Article
Engineering, Mechanical
Atik Faysal, Wai Keng Ngui, M. H. Lim
Summary: The proposed NEEEMD method aims to further reduce white noise and select sensitive mode functions to enhance fault-related impulses through a combination of time and frequency domain characteristics. The application of MOMEDA filter improves fault diagnosis accuracy by identifying more fault characteristic impulses.
JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES
(2021)
Article
Engineering, Multidisciplinary
Xiaoan Yan, Minping Jia
Summary: This study proposes a parameter-optimized feature mode decomposition (POFMD) for bearing fault diagnosis. By designing an objective function and adopting particle swarm optimization, POFMD can automatically select the optimal parameter combination, leading to more efficient extraction of fault characteristics.
Article
Engineering, Multidisciplinary
Jinde Zheng, Miaoxian Su, Wanming Ying, Jinyu Tong, Ziwei Pan
Summary: The study introduces the improved Uniform Phase Empirical Mode Decomposition (IUPEMD) method, which enhances the accuracy and performance of signal decomposition by adaptively selecting the amplitude of the sinusoidal wave and choosing the optimal result based on orthogonality index.
Article
Engineering, Multidisciplinary
Cheng Zhong, Jie-Sheng Wang, Wei-Zhen Sun
Summary: A novel fault diagnosis method for rotating bearings, based on the analysis of bearing rotating speed feature and vibration analysis technique, was proposed. The method utilizes improved EEMD and DBN algorithms to decompose vibration data, eliminate interference signals, and extract data features for fault diagnosis.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Multidisciplinary
Hua Li, Xing Wu, Tao Liu, Shaobo Li, Bangmei Zhang, Gui Zhou, Tao Huang
Summary: This paper introduces a parameter-optimized VMD method for composite fault diagnosis of bearings. The method determines the mode number by analyzing the kurtosis value and optimizes the penalty factor. By decomposing the original signal into IMFs, feature extraction is performed to achieve the diagnosis of composite faults in bearings.
Article
Engineering, Multidisciplinary
Haiyang Pan, Ying Zhang, Jian Cheng, Jinde Zheng, Jinyu Tong
Summary: Traditional signal processing methods cannot effectively segment the optimal frequency band, resulting in the fault characteristics being less obvious. Therefore, this paper proposes a multi-layer empirical Ramanujan decomposition (MLERD) method. In MLERD, the number of decomposed components is gradually increased through multi-level decomposition to ensure obtaining the optimal frequency band in the spectrum segmentation stage. Subsequently, the adaptive spectral weight kurtosis (ASWK) is defined to adaptively identify the optimal mode component. Compared with kurtosis, ASWK is more sensitive to periodic pulses and can better evaluate fault feature information. Based on this, this paper further proposes an adaptive multi-layer empirical Ramanujan decomposition (AMLERD) method, which can achieve adaptive identification of the optimal frequency band and extraction of the optimal mode component of complex signals. The analysis results of roller bearing simulation and experimental signals show that AMLERD can effectively extract fault feature information and has excellent noise robustness.
Article
Engineering, Mechanical
Robert B. Randall, Jerome Antoni
Summary: Empirical mode decomposition (EMD) is a method to decompose complex signals into intrinsic mode functions (IMFs) which can be considered as carrier frequencies modulated in amplitude and phase. This paper shows that EMD is not suitable for rolling element bearing (REB) signals due to their intrinsic properties. Instead, other methods based on relevant criteria should be used to extract the desired diagnostic information. The paper also discusses the limitations of EMD, such as end effects and mode mixing, which make it difficult to guarantee repeatable results. The poor selectivity of the bandpass filters given by EMD is compared to alternative filters.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Chemistry, Multidisciplinary
Manuel A. A. Centeno-Bautista, Angel H. H. Rangel-Rodriguez, Andrea V. V. Perez-Sanchez, Juan P. P. Amezquita-Sanchez, David Granados-Lieberman, Martin Valtierra-Rodriguez
Summary: Sudden cardiac death is a significant global health problem, accounting for 15-20% of global deaths. A research proposes a methodology combining complete ensemble empirical mode decomposition (CEEMD) and convolutional neural network (CNN) to predict SCD events 30 minutes in advance with 97.5% accuracy. The study compares the results with ensemble empirical mode decomposition (EEMD) and empirical mode decomposition (EMD) methods.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Multidisciplinary
Yuhu Liu, Yi Chai, Bowen Liu, Yiming Wang
Summary: A novel method called residual-variational mode decomposition (RVMD) is proposed for accurately extracting bearing fault features. RVMD can adaptively determine the number of modes and balance parameters, showing its superiority in signal decomposition and fault feature extraction.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Electrical & Electronic
Xiaolong Wang, Guiji Tang, Tai Wang, Xiong Zhang, Bo Peng, Longjiang Dou, Yuling He
Summary: The study proposes an innovative diagnostic framework based on LGAEWT and PIED for extracting periodic impacts from original vibration signals, identifying defects, and improving accuracy in bearing fault detection. The feasibility and effectiveness of this framework have been validated through experimental signals and engineering cases, demonstrating its potential for enhancing fault detection under low SNR environments.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Engineering, Multidisciplinary
Junxia Wang, Changshu Zhan, Sanping Li, Qiancheng Zhao, Jiuqing Liu, Zhijie Xie
Summary: An adaptive VMD method using the AOA optimization algorithm is proposed for rotating machinery fault diagnosis. The method can extract fault characteristics more effectively by selecting appropriate parameters.
