Article
Automation & Control Systems
Wei Kang, Yongsheng Zhu, Ke Yan, Zhijun Ren, Dawei Gao, Jun Hong
Summary: This paper proposes a new signal extraction method RWSVD_IFK, which can effectively extract weak repetitive transients from fault rolling element bearings using reweighted singular value decomposition and improved Fast_kurtogram, and overcome the interference of cyclostationary and abnormal shock.
Article
Automation & Control Systems
Hua Li, Tao Liu, Xing Wu, Qing Chen
Summary: The study introduces an enhanced SVD method E-SVD to address the issues with SVD, achieving superior signal reconstruction and noise reduction effects through the combination of ISVD and IWPT. Additionally, an evaluation indicator is introduced to assess the performance of the results.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Chemistry, Analytical
Yuanjing Guo, Youdong Yang, Shaofei Jiang, Xiaohang Jin, Yanding Wei
Summary: This paper proposes a rolling bearing fault diagnosis method based on successive variational mode decomposition (SVMD) and the energy concentration and position accuracy (EP) index. The EP index is used to indicate the target mode by comprehensively considering the energy concentration degree and frequency position accuracy of the fault characteristic component. The line search method guided by the EP index is introduced to determine an optimal value for the balancing parameter of SVMD.
Article
Automation & Control Systems
Lingli Cui, Mengxin Sun, Chunqing Zha
Summary: This article proposes a singular value decomposition method based on fault information content for diagnosing bearing faults. The method effectively selects singular components with fault information and performs fault diagnosis under noise interference.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Hua Li, Tao Liu, Xing Wu, Shaobo Li
Summary: In this article, the application of SVD based on the Hankel matrix in signal processing and fault diagnosis is studied. The influencing factors, including the reconstruction component(s), the structure of the Hankel matrix, and the point number of the analysis data, are systematically analyzed. A method based on correlated SVD (C-SVD) is proposed and applied to bearing fault diagnosis, showing its superiority over existing methods.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Mechanical
Bingyan Chen, Weihua Zhang, James Xi Gu, Dongli Song, Yao Cheng, Zewen Zhou, Fengshou Gu, Andrew Ball
Summary: In this paper, new detection methods of cyclostationarity are developed for rolling bearing fault diagnosis by constructing generalized envelope signals and using product envelope spectrum (PES), which improve the accuracy and robustness of fault diagnosis.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Automation & Control Systems
Lin Liang, Chengxu Liu, Fei Liu
Summary: Extracting periodic impact features from vibration signals is crucial for fault diagnosis of rolling element bearings. This paper proposes a novel approach based on singular value distribution of impulse response segment for bearing fault diagnosis. The characteristics of singular value decomposition (SVD) of the impulse response are analyzed, and a double-order attenuation ratio (DAR) is designed to evaluate the transient component of the short-time segment. The proposed method is verified to be effective through simulation and bearing fault datasets, compared to state-of-art algorithms.
Article
Engineering, Electrical & Electronic
Zhi Xu, Chaoren Qin, Gang Tang
Summary: A novel deconvolution cascaded variational mode decomposition method is proposed in this article for weak bearing fault detection. By compensating transfer function and optimizing resonance component to reduce the impact of noise, the monitored signal is enhanced. Experiments confirmed the effectiveness of the proposed method, showing an increase in envelope factor from 1.0762 to 34.8781, indicating enhancement of fault signal.
IEEE SENSORS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Yang Yang, Hui Liu, Lijin Han, Pu Gao
Summary: This article proposes a new rolling bearing status feature extraction method based on variational mode decomposition (VMD) and improved envelope spectrum entropy (IESE). The feasibility of the proposed method is verified by three experimental cases. Compared with other methods, the performance of this proposed method is better.
IEEE SENSORS JOURNAL
(2023)
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
Engineering, Multidisciplinary
Weiyang Xu, Yehu Shen, Quansheng Jiang, Qixin Zhu, Fengyu Xu
Summary: This study proposes a method for extracting weak fault features from rolling bearing vibration signals using improved singular spectrum decomposition (SSD) and a singular-value energy autocorrelation coefficient spectrum (SVEACS). Experimental results demonstrate that the proposed method can effectively extract features and accurately diagnose faults in rolling bearings under strong noise.
