bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic modelling of two-stage gear systems with localized wear defects
Authors: Huangfu Y F , Yu X L , Dong X J , Long X H , Peng Z K 
Published: May 2022

Abstract
Considering the profile deviation induced by localized wear defects, a dynamic model of two-stage gear systems is established. In the proposed dynamic model, the time-varying mesh stiffness of worn gears is calculated by the loaded tooth contact analysis method. The mesh stiffness and the non-loaded transmission error are regarded as the time-varying stiffness excitation and the displacement excitation, respectively. Based on the proposed dynamic model, the dynamic responses of the two-stage gear system with localized wear defects are acquired. The simulated vibration responses are compared to the measured results to test the effectiveness of the proposed dynamic model. It is found that the proposed model can yield similar fault feature with the experiment, which shows the validity of the proposed dynamic model. This paper can afford theoretical basis for the fault mechanism and dynamic characterization of localized wear defects.
An abnormal vibration diagnosis and control method for internal combustion power plant
Authors: Xu Fanghui , Dong Dawei , Yan Bing , Song Shizhe , Zhang Rui , Huang Yan 
Published: May 2022

Abstract
Focusing on the difficulty in vibration control of internal combustion power plant because of its diverse substructures and complex excitation, an abnormal vibration diagnosis and attenuation method based on the system’s whole-body vibration signals is proposed. The characteristics of the exciting forces, such as toppling torque, inertia force (or moment) and coupling centrifugal force, are analyzed. The resonance frequency distribution of the power unit is obtained by modal analysis. Then an expression that could reveal the relationship between the whole-body vibration intensity and the exciting force amplitude is established, and conclusion is drawn that different excitations would drive the system to vibrate at different frequencies. Based on this basic relation, a fault diagnosis method relying on comprehensive analysis of vibration signals in both time and frequency domain is proposed. Vibration attenuation methods targeted at specific faults are also put forward. Finally, the validity of the proposed method is verified by applying it to a 12V280 diesel generator set.
Construction and application of knowledge graph for fault diagnosis of turbine generator set based on ontology
Authors: Wang J , Yan C F , Zhang Y M , Li Y J , Wang H B 
Published: May 2022

Abstract
Aiming at the problems of complex structure and multi-source heterogeneity, imperfect knowledge representation, single knowledge extraction method, and difficulty of sharing and reuse in the knowledge field of turbine generator set fault diagnosis. The construction of knowledge graph is studied from multiple dimensions such as experts, fault characteristics, diagnosis techniques, research results, and solutions in the field for fault diagnosis knowledge of turbine generator set. And an ontology model of fault diagnosis knowledge for the turbine generator set is constructed. The entities, attributes, and relationships of the fault diagnosis knowledge graph for the turbine generator set are represented based on the model. The knowledge graph data are stored by the Neo4j graph database. The problems caused by multi-source and heterogeneous knowledge, fuzzy knowledge, and difficulty sharing, was solved in this field. The knowledge search system and automated quiz system based on knowledge graph are developed using the B/S framework. Many functions are realized by the knowledge graph, such as knowledge correlation, intelligent retrieval, visual display, and automated quiz, which improves the service and sharing ability of fault diagnosis knowledge for turbine generator set. Finally, the effectiveness and superiority of the system are verified by an example of a turbine generator set.
A new strategy to eliminate interference of varying operating conditions during multivariate signal processing-based fault diagnosis approach
Authors: Yuan Rui , Lv Yong , Yang Di , Lu Zhiwen 
Published: May 2022

