Vibration-based Methods Research Articles

A method to detect cracks in the beams with imperfect boundary conditions

Non-destructive testing of structures involving vibration-based damage detection methods implies knowing the beam’s boundary conditions. For perfect boundary conditions, numerous damage detection methods are developed and ensure more or less accurate estimation of the crack type, position, and severity. On the contrary, for imperfect boundary conditions, which are the real ones, there are only a few dedicated works. This paper presents a methodology that allows the identification of the weak clamping and the crack if both exist. The weak clamping is modelled as a defect that produces an identical relative frequency shift (RFS) for all vibration modes. Therefore, to find the two defects namely the real crack and defect simulating the weakly clamped end, we apply the principle of superposition. The method is implemented as an application written in the Python programming language. Tests show that defects are successfully identified even if there are uncertainties about the fixing of the beam.

Non-contact monitoring of the tension in partially submerged, miter-gate diagonals

Miter gates are water-control structures used as the damming surface on river locks and allow the water levels in the lock to raise or lower as needed. Miter gates have channel-like cross sections and are thus prone to torsional deflection due to gravity loads. To counter-act the tendency for torsional deflection and to add torsional rigidity to the gate, slender steel members termed diagonals are added across the diagonal dimension of the gate and pre-tensioned. To maintain appropriate tension in the diagonals over their lifetime, the tension in the diagonals should be monitored; however, no such monitoring is utilized. Vibration based methods to obtain an estimate of the tensile loads in the diagonal are attractive because they are simple, inexpensive, and do not require continuous monitoring. However, employing vibration-based methods to estimate the tension in the diagonals is particularly challenging because the diagonals are subjected to varying levels of submersion in water. Finding a relationship between the frequency of vibration and applied pretension that adequately addressed the effects of submersion on diagonals is difficult. This paper proposes an approach to account for the effect of submersion on the estimated tension in miter gate diagonals. Laboratory tests are conducted using scale-model diagonal specimens subjected to various levels of tension and submersion in water. The frequency of the diagonal specimens is measured and compared to an approximation using an assumed modes model. The effects of submersion on the frequency of vibration for the partially submerged diagonals are largely explained by added mass on the diagonals. Field validation is performed using a previously developed vision-based method of extracting the frequency of vibration in conjunction with the proposed method of tension estimation of an in-service miter gate diagonal that is also instrumented with load cells. Results for the proposed method show excellent agreement with load cell measurements.

An improved time-varying empirical mode decomposition for structural condition assessment using limited sensors

The safety concerns of transport infrastructure around the world have significantly increased over the past few years and pose a significant threat to the public and economic well-being. Condition assessment of transport infrastructure is currently performed using structural health monitoring (SHM). Over the last few decades, SHM of ageing infrastructure is leveraged using advancements in sensing technologies. However, vibration-based SHM methods that rely on sensor-driven data collection face several practical challenges such as traffic interruptions, availability of limited space, and a limited amount of sensors. In this study, a system identification technique is developed, which can deal with these practical challenges of SHM and provide reliable results. The proposed technique involves a time-varying filtering empirical mode decomposition algorithm that can decompose a single measured signal into its mono-component modal responses. The resulting mono-component signals are then analyzed using a wavelet-based reallocation algorithm called Multi-Synchrosqueezing Transform. The iterative nature of this algorithm is utilized to enhance the time-frequency representation of a nonstationary signal obtained from the ageing structures. The capability of the proposed method to identify the modal parameters is demonstrated using a suite of numerical and full-scale studies under various cases of measurement noise, closely-spaced and low energy modes, and damage detection using the limited sensor measurements.

Structural Damage Identification Based on Integrated Utilization of Inverse Finite Element Method and Pseudo-Excitation Approach.

The attempt to integrate the applications of conventional structural deformation reconstruction strategies and vibration-based damage identification methods is made in this study, where, more specifically, the inverse finite element method (iFEM) and pseudo-excitation approach (PE) are combined for the first time, to give rise to a novel structural health monitoring (SHM) framework showing various advantages, particularly in aspects of enhanced adaptability and robustness. As the key component of the method, the inverse finite element method (iFEM) enables precise reconstruction of vibration displacements based on measured dynamic strains, which, as compared to displacement measurement, is much more adaptable to existing on-board SHM systems in engineering practice. The PE, on the other hand, is applied subsequently, relying on the reconstructed displacements for the identification of structural damage. Delamination zones in a carbon fibre reinforced plastic (CFRP) laminate are identified using the developed method. As demonstrated by the damage detection results, the iFEM-PE method possesses apparently improved accuracy and significantly enhanced noise immunity compared to the original PE approach depending on displacement measurement. Extensive parametric study is conducted to discuss the influence of a variety of factors on the effectiveness and accuracy of damage identification, including the influence of damage size and position, measurement density, sensor layout, vibration frequency and noise level. It is found that different factors are highly correlated and thus should be considered comprehensively to achieve optimal detection results. The application of the iFEM-PE method is extended to better adapt to the structural operational state, where multiple groups of vibration responses within a wide frequency band are used. Hybrid data fusion is applied to process the damage index (DI) constructed based on the multiple responses, leading to detection results capable of indicating delamination positions precisely.

