SDHM Structural Durability and Health Monitoring最新文献

{"title":"Multi-Mode Guided Waves Based Reference-Free Damage Diagnostic Imaging in Plates","authors":"Jiaqi Zhang, Kehai Liu, Chang Gao, Zhanjun Wu, Yuebin Zheng, D. Gao","doi":"10.32604/sdhm.2019.05142","DOIUrl":"https://doi.org/10.32604/sdhm.2019.05142","url":null,"abstract":"Probability-based diagnostic imaging (PDI) is one of the most well-known damage identification methods using guided waves. It is usually applied to diagnose damage in plates. The previous studies were dependent on the certain damage index (DI) which is always calculated from the guided wave signals. In conventional methods, DI is simply defined by comparing the real-time data with the baseline data as reference. However, the baseline signal is easily affected by varying environmental conditions of structures. In this paper, a reference-free diagnostic imaging method is developed to avoid the influence of environmental factors, such as temperature and load conditions. The DI is defined based on the mode conversion of multi-mode guided waves with realtime signals without baseline signals. To improve the accuracy of diagnosis, two terms are included in the reference-free DI. One is called energy DI, which is defined based on the feature of signal energy. The other is called correlation DI and is defined based on the correlation coefficient. Then the PDI algorithm can be carried out instantaneously according to the reference-free DI. The real-time signals which are used to calculate DI are collected by the piezoelectric lead zirconate titanate (PZT) transducers placed on both sides of a plate. The numerical simulations by the finite element (FE) method on aluminum plates with PZT arrays are performed to validate the effectiveness of the reference-free damage diagnostic imaging. The approach is validated by two different arrays: a circle network and a square network. The results of diagnostic imaging are demonstrated and discussed in this paper. Furthermore, the advantage of reference-free DI is investigated by comparing the accuracy of defined reference-free DI and energy DI.","PeriodicalId":35399,"journal":{"name":"SDHM Structural Durability and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69900287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kinematic Analysis and Rock Mass Classifications for Rock Slope Failure at USAID Highways","authors":"I. Rusydy, N. Al-Huda, M. Fahmi, Naufal Effendi","doi":"10.32604/sdhm.2019.08192","DOIUrl":"https://doi.org/10.32604/sdhm.2019.08192","url":null,"abstract":"","PeriodicalId":35399,"journal":{"name":"SDHM Structural Durability and Health Monitoring","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69900660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vibration Based Tool Insert Health Monitoring Using Decision Tree and Fuzzy Logic","authors":"Kundur Shantisagar, R. Jegadeeshwaran, G. Sakthivel, T. M. A. Manghai","doi":"10.32604/sdhm.2019.00355","DOIUrl":"https://doi.org/10.32604/sdhm.2019.00355","url":null,"abstract":"The productivity and quality in the turning process can be improved by utilizing the predicted performance of the cutting tools. This research incorporates condition monitoring of a non-carbide tool insert using vibration analysis along with machine learning and fuzzy logic approach. A non-carbide tool insert is considered for the process of cutting operation in a semi-automatic lathe, where the condition of tool is monitored using vibration characteristics. The vibration signals for conditions such as heathy, damaged, thermal and flank were acquired with the help of piezoelectric transducer and data acquisition system. The descriptive statistical features were extracted from the acquired vibration signal using the feature extraction techniques. The extracted statistical features were selected using a feature selection process through J48 decision tree algorithm. The selected features were classified using J48 decision tree and fuzzy to develop the fault diagnosis model for the improved predictive analysis. The decision tree model produced the classification accuracy as 94.78% with five selected features. The developed fuzzy model produced the classification accuracy as 94.02% with five membership functions. Hence, the decision tree has been proposed as a suitable fault diagnosis model for predicting the tool insert health condition under different fault conditions.","PeriodicalId":35399,"journal":{"name":"SDHM Structural Durability and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69899562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Fatigue Damage Model for FRP Composite Laminate Systems Based on Stiffness Reduction","authors":"Ying Zhao, M. Noori, Wael A. Altabey, Ramin Ghiasi, Zhishen Wu","doi":"10.32604/SDHM.2019.04695","DOIUrl":"https://doi.org/10.32604/SDHM.2019.04695","url":null,"abstract":"This paper introduces a stiffness reduction based model developed by the authors to characterize accumulative fatigue damage in unidirectional plies and (0/θ/0) composite laminates in fiber reinforced polymer (FRP) composite laminates. The proposed damage detection model is developed based on a damage evolution mechanism, including crack initiation and crack damage progress in matrix, matrix-fiber interface and fibers. Research result demonstrates that the corresponding stiffness of unidirectional composite laminates is reduced as the number of loading cycles progresses. First, three common models in literatures are presented and compared. Tensile viscosity, Young’s modulus and ultimate tensile stress of composites