Abstract
Multivariate signal acquisition and processing of faulty mechanical components extract more fault characteristic information, contributing to comprehensive and accurate fault diagnosis. Multivariate empirical mode decomposition (MEMD) is an effective approach in the field of multivariate signal processing. While nuisance attribute projection (NAP) can be used to filter out the components of nuisance attributes caused by varying operating condition. This paper proposes a new strategy for eliminating interference during multivariate signal processing- based fault diagnosis approach. MEMD is used to decompose multivariate signal of faulty rolling bearing into multivariate IMFs depicting dynamical properties, with extracting quantitative features of multivariate IMFs. Then, NAP is used to eliminate nuisance attributes of varying operating conditions in the constructed feature matrices. To illustrate the effectiveness and superiority of the proposed new strategy, the extracted features are presented by t-distribution stochastic neighbour embedding (t-SNE). The dimensionalities of feature vectors are reduced to 3 on account of the visualization simplicity. The comparison analysis during application researches can validate the superiority of the proposed novel strategy.
Multi-fault Classification of Train Wheelset System
Authors: Xiong Libo , Lv Lumei , Jiang Yuhan , Hua Chunrong , Dong Dawei 
Published: May 2022

Abstract
The condition monitoring and faults diagnosis of wheelset are of great significance for the safe and stable operation of trains. Aiming at the axle crack, wheel flat, wheel out-of-roundness and their coupling faults in wheelset system, this paper proposes a method to diagnose these multiple faults simultaneously. Firstly, the dynamic model of a wheelset system with flat and out-of-roundness is established in SIMPACK software to analyze the fault characteristics of these two typical wheel damages. And the wheel flat and out-of-roundness are equivalent to displacement excitation and then loaded into the finite element (FE) model of the cracked wheelset. The vibration responses of the cracked wheelset with flat and out-of-roundness are solved in ABAQUS software. Then, the simulated multi-fault vibration data of wheelset are input into a Light-GBM model to realize the faults classification of axle crack, wheel flat, wheel out-of-roundness and their coupling faults. Finally, the wheelset vibration signals under the conditions of health, axle crack, wheel flat, and crack-flat coupling fault are collected from an experimental bench to verify the proposed method. This work can provide a basis for multi-fault classification and on-line health monitoring of trains.
Digital Twin-Driven Crack Monitoring for Rotating Blade: An L1 regularization Method
Authors: Pang Ding , Yang Laihao , Yan Ruqiang , Chen Xuefeng , Yang Zhibo , Sun Yu 
Published: May 2022

Abstract
Crack-related damage of rotating blade is one of the most common failures of aeroengines. However, conventional blade crack monitoring methods are challenging to obtain the exact location and severity of the crack. In this study, a digital twin-driven blade crack monitoring method using the L1 regularization and sensitivity-based model updating is proposed to quantify the location and severity of crack damage for rotating blade. First and foremost, a digital twin model framework for rotating blade is established, including physical entity, digital entity, and the connection between them. Then a digital entity based on finite element model and an L1 regularized objective function based on the residual of natural frequencies are constructed, where the damage parameter of crack could be obtained by using the sensitivity-based model updating technology, hereby the location and severity of crack could be determined. Finally, numerical simulations are carried out, which verify that the proposed method is capable of accurately identifying the location and severity of crack, and could provide a reference for further research in this field.
On-board vibration-based remaining useful life estimation of hollow worn railway vehicle wheels
Authors: Iliopoulos Ilias A. , Sakellariou John S. , Fassois Spilios D. , Chronopoulos Elias , Deloukas Alexandros , Giannakis Christos , Kapiris Dimosthenis , Kritikakos Kiriakos , Leoutsakos George , Tountas Elias , Vlachospyros Georgios 
Published: May 2022

Abstract
The feasibility of on-board remaining useful life (RUL) estimation of hollow worn railway vehicle wheels under varying travelling speed using vibration signals from the vehicle’s bogie, is for the first time explored. A variant of the Multiple Model Power Spectral Density (MM-PSD) method is employed, treating RUL estimation as a multi-class classification problem, where each class corresponds to a specific condition of hollow worn wheels associated with an empirical remaining mileage. The method classifies the current, unknown, condition of hollow worn wheels to one of the available by examining the vehicular dynamics similarity among them through the amplitude of the sharp periodic valleys (antiresonances) induced due to the Wheelbase Filtering (WF) effect. The vibration signals are obtained from Monte Carlo experiments based on the high-fidelity SIMPACK software, while the remarkable performance of the method is demonstrated via thousands of inspection cases.
Feature Extraction from Charging Profiles for State of Health Estimation of Lithium-ion Battery
Authors: Wang Zuolu , Feng Guojin , Sun Xiuquan , Zhen Dong , Gu Fengshou , Ball Andrew D. 
Published: May 2022