Damage evaluation of functionally graded reinforced concrete beams with composite layers

An experimental investigation of functionally graded reinforced concrete beams with layers of engineered cementitious composites was carried out. The main most objective was to evaluate the damage to the beams under free–free constraints using a non-destructive, vibration-based impact method. Damage levels were assessed at 50, 70 and 90% of ultimate load. Dynamic characteristics such as damping, fundamental natural frequencies, mode shapes and frequency response functions at each level were assessed by means of hammer excitation. The investigation showed that damage levels could be accurately evaluated through discrepancies in natural frequency compared to an undamaged beam. A finite-element analysis for the undamaged condition under free–free constraints was undertaken and compared with the experimental natural frequency values to validate the vibration-based test method.

Identification of Size and Location of Bearing Damage via Deep Learning

Rotating machine is one of the most important machines used in various sectors. The most important unit is the rotating part and the shaft held by bearings. Most of the maintenance and repair cost of these machines is related to the replacement and service of bearings. Therefore, it is very important to identify the damaged bearings and determine the location of the damage. Different methods have been developed to monitor their condition, including recording and analyzing the vibration signals of bearings. So far, vibration-based methods have often been used to analyze them. Recently, the use of machine learning and deep learning techniques have been considered. Therefore, in this paper, a convolutional neural network is developed that directly receives the raw information recorded by vibration sensors as input and after analysis, a healthy bearing is detected from a defective one, the location and size of the damage are determined. In this research, the data set of Case Western Reserve University is used to validate the model and the results show that the proposed model has very high accuracy for analysis of samples.

A proposal of feed rate setting for high-speed CNC milling machines by the vibration-based method

High precision and product surface finish quality are the main characteristics of these precision machine tools. Machining with different tool paths at different feed rates is applied to increase productivity. Today, machine tools using high-speed machining methods have been developed to shorten machining times and increase production capacity. However, the vibration of high-speed machine tools is the main cause of product quality reduction. The effect of the machining speed on the vibration diagnostic process of the machine is to choose the appropriate machining mode. This paper describes the vibration analysis methods of machine tools based on simulated results to determine the natural frequencies of vibration and dynamic modeling of the ball-screw feed drive system. Analysis of structural simulation results shows that the higher the rigidity of the machine, the lower the vibration amplitude, and the greater the ability to absorb and suppress vibrations for the machine tool without using dampers. Meanwhile, the combination of the measurement analysis and dynamics modeling on machine tools is an effective method for optimizing speed and controlling machining vibrations. First, the finite element model (FEM) is applied to determine the stiffness analysis and the natural vibration frequency of the machine tool. The simulation results are analyzed and compared with experimental measurement results. The vibration frequency of the ball-screw drive system during machining at different feed rates is also modeled and verified by the measurement results. Finally, the results from the proposed methods are used to predict the vibration frequency of the system, especially the ball-screw through the feed drive or rotational speed. In addition, the purpose of the proposed method is to prevent resonance by way of the forced frequency away from the natural frequency in high-speed machining. This paper proposes a survey method that can be applied for high-speed machine tools with different structures to choose an appropriate feed rate in machining.

Vibration Stimulation as a Non-Invasive Approach to Monitor the Severity of Meniscus Tears.

Musculoskeletal disorders and injuries are one of the most prevalent medical conditions across age groups. Due to a high load-bearing function, the knee is particularly susceptible to injuries such as meniscus tears. Imaging techniques are commonly used to assess meniscus injuries, though this approach suffers from limitations including high cost, need for skilled personnel, and confinement to laboratory or clinical settings. Vibration-based structural monitoring methods in the form of acoustic emission analysis and vibration stimulation have the potential to address the limits associated with current diagnostic technologies. In this study, an active vibration measurement technique is employed to investigate the presence and severity of meniscus tear in cadaver limbs. In a highly controlled ex vivo experimental design, a series of cadaver knees (n =6) were evaluated under an external vibration, and the frequency response of the joint was analyzed to differentiate the intact and affected samples. Four stages of knee integrity were considered: baseline, sham surgery, meniscus tear, and meniscectomy. Analyzing the frequency response of injured legs showed significant changes compared to the baseline and sham stages at selected frequency bandwidths. Furthermore, a qualitative analytical model of the knee was developed based on the Euler-Bernoulli beam theory representing the meniscus tear as a change in the local stiffness of the system. Similar trends in frequency response modulation were observed in the experimental results and analytical model. These findings serve as a foundation for further development of wearable devices for detection and grading of meniscus tear and for improving our understanding of the physiological effects of injuries on the vibration characteristics of the knee. Such systems can also aid in quantifying rehabilitation progress following reconstructive surgery and / or during physical therapy.

