Article
Engineering, Electrical & Electronic
Chenyang Li, Lingfei Mo, Ruqiang Yan
Summary: Emerging intelligent algorithms have achieved great success in fault diagnosis, but current models struggle with capturing all structure relationships in the data. To address this, a graph convolution network (GCN) incorporating the weighted horizontal visibility graph (WHVG) is proposed, improving performance and benefiting from the internal structure relationships of the data in bearing faults diagnosis.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Engineering, Multidisciplinary
Dong Zuo, Tang Tang, Ming Chen
Summary: This method proposes a fault diagnosis approach for rolling bearings, utilizing a multi-scale weighted visibility graph and a multi-channel graph convolutional network (MCGCN). By converting vibration signals into multiple weighted graphs and extracting both local node feature information and global topology information, our method achieves excellent performance under both sufficient and limited data conditions. It provides a promising approach for real-world industrial bearing fault diagnosis.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2023)
Article
Engineering, Multidisciplinary
Jinde Zheng, Siqi Huang, Haiyang Pan, Jinyu Tong, Chengjun Wang, Qingyun Liu
Summary: The APSFDM method, based on FDM, offers higher fidelity in signal decomposition and more accurate fault feature information for fault diagnosis of rolling bearings.
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
Chemistry, Analytical
Tianjiao Kong, Jie Shao, Jiuyuan Hu, Xin Yang, Shiyiling Yang, Reza Malekian
Summary: In this study, complex network features were extracted from EEG signals for emotion recognition through the construction of two types of complex networks and fusion of feature matrices. The proposed method achieved high emotion recognition accuracies in valence and arousal dimensions, and further improved classification accuracies when combined with time-domain features.
Article
Engineering, Industrial
Ruxue Bai, Zong Meng, Quansheng Xu, Fengjie Fan
Summary: In this paper, a novel data representation method based on fractional Fourier transform (FRFT) and recurrence plot transform is proposed for machinery fault diagnosis. Experimental results show that the proposed method outperforms conventional methods such as Fourier spectrum and short time Fourier transform. The fusion of maximum kurtosis based fractional Fourier domain recurrence plot and time domain recurrence plot achieves the best performance, making the trained convolutional neural network adaptive to variable working conditions.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Acoustics
Baojia Chen, Zhichao Hai, Xueliang Chen, Fafa Chen, Wenrong Xiao, Nengqi Xiao, Wenlong Fu, Qiang Liu, Zhuxin Tian, Gongfa Li
Summary: This paper proposes a time-varying instantaneous frequency fault feature extraction method for rolling bearings under variable speed, which combines the improved multisynchrosqueezing transform, empirical Fourier decomposition, and generalized demodulation. The method can accurately extract fault features of rolling bearings and identify fault types.
JOURNAL OF SOUND AND VIBRATION
(2023)
Article
Engineering, Mechanical
J-h. Cai, Y-l. Xiao, L-y. Fu
Summary: By combining instantaneous spectrum estimation with FRFT and determining the optimal order based on the principle of maximum kurtosis coefficient, this method achieves more accurate characteristic frequency identification, providing a new approach for fault diagnosis of rolling bearing.
EXPERIMENTAL TECHNIQUES
(2022)
Article
Computer Science, Artificial Intelligence
Yiyuan Gao, Dejie Yu
Summary: The Laplacian regularization (LapR) classification method, a graph-based semi-supervised learning algorithm, is proposed to identify the states of rolling bearings by utilizing labeled and cheap unlabeled samples. By constructing a graph model and interpreting labels of dataset elements, unknown data elements can be determined, showing superior performance in identifying rolling bearing states compared to other classification methods.
APPLIED SOFT COMPUTING
(2021)
Article
Automation & Control Systems
Zhu Yan, Yonggang Xu, Kun Zhang, Aijun Hu, Gang Yu
Summary: This paper proposes an adaptive synchroextracting transform (ASET) algorithm for time-frequency postprocessing, which can better handle strong frequency modulation signals and has better noise robustness and signal reconstruction ability.
Article
Engineering, Electrical & Electronic
Peizhe Yin, Jie Nie, Xinyue Liang, Shusong Yu, Chenglong Wang, Weizhi Nie, Xiangqian Ding
Summary: Fault diagnosis for rolling bearings is a significant engineering problem, and engineers use vibration signals to analyze the features and detect damage. Deep-learning technology has gained research interest for fault diagnosis, but most existing methods have limitations in mining the relationship between signals.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Multidisciplinary
Gong Xiaoyun, Feng Kunpeng, Zhi Zeheng, Gao Yiyuan, Du Wenliao
Summary: A multiple fault diagnosis method for rolling bearings is proposed in this paper, which employs CEEMD and GCN to reconstruct the signals and map them to graphic structure data through HVG. The GCN model is trained to diagnose multiple faults. Experimental results show that this method outperforms other methods and exhibits generalization ability for multiple fault diagnosis.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2023)
Article
Engineering, Chemical
Guoguo Wu, Xuerong Ji, Guolai Yang, Ye Jia, Chuanchuan Cao
Summary: Rolling element bearings (REBs) are the most common cause of machine breakdowns. Traditional fault diagnosis methods rely on feature extraction and signal processing, which can be affected by the complexity of patterns and the need for expert knowledge. This paper proposes a novel signal-to-image method using continuous wavelet transform (CWT), which enhances feature extraction and eliminates the need for manual extraction.
