Article
Engineering, Multidisciplinary
Lingli Cui, Xinyuan Zhao, Dongdong Liu, Huaqing Wang
Summary: This paper proposes a novel bidirectional weighted enhanced envelope spectrum (BWEES) analysis method that can better distinguish fault features and interference components by simultaneously considering spectral and cyclic frequency information.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Engineering, Mechanical
Bingchang Hou, Dong Wang, Yikai Chen, Hong Wang, Zhike Peng, Kwok-Leung Tsui
Summary: This paper studies the integration of online monitoring data with cyclostationarity of fault transients to construct a fault cyclostationarity-based convex optimization model. An online weight updating algorithm is developed to make the weight updating of the proposed optimization model adaptive to online monitoring data. Interpretable online updated weights are proposed as an optimized square envelope spectrum (OSES) to enhance the identification of fault characteristic frequency (FCF) and its harmonics. A three-dimensional (3D) OSES and a detector with an alarming threshold are designed to achieve incipient fault time detection, fault type diagnosis, and online fault evolution monitoring. The effectiveness and superiority of this approach are validated using practical bearing datasets and experimental run-to-failure datasets.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Multidisciplinary
Bingyan Chen, Dongli Song, Weihua Zhang, Yao Cheng
Summary: This paper proposes a weighted combined envelope spectrum (WCES) based on spectral coherence for bearing damage detection. By introducing frequency domain signal-to-noise ratio and a weighting function, this method can effectively reveal and extract bearing damage information.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Engineering, Mechanical
Jeung-Hoon Lee
Summary: The study proposes a weighting function for integrating spectral coherence to improve envelope spectrum estimation, amplifying spectral bands with high auto correlations through the integration process. This method alleviates the burden of selecting frequency bands and demonstrates effectiveness in challenging scenarios such as noisy environments or multiple types of faults.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Multidisciplinary
Bingyan Chen, Yao Cheng, Weihua Zhang, Fengshou Gu
Summary: A novel fault detector, weighted combined envelope spectrum (WCES), based on spectral coherence, has been proposed. It effectively detects bearing faults under strong interference noise and multiple resonances, providing potential application value in bearing diagnostics.
Article
Automation & Control Systems
Boyao Zhang, Yonghao Miao, Jing Lin, Hao Li
Summary: The demodulation analysis for bearing diagnosis aims to determine the fault-induced frequency band and detect the potential bearing fault characteristic frequency (FCF) in the demodulated spectrum. A novel FCF-oriented criterion is proposed to determine all informative frequency bands, and a weighted envelope spectrum (WES) is introduced to enhance fault information.
Article
Engineering, Multidisciplinary
Baokun Han, Zujie Yang, Zongzhen Zhang, Huaiqian Bao, Jinrui Wang, Zongling Liu, Shunming Li
Summary: This research proposes a bearing fault diagnosis method based on GNSS, which eliminates the interference of large-amplitude shocks and improves the accuracy of fault extraction by using nonlinear spectral sparsity.
Article
Engineering, Multidisciplinary
Yao Cheng, Bingyan Chen, Weihua Zhang
Summary: Spectral coherence is a dedicated method for characterizing the cyclostationarity of bearing faults. However, the vibration signal produced by complex mechanical systems often exhibits mixed cyclostationarity, which presents a challenge for fault identification. To address this issue, an enhanced spectral coherence method is proposed in this study.
Article
Engineering, Multidisciplinary
Moise Avoci Ugwiri, Marco Carratu, Vincenzo Paciello, Consolatina Liguori
Summary: This paper presents a methodology based on vibrations for fault detection in rotating machines, focusing on the detection of repetitive transients using time-frequency techniques. By measuring the negentropy of squared envelope and squared envelope spectrum, along with utilizing spectral correlation and kurtosis, the paper aims to capture the signature of repetitive behavior in mechanical signals. Results demonstrate that negentropy combined with spectral correlation significantly extends the applicability of kurtogram in fault detection and localization.
Article
Chemistry, Analytical
Di Pei, Jianhai Yue, Jing Jiao
Summary: In this study, a novel method based on envelope spectrum fault characteristic frequency band identification (FCFBI) is proposed for bearing fault diagnosis under variable speed conditions. The method analyzes the characteristics of the bearing fault vibration signal's envelope spectrum under variable speed and introduces the fault characteristic frequency band (FCFB) as a new representation of faults. Fault templates based on FCFB are constructed as references for fault identification. The proposed method achieves satisfactory diagnostic accuracy in two bearing variable speed experiments and demonstrates comprehensive superiority over order tracking (OT) and time-frequency analysis (TFA) methods.