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

The bearing of a bridge, as a critical component, is important in the force transformation of the superstructure; however, due to the service condition and repeated impact load, the bearing is prone to be damaged but difficult to detect the damage; the present research has few studies that focused on the damage detection of the structural bearing. Meanwhile, practical engineering is always surrounded by variational environmental conditions, and sometimes, the element and bearing damage both exist in the structure. Thus, these uncertain conditions all cause inaccurate damage identification results using the vibration‐based damage detection method. In order to detect the damage of the structural bearing and improve the precision, firstly, the structural dynamic characteristic equation considering uncertain conditions has been deduced; then, a damage detection framework constructed by the Bayesian theory and perturbation method has been developed in this article; a numerical example of an 8‐span concrete continuous beam and a practical example of I‐40 steel‐concrete composite bridge are utilized to validate the feasibility of the proposed method, and single type and two types of damage cases are studied. The outcomes demonstrate that the damage of structural elements and bearings can be detected with high accuracy. The proposed method is of great applicability and good potential.

Structural damage detection in steel frames using modal strain energy method and genetic algorithm

In recent years, the field of structural health monitoring (SHM) has been receiving the attention of many researchers. In particular, vibration-based structural damage detection methods have proven to be highly effective in civil engineering, mechanical engineering, aerospace engineering, … This paper presents a two-step procedure for damage detection in steel plane frame structures. In the first step, the damage locations in the frame are detected by Modal Strain Energy Index (MSEBI). This index is calculated on the difference from the modal strain energy value of every element before and after damage. In the second step, the damage extents are identified by Genetic Algorithm (GA). The objective function is established on the basis of the change of modal strain energy. A plane steel frame model is built by the finite element method. The results of the frame’s free vibration analysis are the input data of the proposed damage detection procedure. In order to improve the accuracy of the damage localization, the MSEBI is determined using the combination of the frame's first four bending mode shapes. The proposed method gives highly accurate results in detecting the damage’s location and extent for various damage scenarios.

Vibration-based method for story-level damage detection of the reinforced concrete structure

This study aimed to develop a method for the determination of the damaged story in reinforced concrete (RC) structure with ambient vibrations, based on modified jerk energy methodology. The damage was taken as a localized reduction in the stiffness of the structural member. For loading, random white noise excitation was used, and dynamic responses from the finite element model (FEM) of 4 story RC shear frame were extracted at nodal points. The data thus obtained from the structure was used in the damage detection and localization algorithm. In the structure, two damage configurations have been introduced. In the first configuration, damage to the structure was artificially caused by a local reduction in the modulus of elasticity. In the second configuration, the damage was caused, using the Elcentro1940 and Kashmir2005 earthquakes in real-time history. The damage was successfully detected if the frequency drop was greater than 5% and the mode shape correlation remained less than 0.8. The results of the damage were also compared to the performance criteria developed in the Seismostruct software. It is demonstrated that the proposed algorithm has effectively detected the existence of the damage and can locate the damaged story for multiple damage scenarios in the RC structure.

Development of an Instrument to Assess the Stability of Cementless Femoral Implants Using Vibration Analysis During Total Hip Arthroplasty.

Objective: The level of primary implant fixation in cementless total hip arthroplasty is a key factor for the longevity of the implant. Vibration-based methods show promise for providing quantitative information to help surgeons monitor implant fixation intraoperatively. A thorough understanding of what is driving these changes in vibrational behavior is important for further development and improvement of these methods. Additionally, an instrument must be designed to enable surgeons to leverage these methods. This study addresses both of these issues. Method: An augmented system approach was used to develop an instrument that improves the sensitivity of the vibrational method and enables the implementation of the necessary excitation and measurement equipment. The augmented system approach took into account the dynamics of the existing bone-implant system and its interaction with the added instrument. Results: Two instrument designs are proposed, accompanied by a convergence-based method to determine the insertion endpoint. The modal strain energy density distribution was shown to affect the vibrational sensitivity to contact changes in certain areas. Conclusion: The augmented system approach led to an instrument design that improved the sensitivity to changes in the proximal region of the combined bone-implant-instrument system. This fact was confirmed both in silico and in vitro. Clinical Impact: The presented method and instruments address practical intraoperative challenges and provide perspective to objectively support the surgeon’s decision-making process, which will ensure optimal patient treatment.

