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2024 IEEE International Conference on Sensing, Diagnostics, Prognostics, and control, SDPC 2024

作者： Zhihao, Wu Shixian, Gong Chenguang, Huang Hang, Jin Zechao, Liu Crrc Qingdao Sifang Locomotive and Rolling Stock Co. Ltd National Engineering Laboratory Qingdao China Behavior and System Safety of Traffic Engineering Structure and School of Mechanical Engineering Shijiazhuang Tiedao University State Key Laboratory of Mechanical Shijiazhuang China Data Management Engineering Center Weichai Power Co. Ltd. Weifang China Institute of Magnetic Levitation and Electromagnetic Propulsion China Aerospace Science and Industry Corporation Limited Beijing China Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University State Key Laboratory of Mechanical Shijiazhuang China

ISBN: (纸本)9798350388855

The division and determination of frequency bands are always core problems in fault diagnosis methods for rotating machinery. Currently, the frequency band division strategy of most fault diagnosis methods is the 1/3-binary tree or realized by wavelet packet transform (such as fast kurtosis diagram and Autogram). This method is relatively fixed, making it difficult to accurately cover the resonance frequency band and achieve multi-source fault identification. To address the above problems, an adaptive frequency band division strategy based on Fast Spectral Correlation (FSC) and Scale-Space Representation (SSR) is proposed. The enhanced enveloping spectrum (EES) of each frequency band after division is obtained, and the improved Fault Quantification Index (IFQI) is used to measure the richness of target information in each enveloped spectrum (ES), generating a two-dimensional diagram. The envelope spectrum with the largest IFQI value is selected as the improved envelope spectrum (IES) obtained by the FSC and SSR division strategy (IESFSC-SSRgram), enabling the fault diagnosis of the axle box bearing. The effectiveness and superiority of the proposed method in identifying multi-source concurrent faults in the wheelset bearing system are verified by comparing it with the traditional method. © 2024 IEEE.

关键词： Binary trees

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Design and Experimental Study of Novel controllable Attenuator Systems for Constant Temperature Air-Conditioning 18

Design and Experimental Study of Novel Controllable Attenuat...

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18th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Weichen, Guo Yusong, Hong Zeng, Wang Xuejin, Zhu Zhe, Zhu Wei, Ye School of Mechanical Engineering Tongji University Shanghai China Shanghai Architectural Design and Research Institute Co. LTD Shanghai China Key Laboratory of Performance Evolution and Control for Engineering Structures of Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9798331306816

High-end manufacturing and fundamental physics research require the provision of indoor air environments with ultra-high precision constant temperature. Therefore, the chilled water system, which is the main source of cooling, also requires strict temperature control. Current closed-loop control loops are mainly used to overcome low-frequency disturbances, and attenuators are usually used to overcome high-frequency fluctuations. In this study, two high-precision controlled attenuator systems based on two typical attenuators, i.e., plate heat exchanger and water mixing pump, were proposed, which combined PID control and attenuator through flow control to achieve full-frequency fluctuation control of fluid temperature. Experiments on controlled attenuator operation under two schemes were carried out. And the Fourier transform was used to calculate the fluctuation spectrum and to analyse the sources of disturbances. The control and attenuation processes of the system were analysed in the frequency domain and the fluctuating perturbations caused by the pump were highlighted. © 2024 18th Conference of the International Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - Conference Program and Proceedings. All rights reserved.

关键词： Air conditioning

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A Subdomain Adaptation Based Bearing Fault Diagnosis Method Using Infrared Thermal Images

A Subdomain Adaptation Based Bearing Fault Diagnosis Method ...

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International Conference on Sensing, Diagnostics, Prognostics, and control (SDPC)

作者： Jie Yao Xiaohui Gu State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang China

ISBN: (数字)9798350388855

ISBN: (纸本)9798350388862

A sub-domain transfer learning method based on multi-scale convolutional neural network and infrared thermal images is proposed to improve the diagnostic accuracy of bearing faults. Firstly, infrared thermal images with more characteristic information are used to represent the healthy condition of bearings instead of vibration signals. Then, a multi-scale convolutional neural network model is constructed to enhance the feature extraction ability, and a sub-domain adaptation method is used to deal with the situation when training and testing samples are not consistent of independent identically distribution. The proposed method is verified by two datasets from rotating machinery and railway bearing test bench. The results show its effectiveness and robustness than some popular peer transfer learning strategies and vibration signal based methods.

