels

Abstract: The paper proposes a three-dimensional elastic analysis of the free vibration problem of one-layered spherical, cylindrical, and flat panels. The exact solution is developed for the differential equations of equilibrium written in orthogonal curvilinear coordinates for the free vibrations of simply supported structures. These equations consider an exact geometry for shells without simplifications. The main novelty is the possibility of a general formulation for different geometries. The equations written in general orthogonal curvilinear coordinates allow the analysis of spherical shell panels and they automatically degenerate into cylindrical shell panel, cylindrical closed shell, and plate cases. Results are proposed for isotropic and orthotropic structures. An exhaustive overview is given of the vibration modes for a number of thickness ratios, imposed wave numbers, geometries, embedded materials, and angles of orthotropy. These results can also be used as reference solutions to validate two-dimensional models for plates and shells in both analytical and numerical form (e.g., closed solutions, finite element method, differential quadrature method, and global collocation method).

Modeling and Analysis of a Piezoelectric Energy Harvester with Varying Cross-Sectional Area

Abstract: This paper reports on the modeling and on the experimental verification of electromechanically coupled beams with varying cross-sectional area for piezoelectric energy harvesting. The governing equations are formulated using the Rayleigh-Ritz method and Euler-Bernoulli assumptions. A load resistance is considered in the electrical domain for the estimate of the electric power output of each geometric configuration. The model is first verified against the analytical results for a rectangular bimorph with tip mass reported in the literature. The experimental verification of the model is also reported for a tapered bimorph cantilever with tip mass. The effects of varying cross-sectional area and tip mass on the electromechanical behavior of piezoelectric energy harvesters are also discussed. An issue related to the estimation of the optimal load resistance (that gives the maximum power output) on beam shape optimization problems is also discussed.

Model Reduction Technique Tailored to the Dynamic Analysis of a Beam Structure under a Moving Load

Abstract: This study presents a technique that uses a model reduction method for the dynamic response analysis of a beam structure to a moving load, which can be modeled either as a moving point force or as a moving body. The nature of the dedicated condensation method tailored to address the moving load case is that the master degrees of freedom are reselected, and the coefficient matrices of the condensed model are recalculated as the load travels from one element to another. Although this process increases computational burden, the overall computational time is still greatly reduced because of the small scale of motion equations. To illustrate and validate the methodology, the technique is initially applied to a simply supported beam subjected to a single-point load moving along the beam. Subsequently, the technique is applied to a practical model for wheel-rail interaction dynamic analysis in railway engineering. Numerical examples show that the condensation model can solve the moving load problem faster than an analytical model or its full finite element model. The proposed model also exhibits high computational accuracy.

Valve Fault Diagnosis in Internal Combustion Engines Using Acoustic Emission and Artificial Neural Network

Abstract: This paper presents the potential of acoustic emission (AE) technique to detect valve damage in internal combustion engines. The cylinder head of a spark-ignited engine was used as the experimental setup. The effect of three types of valve damage (clearance, semicrack, and notch) on valve leakage was investigated. The experimental results showed that AE is an effective method to detect damage and the type of damage in valves in both of the time and frequency domains. An artificial neural network was trained based on time domain analysis using AE parametric features (, count, absolute AE energy, maximum signal amplitude, and average signal level). The network consisted of five, six, and five nodes in the input, hidden, and output layers, respectively. The results of the trained system showed that the AE technique could be used to identify the type of damage and its location.

Some Elements of Operational Modal Analysis

Abstract: This paper gives an overview of the main components of operational modal analysis (OMA) and can serve as a tutorial for research oriented OMA applications. The paper gives a short introduction to the modeling of random responses and to the transforms often used in OMA such as the Fourier series, the Fourier integral, the Laplace transform, and the Z-transform. Then the paper introduces the spectral density matrix of the random responses and presents the theoretical solutions for correlation function and spectral density matrix under white noise loading. Some important guidelines for testing are mentioned and the most common techniques for signal processing of the operating signals are presented. The algorithms of some of the commonly used time domain and frequency domain identification techniques are presented and finally some issues are discussed such as mode shape scaling, and mode shape expansion. The different techniques are illustrated on the difficult case of identifying the three first closely spaced modes of the Heritage Court Tower building.

