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bearing fault Numerical Model for the Closed-slot Rotor Submersible Motor

Chinese Journal of Electrical Engineering 2023年第2期9卷 84-93页

作者： Zhe Ke Bokai Guan Chong Di Jingwen Yan Xiaohua Bao School of Electrical Engineering and Automation Hefei University of TechnologyHefei 230009China School of Electrical and Computer Engineering The Ohio State UniversityColumbus OH 43210USA

A numerical model of the bearing fault of a motor with a closed-slot rotor using the finite element method(FEM)is *** rotor’s radial motion can be regarded as static eccentric at the defect time points and healthy at other time *** frequency of the harmonic component is analyzed corresponding to bearing fault in stator current according to the radial movement of the motor ***,the relative permeability variation region is established to achieve the radial motion of the rotor with bearing ***,the relative permeability variation region is established in the health and static eccentric ***,the defect time points are estimated and the static eccentricity model by transient field is ***,the relative permeability of the variable region in the static eccentric model is imported into the variable region of the health model at the defect time *** simulation results show that the air gap flux density of the bearing fault model is different from that of the health model and static eccentric *** addition,the stator current contains harmonic components of the bearing *** analysis results prove the applicability of the proposed model.

关键词： bearing fault finite element method relative permeability variation region closed-slot rotor stator current

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Enhanced Detection of Rolling Element bearing fault Based on Stochastic Resonance

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Chinese Journal of Mechanical Engineering 2012年第6期25卷 1287-1297页

作者： ZHANG Xiaofei HU Niaoqing CHENG Zhe HU Lei Key Laboratory of Science and Technology on Integrated Logistics Support National University of Defense TechnologyChangsha 410073China

Early bearing faults can generate a series of weak impacts. All the influence factors in measurement may degrade the vibration signal. Currently, bearing fault enhanced detection method based on stochastic resonance（SR） is implemented by expensive computation and demands high sampling rate, which requires high quality software and hardware for fault diagnosis. In order to extract bearing characteristic frequencies component, SR normalized scale transform procedures are presented and a circuit module is designed based on parameter-tuning bistable SR. In the simulation test, discrete and analog sinusoidal signals under heavy noise are enhanced by SR normalized scale transform and circuit module respectively. Two bearing fault enhanced detection strategies are proposed. One is realized by pure computation with normalized scale transform for sampled vibration signal, and the other is carried out by designed SR hardware with circuit module for analog vibration signal directly. The first strategy is flexible for discrete signal processing, and the second strategy demands much lower sampling frequency and less computational cost. The application results of the two strategies on bearing inner race fault detection of a test rig show that the local signal to noise ratio of the characteristic components obtained by the proposed methods are enhanced by about 50% compared with the band pass envelope analysis for the bearing with weaker fault. In addition, helicopter transmission bearing fault detection validates the effectiveness of the enhanced detection strategy with hardware. The combination of SR normalized scale transform and circuit module can meet the need of different application fields or conditions, thus providing a practical scheme for enhanced detection of bearing fault.

关键词： bearing fault stochastic resonance normalized scale transform nonlinear bistable system

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Rolling bearing fault feature extraction based on Daubechies wavelet decomposition

Rolling bearing fault feature extraction based on Daubechies...

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第37届中国控制会议

作者： Huazhao Ding Yongjian Sun School of Electrical Engineering University of Jinan

Rolling bearing is an important mechanical component existing in various equipment. Due to different structure,besides the normal operation status, the usual faults may be classified into ball fault, outrace fault and inner race fault. In order to deal with the non-stationary fault signal, an orthogonal power distribution space is developed in this manuscript, in which the coordinate is obtained according to the wavelet decomposition. In this way, different signal is decomposed and mapped into higher dimensional fault space. Detailed process is given and numerical simulation is carried out to prove this method. Simulation results indicates that present method may distinguish the four main operational status of rolling bearing, which supplies a novel angle of view in practical engineering.

关键词： bearing fault wavelet decomposition power spectrum fast fourier transform

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The multilabel fault diagnosis model of bearing based on integrated convolutional neural network and gated recurrent unit

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International Journal of Intelligent Computing and Cybernetics 2022年第3期15卷 401-413页

作者： Shanling Han Shoudong Zhang Yong Li Long Chen College of Mechanical and Electronic Engineering Shandong University of Science and TechnologyQingdaoChina College of Materials Science and Engineering Shandong University of Science and TechnologyQingdaoChina