Vibration-Based Thermal Health Monitoring for Face Layer Debonding Detection in Aerospace Sandwich Structures

This paper investigates the potential of a novel vibration-based thermal health monitoring method for continuous and on-board damage detection in fiber reinforced polymer sandwich structures, as typically used in aerospace applications. This novel structural health monitoring method uses the same principles, which are used for vibration-based thermography in combination with the concept of the local defect resonance, as a well known non-destructive testing method (NDT). The use of heavy shakers for applying strong excitation and infrared cameras for observing thermal responses are key hindrances for the application of vibration-based thermography in real-life structures. However, the present study circumvents these limitations by using piezoelectric wafer active sensors as excitation source, which can be permanently bonded on mechanical structures. Additionally, infrared cameras are replaced by surface temperature sensors for observing the thermal responses due to vibrations and damage. This makes continuous and on-board thermal health monitoring possible. The new method is experimentally validated in laboratory experiments by a sandwich structure with face layer debonding as damage scenario. The debonding is realized by introduction of an insert during the manufacturing process of the specimen. The surface temperature sensor results successfully show the temperature increase in the area of the debonding caused by a sinusoidal excitation of the sandwich structure with the PWAS at the first resonance frequency of the damage. This is validated by conventional infrared thermography. These findings demonstrate the potential of the proposed novel thermal health monitoring method for detecting, localizing and estimating sizes of face layer debonding in sandwich structures.

Damage Sensitive PCA-FRF Feature in Unsupervised Machine Learning for Damage Detection of Plate-Like Structures

Damage detection is important in maintaining the integrity and safety of structures. The vibration-based Structural Health Monitoring (SHM) methods have been explored and applied extensively by researchers due to its non-destructive manner. The damage sensitivity of features used can significantly affect the accuracy of the vibration-based damage identification methods. The Frequency Response Function (FRF) was used as a damage sensitive feature in several works due to its rich yet compact representation of dynamic properties of a structure. However, utilizing the full size of FRFs in damage assessment requires high processing and computational time. A novel reduction technique using Principal Component Analysis (PCA) and peak detection on raw FRFs is proposed to extract the main damage sensitive feature while maintaining the dynamic characteristics. A rectangular Perspex plate with ground supports, simulating an automobile, was used for damage assessment. The damage sensitivity of the extracted feature, i.e. PCA-FRF is then evaluated using unsupervised [Formula: see text]-means clustering results. The proposed method is found to exaggerate the shift of damaged data from undamaged data and improve the repeatability of the PCA-FRF. The PCA-FRF feature is shown to have higher damage sensitivity compared to the raw FRFs, in which it yielded well-clustered results even for low damage conditions.

Dynamic analysis of rotor system with slant cracked shaft

Abstract The anisotropy, plane action and operating time of revolving machinery depend on the performances that identify the signs of faults. Crack is one of the peaks unreliable and insecure faults that reduction working life of component or machine systems, thereby most important to impending injury to person if it is invisible. Crack or cracks existent in a machine or system brings a modification in the mass, damping, and stiffness of the rotor, and subsequently measureable changes seem in the modal things (natural frequencies, modal damping, and mode shapes). Many methods and models have been settled to detect a crack (or cracks) in stationary and rotating systems. Identification of cracks is usually visual inspection; techniques and models are based on vibration-based methods such as destructive method. Optical examination is a time overwhelming method and determining of mode shape as well as structural deflection is tough rather than calculating frequency. Finite Element Analysis of solid shaft such as slant cracked shaft at various rpm is done in this work. Healthy and slant cracked shaft is modeled and analyzed with numerical method. FFT analyzer is used to record the results of vibration, which are used to analyze the vibration characteristics of slant cracks. From the comparison of ANSYS & FFT results 23.03% maximum variations were saw for healthy Shaft & 8.36% to 26.96% increasing variation were saw for 45° to 60° Orientation for 100 mm Crack for Defected Shaft. The investigational results openly exhibit the ability of the recommended methodology for the credentials and position of cracks in fixed and revolving shafts.