Review of Response and Damage of Linear and Nonlinear Systems under Multiaxial Vibration

Abstract: A review of past and recent developments in multiaxial excitation of linear and nonlinear structures is presented. The objective is to review some of the basic approaches used in the analytical and experimental methods for kinematic and dynamic analysis of flexible mechanical systems, and to identify future directions in this research area. In addition, comparison between uniaxial and multiaxial excitations and their impact on a structure’s life-cycles is provided. The importance of understanding failure mechanisms in complex structures has led to the development of a vast range of theoretical, numerical, and experimental techniques to address complex dynamical effects. Therefore, it is imperative to identify the failure mechanisms of structures through experimental and virtual failure assessment based on correctly identified dynamic loads. For that reason, techniques for mapping the dynamic loads to fatigue were provided. Future research areas in structural dynamics due to multiaxial excitation are identified as (i) effect of dynamic couplings, (ii) modal interaction, (iii) modal identification and experimental methods for flexible structures, and (iv) computational models for large deformation in response to multiaxial excitation.

Vibration Suppression of a Large Beam Structure Using Tuned Mass Damper and Eddy Current Damping

Abstract: For a few decades, various methods to suppress the vibrations of structures have been proposed and exploited. These include passive methods using constrained layer damping (CLD) and active methods using smart materials. However, applying these methods to large structures may not be practical because of weight, material, and actuator constraints. The objective of the present study is to propose and exploit an effective method to suppress the vibration of a large and heavy beam structure with a minimum increase in mass or volume of material. Traditional tuned mass dampers (TMD) are very effective for attenuating structural vibrations; however, they often add substantial mass. Eddy current damping is relatively simple and has excellent performance but is force limited. The proposed method is to apply relatively light-weight TMD to attenuate the vibration of a large beam structure and increase its performance by applying eddy current damping to a TMD. The results show that the present method is simple but effective in suppressing the vibration of a large beam structure without a substantial weight increase.

Propeller Excitation of Longitudinal Vibration Characteristics of Marine Propulsion Shafting System

Abstract: The submarine experiences longitudinal vibration in the propulsion shafting system throughout most of run. A transfer matrix model of the propulsion shafting system, in which the dynamic characteristics of oil film within thrust bearing are considered, is established to describe the dynamic behavior. Using hydrodynamic lubrication theory and small perturbation method, the axial stiffness and damping of oil film are deduced in great detail, followed by numerical estimation of the foundation stiffness with finite element method. Based upon these values of dynamic parameters, the Campbell diagram describing natural frequencies in terms of shafting rotating speeds is available, and the effect on the 1st natural frequency of considerable variations in thrust bearing stiffness is next investigated. The results indicate that the amplitude of variation of the 1st natural frequency in range of low rotating speeds is great. To reduce off-resonance response without drastic changes in propulsion shafting system architecture, the measure of moving thrust bearing backward is examined. The longitudinal vibration transmission through propulsion shafting system results in subsequent axial excitation of hull; the thrust load acting on hull is particularly concerned. It is observed that the measures of structural modification are of little benefit to minimize thrust load transmitted to hull.

Quantitative Diagnosis of Rotor Vibration Fault Using Process Power Spectrum Entropy and Support Vector Machine Method

Abstract: To improve the diagnosis capacity of rotor vibration fault in stochastic process, an effective fault diagnosis method (named Process Power Spectrum Entropy (PPSE) and Support Vector Machine (SVM) (PPSE-SVM, for short) method) was proposed. The fault diagnosis model of PPSE-SVM was established by fusing PPSE method and SVM theory. Based on the simulation experiment of rotor vibration fault, process data for four typical vibration faults (rotor imbalance, shaft misalignment, rotor-stator rubbing, and pedestal looseness) were collected under multipoint (multiple channels) and multispeed. By using PPSE method, the PPSE values of these data were extracted as fault feature vectors to establish the SVM model of rotor vibration fault diagnosis. From rotor vibration fault diagnosis, the results demonstrate that the proposed method possesses high precision, good learning ability, good generalization ability, and strong fault-tolerant ability (robustness) in four aspects of distinguishing fault types, fault severity, fault location, and noise immunity of rotor stochastic vibration. This paper presents a novel method (PPSE-SVM) for rotor vibration fault diagnosis and real-time vibration monitoring. The presented effort is promising to improve the fault diagnosis precision of rotating machinery like gas turbine.