Abstract
Accurate state of health (SOH) estimation of lithium-ion batteries is of great importance to ensure the reliability and safety of battery management systems (BMS). The difficulty of modelling the complex degradation mechanism has made the data-driven methods gain much attention in battery SOH prediction. To improve the estimation accuracy of battery SOH, extracting the suitable health indicators is still a challenging work. In this work, the health indication features are attracted from the charging voltage profile based on the experimental data measured under constant current charging mode. Subsequently, the Pearson correlation coefficient is used to evaluate the relationships between the extracted health features and battery capacity, thus selecting the most effective health features for establishing the prediction models. Finally, the battery SOH is estimated using a Gaussian process regression (GPR) method. The estimation results with R
2 of 1 and lower mean absolute error (MAE) and maximum error (MAX) provide higher accuracy based on the extracted health feature.
Directional wavelet modal curvature method for damage detection in plates
Authors: Yang Gang , Yang Zhi-bo , Zhu Ming-feng , Tian Shao-hua , Chen Xue-feng 
Published: May 2022

Abstract
Vibration-based damage detection using the 2D modal curvature has become a research focus. However, the traditional methods based on modal curvature lack the sensitivity to direction of the damage. To address this problem, a directional 2D Morlet wavelet modal curvature is proposed in this paper. The directional wavelet modal curvatures show the following merits: robust to noise interference and sensitive to direction of damage. By the numerical simulation, the efficiency of the proposed method is demonstrated in the plate-like structure.
Toward on-orbit structural health monitoring of inflatablestructures using electromechanical impedance method
Authors: Li Pengfei , Yan Jinwei , Cao Shancheng , Xu Chao 
Published: May 2022

Abstract
Inflatable structures are promising candidates for a wide range of aerospace vehicles due to their volume/weight savings, high storage rate, low cost, and easy deployment. However, space survivability is a major concern for such structures. Therefore, structural health monitoring (SHM) of inflatable structures has been increasingly studied. Electromechanical impedance (EMI) method is one of the most-popular SHM methods, which can promptly and accurately identify early structural damage. Nevertheless, the necessary of using bulky, expensive and high-power commercial impedance analyzer hampers electromechanical impedance method from being used in-situ and online. In recent years, several miniature impedance measurement devices have been developed for practical applications. However, the aerospace application of such devices is still absence. In this paper, a miniature integrated impedance measurement printed circuit board (PCB) prototype toward on-orbit SHM of inflatable structures is developed. The proposed PCB prototype consists of impedance measurement module, in which the AD5933 chip and the ADG708 chip were adopted to achieve impedance signals. In this case, the PCB prototype can effectively measure the electrical impedance of up to six channels of the piezoelectric transducers at 0.2 ∼ 2V excitation voltage in the frequency range of 10 ∼ 100kHz. Moreover, an inflatable boom was taken as the inspected structure, and a PZT-5H was used as the piezoelectric transducer for experimental validation. The results demonstrate that the proposed PCB prototype works functionally and can accurately quantify the simulated damage on the inflatable boom. In addition, it is found that the miniature integrated impedance measurement PCB prototype developed in this paper has the advantages of low bulk and less weight, which can be further enhanced to satisfy the demands of on-orbit SHM of inflatable structures.
A circumferential SH wave piezoelectric transducer array for damage detection in large-diameter pipes
Authors: Du Yuehao , Kan Qianhua , Kang Guozheng , Miao Hongchen 
Published: May 2022

