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A novel rotor dynamic balancing method based on blade tip clearance measurement without the once per revolution sensor

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Chinese Journal of Aeronautics 2025年第2期38卷 445-458页

作者： Weibo LI Weimin WANG Shuai ZHANG Jiale WANG Yulong LIN Tianqing LI Key Lab of Engine Health Monitoring-Control and Networking of Ministry of Education Beijing University of Chemical TechnologyBeijing 100029China State Key Laboratory of High-end Compressor and System Technology Beijing University of Chemical TechnologyBeijing 100029China

The existence of the aeroengine casing,limited monitoring points,and multi-fault characteristics make obtaining the rotor’s vibration transmission characteristics challenging,resulting in difficulties accurately identifying the rotor *** paper utilizes a high-frequency composite sensor to monitor the engine’s blade tip clearance(BTC)and extracts unbalanced information from BTC signals for rotor dynamic balancing,while avoiding the need for the once per revolution(OPR)***,the vibration characteristics of the rotor-blade system under multi-fault conditions are ***,based on BTC measurement,a none OPR method and an unbalance identification method are proposed,in which the radial vibration of the blade tip in the BTC signals at different speeds is extracted and operated in the time domain to obtain the rotor unbalanced vibration,the signal is reconstructed,and cross-correlation analysis is used to accurately identify the magnitude and phase of the unbalanced ***,a rotor test bench is utilized for experimental *** results reveal that the dynamic balancing method based on the BTC signal can more precisely identify the rotor unbalance than the traditional rotor dynamic balancing *** application of this technique will effectively improve engine health management and fault prediction.

关键词： Aeroengine Rotor unbalance Composite sensor None once per revolution Blade tip clearance Dynamic balancing

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Flow Field Simulation and Parameter Analysis of Hydraulic Unbalanced Bionic Self-recovery Actuator for Rotary Equipment

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Journal of Bionic engineering 2024年第1期21卷 325-343页

作者： Wei Li Xin Pan Dehong Ge Jinji Gao Key Laboratory of Engine Health Monitoring-Control and Networking of Ministry of Education Beijing University of Chemical TechnologyBeijing 100029China Beijing Key Laboratory of High-End Mechanical Equipment Health Monitoring and Self-Recovery Beijing University of Chemical TechnologyBeijing 100029China

The rotor is the most important component of rotating machinery,and the vibration produced by its mass unbalance has a serious influence on the secure and steady operation of the machine,so an effective online suppression technology is urgently needed.A new hydraulic unbalanced bionic self-recovery system is introduced,imitating the way of manually repairing faulty *** accomplish the effect of actuator mass redistribution,the technology employs pressurized air to drive the quantitative transfer of liquid in the reservoir cavity at opposite *** can complete the online adjustment of the equipment's balancing state and suppress the unbalanced vibration of equipment in real time,which gives the equipment the ability to maintain an autonomous health state and improve equipment *** composition and working principle of the system are introduced in detail,and the key performance parameters,such as the minimum running speed and the balancing liquid transfer speed,are analyzed *** fluid-solid coupling model of the actuator was established,and the two-phase flow from inside the hydraulic unbalanced bionic self-recovery actuator was simulated under multiple working conditions and the performance parameters were quantitatively analyzed.A balancing simulation test bed was built,and its effectiveness was verified by performance parameter tests and unbalanced bionic self-recovery *** experimental results show that the mass distribution adjustment of the balancing disk can be achieved using different viscosity balancing liquid,and the response of liquid viscosity 10 cSt is faster than that of liquid viscosity 100 cSt in the process of balancing liquid transfer,and the time is reduced by more than 75%;the system can reduce the simulated rotor amplitude from 18.3μm to 10.6μm online in real time,which provides technical support for the subsequent development of a new generation of bionic intelligent equipment.