关键词： Vibrations Fault diagnosis Training Time-frequency analysis Accuracy Transfer learning Feature extraction Convolutional neural networks Spectrogram Testing

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Fuzzy-SMC Stabilization control Based on Vehicle-Road Recognition for Real-time and Variable Speed Conditions (October 2024)

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IEEE Access 2025年

作者： Wang, Guiyang Li, Shaohua Li, Jianchao Hebei College of Industry and Technology Shijiazhuang050091 China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang050043 China

Distributed drive vehicles are able to control the output torque of each wheel independently, which can improve vehicle stability. The accuracy of road adhesion coefficient identification has a large impact on the results of yaw rate and side-slip angle estimation. A multivariate controller for real-time identification of road adhesion coefficients is designed for the Fuzzy-SMC (Fuzzy Sliding Mode control) stability-vehicle speed coupling control of yaw stability and speed tracking of distributed drive electric vehicles. The Improved LM-MMSOFNN ( Levenberg Marquardt Multi-Module Self-Organizing Neural Networks) method is utilized to realize the road adhesion coefficient identification online, fuzzy sliding mode control is used to estimate the gain of the system to eliminate uncertainties and chattering. Hierarchical control method is adopted, the upper layer calculates the additional yaw moment with vehicle longitudinal speed tracking, and the lower layer is torque distribution layer. Considering motor characteristics and longitudinal force requirements, this control problem is transformed into a multi objective optimization problem. In variable speed working condition, compared with SMC control Fuzzy SMC control yaw rate curve is smoother, has less oscillation, the vehicle driving state is smoother. The value of side-slip angle is smaller the whole distance, and the maximum is 0.015deg. Thus it can be verified that the proposed method is adaptive to the real driving requirements. © 2013 IEEE.

关键词： Parameter estimation

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Low-light traffic Objects Detection for Automated Vehicles 6

Low-light Traffic Objects Detection for Automated Vehicles

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6th CAA International Conference on Vehicular control and Intelligence, CVCI 2022

作者： Wang, Xuewei Wang, Dongmei Li, Siyuan Li, Shaohua Zeng, Pengtian Liang, Xiao Shijiazhuang Tiedao University State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang China School of Mechanical Engineering Shijiazhuang Tiedao University Shijiazhuang China

ISBN: (数字)9781665453745

ISBN: (纸本)9781665453745

The low-light condition brings huge challenges to the traffic object detection, limiting its application in complex scenarios such as the round-the-clock traffic monitoring and automatic driving. To address this issue, an accurate traffic object detection method in low-light conditions is proposed. First, the dark channel prior knowledge is utilized to restore the scene radiance via the transmission map and the estimation of the atmospheric light. Meanwhile, the grayscale is adjusted by adaptive gamma transformation to further improve the brightness of the image and reduce the impact of low-light conditions. Second, a LL4PH-Net framework equipped with preset anchors and detection branches is developed to detect low-light traffic objects. The performance of the algorithm is tested on the public BDD100K dataset. Experimental results show that compared with the SOTA methods, the proposed LL4PH-Net acquires the best detection mAP, the most lightweight model and a good time efficiency. It can effectively detect traffic objects even under low-light conditions. © 2022 IEEE.

关键词： Image enhancement

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A NOVEL BEARING FAULT DIAGNOSIS METHOD BASED ON FEATURE FUSION AND CONVOLUTIONAL NEURAL NETWORK 1

A NOVEL BEARING FAULT DIAGNOSIS METHOD BASED ON FEATURE FUSI...

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1st International Conference on mechanical System Dynamics, ICMSD 2022

作者： Zhao, Jing Yang, Shaopu Li, Qiang Liu, Yongqiang School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang China School of Mechanical Engineering Shijiazhuang Tiedao University Shijiazhuang China

ISBN: (数字)9781839537837

ISBN: (纸本)9781839537837

The effective fault diagnosis method is crucial for the engineering. At present, the fault diagnosis methods based on data-driven have achieved much attention. The traditional methods only utilize one sensor or one channel data. However, there are more than one sensor or channel in the data acquisition system. To take full advantage of the connection between different channels data, a bearing fault diagnosis method based on feature fusion and convolutional neural network is put forward in this paper. First, two different channels data are fused to obtain different fault features. Then, convolutional neural network is applied to classify the different faults through the fusion features. Finally, the performance of the proposed approach is verified by the drive train dynamics simulator test. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Failure analysis

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EFFECT OF TOOTH CRACK ON MESH STIFFNESS AND VIBRATION RESPONSE OF A SPUR GEAR SYSTEM WITH CLEARANCE NONLINEARITY 1

EFFECT OF TOOTH CRACK ON MESH STIFFNESS AND VIBRATION RESPON...