Magnetic Flux Leakage Sensing-Based Steel Cable NDE Technique

Abstract: Nondestructive evaluation (NDE) of steel cables in long span bridges is necessary to prevent structural failure. Thus, an automated cable monitoring system is proposed that uses a suitable NDE technique and a cable-climbing robot. A magnetic flux leakage- (MFL-) based inspection system was applied to monitor the condition of cables. This inspection system measures magnetic flux to detect the local faults (LF) of steel cable. To verify the feasibility of the proposed damage detection technique, an 8-channel MFL sensor head prototype was designed and fabricated. A steel cable bunch specimen with several types of damage was fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. To interpret the condition of the steel cable, magnetic flux signals were used to determine the locations of the flaws and the levels of damage. Measured signals from the damaged specimen were compared with thresholds that were set for objective decision-making. In addition, the measured magnetic flux signals were visualized as a 3D MFL map for intuitive cable monitoring. Finally, the results were compared with information on actual inflicted damages, to confirm the accuracy and effectiveness of the proposed cable monitoring method.

Vibration Characteristics of Piezoelectric Microbeams Based on the Modified Couple Stress Theory

Abstract: The vibration behavior of piezoelectric microbeams is studied on the basis of the modified couple stress theory. The governing equations of motion and boundary conditions for the Euler-Bernoulli and Timoshenko beam models are derived using Hamilton’s principle. By the exact solution of the governing equations, an expression for natural frequencies of microbeams with simply supported boundary conditions is obtained. Numerical results for both beam models are presented and the effects of piezoelectricity and length scale parameter are illustrated. It is found that the influences of piezoelectricity and size effects are more prominent when the length of microbeams decreases. A comparison between two beam models also reveals that the Euler-Bernoulli beam model tends to overestimate the natural frequencies of microbeams as compared to its Timoshenko counterpart.

Damage Detection of a Continuous Bridge from Response of a Moving Vehicle

Abstract: This paper presents a multistage multipass method to identify the damage location of a continuous bridge from the response of a vehicle moving on the rough road surface of the bridge. The vehicle runs over the bridge several times at different velocities and the corresponding responses of the vehicle can be obtained. The vertical accelerations of the vehicle running on the intact and damaged bridges are used for identification. The multistage damage detection method is implemented by the modal strain energy based method and genetic algorithm. The modal strain energy based method estimates the damage location by calculating a damage indicator from the frequencies extracted from the vehicle responses of both the intact and damaged states of the bridge. At the second stage, the identification problem is transformed into a global optimization problem and is solved by genetic algorithm techniques. For each pass of the vehicle, the method can identify the location of the damage until it is determined with acceptable accuracy. A two-span continuous bridge is used to verify the method. The numerical results show that this method can identify the location of damage reasonably well.

Study of the Complex Stiffness of a Vibratory Mechanical System with Shape Memory Alloy Coil Spring Actuator

Abstract: The vibration control is an important area in the dynamic of structures that seeks to reduce the amplitude of structural responses in certain critical frequency ranges Currently, the scientific development leads to the application of some actuators and sensors technologically superior comparing to the same features available on the market For developing these advanced sensors and actuators, smart materials that can change their mechanical properties when subjected to certain thermomechanical loads can be employed In this context, Shape memory alloys (SMAs) may be used for developing dynamic vibration dampers which are capable of acting on the system providing proper tuning of the excitation frequency and the natural frequency This paper aims to analyze the behavior of the stiffness and damping of a SMA helical coil spring actuator coupled to a mechanical system of one degree of freedom (1 DOF) subjected to an unbalanced excitement force and a temperature control system By analyzing the effect of these parameters on the structural response and considering the concept of complex stiffness, it can be possible to predict the system's behavior within certain acceptable ranges of vibration, already in the design phase

Satellite Attitude Control System Design considering the Fuel Slosh Dynamics

Abstract: The design of the satellite attitude control system (ACS) becomes more complex when the satellite structure has different type of components like, flexible solar panels, antennas, mechanical manipulators, and tanks with fuel. A crucial interaction can occur between the fuel slosh motion and the satellite rigid motion during translational and/or rotational manoeuvre since these interactions can change the satellite centre of mass position damaging the ACS pointing accuracy. Although, a well-designed controller can suppress such disturbances quickly, the controller error pointing may be limited by the minimum time necessary to suppress such disturbances thus affecting the satellite attitude acquisition. As a result, the design of the satellite controller needs to explore the limits between the conflicting requirements of performance and robustness. This paper investigates the effects of the interaction between the liquid motion (slosh) and the satellite dynamics in order to predict what the damage to the controller performance and robustness is. The fuel slosh dynamics is modelled by a pendulum which parameters are identified using the Kalman filter technique. This information is used to design the satellite controller by the linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) methods to perform a planar manoeuvre assuming thrusters are actuators.