Article
Engineering, Multidisciplinary
Danchen Zhu, Guoqiang Liu, Xingyu Wu, Bolong Yin
Summary: To address the problem of bearing fault signals being contaminated by strong background interference, an enhanced empirical Fourier decomposition technique was proposed. The method includes a trend-line-extraction-based method to weaken the influence of transmission path, a correlation-coefficient-based decomposition number selection approach to avoid irrelevant modal functions, and a band improvement strategy to reduce invalid frequency bands. The results show that this method effectively extracts fault characteristics from strong background interference.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Computer Science, Artificial Intelligence
Jinxi Wang, Faye Zhang, Lei Zhang, Mingshun Jiang
Summary: This paper proposes a maximum average impulse energy ratio deconvolution (MAIERD) method for enhancing periodic fault impulses in vibration signals. The method utilizes an objective function and autocorrelation function to locate and detect the fault period, with the initial filter being a Morlet wavelet. Experimental results demonstrate that the proposed MAIERD method is superior to other deconvolution methods.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Hui Lu, Kun Yang, Wen-bin Shangguan, Hui Yin, D. J. Yu
ENGINEERING COMPUTATIONS
(2020)
Article
Computer Science, Theory & Methods
Hui Yin, Ye-Hwa Chen, Dejie Yu
FUZZY SETS AND SYSTEMS
(2020)
Article
Engineering, Multidisciplinary
Dingcheng Zhang, Edward Stewart, Mani Entezami, Clive Roberts, Dejie Yu
Article
Engineering, Mechanical
Yiyuan Gao, Dejie Yu
MECHANISM AND MACHINE THEORY
(2020)
Article
Automation & Control Systems
Hui Yin, Ye-Hwa Chen, Dejie Yu
IEEE TRANSACTIONS ON CYBERNETICS
(2020)
Article
Physics, Applied
Tinggui Chen, Junrui Jiao, Dejie Yu
Summary: The GCM proposed in this study combines gradient and coiled structures to achieve enhanced broadband acoustic sensing, with the ability to amplify acoustic signals up to approximately 80 times over a wide frequency range. By coupling coiled structures, trapped and enhanced frequencies in the GCM can be reduced by nearly 43%. Experimental results demonstrate that GCM can enhance frequency-selective unknown signals and effectively recognize and recover harmonic signals from strong background noise.
JOURNAL OF PHYSICS D-APPLIED PHYSICS
(2021)
Article
Engineering, Multidisciplinary
Tinggui Chen, Junrui Jiao, Dejie Yu
Summary: The study proposes a method based on the gradient acoustic-grating metamaterial (GAGM) for detecting harmonic and periodic impulse signals more easily. Numerical and experimental investigations demonstrate that GAGM achieves acoustic rainbow trapping to spatially separate different frequency components. This work opens up new vistas for weak signals detection in various areas.
Article
Physics, Applied
Hongqing Dai, Baizhan Xia, Dejie Yu
Summary: Acoustic topological insulators enable non-contact particle manipulations, such as microparticle trapping and separation. Based on the SSH model, we can separate particles of the same size and density.
APPLIED PHYSICS LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Tinggui Chen, Dejie Yu, Bo Wu, Baizhan Xia
Summary: A sensor based on acoustic metamaterials is proposed for detecting weak signals, utilizing a trapezoidal structure to enhance the acoustic pressure field and amplify pressure amplitudes by over 20 times around maximum gain frequencies, achieving broadband acoustic enhancement. Harmonic and periodic impulse signals are detected more easily, and experimental results show effective recovery of signals from background noise due to improved signal to noise ratios.
IEEE SENSORS JOURNAL
(2021)
Article
Automation & Control Systems
Tinggui Chen, Dejie Yu
Summary: This article proposes a novel method to diagnose bearing faults using acoustic metamaterials, which enhances the resonance frequency band to extract fault features. Compared to conventional denoising techniques, this method shows superior performance in low signal to noise ratios.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Acoustics
Tinggui Chen, Junrui Jiao, Dejie Yu
Summary: The detection and localization of acoustic signals are important in many areas, but achieving both high sensitivity and high directivity in an acoustic system remains a challenge. This study proposes a structure that combines phononic crystal point defects with four-sided Helmholtz resonators to enhance acoustics and enable directional sensing. The proposed structure surpasses the detection limit of conventional acoustic sensing systems and provides a new method for developing coupled acoustic sensing devices.
JOURNAL OF SOUND AND VIBRATION
(2022)
Article
Physics, Applied
Guiju Duan, Shengjie Zheng, Jie Zhang, Zihan Jiang, Xianfeng Man, Dejie Yu, Baizhan Xia
Summary: This study reports the realization of a synthetic gauge field in acoustic Moire superlattices consisting of two superimposed periodic phononic crystals with mismatched lattice constants. The symmetric and antisymmetric Landau levels and interface states are observed in the acoustic Moire superlattices with the help of the synthetic gauge field. Sound pressure field distributions of Landau levels are experimentally measured and consistent with full-wave simulations. This study provides a simple way to generate synthetic gauge fields in phononics and expands the avenues for manipulating sound waves that were previously inaccessible in traditional periodic acoustic systems.
APPLIED PHYSICS LETTERS
(2023)
Article
Physics, Applied
Yue Chu, Tinggui Chen, Dejie Yu
APPLIED PHYSICS EXPRESS
(2020)
Article
Computer Science, Artificial Intelligence
Yiyuan Gao, Dejie Yu
Summary: The study introduces an intelligent method using directed graphs for fault diagnosis, which improves diagnostic performance by constructing a directed and weighted k-nearest neighbor graph and measuring the similarity between samples using cosine distance. Experimental results show that the method is better than traditional convolutional neural networks and support vector machines in rolling bearing fault diagnosis.
ADVANCED ENGINEERING INFORMATICS
(2021)
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.
