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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Peng, Yu Li, Xiaoyu Lu, Chao Tang, Xiaolan Lin, Bin School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China Science and Technology on Altitude Simulation Laboratory Sichuan Gas Turbine Establishment Aero Engine Corporation of China Mianyang621000 China School of Computer Science Southwest Petroleum University Chengdu610500 China School of Engineering Sichuan Normal University Chengdu610066 China

ISBN: (纸本)9783030786083

Surge is an abnormal fault caused by compressor in the process of aero-engine flight, which will reduce the performance of aero-engines. When the surge gets serious, it will even cause engine damage, endanger flight safety, and cause a huge loss of personnel and property. Therefore, it is of great significance to predict the aero-engine surge timely and accurately. At present, little research have been done on the prediction task of aero-engine surge, and there are problems of low prediction accuracy and long calculation time. In order to solve these problems, a light-weight prediction model for aero-engine surge based on Seq2Seq (sequence to sequence) is proposed, which is called Ligh4S. Ligh4S uses the one-dimensional convolution neural network instead of the LSTM (long short-term memory network) structure in tradition-al Seq2Seq, which allows the model to compute in parallel, thus greatly improving computational efficiency and reducing prediction time. Experiments on the experimental data of an aero-engine show that the model achieves the performances of 94.3%, 92.1%, 93.2% respectively on precision rate, recall rate and F1 score under the condition of significantly reducing the size of model and the amount of calculation. What’s more, the model takes only 2ms to make a single prediction, which increases the prediction speed by about 98% compared with the LSTM-based Seq2Seq model. © 2021, Springer Nature Switzerland AG.

关键词： Long short-term memory

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Active disturbance rejection intake pressure control of aeropropulsion systems test facility with adaptive parameter b0

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Aerospace science and technology 2025年 163卷

作者： Xu, Zhuang Zhang, Hehong Zhai, Chao Xiao, Gaoxi Qian, Qiumeng Huang, Feng College of Computer and Data Science Fuzhou University Fuzhou350108 China Wuhan430074 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Science and Technology on Altitude Simulation Laboratory AECC Sichuan Gas Turbine Establishment Mianyang621703 China School of Mechanical Engineering and Automation Fuzhou University Fuzhou350108 China

Establishing a precise intake pressure environment in the aeropropulsion systems test facility (ASTF) is critical for evaluating aeroengines' flight characteristics. The model-partial and robust active disturbance rejection control (ADRC), that is extended state observer (ESO)-based controller, has become a favorable solution to the complex intake pressure control system. The parameter b0, as the estimated value of the closed-loop system control gain b under the ADRC paradigm, significantly influences ADRC performances, evidenced by extensive flight tests. In this work, an enhanced ADRC with an adaptive parameter b0 is proposed to improve the control quality of the intake pressure. In particular, the simplified model of b is utilized to dynamically adjust b0. Meanwhile, the differential signals obtained from a tracking differentiator (TD) are applied to further improve the responsiveness of b0. The stable region of b0 is theoretically analyzed by using the time delay estimation technique, and the quantitative relationship between b0 and disturbance observation ability of ESO is given. Experimental results demonstrate that the proposed controller can effectively suppress the valve swing amplitude in steady state and reduce the maximum pressure error in transitional state, with improvement rates of 50% and 62%, respectively. © 2025 Elsevier Masson SAS

关键词： Disturbance rejection

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A Model Average Algorithm for Housing Price Forecast with Evaluation Interpretation

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Journal of Quantum Computing 2022年第3期4卷 147-163页

作者： Jintao Fu Yong Zhou Qian Qiu Guangwei Xu Neng Wan School of Computer Science Southwest Petroleum UniversityChengdu610500China Key Laboratory on Aero-Engine Altitude Simulation Technology Sichuan Gas Turbine EstablishmentAECCMianyang621000China Aero Engine Academy of China Aero Engine Corporation of ChinaBeijing101300China

In the field of computer research,the increase of data in result of societal progress has been remarkable,and the management of this data and the analysis of linked businesses have grown in *** are numerous practical uses for the capability to extract key characteristics from secondary property data and utilize these characteristics to forecast home *** regression methods in machine learning to segment the data set,examine the major factors affecting it,and forecast home prices is the most popular method for examining pricing *** is challenging to generate precise forecasts since many of the regression models currently being utilized in research are unable to efficiently collect data on the distinctive elements that correlate y with a high degree of house price *** today’s forecasting studies,ensemble learning is a very prevalent and well-liked study *** regression integration computation of large housing datasets can use a lot of computer resources as well as computation time,and ensemble learning uses more resources and calls for more machine support in integrating diverse *** Average Model suggested in this paper uses the concept of fusion to produce integrated analysis findings from several models,combining the best benefits of separate *** Average Model has a strong applicability in the field of regression prediction and significantly increases computational *** technique is also easier to replicate and very effective in regression *** using regression processing techniques,this work creates an average of different regression models using the AM(Average Model)algorithm in a novel *** evaluating essential models with 90%accuracy,this technique significantly increases the accuracy of house price *** experimental results show that the AM algorithm proposed in this paper has lower prediction error than other comparison algorithms,and the prediction accurac