Article
Automation & Control Systems
Vikas Sharma, Pradeep Kundu
Summary: This study proposes a systematic approach to detect and classify bearing faults using vibration signals under varying speeds. The approach includes segmentation of the signal, extraction of speed-invariant features, and development of a machine learning model for online classification. The empirical wavelet transformation (EWT) algorithm is used to decompose the signal and detect faults. The most impulsive mode function (MF) is selected based on instantaneous frequency estimation, and statistical analysis is conducted using ten entropies, root-mean-square, and kurtosis. The proposed approach shows higher accuracy in detecting and classifying faults compared to the ensemble empirical mode decomposition.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Yun Li, Jiwen Zhou, Hongguang Li, Guang Meng, Jie Bian
Summary: In this article, a fast and adaptive empirical mode decomposition method (FAEMD) is proposed to address the limitations of the original EMD method, such as differences in white noise amplitude, number of trials, and low computational efficiency. FAEMD combines the advantages of the order statistics filter (OSF) with the original EMD to effectively extract key feature information from fault signals with low calculation cost.
IEEE SENSORS JOURNAL
(2023)
Article
Acoustics
Siqi Huang, Jinde Zheng, Haiyang Pan, Jinyu Tong
Summary: A new nonstationary signal analysis method called order-statistic filtering Fourier decomposition is proposed in this article, which solves the boundaries issue in existing methods and achieves more accurate and reasonable results in analyzing simulation signals and faulty bearing vibration signals.
JOURNAL OF VIBRATION AND CONTROL
(2022)
Article
Automation & Control Systems
Jinde Zheng, Shijun Cao, Haiyang Pan, Qing Ni
Summary: This paper proposes a novel spectral envelope-based adaptive empirical Fourier decomposition (SEAEFD) method to improve the performance of AEFD in rolling bearing vibration signal analysis. SEAEFD optimizes the spectrum segmentation boundary to achieve adaptive segmentation and minimize noise components, allowing nonstationary signals to be decomposed into single-component signals with physical significance.
Article
Automation & Control Systems
Yiheng Wei, Peter W. Tse, Bin Du, Yong Wang
Article
Acoustics
Xiang Wan, Guanghua Xu, Qing Zhang, Peter W. Tse, Haihui Tan
Article
Acoustics
Shilong Sun, Peter W. Tse, Y. L. Tse
SHOCK AND VIBRATION
(2017)
Article
Engineering, Multidisciplinary
Yi Wang, Peter W. Tse, Baoping Tang, Yi Qin, Lei Deng, Tao Huang
Article
Engineering, Mechanical
Yi Wang, Peter W. Tse, Baoping Tang, Yi Qin, Lei Deng, Tao Huang, Guanghua Xu
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2019)
Article
Materials Science, Characterization & Testing
P. Tse, Z. Fang, K. Ng
NDT & E INTERNATIONAL
(2019)
Article
Mathematics, Applied
Yiheng Wei, Da-Yan Liu, Peter W. Tse, Yong Wang
INTEGRAL TRANSFORMS AND SPECIAL FUNCTIONS
(2020)
Article
Metallurgy & Metallurgical Engineering
Fan Xu, Peter W. Tse
JOURNAL OF CENTRAL SOUTH UNIVERSITY
(2019)
Article
Construction & Building Technology
Peter Tse, Faeez Masurkar, Nitesh P. Yelve
STRUCTURAL CONTROL & HEALTH MONITORING
(2020)
Article
Acoustics
Maodan Yuan, Peter W. Tse, Weiming Xuan, Wenjin Xu
Summary: This paper combines theoretical and numerical methods to study the propagation of UGW on a standard rail track, and proposes a method to extract efficient UGW modes from the frequency domain. The results show that this method can effectively assess the integrity of rail tracks.