Abstract
Torsional or longitudinal wave-based inspection is an effective method for rapid defect screening in pipes, but it has difficulty to locate the circumferential position of a defect due to the axially symmetric properties of torsional and longitudinal modes. In order to overcome this problem, several flexural-wave-based focusing methods have been proposed while multiple mode propagation associated with dispersion has to be taken into account in them, which increases the complexity of identifying defects in practical applications. In this work, based on our recently developed bidirectional SH wave piezoelectric transducer (BSH-PT), a fundamental circumferential shear horizontal (CSH0) wave linear phased array was proposed for in-situ defect localization in large-diameter pipes. Firstly, the working principle of the BSH-PT array was presented and its performance on defects detection was assessed by simulations using the total focusing method (TFM). Then, experiments were conducted to examine the array’s performance. Results showed that the proposed BSH-PT array can detect multiple defects simultaneously at varied frequencies. Finally, a method for eliminating the mirrored artifact was proposed and then validated by both simulations and experiments on pipes. Considering the quasi-nondispersive character of CSH0 wave and the desirable performance of the BSH-PT on exciting and receiving pure CSH0 wave, the proposed CSH0 wave phased array may be useful in structural health monitoring (SHM) of large-diameter pipes such as pressure vessels and oil tanks.
Nonlinear assessment of “breathing” fatigue crack using steady-state vibration responses
Authors: Lu Q , Cao M , Xu W 
Published: May 2022

Abstract
Fatigue cracks can occur in structural components under long-term cyclic loads. Such fatigue cracks can open and close like "breathing" under harmonic excitations. Fatigue cracks can develop and jeopardize safety of structures. Therefore, there is a great need to assess fatigue cracks especially in their early stages. Higher harmonics have been widely used as crack indicators, however, slight opening-closing motion can lead to weak higher harmonics with much less amplitudes compared to the first harmonics. In these situations, higher harmonics can be barely identified for crack detection. Addressing this problem, this study develops the damage assessment approach based on singular spectrum analysis to distinguish crack-induced nonlinearities in steady-state vibration responses, whereby nonlinear assessment of the crack can be achieved. The capability of the approach is experimentally validated on a steel beam with a “breathing” fatigue crack, steady-state velocity responses of which are acquired through non- contact laser measurement using a Doppler laser vibrometer.
A two-step identification method for crack parameter identification of train axles
Authors: Zhang Wei , Dong Dawei , Song Shizhe , Xiong libo 
Published: May 2022

AbstractIn this paper, a crack parameter identification method based on the coordinate of 1x intersections and Kriging surrogate model with enhanced samples is proposed to solve the crack parameter identification problem of train axles in start-stop condition. The location of the crack is identified in the first step by the x-coordinate of the linear intersection of 1x frequency components. Then, the intersecting coordinates and rigid constraint points were used to solve response curves of equal crack depth, and numerous enhanced samples of same depth at different positions were obtained to establish a Kriging model. Finally, the crack depth was directly obtained by the Kriging model. In this paper, response curve s of equal crack depth is proposed according to the symmetry of the train structure, which greatly reduces the number of samples needed to construct the Kriging model. Numerical simulation and experimental results demonstrate the effectiveness and robustness of the proposed method.
Structural Health Monitoring of Large Structures via mmWave Sensing
Authors: Li Songxu , Xiong Yuyong , Ren Zesheng , Peng Zhike 
Published: May 2022

Abstract
Vibration and deformation measurement are of great significance for structural health monitoring (SHM). While the existing accelerometer, laser and vision-based approaches have limitations in multi-point vibration measurement, efficiency and environmental adaptability, especially for large structures. In this paper, we present a method for structural health monitoring with multi-point vibration and deformation measurement via millimetre- wave sensing. First, we describe the mathematical model and the principle of multi-target synchronous vibration and deformation monitoring. Second, with a built prototype of mmWave sensing system, we evaluate our method with both laboratory and field tests. The experimental results of different amplitudes, frequencies and velocities show that our approach can accurately monitor the vibration and deformation of multi-point with μm-level accuracy. The field test of Shanghai Songpu Bridge is provided to further validate the effectiveness of the method, offering a novel approach for contactless vibration and deformation monitoring of large structures in SHM.
Output-only modal analysis of the Humen Bridge from video measurement
Authors: Lin Guanfu , Wang Li , Lu Zhong-Rong 
Published: May 2022