关键词： Machine learning AM algorithm price forecast regression algorithm Model evaluation

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An Adaptive Formulation-based Many-Objective Evolutionary Algorithm for Multi-Scenario Optimization in Data Enrichment

An Adaptive Formulation-based Many-Objective Evolutionary Al...

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Congress on Evolutionary Computation

作者： Liang Fan Xudong Feng Handing Wang School of Artificial Intelligence Xidian University Xi'an China Science and Technology on Altitude Simulation Laboratory AECC Sichuan Gas Turbine Establishment Mianyang China

In many practical applications, data enrichment can generate a large amount of accurate data to alleviate the problem of data scarcity. In order to make the fake data generated in data enrichment as close to the real data as possible, the data enriching model must be tuned to meet the loss requirements of multiple objectives in different scenarios, which makes it a multi-scenario many-objective optimization problem. However, due to the curse of the dimensionality of the scenario space and the objective space, the existing many-objective evolutionary algorithms cannot solve the problem in data enrichment well. To effectively handle this problem, we propose an adaptive formulation-based multi-objective evolutionary algorithm, where the aggregation function is used to reduce the dimension of the scenario space to one and the multiple objectives into three objectives through the adaptive formulation of the original problem. In this way, a multi-scenario many-objective problem is converted into a multi-objective problem which could be solved by existing multi-objective evolutionary algorithms. The proposed algorithm is applied to the practical data enrichment problem to solve the multi-scenario many-objective optimization problem and compared with NSGA-III. The experimental results demonstrate the remarkable superiority of the proposed algorithm over NSGA-III.

关键词： Evolutionary computation Data models Optimization

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Extended State Observer based Attitude Control of a Bird-like Flapping-wing Flying Robot

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Journal of Bionic Engineering 2020年第4期17卷 708-717页

作者： Keqiang Bai YunZhi Luo Zhihong Dan Song Zhang Meiling Wang Qiumeng Qian Jun Zhong School of Information Engineering Southwest University of Science and TechnologyRobot Technology Used for Special Environment Key Laboratory of Sichuan ProvinceMianyang 621010China Automation Research Institute Co. Ltd.of China South Industries Group CorporationMianyang 621000China Science and Technology on Altitude Simulation Laboratory AECC Sichuan Gas Turbine EstablishmentMianyang 621703China AECC Sichuan Gas Turbine Establishment Mianyang 621703China Chinese Academy of Sciences Hefei Institutes of Physical Science Hefei 230022China College of Mechanical and Electrical Engineering Hohai UniversityChangzhou 213022China

The attitude control system of a flapping-wing flying robot plays an important role in the precise orientation and tracking of the *** this paper,the modeling of a bird-like micro flapping-wing system is introduced,and the design of a sliding mode controller based on an Extended State Observer(ESO)is *** main design difficulties are the control law and the adaptive law for the attitude control *** address this problem,a sliding mode adaptive extended state observer algorithm is ***,a new extended state approximation method is used to estimate the final output as a disturbance ***,a sliding mode observer with good robustness to the model approximation error and external disturbance is used to estimate the system *** with traditional algorithms,this method is not only suitable for more general cases,but also effectively reduces the influence of the approximation error and ***,the simulation and experiment example is given to illustrate the implementation *** results show that the algorithm can effectively estimate the state of the attitude control system of the flapping-wing flying robot,and further guarantee the robustness of the model regarding error and external disturbance.

