Article
Engineering, Multidisciplinary
Ahmad Amer, Fotis P. Kopsaftopoulos
Summary: A novel statistical framework for active-sensing SHM based on ultrasonic guided waves is proposed in this study, with three methods and corresponding statistical quantities experimentally evaluated for damage detection, showing increased sensitivity and robustness compared to conventional approaches, as well as better tracking capability of damage evolution.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2022)
Article
Automation & Control Systems
Josef Koutsoupakis, Dimitrios Giagopoulos, Iraklis Chatziparasidis
Summary: Real-time monitoring of mechanical systems through vibration measurements enables fault detection and predictive maintenance. The use of Artificial Intelligence (AI) in damage detection provides automated means for Condition Monitoring (CM) and characterization of health states. This study proposes a novel CM framework using Convolutional Neural Networks (CNNs) for damage detection and identification, applied to an elevator door rail using simulated data. Rating: 8 out of 10.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Acoustics
William A. Gardner
Summary: This paper reviews the necessary transition from abstract stochastic process models to more concrete Fraction-of-Time Probability models for time-series data. It introduces a new type of stochastic process model as a pedagogical tool to facilitate the conceptual transition. Despite accumulating evidence in support, resistance to change remains a challenge.
JOURNAL OF SOUND AND VIBRATION
(2023)
Article
Construction & Building Technology
Jiayan Lei, Yiguan Cui, Wei Shi
Summary: This study presents a support vector machine (SVM) based structural damage detection approach for a steel frame model. By simulating different damage scenarios and extracting damage indicator features, the SVM classifiers are developed to identify multiple damage states. The results demonstrate that the approach has good performance in terms of feature extraction and identification.
ADVANCES IN STRUCTURAL ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
Xiansong Gao, Rui Zhong, Qingshan Wang, Qin Bin, Hailiang Xu
Summary: This paper presents a Spectral-Tchebychev (S-T) dynamic model to examine the free and random vibration properties of functionally gradient plates with piezoelectric patches under random excitation. The model considers the division of the plate into sub-plates based on the position of the patches, derivation of dynamical equations using FSDT and Hamilton's variational principle, handling of boundary conditions and coupling relationships, and obtaining vibration characteristics using the Spectral-Tchebychev technique. The results validate the rationality and validity of the S-T model in predicting the vibration characteristics and investigate the influence mechanism of key parameters.
ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS
(2023)
Article
Engineering, Mechanical
Josef Koutsoupakis, Panagiotis Seventekidis, Dimitrios Giagopoulos
Summary: This paper proposes a CM scheme for mechanical systems using a CNN trained with simulated data. The method shows potential for damage identification in real systems where experimental measurements are difficult to acquire.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Multidisciplinary Sciences
Shigeki Kishi, Jianqiang Sun, Akira Kawaguchi, Sunao Ochi, Megumi Yoshida, Takehiko Yamanaka
Summary: While traditional statistical methods and machine learning methods have been widely used to predict future population dynamics of crop pests and diseases, the characteristic features of these methods have not been fully understood. By comparing two statistical and seven machine learning methods using 203 monitoring datasets on four major crops in Japan, it was found that the decision tree and random forest methods of machine learning were the most effective, while the regression models of both statistical and machine learning methods were relatively inferior. The best methods were better for biased and scarce data, while the statistical Bayesian model was better for larger dataset sizes. Therefore, researchers should consider data characteristics when selecting the most appropriate method.
ROYAL SOCIETY OPEN SCIENCE
(2023)
Article
Engineering, Multidisciplinary
Andeas Panagiotopoulos, Tcherniak Dmitri, Fassois D. Spilios
Summary: This study focuses on detecting damage on the blade of an operating Vestas V27 wind turbine using a single vibration response sensor under varying environmental and operating conditions. Three different lengths of damage scenarios are examined, and the performance of robust vibration-based Statistical Time Series type methods is explored. The results show that single-sensor-based detection is feasible using the U-PCA-MM-AR method, with a True Positive Rate of 100% and a False Positive Rate of 4%, 1%, and 0% for the 15, 30, and 45 cm damage scenarios, respectively. This performance is comparable to that of the 8-sensor-based method.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Review
Construction & Building Technology
Jiafeng Yang, Lei Huang, Kai Tong, Qizhi Tang, Houxuan Li, Haonan Cai, Jingzhou Xin
Summary: This paper provides a systematic review of the damage monitoring and identification methods of arch bridges. It reviews the methods for monitoring local diseases and identifies damage of the overall performance of arch bridges. The aim of this review is to assist researchers and practitioners in implementing existing methods effectively and developing more reliable and practical methods for arch bridges in the future.