MEASUREMENT SCIENCE AND 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
Engineering, Electrical & Electronic
Zhixiang Chen, Yang Yang, Changbo He, Yongbin Liu, Xianzeng Liu, Zheng Cao
Summary: Bearing is a key part of mechanical equipment and timely diagnosis of bearing faults is crucial for ensuring proper functioning. This paper proposes a new method for rolling bearing fault diagnosis based on hierarchical improved envelope spectrum entropy. The method uses hierarchical decomposition to divide the bearing vibration signal into multiple components and calculates the improved envelope spectrum entropy of each component to obtain the original feature set. The features are then fused using joint approximate diagonalization of eigenmatrices and support vector machines are used for bearing status identification. Experimental results show that the proposed method has good performance in feature extraction, providing a new method for rolling bearing feature extraction.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Multidisciplinary
Chaoang Xiao, Hesheng Tang, Yan Ren, Anil Kumar
Summary: This study introduces a fuzzy entropy assisted singular spectrum decomposition denoising method for extracting fault features in axial piston pump bearings. The method effectively reduces interference noise through two rounds of screening and demonstrates good application performance with practical engineering signals.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Engineering, Multidisciplinary
Xiaoan Yan, Wan Zhang, Minping Jia
Summary: In this paper, a bearing fault feature extraction method based on optimized singular spectrum decomposition and linear predictor is proposed to effectively extract bearing defect frequencies and diagnose fault categories. The method preprocesses data, decomposes it into components, and calculates the correlation kurtosis indicator to select the optimal component for envelope demodulation analysis. Experimental results validate the effectiveness of the proposed method, showing better fault feature extraction capability compared to original methods and popular techniques.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2021)
Article
Engineering, Mechanical
Shuai Gao, Steven Chatterton, Lorenzo Naldi, Paolo Pennacchi
Summary: Rolling elements in rolling element bearings should continuously roll on raceways for pure rolling, but skidding or over-skidding may occur with improper loading and lubrication, especially in low-load roller bearings. An empirical study shows the inaccuracy of theoretical values for determining slipping of rolling elements, and proposes a more accurate KH-THD model that considers thermal effects for large-scale industrial bearings.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Mechanical
Shuai Gao, Qinkai Han, Ningning Zhou, Paolo Pennacchi, Fulei Chu
Summary: Experimental study was conducted on the stability and skidding degree of the porous oil-containing polyimide cage used in spacecraft rolling bearings. The results showed that the oil-content ratio, applied load, and rotation speed all influenced the vibration level, skidding ratio, and whirl radius fluctuation amplitude of the cage.
TRIBOLOGY INTERNATIONAL
(2022)
Article
Engineering, Mechanical
Shuai Gao, Steven Chatterton, Paolo Pennacchi, Qinkai Han, Fulei Chu
Summary: This paper presents a KH-TEHD model to address the damage problems introduced by skidding behavior and validates its accuracy and effectiveness through experimental studies. The results show that the degree of overskidding is approximately proportional to the square of the bearing size, and the maximum thermal deformation at the bearing raceway under starvation lubrication reaches 4 times the ball-raceway clearance.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Chemistry, Analytical
Syed Muhammad Tayyab, Steven Chatterton, Paolo Pennacchi
Summary: This paper presents a defect diagnosis method for rolling element bearings based on CNN and order maps, which can accurately diagnose faults under variable speed and load conditions.
Article
Engineering, Mechanical
He Biao, Yi Qin, Jun Luo, Weixin Yang, Lang Xu
Summary: In this paper, a fault feature extraction methodology based on an adaptive spectrum segmentation method, a new voting index, and a new variational model is proposed. The results show that this method outperforms other classical methods in extracting fault characteristics from vibration signals.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Electrical & Electronic
Federico Longoni, Anders Hagglund, Francesco Ripamonti, Paolo L. M. Pennacchi
Summary: The powertrain of a car plays a crucial role in the comfort offered by the vehicle due to vibrations. This paper focuses on identifying quantities that correlate with the vibration performance of powertrain setups and proposes a method to test the specificity of requirements.
Article
Engineering, Electrical & Electronic
Syed Muhammad Tayyab, Steven Chatterton, Paolo Pennacchi
Summary: Convolutional neural networks (CNN) have excellent image recognition characteristics and can be used for defect diagnosis tasks in image processing. This study compares different image processing methods in terms of fault detection accuracy and computational expense, and proposes a hybrid-ensemble method involving decision-level fusion that is computationally less expensive. The performance of these models is also compared with minimal training data availability and slight variation in operating conditions.
Article
Engineering, Electrical & Electronic
Edoardo Gheller, Steven Chatterton, Andrea Vania, Paolo Pennacchi
Summary: This paper investigates the modeling of squeeze film dampers (SFDs) and highlights the key phenomena involved in their characterization, including oil film cavitation, air ingestion, and inertia. A numerical model based on the Reynolds equation is introduced and validated with experimental results. Different designs and configurations of the feeding and sealing system are considered, and an example of applying SFDs to a compressor rotor is proposed.
Article
Engineering, Electrical & Electronic
Davide Massocchi, Marco Lattuada, Steven Chatterton, Paolo Pennacchi
Summary: This study aims to optimize lubrication systems and achieve energy efficiency and CO2 emissions reduction. By using a specific tribological testing procedure, significant time and operational cost savings can be achieved, with good correlation to the FZG test results.
Article
Engineering, Electrical & Electronic
Steven Chatterton, Edoardo Gheller, Andrea Vania, Paolo Pennacchi, Phuoc Vinh Dang
Summary: This paper investigates the static characteristics of tilting-pad journal bearings lined with different materials. A full 3D thermal model is used to evaluate the temperature distribution in the bearing, while a finite element model is used to evaluate the deformation of the pads. The permissible operating range in terms of load and speed for each material is defined by considering the limits on the maximum temperature, permissible mechanical stress, and minimum oil-film thickness.
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)