Experimental and Numerical Simulation of Wheel-Rail Adhesion and Wear Using a Scaled Roller Rig and a Real-Time Contact Code

Abstract: The work shows the use of a scaled roller rig to validate a real time wheel-rail contact code developed to study the wheel rail adhesion and the wear evolution. The code allows the profiles to change at each time step in order to take into account the material loss due to the wear process. The contact code replicates a testing machine composed of a roller rig with a prototype of a single suspended wheelset pressed onto it with a variable load. The roller rig, developed at Politecnico di Torino, is used to validate and optimize the contact code referring to experimental data directly measured in real time. The test bench, in fact, allows measurement of specific kinematical quantities and forces that are elaborated by the real-time code in order to produce numerical results for comparison with the experimental ones. This approach can be applied both to the determination of wheel-rail adhesion and to the wear process. The test rig is also equipped with a laser profilometer that allows measurement of the wheel and rail profiles with a very high accuracy.

Perspectives of Second-Order Blind Identification for Operational Modal Analysis of Civil Structures

Abstract: Innovative methods for output-only estimation of the modal properties of civil structures are based on blind source separation techniques In the present paper attention is focused on the second-order blind identification (SOBI) algorithm and the influence of its analysis parameters on computational time and accuracy of modal parameter estimates These represent key issues in view of the automation of the algorithm and its integration within vibration-based monitoring systems The herein reported analyses and results provide useful hints for reduction of computational time and control of accuracy of estimates The latter topic is of interest in the case of single modal identification tests, too A criterion for extraction of accurate modal parameter estimates is identified and applied to selected experimental case studies They are representative of the different levels of complexity that can be encountered during real modal tests The obtained results point out that SOBI can provide accurate estimates and it can also be automated, confirming that it represents a profitable alternative for output-only modal analysis and vibration-based monitoring of civil structures

Bearing Degradation Process Prediction Based on the Support Vector Machine and Markov Model

Abstract: Predicting the degradation process of bearings before they reach the failure threshold is extremely important in industry. This paper proposed a novel method based on the support vector machine (SVM) and the Markov model to achieve this goal. Firstly, the features are extracted by time and time-frequency domain methods. However, the extracted original features are still with high dimensional and include superfluous information, and the nonlinear multifeatures fusion technique LTSA is used to merge the features and reduces the dimension. Then, based on the extracted features, the SVM model is used to predict the bearings degradation process, and the CAO method is used to determine the embedding dimension of the SVM model. After the bearing degradation process is predicted by SVM model, the Markov model is used to improve the prediction accuracy. The proposed method was validated by two bearing run-to-failure experiments, and the results proved the effectiveness of the methodology.

Real-Time Structural Damage Assessment Using Artificial Neural Networks and Antiresonant Frequencies

Abstract: The main problem in damage assessment is the determination of how to ascertain the presence, location, and severity of structural damage given the structure's dynamic characteristics The most successful applications of vibration-based damage assessment are model updating methods based on global optimization algorithms However, these algorithms run quite slowly, and the damage assessment process is achieved via a costly and time-consuming inverse process, which presents an obstacle for real-time health monitoring applications Artificial neural networks (ANN) have recently been introduced as an alternative to model updating methods Once a neural network has been properly trained, it can potentially detect, locate, and quantify structural damage in a short period of time and can therefore be applied for real-time damage assessment The primary contribution of this research is the development of a real-time damage assessment algorithm using ANN and antiresonant frequencies Antiresonant frequencies can be identified more easily and more accurately than mode shapes, and they provide the same information This research addresses the setup of the neural network parameters and provides guidelines for the selection of these parameters in similar damage assessment problems Two experimental cases validate this approach: an 8-DOF mass-spring system and a beam with multiple damage scenarios

Efficient Model Order Reduction for the Dynamics of Nonlinear Multilayer Sheet Structures with Trial Vector Derivatives

Abstract: The mechanical response of multilayer sheet structures, such as leaf springs or car bodies, is largely determined by the nonlinear contact and friction forces between the sheets involved. Conventional computational approaches based on classical reduction techniques or the direct finite element approach have an inefficient balance between computational time and accuracy. In the present contribution, the method of trial vector derivatives is applied and extended in order to obtain a-priori trial vectors for the model reduction which are suitable for determining the nonlinearities in the joints of the reduced system. Findings show that the result quality in terms of displacements and contact forces is comparable to the direct finite element method but the computational effort is extremely low due to the model order reduction. Two numerical studies are presented to underline the method’s accuracy and efficiency. In conclusion, this approach is discussed with respect to the existing body of literature.