Abstract
Video-based vibration testing is a promising non-contact method for structural health monitoring. This article develops an innovative methodology for estimating the structural modal parameters from videos without recovering the responses of structures. Firstly, an image processing (i.e., Gaussian smoothing) are adopted to smooth frames and alleviate the noises. Secondly, several regions of interest (ROIs) contained the projection area of structure are selected, and edge detection is performed to that to reduce the size of vision data. Then under some assumptions, the reduced vision data can be subjected to the frequency domain decomposition (FDD) similar to the structural modal analysis to identify the modal parameters of structure. Moreover, the structural mode shapes are recovering from such decomposition. The feasibility and accuracy of the proposed method were validated by a field experiment on the Humen Bridge in Guangzhou, China.
A new explanation of Rolling Contact Fatigue in bearing steels based on multiscale models
Authors: Sun Yachao , Cao Hongrui 
Published: May 2022

Abstract
Rolling Contact Fatigue (RCF) is harmful and inevitable to bearings and usually results in the initiation of subsurface damage. The root cause for this damage is the cumulative plastic deformation accentuated by carbides. This paper gives a new explanation of RCF based on multiscale models. The distribution and change law of subsurface shear stress in bearing steels was previously investigated by a finite element model. A two-phase atomic model of bcc-Fe and cementite was built. Ten alternating shear load cycles were designed to explore the mechanisms of the cyclic plastic accumulation when the atomic model was initially in the elastic, elastic- plastic and plastic stages, respectively. The results show that cyclic softening diversely occurs in all three types of stress responses. Severe cyclic shear deformation eventually leads to earlier cyclic softening and stress yield, which might be the micromechanism of plastic accumulation and RCF in bearing steels.
The effect of strain rate on the mechanical property of PDMS and PDMS/graphene: A molecular dynamics study
Authors: Han Tianrui , Sun Yu , Zhao Zhou , Chen Xuefeng 
Published: May 2022

Abstract
Molecular dynamics simulation was used to study the mechanical behavior of polydimethylsiloxane (PDMS) and PDMS/graphene at different strain rates. Firstly, the mechanical behavior of PDMS under uniaxial tension at different strain rates (109 /s-1010 /s) was studied. Secondly, graphene with a mass ratio of 3.62 was added to PDMS to study the mechanical behavior of the mixed system under uniaxial tension at different strain rates (108/s - 1010 /s). The results showed that the Young’s modulus and tensile strength of PDMS were greatly affected by strain rate. After adding graphene into PDMS, the mechanical properties of the blends at different strain rates were almost the same. This work may provide a deeper understanding on mechanical property of PDMS composites.
Microstructure of laser cladding nickel-based superalloy: characterization, finite element modeling, and fatigue analysis
Authors: Zhang Miao , Liu Shujie 
Published: May 2022

Abstract
After laser cladding, the mechanical response of nickel-based single crystal superalloy is more complex when the loading direction is perpendicular to the columnar grain growth direction. In order to understand the deformation at grain level, a representative volume element (RVE) model based on the randomness of columnar grain texture was established for DD6 single crystal alloy, and the finite element model simulation of crystal plasticity (CPFEM) was performed. The results show that the stress and strain responses of the cladding microstructure are related to the grain distribution. The orientation difference between columnar grains in the epitaxial growth microstructure leads to non-uniform deformation and local stress concentration. The greater the crystal orientation difference is, the more obvious the stress concentration phenomenon is. On this basis, the statistical standard deviation of strain component is chosen to represent the fatigue damage of material, and the relationship between the statistical standard deviation of strain component and the external load strain is studied, which has certain reference value for the fatigue damage research of micro-cladding.