Purpose-Intelligent diagnosis of equipment faults can effectively avoid the shutdown caused by equipment faults and improve the safety of the *** present,the diagnosis of various kinds of bearing fault information,such as the occurrence,location and degree of fault,can be carried out by machine learning and deep learning and realized through the multiclassification ***,the multiclassification method is not perfect in distinguishing similar fault categories and visual representation of fault *** improve the above shortcomings,an end-to-end fault multilabel classification model is proposed for bearing fault ***/methodology/approach-In this model,the labels of each bearing are binarized by using the binary relevance ***,the integrated convolutional neural network and gated recurrent unit(CNN-GRU)is employed to classify *** from the general CNN networks,the CNN-GRU network adds multiple GRU layers after the convolutional layers and the pool ***-The Paderborn University bearing dataset is utilized to demonstrate the practicability of the *** experimental results show that the average accuracy in test set is 99.7%,and the proposed network is better than multilayer perceptron and CNN in fault diagnosis of bearing,and the multilabel classification method is superior to the multiclassification ***,the model can intuitively classify faults with higher ***/value-The fault labels of each bearing are labeled according to the failure or not,the fault location,the damage mode and the damage degree,and then the binary value is *** multilabel problem is transformed into a binary classification problem of each fault label by the binary relevance method,and the predicted probability value of each fault label is directly output in the output layer,which visually distinguishes different fault conditions.

关键词： Intelligent fault diagnosis bearing fault Multilabel classification CNN-GRU Binary relevance method

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fault Detection of Motor bearing with Embedded coils and PCA Algorithm 36

Fault Detection of Motor Bearing with Embedded coils and PCA...

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第36届中国控制会议

作者： Shirong Zhang Qin Cheng Qiqiang Zhang Wenlian Chen Longbo Zhang Department of Automation School of Power and Mechanical EngineeringWuhan University Zhejiang Erg Technology Joint Stock Co. Ltd

ISBN: (纸本)9781538629185

bearing faults are the main contributors to the failures of induction motors,which are widely used in industrial *** this paper,8 embedded coils are firstly proposed for air gap *** the 8 coils,6 differential signals are generated,which are sensitive indicators to the bearing ***,PCA is introduced for fault *** with an oil pump fault detection are carried out to verify our *** results convince the validity and effectiveness of the embedded coils and PCA based method.

关键词： Induction motor bearing fault PCA algorithm Air gap eccentricity Embedded coils

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Feature Extraction of bearing faults based on a Novel Index of Cepstrum

Feature Extraction of Bearing Faults based on a Novel Index ...

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第37届中国控制会议

作者： Huazhao Ding Yongjian Sun Xiaohong Wang School of Electrical Engineering University of Jinan

bearing is the common component used in modern mechanical equipment, its fault feature extraction is of importance to the safe operation. A new feature extraction index named pseudo distance of cepstrum edge（PDCE） is proposed in this paper,and the detailed process is discussed. Four principles of determining the diacritical standard is summed up. In order to validate the capability of this new method, 8000 points of vibration data representing four different operational status are adopted, which are all from practical bearing fault experiment. Numerical simulation experiment including a test simulation analysis is carried out, results testify the usability of present index.

关键词： bearing fault fault diagnosis feature extraction cepstrum

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Analysis of temperature characteristics of high-speed train wheelset system under complex operating conditions

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International Journal of Mechanical System Dynamics 2024年第3期4卷 331-345页

作者： Baosen Wang Yongqiang Liu Yingying Liao Yixuan Wang School of Mechanical Engineering Shijiazhuang Tiedao UniversityShijiazhuangChina Hebei Key Laboratory of Mechanical Power and Transmission Control Shijiazhuang Tiedao UniversityShijiazhuangChina School of Civil Engineering Shijiazhuang Tiedao UniversityShijiazhuangChina Taiyuan Vehicle Depot Daqin Railway Co.Ltd.TaiyuanChina

With the rapid advancements in high-speed train technology,the importance of ensuring the safety of train operations has become ***,being a critical component of train bogies,have garnered significant attention for their role in maintaining safety *** the temperature of bearings to evaluate their motion state is a common practice in high-speed trains,emphasizing the need for further research into temperature *** this study,a dynamic model is developed for the bearing rotor system of high-speed *** considering the contact points between raceways and rolling elements,the power loss in the bearing is obtained and a transient temperature-field model of the system is *** relationship between node temperature and factors such as ambient temperature,train running speed,and load is illustrated,with a detailed presentation of the influence of bearing fault type and size on node *** analysis results reveal that the node temperature increases with higher values corresponding to those quantifiable factors and is most affected by rolling element ***,it is observed that the temperature rises rapidly in the initial stage and gradually flattens out over *** comparative analysis of temperature under different fault conditions shows that the node temperature is most affected by the rolling element *** and actual line temperature data are used to verify the validity of the *** comparison results show that the simulation aligns well with experimental and line *** transient temperature-field model of the bearing rotor system in high-speed trains can effectively simulate and predict the temperature change process of each node of the *** simulation results hold certain theoretical guiding significance for further research and practical applications in ensuring train operation safety.

关键词： high-speed train dynamic model transient temperature field bearing fault line data

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