Probabilistic Neural Network and Fuzzy Cluster Analysis Methods Applied to Impedance-Based SHM for Damage Classification

Abstract: Impedance-based structural health monitoring technique is performed by measuring the variation of the electromechanical impedance of the structure caused by the presence of damage The impedance signals are collected from patches of piezoelectric material bonded on the surface of the structure (or embedded) Through these piezoceramic sensor-actuators, the electromechanical impedance, which is directly related to the mechanical impedance of the structure, is obtained Based on the variation of the impedance signals, the presence of damage can be detected A particular damage metric is used to quantify the damage Distinguishing damage groups from a universe containing different types of damage is a major challenge in structural health monitoring There are several types of failures that can occur in a given structure, such as cracks, fissures, loss of mechanical components (eg, rivets), corrosion, and wear It is important to characterize each type of damage from the impedance signals considered In the present paper, probabilistic neural network and fuzzy cluster analysis methods are used for identification, localization, and classification of two types of damage, namely, cracks and rivet losses The results show that probabilistic neural network and fuzzy cluster analysis methods are useful for identification, localization, and classification of these types of damage

Certain Type Turbofan Engine Whole Vibration Model with Support Looseness Fault and Casing Response Characteristics

Abstract: Support looseness fault is a type of common fault in aeroengine. Serious looseness fault would emerge under larger unbalanced force, which would cause excessive vibration and even lead to rubbing fault, so it is important to analyze and recognize looseness fault effectively. In this paper, based on certain type turbofan engine structural features, a rotor-support-casing whole model for certain type turbofan aeroengine is established. The rotor and casing systems are modeled by means of the finite element beam method; the support systems are modeled by lumped-mass model; the support looseness fault model is also introduced. The coupled system response is obtained by numerical integral method. In this paper, based on the casing acceleration signals, the impact characteristics of symmetrical stiffness and asymmetric stiffness models are analyzed, finding that the looseness fault would lead to the longitudinal asymmetrical characteristics of acceleration time domain wave and the multiple frequency characteristics, which is consistent with the real trial running vibration signals. Asymmetric stiffness looseness model is verified to be fit for aeroengine looseness fault model.

Intelligent Diagnosis Method for Centrifugal Pump System Using Vibration Signal and Support Vector Machine

Abstract: This paper proposed an intelligent diagnosis method for a centrifugal pump system using statistic filter, support vector machine (SVM), possibility theory, and Dempster-Shafer theory (DST) on the basis of the vibration signals, to diagnose frequent faults in the centrifugal pump at an early stage, such as cavitation, impeller unbalance, and shaft misalignment. Firstly, statistic filter is used to extract the feature signals of pump faults from the measured vibration signals across an optimum frequency region, and nondimensional symptom parameters (NSPs) are defined to represent the feature signals for distinguishing fault types. Secondly, the optimal classification hyperplane for distinguishing two states is obtained by SVM and NSPs, and its function is defined as synthetic symptom parameter (SSP) in order to increase the diagnosis’ sensitivity. Finally, the possibility functions of the SSP are used to construct a sequential fuzzy diagnosis for fault detection and fault-type identification by possibility theory and DST. The proposed method has been applied to detect the faults of the centrifugal pump, and the efficiency of the method has been verified using practical examples.

A New Flexibility Based Damage Index for Damage Detection of Truss Structures

Abstract: A new damage index, called strain change based on flexibility index (SCBFI), is introduced to locate damaged elements of truss systems. The principle of SCBFI is based on considering strain changes in structural elements, between undamaged and damaged states. The strain of an element is evaluated using the columnar coefficients of the flexibility matrix estimated via modal analysis information. Two illustrative test examples are considered to assess the performance of the proposed method. Numerical results indicate that the method can provide a reliable tool to accurately identify the multiple-structural damage for truss structures.