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1st International Conference on mechanical System Dynamics, ICMSD 2022

作者： Hou, Jingyu Li, Qiang Yang, Shaopu Liu, Yongqiang School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang China School of Mechanical Engineering Shijiazhuang Tiedao University Shijiazhuang China

ISBN: (数字)9781839537837

ISBN: (纸本)9781839537837

The mesh stiffness and vibration characteristics of a spur gear system are investigated when the crack propagates beyond the central line of the tooth. The time-varying mesh stiffness (TVMS) in the single-tooth engagement region and in the double-tooth engagement region for a spur gear with tooth crack is obtained based on the potential energy principle. A 4 DOF gear system considering the tooth backlash and the clearance of supporting system in the radial direction is established, and the effect of different crack sizes on the response of the system is studied. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Spur gears

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Research on the control Technology of High Water Temperature Tunnel Grouting Water Plugging and Heat Insulation 11th

Research on the Control Technology of High Water Temperature...

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11th International Conference on Civil engineering, ICCE 2024

作者： Yang, Tengjie Tian, Baolei Xue, Yongqing Gao, Xinqiang State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang050043 China School of Civil Engineering Shijiazhuang Tiedao University Shijiazhuang050043 China China Railway 18th Bureau Group Corporation Limited Tianjin300222 China

ISBN: (纸本)9783031879586

The surrounding rock experiences the combined impacts of elevated ground stress, high water pressure, and hot groundwater during the deep-buried tunnels with high water temperatures. The stress in the surrounding rock and groundwater flow significantly affects the temperature variations in the tunnel's construction environment. Therefore, studying heat insulation and cooling measures while constructing high-water temperature tunnels is significant. This study uses a numerical simulation method to analyze water plugging and cooling feasibility in high-water temperature tunnels through grouting measures under thermal-fluid-solid coupling conditions. The variation characteristics and laws of the tunnel's stress field, seepage field, and temperature field surrounding rock under different grouting parameters are discussed. The results show that underground hot water is significantly lost when tunnels are excavated without grouting, and the tunnel wall's cooling effect is inferior. After constructing a 5 m grouting ring, excavating the tunnel significantly affects the seepage and temperature fields within the grouting ring. The seepage flow of underground hot water in the tunnel is reduced to about 1/2942 of its original value before grouting, and the temperature of the tunnel wall is significantly reduced. Through orthogonal testing, the order of influence of different grouting parameters on the average temperature of the tunnel wall is determined as follows: grouting permeability k > grouting thickness d > solid thermal conductivity of the grouting ring λ > thermal expansion coefficient of the grouting ring β. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Thermal insulation

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Mesh stiffness calculation and vibration analysis of the spur gear pair with tooth crack,considering the misalignment between the base and root circles

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International Journal of mechanical System Dynamics 2021年第1期1卷 143-156页

作者： Jingyu Hou Shaopu Yang Qiang Li Yongqiang Liu Jiujian Wang School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijingChina State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuangChina School of Mechanical Engineering Shijiazhuang Tiedao UniversityShijiazhuangChina State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan UniversityChangshaChina

An improved variable cross‐section cantilever beam model for evaluating the time‐varying mesh stiffness(TVMS)of the perfect gear tooth is developed in which the tooth number of driving gear is less than 42 and that of driven is more than *** TVMS obtained by the proposed method is compared with the result without considering the misalignment between the base circle and gear *** types of root crack models and changes inTVMS of 13‐crack levels are *** fault vibration characteristic of a single‐stage spur gear reducer with root crack is ana-lyzed and the correctness is qualitatively verified by the vibration signals of an experimental gearbox with crack or missing *** results presented in this paper are of great significance for a deep understanding of the possible causes of vibration and noise of gears and provide a theoretical foundation for the fault diagnosis of the gearbox.

关键词： backlash gear potential energy method time‐varying mesh stiffness(TVMS) tooth crack

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An Extension of Correlated Kurtosis to Tunable Q-Factor Wavelet Transform in Fault Diagnosis of Rolling Element Bearings

An Extension of Correlated Kurtosis to Tunable Q-Factor Wave...

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2021 IEEE International Conference on Sensing, Diagnostics, Prognostics, and control, SDPC 2021

作者： Zhao, Jing Li, Qiang Yang, Shaopu Liu, Yongqiang School of Mechanical Electronic and control Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang China

ISBN: (纸本)9781665449762

In engineering practice, the type of rolling bearing failures are typical, and the fault signals are impulsive, which are influenced by the running status, the frequency component of the vibration signals become extremely complicated. Tunable Q-Factor wavelet transform (TQWT) method based on correlation kurtosis is proposed. This method decomposes the bearing fault signal into two different parts, high and low resonance components (HRC and LRC), basing on the different characteristics of signal oscillation. Then, calculating the correlation kurtosis of each decomposition layer of LRC to achieve signal reconstruction. Envelope demodulation analysis is performed on the reconstructed LRC . This method replaces the kurtosis index used in previous studies with correlated kurtosis index, which can effectively eliminate or weaken the influence of peak value interference. Finally, the simulation signals and wheelset bearing test signals are validated. The results show that this method can extract the features of bearing outer, inner and roller under strong background noise. © 2021 IEEE.

关键词： Wavelet transforms

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