Article
Plant Sciences
Di Chen, Buchun Liu, Tianjie Lei, Xiaojuan Yang, Yuan Liu, Wei Bai, Rui Han, Huiqing Bai, Naijie Chang
Summary: This study proposes a novel method that utilizes remote sensing index and statistical data to monitor and assess spring frost damage to winter wheat. The method was applied to a specific event in Shandong province and proved effective in delineating the spatial distribution and evaluating the extent of the disaster. The results showed a significant impact on winter wheat production in western Shandong province, with severe yield reduction rates.
Article
Chemistry, Analytical
Emrah Erduran, Frida Kristin Ulla, Lone Naess
Summary: A new framework for long-term monitoring of bridges is proposed using vibration-based damage indicators with physical correlation to effectively detect and locate damage levels on a simulated railway bridge. The framework demonstrates a clear picture of damage initiation and development over time, and successfully identifies the location of simulated damage even under high noise levels.
Review
Computer Science, Interdisciplinary Applications
Rene Jaros, Radek Byrtus, Jakub Dohnal, Lukas Danys, Jan Baros, Jiri Koziorek, Petr Zmij, Radek Martinek
Summary: This research article provides a comprehensive overview of condition monitoring techniques for induction motors (IM) and advanced signal processing techniques. The comparison shows that Wavelet Transform (WT) along with Empirical Mode Decomposition (EMD), Principal Component Analysis (PCA), and Park's Vector Approach (PVA) yield the most interesting results for real deployment.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Environmental Sciences
Gaia Olcese, Paul D. Bates, Jeffrey C. Neal, Christopher C. Sampson, Oliver E. J. Wing, Niall Quinn, Hylke E. Beck
Summary: Typical flood models neglect the spatial structure of flood events, but large-scale stochastic flood models can simulate synthetic flood events with realistic spatial structure. Global hydrological models' discharge hindcasts can be used to build stochastic river flood models globally. The model-based approach shows promising performance in simulating spatial dependency in large-scale flood modeling, providing reliable flood risk assessment for data-scarce regions.
WATER RESOURCES RESEARCH
(2022)
Article
Economics
Andrew Chesher, Dongwoo Kim, Adam M. Rosen
Summary: This paper studies models of processes generating censored outcomes with endogenous explanatory variables and instrumental variable restrictions. It focuses on Tobit-type left censoring at zero and briefly sketches the extension to stochastic censoring. The models do not specify the process determining endogenous explanatory variables and they do not embody restrictions justifying control function approaches. In an application using data on UK household tobacco expenditures, inference is conducted on the coefficient of an endogenous total expenditure variable with and without a Gaussian distributional restriction on the unobservable, and compared with the results obtained using a point identifying complete triangular model.
JOURNAL OF ECONOMETRICS
(2023)
Article
Environmental Sciences
Joaquin Andres Valencia Ortiz, Antonio Miguel Martinez-Grana, Lenny Mejia Mendez
Summary: Mass movements have significant negative impacts on the study area, and evaluating their susceptibility is crucial for territorial planning and disaster risk management. Various stochastic and statistical methods, including artificial neural network, bivariate statistical method, and logistic regression method, were used to evaluate the mass movements based on inherent variables. The results demonstrate that the bivariate method performs well in spatial prediction.