Article
Automation & Control Systems
Bingyan Chen, Yao Cheng, Weihua Zhang, Fengshou Gu, Guiming Mei
Summary: In this study, a new targeted feature is proposed to distinguish the optimal frequency band of spectral coherence, and the effectiveness of different methods in bearing fault diagnosis is validated and compared. The advantages and limitations of blind and targeted feature-based methods in different scenarios are summarized, and it is concluded that the presented approach can accurately detect bearing faults.
Article
Acoustics
Yao Cheng, Shengbo Wang, Bingyan Chen, Guiming Mei, Weihua Zhang, Han Peng, Guangrong Tian
Summary: This study proposes a method based on spectral coherence to identify bearing faults. By displaying the energy flow of vibration signal in a two-dimensional plane, the periodic faults of the bearings can be accurately identified. To address the interference and noise issues, an adaptive method is introduced to determine the informative spectral frequency band.
JOURNAL OF SOUND AND VIBRATION
(2022)
Article
Computer Science, Information Systems
Tian Xue, Huaiguang Wang, Dinghai Wu
Summary: This paper proposes a method for bearing fault diagnosis using the MobileNetV2 network and fast spectral kurtosis. By compressing the feature information layer by layer and adding a cross-local connection structure, the method achieves high-precision and rapid identification and classification. The fast spectral kurtosis algorithm is used to process the signal and improve the efficiency of fault feature extraction. Experimental results show the advantages of the proposed method in terms of accuracy, model size, and training speed, and demonstrate its effectiveness and generality in the field of fault diagnosis.
Article
Engineering, Multidisciplinary
Bo Li, Xuefang Xu, Hang Tan, Peiming Shi, Zijian Qiao
Summary: Frequency band selection is crucial for fault diagnosis of rolling element bearings using the kurtogram and its variants. Existing methods often neglect the cyclostationarity, a typical symptom of faulty bearings, resulting in the inability to extract weak fault features. To address this issue, a novel method called Cyclogram is proposed, which combines kurtosis and cyclostationarity to select frequency bands effectively. The proposed method decomposes a signal into different frequency bands using a wavelet packet transform, calculates squared envelopes for these bands, and constructs a robust indicator based on cyclic spectral coherence and kurtosis. This method outperforms traditional fault-diagnosis methods and can identify faults in signals corrupted with Gaussian and non-Gaussian noise.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2023)
Article
Engineering, Multidisciplinary
Xiumei Li, Jianyan Sun
Summary: This paper proposes a fault diagnosis method for rolling bearing faults based on an improved fast kurtogram and novel envelope spectrum analysis. The method efficiently extracts features and diagnoses rolling bearing faults.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Mechanical
Kaigan Zhang, Tangbin Xia, Dong Wang, Genliang Chen, Ershun Pan, Lifeng Xi
Summary: This paper proposes a privacy-preserving and sensor-fused framework for time-to-failure updating and predictive maintenance arrangement in a leased manufacturing system. By encrypting and using functional features, the privacy signals of both parties are protected, and real-time updating and maintenance adjustment are achieved.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Mechanical
Khandaker Noman, Bingchang Hou, Dong Wang, Yongbo Li, Shun Wang
Summary: Diversity entropy (DE) is a new nonlinear dynamic measure that quantifies the complexity of vibration signals for prognostics of rolling element bearings. However, in real-life maintenance operations, the distinctive fault signals are often submerged under random noise components, leading to poor performance of DE in detecting and tracking bearing faults. To overcome these limitations, this paper proposes a weighted square envelope based DE (WSEDE) that suppresses unwanted noise components. Experimental results using two different datasets demonstrate that WSEDE outperforms the original DE and conventional fuzzy entropy (FE) as well as an advanced DE-based measure called multiscale DE (MDE).
NONLINEAR DYNAMICS
(2023)
Article
Mechanics
Xin Wen, Dong Wang, Ziyu Chen, Fan Yang, Chengru Jiang, Yingzheng Liu
Summary: Kirigami structures are used for the first time to achieve dynamic passive flow control by activating and deactivating an array of tilted surface elements on a bluff body. The control performance is validated in a wind tunnel, showing that activated kirigami structures can push the shedding vortices downstream and reduce turbulent intensity and Reynolds shear stress. The performance depends largely on the height and shape of the kirigami structures.
Article
Engineering, Manufacturing
Le Dong, Jinqiang Wang, Dong Wang
Summary: This research proposes a design framework for 3D voxel printed lattice metamaterials, combining theoretical models, finite element modeling (FEM), and experimental validations. A theoretical model and a python-assisted FEM for voxel lattice metamaterials with curled microstructures and arbitrary material distributions are developed. A parametric algorithm is developed to automatically generate the voxel matrix for manufacturing. The design framework is used to program mechanical properties and demonstrate multifunctionality in various applications.