are incorporated as key factors in this model and are modified in accordance with temperature. Four types of FRP composite property parameters, including Carbon Fiber Reinforced Polymer (CFRP), Aramid Fiber Reinforced Polymer (AFRP), Glass Fiber Reinforced Polymer (GFRP), and Basalt Fiber Reinforced Polymer (BFRP), are considered in this research, and a comparative parameter study of FRP unidirectional composite laminates with different off-angle plies using control variate method are discussed. It is concluded that the relationship between the drop in stiffness and the number of cycles also shows three different regions, following the mechanism of damage of FRP composites and the matrix is the dominant factor determined by temperature, while fiber strength is the dominant factor that determine the reliability of composite.","PeriodicalId":35399,"journal":{"name":"SDHM Structural Durability and Health Monitoring","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69900260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring of Real-Time Complex Deformed Shapes of Thin-Walled Channel Beam Structures Subject to the Coupling Between Bi-Axial Bending and Warping Torsion","authors":"Rui Lu, Zhanjun Wu, Qi Zhou, Hao Xu","doi":"10.32604/sdhm.2019.06323","DOIUrl":"https://doi.org/10.32604/sdhm.2019.06323","url":null,"abstract":"","PeriodicalId":35399,"journal":{"name":"SDHM Structural Durability and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69900765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crack Detection and Localization on Wind Turbine Blade Using Machine Learning Algorithms: A Data Mining Approach","authors":"Joshuva Arockia Dhanraj, V. Sugumaran","doi":"10.32604/SDHM.2019.00287","DOIUrl":"https://doi.org/10.32604/SDHM.2019.00287","url":null,"abstract":"Wind turbine blades are generally manufactured using fiber type material because of their cost effectiveness and light weight property however, blade get damaged due to wind gusts, bad weather conditions, unpredictable aerodynamic forces, lightning strikes and gravitational loads which causes crack on the surface of wind turbine blade. It is very much essential to identify the damage on blade before it crashes catastrophically which might possibly destroy the complete wind turbine. In this paper, a fifteen tree classification based machine learning algorithms were modelled for identifying and detecting the crack on wind turbine blades. The models are built based on computing the vibration response of the blade when it is excited using piezoelectric accelerometer. The statistical, histogram and ARMA methods for each algorithm were compared essentially to suggest a better model for the identification and localization of crack on wind turbine blade.","PeriodicalId":35399,"journal":{"name":"SDHM Structural Durability and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69899612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flexural Property of String Beam of Pre-Stressed Glulam Based on Influence of Regulation and Control","authors":"N. Guo, Wenbo Wang, H. Zuo","doi":"10.32604/sdhm.2019.04640","DOIUrl":"https://doi.org/10.32604/sdhm.2019.04640","url":null,"abstract":"Applying pre-stress in glulam beam can reduce its deformation and make full use of the compressive strength of wood. However, when the glulam with low strength and the pre-stressed steel with high strength form combined members, materials of high strength can’t be fully utilized. Therefore, this study puts forward the idea of regulating and controlling string beam of pre-stressed glulam. By regulating and controlling the pre-stress, a part of the load borne by the wood is allocated to the pre-stressed tendon, which is equivalent to completing a redistribution of internal force, thus realizing the repeated utilization of the wood strength and the full utilization of the strength of the high-strength pre-stressed tendon. The bending experiments of 10 beams under 5 working conditions are carried out. The failure mode, bearing capacity and deformation of the beams are analyzed. The results show that 90% of beams are deformed under compression. The ultimate load of the regulated and controlled beam is obviously larger than that of the unregulated beam, and the ultimate load of the beam increases with the increase of the degree of regulation and control. Compared with that of the unregulated beams, the ultimate load of beams regulated by 7.5%-30% increases by 25.42%-65.08%, and the regulated and controlled effect is obvious. With the increase of the regulation and control amplitude of pre-stress, the stiffness of string beam of pre-stressed glulam increases. In addition, with the increase of the regulation and control amplitude, the compression height of the beam increases before the failure, and it reaches the state of full-section compression at the time of failure, giving full play to the compressive property of the glulam. At the end of the experiment, the constitutive relation which can reflect the anisotropy of the wood is established combined with the experimental data. The finite element analysis of the beam under 7 working conditions is carried out by using ABAQUS finite element program, and the influence of the regulation and control amplitude on the stress distribution and ultimate bearing capacity of the beam is discussed.","PeriodicalId":35399,"journal":{"name":"SDHM Structural Durability and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69899806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seismic Reliability Assessment of Inelastic SDOF Systems Subjected to