关键词： engineering self-recovery-Bionics Simulation analysis Self-recovery regulation

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Time Synchronous Averaging Based on Cross-power Spectrum

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Chinese Journal of Mechanical engineering 2023年第2期36卷 198-205页

作者： Ling Wang Minghui Hu Bo Ma Zhinong Jiang Key Laboratory of Engine Health Monitoring‑control and Networking of Ministry of Education Beijing University of Chemical TechnologyBeijing 100029China Beijing Key Laboratory of High‑end Mechanical Equipment Health Monitoring and Self‑Recovery Beijing University of Chemical TechnologyBeijing 100029China

Periodic components are of great significance for fault diagnosis and health monitoring of rotating *** synchronous averaging is an effective and convenient technique for extracting those ***,the performance of time synchronous averaging is seriously limited when the separate segments are poorly *** paper proposes a new averaging method capable of extracting periodic components without external reference and an accurate period to solve this *** this approach,phase detection and compensation eliminate all segments'phase differences,which enables the segments to be well *** effectiveness of the proposed method is validated by numerical and experimental signals.

关键词： Time synchronous averaging Phase detection Cross-power spectrum Fault diagnosis

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Prediction of Coefficient of Restitution for Impact Elastoplastic Spheres Considering Finite Plate Thickness

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Chinese Journal of Mechanical engineering 2024年第4期37卷 183-193页

作者： Yunfeng Fan Hao Wang Tao Zhou Limin Zou Zhinong Jiang Minghui Hu State Key Laboratory of High-end Compressor and System Technology Beijing University of Chemical TechnologyBeijing 100029China China Ship Research and Development Academy Beijing 100101China Key Lab of Engine Health Monitoring-Control and Networking of Ministry of Education Beijing University of Chemical TechnologyBeijing 100029China Beijing Key Laboratory of High-End Mechanical Equipment Health Monitoring and Self-Recovery Beijing University of Chemical TechnologyBeijing 100029China

Collisions between objects are a relatively common phenomenon in *** of collision processes can greatly contribute to solving problems such as impact-rub faults and particle *** coefficient of restitution is a critical parameter in the analysis of collision *** experiments have shown that the coefficient of restitution is closely related to the plate thickness,and the smaller the plate thickness,the more inaccurate the coefficient of restitution predicted by the existing model,which seriously affects the process of collision *** remedy this shortcoming,this paper proposes a plate thickness influence factor with the ratio of sphere diameter to plate thickness as the *** plate thickness influence factor can optimize the coefficient of restitution model to effectively predict the coefficient of restitution of impacting elastoplastic spheres with finite plate ***,the validity of the new model is verified using a large amount of experimental data.

关键词： Collision Coefficient of restitution Energy loss Sphere

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Bionic Artificial Self-Recovery Enables Autonomous health of Machine

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Journal of Bionic engineering 2022年第6期19卷 1545-1561页

作者： Gao Jinji Key Laboratory of Beijing for High-End Mechanical Equipment Health Monitoring and Self-Recovery Beijing University of Chemical TechnologyBeijing100029China Key Laboratory of Engine Health Monitoring-Control and Networking of Ministry of Education Beijing University of Chemical TechnologyBeijing100029China

This paper explores engineering self-recoveries theory,which emerged from the research of Bionics to meet the great demand of modern high-risk process manufacturing and the development of aerospace *** opens a new era in which artefact s learn from natural *** the rapid development of the industrial Internet and Artificial intelligence technology,we have gained a deep understanding of the law of fault generation and development,which provides an opportunity for the emergence of engineering self-recoveries *** self-recoveries expands the research field of Cybernetics and engineering cybernetics,endows machines with the self-recovery mechanism,which is unique to humans and animals,and enables machines to store,supplement and activate self-recovery power to maintain body *** research on Artificial intelligence has greatly enhanced the function of imitating the human brain,but has ignored the important system and function of humans and animals to maintain their own health—the self-recovery system and self-recovery *** intelligence imitates the conscious thinking control behaviour of the human brain to realize automation and intellectualization,making machines *** self-recovery can imitate the self-recovery mechanism of human unconscious thinking,and prevent and suppress faults in operation to realize self-recovery,possibly making machines *** self-recovery technology includes self-repair,compensation,self-protection and self-recovery *** self-recoveries is the basis of the autonomous health of machines and even artificial systems,and a new research field of *** has broad application prospects in engineering.