SHOCK AND VIBRATION
(2021)
Article
Chemistry, Analytical
Imran Ghafoor, Peter W. Tse, Javad Rostami, Kim-Ming Ng
Summary: The study combines laser ultrasonic technology (LUT) and enhanced matching pursuit (MP) to achieve a fully non-contact inspection of train rails. It explores the use of non-contact laser-based inspection to detect artificial defects at railheads of different dimensions, using enhanced MP with novel dictionaries to process laser-generated Rayleigh wave signals effectively. The enhanced MP method demonstrates high efficiency in noise removal and defect detection, especially when using the finite element method (FEM) simulation dictionary.
Article
Chemistry, Analytical
Muhammad Mohsin Khan, Peter W. Tse, Amy J. C. Trappey
Summary: The study proposes a strategy for RUL prediction using real-time data and develops a hybrid model to predict degradation trends based on vibration signals.
Article
Optics
K. Ng, I. Ghafoor, P. Tse
Summary: A new method for detecting various defects in railway head using laser-generated Rayleigh wave and chaotic oscillator is proposed in this study. Experimental results show that this method can accurately and reliably reveal defect signals under strong noise conditions, and have great potential for application.
OPTICS AND LASERS IN ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Zhou Fang, Peter W. Tse
Summary: This article proposes a new method for detecting defects in pipes by using a spirally propagating circumferential Lamb wave triggered by a magnetostrictive patch transducer. This method can quickly detect the position of defects without the need for traditional axial scanning, while also evaluating the axial extent of defects. It was experimentally proven that the circumferential Lamb wave could supplement the traditional modes effectively.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Computer Science, Information Systems
Yujuan Xie, Shengjiang Chen, Xiang Wan, Peter W. Tse
Article
Engineering, Multidisciplinary
Sicheng Jiao, Shixiang Wang, Minge Gao, Min Xu
Summary: This paper presents a non-contact method of thickness measurement for thin-walled rotary shell parts based on a chromatic confocal sensor. The method involves using a flip method to obtain surface profiles from both sides of the workpiece, measuring the decentration and tilt errors of the workpiece using a centering system, establishing a unified reference coordinate system, reconstructing the external and internal surface profiles, and calculating the thickness. Experimental results show that the method can accurately measure the thickness of a sapphire spherical shell workpiece and is consistent with measurements of other materials.
Article
Engineering, Multidisciplinary
Rajeev Kumar, Sajal Agarwal, Sarika Pal, Alka Verma, Yogendra Kumar Prajapati
Summary: This study evaluated the performance of a CaF2-Ag-MXene-based surface plasmon resonance (SPR) sensor at different wavelengths. The results showed that the sensor achieved the maximum sensitivity at a wavelength of 532 nm, and higher sensitivities were obtained at shorter wavelengths at the expense of detection accuracy.
Article
Engineering, Multidisciplinary
Attilio Di Nisio, Gregorio Andria, Francesco Adamo, Daniel Lotano, Filippo Attivissimo
Summary: Capacitive sensing is a widely used technique for a variety of applications, including avionics. However, current industry standard Capacitive Level Sensors (CLSs) used in helicopters perform poorly in terms of sensitivity and dynamic characteristics. In this study, novel geometries were explored and three prototypes were built and tested. Experimental validation showed that the new design featuring a helicoidal slit along the external electrode of the cylindrical probe improved sensitivity, response time, and linearity.
Article
Engineering, Multidisciplinary
Kai Yang, Huiqin Wang, Ke Wang, Fengchen Chen
Summary: This paper proposes an effective measurement method for dynamic compaction construction based on time series model, which enables real-time monitoring and measurement of anomalies and important construction parameters through simulating motion state transformation and running time estimation.
Article
Engineering, Multidisciplinary
Hui Fu, Qinghua Song, Jixiang Gong, Liping Jiang, Zhanqiang Liu, Qiang Luan, Hongsheng Wang
Summary: An automatic detection and pixel-level quantification model based on joint Mask R-CNN and TransUNet is developed to accurately evaluate microcrack damage on the grinding surfaces of engineering ceramics. The model is effectively trained on actual micrograph image dataset using a joint training strategy. The proposed model achieves reliable automatic detection and fine segmentation of microcracks, and a skeleton-based quantification model is also proposed to provide comprehensive and precise measurements of microcrack size.
Review
Engineering, Multidisciplinary
Sang Yeob Kim, Da Yun Kwon, Arum Jang, Young K. Ju, Jong-Sub Lee, Seungkwan Hong
Summary: This paper reviews the categorization and applications of UAV sensors in forensic engineering, with a focus on geotechnical, structural, and water infrastructure fields. It discusses the advantages and disadvantages of sensors with different wavelengths and addresses the challenges of current UAV technology and recommendations for further research in forensic engineering.
