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, Electrical & Electronic
Yaru Yue, Chengdong Chen, Xiaoyuan Wu, Xiaoguang Zhou
Summary: This article proposes an effective method for denoising ECG signals, which combines the ensemble empirical mode decomposition (EEMD), empirical mode decomposition (EMD), and wavelet packet (WP) techniques. The ECG signal is decomposed using EEMD, and then the highest frequency component is decomposed using EMD for a second time, and the high frequency components obtained from the second decomposition are decomposed and reconstructed using WP for a third time. The processed signal components are then fused to obtain the denoised ECG signal. Various evaluation metrics such as signal-to-noise ratio (SNR), mean square error (MSE), root mean square error (RMSE), and normalized cross correlation coefficient (R) are used to assess the noise reduction algorithm.
IET SIGNAL PROCESSING
(2023)
Article
Chemistry, Analytical
Zhenbao Li, Wanlu Jiang, Sheng Zhang, Yu Sun, Shuqing Zhang
Summary: An integrated hydraulic pump fault diagnosis method based on MEEMD, AR spectrum, and WKELM is proposed, achieving 100% accuracy in diagnosing hydraulic pump vibration signal faults. Compared with other methods, this approach offers higher fault recognition accuracy and faster diagnostic speed.
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
Energy & Fuels
Boyan Zhang, Xiuying Yan, Guangyu Liu, Kaixing Fan
Summary: This paper proposes an improved EEMD-HTD-GMM method for sensor fault diagnosis in HVAC systems, and the experimental results show that it has higher diagnostic ability and distinguishability.
Article
Environmental Sciences
Ronald William Lake, Saeed Shaeri, S. T. M. L. D. Senevirathna
Summary: This study further explores the application of the parametric group method of data handling (GMDH) in rainfall modeling and prediction using publicly available temperature and rainfall data. The ordinary GMDH approaches do not provide conclusive results due to lack of consistency in coefficients of determination and analysis of variance. Therefore, an empirical assessment is conducted to explain this inconsistency and improvements such as hybridization with least square support vector machines (LSSVM), application of filters for parameter estimation, and combination with signal processing techniques are investigated.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Automation & Control Systems
Xiaohui Jia, Xinping Xiao, Jianghui Wen
Summary: An integrated learning method based on wavelet neural networks was proposed in this paper for fault diagnosis of rotating machinery. The method combines multiple models to achieve accurate diagnosis of faults, and demonstrated high fault diagnosis accuracies on two datasets.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
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
Business, Finance
Kunliang Xu, Weiqing Wang
Summary: A reliable crude oil price forecast is crucial for market pricing. This study incorporates a rolling window into two prevalent EEMD-based modeling paradigms to improve accuracy. The results show that EEMD plays a weak role in improving crude oil price forecasts when only the in-sample set is preprocessed, but the rolling EEMD-denoising model has an advantage for long-term forecasting.
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS
(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
Thermodynamics
Lean Yu, Yueming Ma, Mengyao Ma
Summary: This paper proposes an effective rolling decomposition-ensemble model for quarterly gasoline consumption forecasting in China, involving data decomposition, component prediction, and ensemble output. By utilizing wavelet decomposition and support vector regression, the model addresses data scarcity issue and improves prediction accuracy.
Article
Acoustics
Geng Chen, Lihua Tang, Zhibin Yu, Brian Mace
Summary: This study investigates the mode transition phenomenon in a standing-wave thermoacoustic engine using computational fluid dynamics (CFD). It is found that with increasing temperature ratio, the TAE undergoes a series of bifurcations, leading to different oscillation modes. Nonlinear mode competition occurs during saturation, and the acoustic energy density, intensity and efficiency increase with increasing temperature ratio.
JOURNAL OF SOUND AND VIBRATION
(2021)
Article
Engineering, Chemical
Xianbiao Zhan, Huajun Bai, Hao Yan, Rongcai Wang, Chiming Guo, Xisheng Jia
Summary: This paper proposes a fault analysis method based on optimized VMD and improved CNN, which can successfully identify fault states of diesel engines with high classification accuracy, showing promising application prospects.
Article
Engineering, Environmental
Farshad Ahmadi, Saeid Mehdizadeh, Vahid Nourani
Summary: Estimation of monthly reservoir inflow in Iran's Maroon Dam reservoir utilizing climatic data showed that rainfall is the most important parameter affecting reservoir inflow. Proposed hybrid models combining random forest with complete ensemble empirical mode decomposition and wavelet analysis outperformed classic models in accuracy assessment.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2022)
Article
Acoustics
Lei Li, Qian Wang, Xin Qing, Gang Qiao, Xinyu Liu, Songzuo Liu
Summary: This study proposes a robust unsupervised whistle enhancement scheme based on improved local mean decomposition, which plays an important role in studying dolphin behavior and population distributions. Experimental results demonstrate that the proposed scheme outperforms other compared whistle enhancement schemes under different signal-to-noise ratios.
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
(2022)
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)