Article
Engineering, Mechanical
Luis David Avendano-Valencia, Spilios D. Fassois
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2017)
Article
Engineering, Mechanical
J. S. Sakellariou, S. D. Fassois
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2017)
Article
Engineering, Mechanical
Luis David Avendano-Valencia, Spilios D. Fassois
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2017)
Article
Engineering, Mechanical
K. J. Vamvoudakis-Stefanou, J. S. Sakellariou, S. D. Fassois
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2018)
Article
Engineering, Multidisciplinary
John S. Sakellariou, Spilios D. Fassois, Christos S. Sakaris
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2018)
Article
Engineering, Multidisciplinary
Nikos A. Spanos, John S. Sakellariou, Spilios D. Fassois
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2020)
Article
Acoustics
T-C Aravanis, J. S. Sakellariou, S. D. Fassois
JOURNAL OF SOUND AND VIBRATION
(2020)
Article
Chemistry, Analytical
Panayiotis Theodoropoulos, Christos C. Spandonidis, Fotis Giannopoulos, Spilios Fassois
Summary: The ability to use data for improvement in the shipping sector is crucial, with marine engineering considering data as an asset and focusing on system design. A methodology using a 1D Convolutional Neural Network is developed to identify early signs of defective behavior in vessel operation through data analysis. The study shows the applicability of 1D-CNN models in condition monitoring for ships, a topic not thoroughly explored in the maritime sector.
Article
Engineering, Electrical & Electronic
Nikolaos Kaliorakis, John S. Sakellariou, Spilios D. Fassois
Summary: This study investigates the prompt detection of early-stage hollow worn wheels in railway vehicles using on-board random vibration measurements. Two unsupervised statistical time series methods were proposed and assessed through case studies. The results show that both methods exhibit remarkable performance in detecting wheel wear.
Proceedings Paper
Engineering, Mechanical
T-C. Aravanis, J. Sakellariou, S. Fassois
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2018) / INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2018)
(2018)
Proceedings Paper
Engineering, Mechanical
C. N. Kapsalas, S. D. Fassois, J. S. Sakellariou
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2018) / INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2018)
(2018)
Proceedings Paper
Engineering, Mechanical
L. D. Avendano-Valencia, E. N. Chatzi, S. D. Fassois
ROTATING MACHINERY, HYBRID TEST METHODS, VIBRO-ACOUSTICS & LASER VIBROMETRY, VOL 8
(2017)
Proceedings Paper
Engineering, Civil
C. S. Sakaris, J. S. Sakellariou, S. D. Fassois
X INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (EURODYN 2017)
(2017)
Proceedings Paper
Engineering, Civil
Nikos I. Spanos, Johns. Sakellariou, Spilios D. Fassois
X INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (EURODYN 2017)
(2017)
Proceedings Paper
Engineering, Civil
K. J. Vamvoudakis-Stefanou, S. D. Fassois
X INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (EURODYN 2017)
(2017)
Article
Engineering, Mechanical
Xuanen Kan, Yanjun Lu, Fan Zhang, Weipeng Hu
Summary: A blade disk system is crucial for the energy conversion efficiency of turbomachinery, but differences between blades can result in localized vibration. This study develops an approximate symplectic method to simulate vibration localization in a mistuned bladed disk system and reveals the influences of initial positive pressure, contact angle, and surface roughness on the strength of vibration localization.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Zimeng Liu, Cheng Chang, Haodong Hu, Hui Ma, Kaigang Yuan, Xin Li, Xiaojian Zhao, Zhike Peng
Summary: Considering the calculation efficiency and accuracy of meshing characteristics of gear pair with tooth root crack fault, a parametric model of cracked spur gear is established by simplifying the crack propagation path. The LTCA method is used to calculate the time-varying meshing stiffness and transmission error, and the results are verified by finite element method. The study also proposes a crack area share index to measure the degree of crack fault and determines the application range of simplified crack propagation path.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Rongjian Sun, Conggan Ma, Nic Zhang, Chuyo Kaku, Yu Zhang, Qirui Hou
Summary: This paper proposes a novel forward calculation method (FCM) for calculating anisotropic material parameters (AMPs) of the motor stator assembly, considering structural discontinuities and composite material properties. The method is based on multi-scale theory and decouples the multi-scale equations to describe the equivalence and equivalence preconditions of AMPs of two scale models. The effectiveness of this method is verified by modal experiments.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Hao Zhang, Jiangcen Ke
Summary: This research introduces an intelligent scheduling system framework to optimize the ship lock schedule of the Three Gorges Hub. By analyzing navigational rules, operational characteristics, and existing problems, a mixed-integer nonlinear programming model is formulated with multiple objectives and constraints, and a hybrid intelligent algorithm is constructed for optimization.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Jingjing He, Xizhong Wu, Xuefei Guan