Article
Engineering, Multidisciplinary
Anton Nunez-Seoane, Joaquin Martinez-Sanchez, Erik Rua, Pedro Arias
Summary: This article compares the use of Mobile Laser Scanners (MLS) and Aerial Laser Scanners (ALS) for digitizing the road environment and detecting road slopes. The study found that ALS data and its corresponding algorithm achieved better detection and delimitation results compared to MLS. Measuring the road from a terrestrial perspective negatively impacted the detection process, while an aerial perspective allowed for scanning of the entire slope structure.
Article
Engineering, Multidisciplinary
Nur Luqman Saleh, Aduwati Sali, Raja Syamsul Azmir Raja Abdullah, Sharifah M. Syed Ahmad, Jiun Terng Liew, Fazirulhisyam Hashim, Fairuz Abdullah, Nur Emileen Abdul Rashid
Summary: This study introduces an enhanced signal processing scheme for detecting mouth-click signals used by blind individuals. By utilizing additional band-pass filtering and other steps, the detection accuracy is improved. Experimental results using artificial signal data showed a 100% success rate in detecting obstacles. The emerging concepts in this research are expected to benefit radar and sonar system applications.
Article
Engineering, Multidisciplinary
Jiqiang Tang, Shengjie Qiu, Lu Zhang, Jinji Sun, Xinxiu Zhou
Summary: This paper studies the magnetic noise level of a compact high-performance magnetically shielded room (MSR) under different operational conditions and establishes a quantitative model for magnetic noise calculation. Verification experiments show the effectiveness of the proposed method.
Review
Engineering, Multidisciplinary
Krzysztof Bartnik, Marcin Koba, Mateusz Smietana
Summary: The demand for miniaturized sensors in the biomedical industry is increasing, and optical fiber sensors (OFSs) are gaining popularity due to their small size, flexibility, and biocompatibility. This study reviews various OFS designs tested in vivo and identifies future perspectives and challenges for OFS technology development from a user perspective.
Article
Engineering, Multidisciplinary
Yue Wang, Lei Zhou, Zihao Li, Jun Wang, Xuangou Wu, Xiangjun Wang, Lei Hu
Summary: This paper presents a 3-D reconstruction method for dynamic stereo vision of metal surface based on line structured light, overcoming the limitation of the measurement range of static stereo vision. The proposed method uses joint calibration and global optimization to accurately reconstruct the 3-D coordinates of the line structured light fringe, improving the reconstruction accuracy.
Article
Engineering, Multidisciplinary
Jaafar Alsalaet
Summary: Order tracking analysis is an effective tool for machinery fault diagnosis and operational modal analysis. This study presents a new formulation for the data equation of the second-generation Vold-Kalman filter, using separated cosine and sine kernels to minimize error and provide smoother envelopes. The proposed method achieves high accuracy even with small weighting factors.
Article
Engineering, Multidisciplinary
Tonglei Cao, Kechen Song, Likun Xu, Hu Feng, Yunhui Yan, Jingbo Guo
Summary: This study constructs a high-resolution dataset for surface defects in ceramic tiles and addresses the scale and quantity differences in defect distribution. An improved approach is proposed by introducing a content-aware feature recombination method and a dynamic attention mechanism. Experimental results demonstrate the superior accuracy and efficiency of the proposed method.
Article
Engineering, Multidisciplinary
Qinghong Fu, Yunxi Lou, Jianghui Deng, Xin Qiu, Xianhua Chen
Summary: Measurement and quantitative characterization of aging-induced gradient properties is crucial for accurate analysis and design of asphalt pavement. This research proposes the composite specimen method to obtain asphalt binders at different depths within the mixture and uses dynamic shear rheometer tests to measure aging-induced gradient properties and reveal internal mechanisms. G* master curves are constructed to investigate gradient aging effects in a wide range. The study finds that the composite specimen method can effectively restore the boundary conditions and that it is feasible to study gradient aging characteristics within the asphalt mixture. The study also observes variations in G* and delta values and the depth range of gradient aging effects for different aging levels.
Article
Engineering, Multidisciplinary
Min Li, Kai Wei, Tianhe Xu, Yali Shi, Dixing Wang
Summary: Due to the limitations of ground monitoring stations in China for the BDS, the accuracy of BDS Medium Earth Orbit (MEO) satellite orbits can be influenced. To overcome this, low Earth orbit (LEO) satellites can be used as additional monitoring stations. In this study, data from two LEO satellites were collected to improve the precise orbit determination of the BDS. By comparing the results with GPS and BDS-2/3 solutions, it was found that including the LEO satellites significantly improved the accuracy of GPS and BDS-2/3 orbits.