ADDITIVE MANUFACTURING
(2023)
Article
Engineering, Mechanical
Tongtong Yan, Dong Wang, Tangbin Xia, Zhike Peng, Lifeng Xi
Summary: In this study, a sparsity preserving projection aided baselined hyperdisk model is proposed for interpretable initial fault detection, diagnosis, and degradation assessment. The methodology extracts interpretable projection features for immediate fault diagnosis and constructs a HI for initial fault detection based on low-dimensional features. Case studies show that the proposed methodology outperforms SVDD, hyperplane based degradation modeling, and other statistical based HIs.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Mechanical
Yikai Chen, Dong Wang, Bingchang Hou, Tangbin Xia
Summary: Interpretable learning models have become an emerging topic in machine condition monitoring, connecting signal processing algorithms with statistical learning and machine learning. These models generate interpretable weights and parameters as physically interpretable fault features for monitoring and diagnosis.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Mechanical
Tongtong Yan, Dong Wang, Meimei Zheng, Changqing Shen, Tangbin Xia, Zhike Peng
Summary: This study proposes a physics-informed learning framework that combines weight-based sparse degradation modeling with entropy-based indicators for online incipient fault detection and diagnosis. The weak fault characteristics can be significantly enhanced by continuously updating the model weights. A family of entropy-based indicators is introduced for machine health monitoring, aiming to quantify the amplified fault characteristics revealed by the updated model weights for online incipient fault detection.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Review
Engineering, Mechanical
Peng Zhou, Shiqian Chen, Qingbo He, Dong Wang, Zhike Peng
Summary: Rotating machinery faults can be diagnosed by extracting fault-induced modulation features in vibration signals. The research on fault-induced signal modulation mechanisms, modulation feature extraction methods, and applications for diagnosis has achieved great progress. A systematic review is urgently needed to summarize these achievements and guide future directions and developments. This paper aims to fill these gaps by reviewing and summarizing typical modulation effects induced by transmission elements, reviewing different time-frequency analysis and signal decomposition methods, and introducing representative works of vibration signal modulation feature extraction-based fault diagnosis.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Electrical & Electronic
Bingchang Hou, Dong Wang
Summary: This article proposes an optimal noise subtraction (ONS) method for fault components extraction. The ONS is based on an optimized weights spectrum (OWS) modeling of healthy and faulty signals, reducing the influence of interferential components. The enhanced fault components by the ONS are used to obtain an improved spectral coherence (SC) diagram for machinery fault diagnosis (MFD).
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Dong Wang, Naifu Zhang, Meixia Tao, Xu Chen
Summary: Federated learning is a distributed learning paradigm that allows edge devices to collaborate on training a shared model while preserving privacy. This paper introduces knowledge distillation to handle model heterogeneity, and proposes an algorithm for efficient knowledge aggregation. It also presents a threshold-based technique to optimize the local model updating and distillation intensity. Experimental results demonstrate the superior performance of the proposed approach compared to existing methods.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2023)
Article
Automation & Control Systems
Meimei Zheng, Hongqing Ye, Dong Wang, Ershun Pan
Summary: This paper investigates the role of spare parts ordering decisions from different suppliers in reducing related costs. The quality of spare parts is rarely considered in previous studies. The joint optimization of equipment maintenance and spare parts ordering is explored using a Markov decision process and an exact value iteration algorithm. Heuristic methods are also developed to improve computation efficiency.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Letter
Gastroenterology & Hepatology
Xian Zheng Qin, Chun Hua Zhou, Ben Yan Zhang, Ling Zhang, Ting Ting Gong, Min Min Zhang, Dong Wang, Duo Wu Zou
JOURNAL OF DIGESTIVE DISEASES
(2023)
Article
Engineering, Electrical & Electronic
Bingchang Hou, Jie Liu, Dong Wang
Summary: This article proposes an equivalent and easier computational approach to calculate interpretable optimized weights for machine condition monitoring (MCM). The idea is extended to spectral correlation to construct 2-D optimized weights for enhancing fault features. Furthermore, a health index based on the optimized weights is constructed, which has a strong degradation assessment ability. Experimental results verify the effectiveness of these new ideas for MCM.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Industrial
Meimei Zheng, Zhiyun Su, Dong Wang, Ershun Pan
Summary: This paper investigates the joint optimization of maintenance and spare part ordering from multiple suppliers for systems consisting of multiple components. A model is established through a Markov decision process, and a value iteration algorithm and a hybrid deep reinforcement learning algorithm (HDRL) are designed to solve the model. Numerical experiments validate the effectiveness of the HDRL algorithm.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
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)