A Comparative Study on Vibration-Based Damage Identification and Localization Methods

This paper outlines various vibration-based methods for detecting and locating damage in mechanical and civil structural systems. The basic premises of these methods are that any changes in physical characteristics (mass and stiffness) of the structure will induce detectable changes in the modal properties of the structure (natural frequency, mode shape and damping). A comparative study of eight extensively used damage identification methods is done on a simulated simply supported beam to demonstrate the validity and effectiveness. The outcomes of various methods are compared in terms of damage detection and localization under single and multiple damage scenarios.

Remaining useful life (RUL) prediction of internal combustion engine timing belt based on vibration signals and artificial neural network

Timing belt rupture, which can develop quickly and cause severe harm to various engine components, usually occurs unexpectedly and without prior warning signs. Due to the rapid occurrence of timing belt rupture, fault diagnosis strategies are not indeed efficient. In this paper, a vibration-based intelligent method has been proposed to predict the remaining useful life (RUL) of the timing belt using data mining techniques and multi-layer perceptron neural network (MLP-NN). To achieve this goal, two categories of experimental tests were designed and carried out on the timing belt, namely, fault thresholding (FT) and accelerated life (AL) tests. FT test was performed by comparing the defect-free belt vibration signals with those of a faulty belt to determine the failure threshold. This is while, in the AL test, the engine was continuously run with a defect-free timing belt until initiation of rupture or damage was detected. Four feature functions, regarded as timing belt health indicators, were applied to the collected vibration signals, namely, energy, impulse factor, root mean square, and FM4. The extracted features were then fed to the MLP-NN to predict the timing belt RUL by continuously comparing the feature values and the failure threshold. The results showed that the proposed method is able to predict the timing belt RUL with an accuracy of 90%. In addition, data predicted by the MLP-NN showed high correlation with the actual measured data, which emphasizes the robustness and precision of the proposed method for timing belt RUL prediction.

Local vibration mode pairs for damage identification in axisymmetric tubular structures

Tubular structures are widely used in infrastructure, especially for pipes and marine installations. Corrosion is a key damage type for these structures, and if undetected may cause structural deficiency or even collapse. This paper investigates the effects of localised corrosion on the vibration properties of axisymmetric tubular structures and proposes a novel baseline-free damage identification method to overcome the fact that the difference between undamaged and damaged properties is usually small and contaminated by noise. The proposed vibration-based method exploits the phenomenon of repeated mode pairs which is peculiar to axisymmetric tubular structures with non-axisymmetric damage. Unlike intact tubular structures, it is found that each vibration mode of a locally damaged tubular structure comprises of two components: active and passive. The active component is sensitive to the local damage and can be used to infer damage existence while the passive component is retentive of the undamaged pipe's properties. Therefore, the passive component of a damaged pipe’s local vibration mode pair (LVMP) can be used to predict its baseline (undamaged) modal properties, which in this research was achieved within a margin of ±2%, whereas the active component confirms damage existence. The work also establishes the criteria for validation of LVMPs through experimental tests involving various corrosion scenarios ranging from longitudinal strips to through-thickness pits. Based on the obtained results, it is proposed that the properties of LVMPs can be linked to corrosion-like local damage in axisymmetric tubular structures, underpinning a new damage detection and identification approach.

Vibration-based Method for Mechanochemical Coating of Metallic Surfaces

Vibration-based Method for Mechanochemical Coating of Metallic Surfaces

Evaluation of Cable Force Changes Effects on Cable Stayed Bridge

The proposed bridge, which is cable stayed bridge crosses the Hlaing River that flows through Western Yangon. It was completed in 2000 and is currently used to connect Insein Township with Hlaing Tharyar Township. It has the 20 years’ service life. It requires the inspection and the evaluation of the real condition of the structure. As cable element plays an important role in cable structures, evaluation of the real state of the stay cable is one of the main focuses of the cable stayed bridge. Firstly, in the research work all cables are inspected to evaluate the current condition of the cables with included visual inspection and vibration-based cable force measurement method. With the help of static and moving load analysis, the effect of force change cables in which the successive force changes are considered, and the possible cable loss effect on the structural behavior of the bridge are also investigated. The finite element model of the cable stayed bridge is developed based on the geometric shape and material properties from MOC and is modelled with finite element software MIDAS Civil. The tension forces obtained by inspection over years (2000 to 2018) using vibration-based measurements method are compared with the measured intact cable forces. According to the results of the data analysis, it is observed that the cables force variations of the seven cables are abnormal conditions. In order to evaluate the condition of a bridge effected by cable force variation, the two parameters are considered; percentage increase in tension stress of all cables and percentage increase in deflection of the deck. The present study describes the structural response of the bridge in order to evaluate the actual safety of the bridge with abnormal force change cables, and also examines the consequences of one cable failure. Doi: 10.28991/cej-2020-03091609 Full Text: PDF