Near-Fault Ground Motions Considering Pulse Occurrence","authors":"Jilei Zhou, Chuansong Sun, X. Dai, Guohai Chen","doi":"10.32604/sdhm.2019.05171","DOIUrl":"https://doi.org/10.32604/sdhm.2019.05171","url":null,"abstract":"The ground motions in the orientation corresponding to the strongest pulse energy impose more serious demand on structures than that of ordinary ground motions. Moreover, not all near-fault ground motion records present distinct pulses in the velocity time histories. In this paper, the parameterized stochastic model of near-fault ground motion with the strongest energy and pulse occurrence probability is suggested, and the Monte Carlo simulation (MSC) and subset simulation are utilized to calculate the first excursion probability of inelastic single-degree-of-freedom (SDOF) systems subjected to these types of near-fault ground motion models, respectively. Firstly, the influences of variation of stochastic pulse model parameters on structural dynamic reliability with different fundamental periods are explored. It is demonstrated that the variation of pulse period, peak ground velocity and pulse waveform number have significant effects on structural reliability and should not be ignored in reliability analysis. Then, subset simulation is verified to be unbiased and more efficient for computing small reliable probabilities of structures compared to MCS. Finally, the reliable probabilities of the SDOF systems with different fundamental periods subjected to impulsive, non-pulse ground motions and the ground motions with pulse occurrence probability are performed, separately. It is indicated that the ground motion model with the pulse occurrence probability can give a rational estimate on structural reliability. The impulsive and ordinary ground motion models may overestimate and underestimate the reliability of structures with fundamental period much less than the mean pulse period of earthquake ground motions.","PeriodicalId":35399,"journal":{"name":"SDHM Structural Durability and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69900111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"System Identification of Heritage Structures through AVT and OMA: A Review","authors":"Vinay Shimpi, M. Sivasubramanian, S. B. Singh","doi":"10.32604/sdhm.2019.05951","DOIUrl":"https://doi.org/10.32604/sdhm.2019.05951","url":null,"abstract":"In this review article, the past investigations carried out on heritage structures using Ambient Vibration Test (AVT) and Operational Modal Analysis (OMA) for system identification (determination of dynamic properties like frequency, mode shape and damping ratios) and associated applications are summarized. A total of 68 major research studies on heritage structures around the world that are available in literature are surveyed for this purpose. At first, field investigations carried out on heritage structures prior to conducting AVT are explained in detail. Next, specifications of accelerometers, location of accelerometers and optimization of accelerometer networks have been elaborated with respect to the geometry of the heritage structures. In addition to this, ambient vibration loads and data acquisition procedures are also discussed. Further, the state of art of performing OMA techniques for heritage structures is explained briefly. Furthermore, various applications of system identification for heritage structures are documented. Finally, conclusions are made towards errorless system identification of heritage structures through AVT and OMA.","PeriodicalId":35399,"journal":{"name":"SDHM Structural Durability and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69900454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seismic Vulnerability Analysis of Single-Story Reinforced Concrete Industrial Buildings with Seismic Fortification","authors":"Jieping Liu, Lingxin Zhang, Haohao Zhang, Tao Liu","doi":"10.32604/sdhm.2019.04486","DOIUrl":"https://doi.org/10.32604/sdhm.2019.04486","url":null,"abstract":"As there is a lack of earthquake damage data for factory buildings with seismic fortifications in China, seismic vulnerability analysis was performed by numerical simulation in this paper. The earthquake-structure analysis model was developed with considering the influence of uncertainties of the ground motion and structural model parameters. The small-size sampling was conducted based on the Latin hypercube sampling and orthogonal design methods. Using nonlinear analysis, the seismic vulnerability curves and damage probability matrix with various seismic fortification intensities (SFI) were obtained. The seismic capacity of the factory building was then evaluated. The results showed that, with different designs at different SFIs, the factory building could consistently achieve the three seismic fortification objectives. For the studied factory buildings with the SFI of 6, they satisfied the seismic fortification requirements of “no damage in moderate earthquakes, mendable in strong earthquakes”; for those buildings with SFIs of 7 and 8, the requirement of “no collapsing in super strong earthquakes” was generally met; while for those with SFIs of 9, the requirement of “mendable in moderate earthquakes” was almost satisfied. The results showed factory buildings designed with low SFIs are better at achieving the seismic fortification objectives than those designed with high SFIs.","PeriodicalId":35399,"journal":{"name":"SDHM Structural Durability and Health Monitoring","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69899685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}