关键词： engineering self-recoveries Bionics Artificial self-recovery Artificial intelligence Fault self-recovery regulation

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Digital twin model of gas turbine and its application in warning of performance fault

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Chinese Journal of Aeronautics 2023年第3期36卷 449-470页

作者： Minghui HU Ya HE Xinzhi LIN Ziyuan LU Zhinong JIANG Bo MA Key Lab of Engine Health Monitoring-Control and Networking of Ministry of Education Beijing University of Chemical TechnologyBeijing 100029China Beijing Key Laboratory of High-end Mechanical Equipment Health Monitoring and Self-Recovery Beijing University of Chemical TechnologyBeijing 100029China Capital Aerospace Machinery Corporation Limited Beijing 100076China Hangli(Group)Industrial Co. LtdChengdu 611936China

The digital twin-driven performance model provides an attractive option for the warn gas-path faults of the gas ***,three technical difficulties need to be solved:(1)low modeling precision caused by individual differences between gas turbines,(2)poor solution efficiency due to excessive iterations,and(3)the false alarm and missing alarm brought by the traditional fixed threshold *** paper proposes a digital twin model-based early warning method for gas-path faults that breaks through the above obstacles from three ***,a novel performance modeling strategy is proposed to make the simulation effect close to the actual gas turbine by fusing the mechanism model and measurement ***,the idea of controlling the relative accuracy of model parameters is *** introduction of an error module to the existing model can greatly shorten the modeling *** third solution focuses on the early warning based on the digital twin model,which self-learns the alarm threshold of the warning feature of gas-path parameters using the kernel density *** proposed method is utilized to analyze actual measured data of LM2500+,and the results verify that the new-built digital model has higher accuracy and better *** comparisons show that the proposed method shows evident superiority in early warning of performance faults for gas turbines over other methods.

关键词： Gas turbine Digital twin model Gas-path fault warning Deviation degree analysis Performance simulation

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Research on the life prediction of vehicle engine cylinder head driven by dual channel Markov chain

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High Technology Letters 2025年第1期31卷 12-19页

作者： LI Zhijie WANG Yonglai CHEN Cuicui ZHOU Long WANG Yao YUAN Shaoshe National Key Laboratory of Internal Combustion Engines and Power Systems Weichai Power Co.Ltd.Weifang 261061P.R.China Key Laboratory of Engine Health Monitoring-control and Networking Ministry of EducationBeijing University of Chemical TechnologyBeijing 100029P.R.China

The performance degradation of vehicle engine cylinder heads is a complex phenomenon,and the accurate prediction of their remaining useful life is essential for maintenance *** address the problem of low prediction accuracy caused by insufficient data mining depth in current prediction models for the remaining service life of engine cylinder heads,a prediction method of dualchannel model is ***,the driving status data of multiple vehicles is summarized and analyzed,and the on-board network common variables related to cylinder head life are ***,driving segments are defined,the driving state features of each driving segment are extracted,and feature correlation analysis and principal component analysis are *** driving state profiles of the vehicle are divided using the clustering algorithm,and the cumulative degradation factors for driving state profiles are defined and ***,the mileage of each driving segment is classified into intervals by applying fuzzy set theory,and the state transfer probability matrices of driving state profiles and driving segment mileage are calculated.A new engine head life prediction model based on dual channel Markov chain(DCMC)is ***,the proposed method is applied to the residual life prediction of cylinder head of seven actual vehicles,and the comparison with actual life statistics results proved the validity of the proposed method.

关键词： engine cylinder head driving cycle vehicle networking life prediction

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The construction method of typical engine fault identification model based on Simulink

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IFAC-PapersOnLine 2024年第29期58卷 19-24页

作者： Xin bo Zhu Cheng Hu RuiJie Jiang Zhinong Gao Zhilong Key Laboratory of Engine Health Monitoring-Control and Networking Ministry of Education Beijing University of Chemical Technology Beijing China China North Engine Research Institute Tianjin China Key Laboratory of Engine Health Monitoring-Control and Networking Ministry of Education Beijing Key Laboratory of Health Monitoring Control and Fault Self-Recovery for High-end Machinery Beijing University of Chemical Technology Beijing China

This paper provides a summary and overview of methods for constructing typical fault identification model for diesel engines based on Simulink, aiming at improving the efficiency of engine fault diagnosis and maintenance. First of all, the common types of diesel engine faults were analyzed, including intake and exhaust system faults, cooling system faults, lubrication system faults and fuel system faults. Then, the basic steps and methods of Simulink modeling are introduced in detail, by using data acquisition and preprocessing techniques, a large amount of sensor data was converted into signals that can be used as inputs. Next, this paper discussed the specific process of the fault identification model, including the data reading module, speed discrimination module, threshold discrimination module and state identification module, and the feasibility of the model is verified through practical application cases. The research show that the fault identification model based on Simulink can effectively improve the accuracy and efficiency of engine fault diagnosis, providing a new technical method to enhance the operational safety and reliability of engines, and also offering valuable reference for subsequent related research.