Summary: A sensitivity and reliability enhanced ultrasonic method has been developed in this study to monitor and predict stress loss in pre-stressed multi-layer structures. The method leverages the potential breathing effect of porous cushion materials in the structures to increase the sensitivity of the signal feature to stress loss. Experimental investigations show that the proposed method offers improved accuracy, reliability, and sensitivity to stress change.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Benyamin Hosseiny, Jalal Amini, Hossein Aghababaei
Summary: This paper presents a method for monitoring sub-second or sub-minute displacements using GBSAR signals, which employs spectral estimation to achieve multi-dimensional target detection. It improves the processing of MIMO radar data and enables high-resolution fast displacement monitoring from GBSAR signals.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xianze Li, Hao Su, Ling Xiang, Qingtao Yao, Aijun Hu
Summary: This paper proposes a novel method for bearing fault identification, which can accurately identify faults with few samples under complex working conditions. The method is based on a Transformer meta-learning model, and the final result is determined by the weighted voting of multiple models.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xiaomeng Li, Yi Wang, Guangyao Zhang, Baoping Tang, Yi Qin
Summary: Inspired by chaos fractal theory and slowly varying damage dynamics theory, this paper proposes a new health monitoring indicator for vibration signals of rotating machinery, which can effectively monitor the mechanical condition under both cyclo-stationary and variable operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Hao Wang, Songye Zhu
Summary: This paper extends the latching mechanism to vibration control to improve energy dissipation efficiency. An innovative semi-active latched mass damper (LMD) is proposed, and different latching control strategies are tested and evaluated. The latching control can optimize the phase lag between control force and structural response, and provide an innovative solution to improve damper effectiveness and develop adaptive semi-active dampers.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Menghao Ping, Xinyu Jia, Costas Papadimitriou, Xu Han, Chao Jiang, Wang-Ji Yan
Summary: Identification of non-Gaussian processes is a challenging task in engineering problems. This article presents an improved orthogonal series expansion method to convert the identification of non-Gaussian processes into a finite number of non-Gaussian coefficients. The uncertainty of these coefficients is quantified using polynomial chaos expansion. The proposed method is applicable to both stationary and nonstationary non-Gaussian processes and has been validated through simulated data and real-world applications.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Lei Li, Wei Yang, Dongfa Li, Jianxin Han, Wenming Zhang
Summary: The frequency locking phenomenon induced by modal coupling can effectively overcome the dependence of peak frequency on driving strength in nonlinear resonant systems and improve the stability of peak frequency. This study proposes the double frequencies locking phenomenon in a three degrees of freedom (3-DOF) magnetic coupled resonant system driven by piezoelectricity. Experimental and theoretical investigations confirm the occurrence of first frequency locking and the subsequent switching to second frequency locking with the increase of driving force. Furthermore, a mass sensing scheme for double analytes is proposed based on the double frequencies locking phenomenon.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Kai Ma, Jingtao Du, Yang Liu, Ximing Chen
Summary: This study explores the feasibility of using nonlinear energy sinks (NES) as replacements for traditional linear tuned mass dampers (TMD) in practical engineering applications, specifically in diesel engine crankshafts. The results show that NES provides better vibration attenuation for the crankshaft compared to TMD under different operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Wentao Xu, Li Cheng, Shuaihao Lei, Lei Yu, Weixuan Jiao
Summary: In this study, a high-precision hydraulic mechanical stand and a vertical mixed-flow pumping station device were used to conduct research on cavitation signals of mixed-flow pumps. By analyzing the water pressure pulsation signal, it was found that the power spectrum density method is more sensitive and capable of extracting characteristics compared to traditional time-frequency domain analysis. This has significant implications for the identification and prevention of cavitation in mixed-flow pump machinery.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xiaodong Chen, Kang Tai, Huifeng Tan, Zhimin Xie
Summary: This paper addresses the issue of parasitic motion in microgripper jaws and its impact on clamping accuracy, and proposes a symmetrically stressed parallelogram mechanism as a solution. Through mechanical modeling and experimental validation, the effectiveness of this method is demonstrated.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Zhifeng Shi, Gang Zhang, Jing Liu, Xinbin Li, Yajun Xu, Changfeng Yan
Summary: This study provides useful guidance for early bearing fault detection and diagnosis by investigating the effects of crack inclination and propagation direction on the vibration characteristics of bearings.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