关键词： Diesel engine Fault Identification Model Construction Simulink

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A Modified Iterative Learning control Approach for the Active Suppression of Rotor Vibration Induced by Coupled Unbalance and Misalignment

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Chinese Journal of Mechanical engineering 2024年第1期37卷 242-253页

作者： Yifan Bao Jianfei Yao Fabrizio Scarpa Yan Li College of Mechanical and Electrical Engineering Beijing University of Chemical TechnologyBeijing 100029China State Key Laboratory of High-end Compressor and System Technology Beijing 100029China Beijing Key Laboratory of High-end Mechanical Equipment Health Monitoring and Self-Recovery Beijing University of Chemical TechnologyBeijing 100029China Key Lab of Engine Health Monitoring-Control and Networking of Ministry of Education Beijing University of Chemical TechnologyBeijing 100029China Bristol Composites Institute(ACCIS) University of BristolBristol BS81TRUK Dynamics and Control Research Group(DCRG) University of BristolBristol BS81TRUK

This paper proposes a modified iterative learning control(MILC)periodical feedback-feedforward algorithm to reduce the vibration of a rotor caused by coupled unbalance and parallel *** control of the vibration of the rotor is provided by an active magnetic actuator(AMA).The iterative gain of the MILC algorithm here presented has a self-adjustment based on the magnitude of the *** filters are adopted to extract the synchronous(1×Ω)and twice rotational frequency(2×Ω)components of the rotor *** the notch frequency of the filter and the size of feedforward storage used during the experiment have a real-time adaptation to the rotational *** method proposed in this work can provide effective suppression of the vibration of the rotor in case of sudden changes or fluctuations of the rotor *** and experiments using the MILC algorithm proposed here are carried out and give evidence to the feasibility and robustness of the technique proposed.

关键词： Rotor vibration suppression Modified iterative learning control Unbalance Parallel misalignment Active magnetic actuator

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Research on mechanical wear life feature fusion prediction method based on temporal pattern attention mechanism

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High Technology Letters 2023年第1期29卷 12-21页

作者：江志农 CHEN Yuyang ZHANG Jinjie LI Zhaoyang MAO Zhiwei ZHI Haifeng LIU Fengchun Beijing Key Laboratory of Health Monitoring and Self-Healing of High-end Mechanical Equipment Beijing University of Chemical TechnologyBeijing 100029P.R.China Key Laboratory of Engine Health Monitoring-control and Networking Ministry of EducationBeijing University of Chemical TechnologyBeijing 100029P.R.China China North Engine Research Institute(Tianjin) Tianjin 300400P.R.China

In order to solve the problem of low prediction accuracy when only vibration or oil signal is used to predict the remaining life of gear wear,a gear wear life feature fusion prediction method based on temporal pattern attention mechanism is ***,deep residual shrinkage network(DRSN)is used to extract the features of the original vibration time series signals with low signal-tonoise ratio,and the vibration features associated with gear wear evolution are ***,the extracted vibration features and the oil monitoring data that can intuitively reflect the wear process information are jointly input into the bi-directional long short-term memory neural network based on temporal pattern attention mechanism(TPA-BiLSTM),the complex nonlinear relationship between vibration features,oil features and gear wear process evolution is further explored to improve the prediction *** gear life cycle dynamic response and wear process signals are obtained based on the gear numerical simulation model,and the feasibility of the proposed method is ***,the proposed method is applied to the residual life prediction of gear on a test bench,and the comparison between different methods proved the validity of the proposed method.

关键词： prediction of gear remaining useful life information fusion numerical simulation neural network oil monitoring

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