关键词： bionic attitude control flapping-wing flying robot sliding mode adaptive control extended state observer

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Multi-dimensional simulations for extensive off-design conditions of gas turbines by iterative-coupled methods using different characteristic maps of coaxial compressor and turbine

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Case Studies in Thermal Engineering 2025年 72卷

作者： Weimin Deng Guangming Ren Linyuan Jia Zuojun Wei Yuchun Chen Xiaohua Gan School of Power and Energy Northwestern Polytechnical University Xi'an 710072 China Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen 518055 China Science and Technology on Altitude Simulation Laboratory Mianyang 621000 China Shenzhen Key Laboratory of Wide-Speed-Range and Variable-Density Continuous Wind Tunnel Southern University of Science and Technology Shenzhen 518000 China National Key Laboratory of Science and Technology on Advanced Light-duty Gas-turbine Xi'an 710129 China

Multi-dimensional simulations offer a complementary numerical platform to gas turbine experimentation, generating supportive data for training adaptation and artificial intelligence models. However, the application of iterative-coupled simulations to extensive off-design conditions depends significantly on the accuracy of generic characteristic maps, particularly near choke and stall regions. In this study, multi-dimensional simulation based on iterative-coupled models using three different sets of maps was developed. Based on experimental speed characteristics data, the standard deviation of performance parameters simulated from the three iterative-coupled models was found to be less than 10 −3 . Further analysis reveals the convergence consistent traits that the different characteristic maps used in the iterative-coupled simulations only affect convergence speed and scope and do not impact the final convergence results. To apply iterative-coupled simulations to extensive off-design conditions, a self-moving strategy based on the convergence consistent traits of different characteristic maps was developed. The iterative-coupled simulations using the self-moving strategy have an extensive convergence scope, including adjustable-nozzle-area conditions (0.0013–0.008 m 2 , 78 %–479 %) and adjustable-power-extraction conditions (0–16 kW, 0 %–80 %). This demonstrates that the self-moving strategy for inexact generic characteristic maps can apply iterative-coupled simulations to extensive off-design, compared to the CLM with exact specific characteristic maps.

关键词： Iterative-coupled simulations Component-level model Adaptation method Gas turbine Thermodynamics Computational fluid dynamics

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Aerodynamic modeling and transient performance improvement of a free jet altitude test facility 6th

Aerodynamic modeling and transient performance improvement o...

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6th International Conference on Artificial Intelligence and Security,ICAIS 2020

作者： Wu, Feng Gao, Limin Wu, Xinyun Feng, Xudong Leng, Lintao Li, Yaoyu School of Power and Energy Northwestern Polytechnical University Xi’an710072 China The National Key Laboratory of Aerodynamic Design and Research Xi’an710129 China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China Key Laboratory of Science and Technology on Aero-Eigine Altitude Simulation AECC Sichuan Gas Turbine Establishment Chengdu610000 China

ISBN: (纸本)9789811581007

An inlet-engine altitude test facility for flight condition simulation is modeled for the system dynamic performance improvement. The system model equations are solved with an improved Euler integral method. To simulate the interaction between the tested engine and the test bench accurately, a turbojet engine module is introduced in the system model. By modeling and simulation, a linear temperature compensation control algorithm based on the control error is validated for feasibility;controller parameters optimization for cabin static pressure stabilizing is also carried out. In this paper, some issues like temperature transient performance and engine operate impact restraint on cabin static pressure are discussed efficiently and economically. With the characteristics of high efficiency and economy, the modeling and simulation tools are suitable for the optimization of such systems. © Springer Nature Singapore Pte Ltd 2020.

关键词： Engines

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Nonlinear PID Pressure Control Based on Extremum Seeking

Nonlinear PID Pressure Control Based on Extremum Seeking

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第三十九届中国控制会议

作者： Song Zhang Zhihong Dan Qiumeng Qian Yuying Guo Jianping Zhang AECC Sichuan Gas Turbine Establishment Science and Technology on Altitude Simulation Laboratory School of Information Engineering Southwest University of Science and Technology School of Manufacturing Science and Engineering Southwest University of Science and Technology

Rear-cabin pressure control system of high-altitude test facility has the characteristics of large time-delay, nonlinearity and strong disturbances. In China, the rear-cabin pressure control system uses the conventional PID control method which can't nonlinearly regulate pressure very well;especially in engine transient experiments, it can't automatically turn PID parameters to adapt the changes of system's nonlinearities, which has seriously affected the dynamic regulation and control accuracy of the rear-cabin pressure. Therefore, in this paper, firstly the dynamics of hydraulic butterfly valve is modeled and the nonlinear characteristics of exhaust diffuser are analyzed and the simulation model of the rear-cabin pressure control system is established. Secondly, the nonlinear PID controller is developed based on extremum seeking and its parameters are turned online according to the pressure errors between the setting valves and system outputs of the pressure system by minimizing the cost ***, with and without engine flow disturbances, some simulation results of the linear and nonlinear PID control are given for pressure regulation to show that the proposed nonlinear PID based on extremum seeking can not only turn the controller parameters online, but also reject time-varying and large amplitude disturbances, so it has effectively enhanced the nonlinear adaptability of controller and improved the control accuracy of transient responses of the rear-cabin pressure control system.

关键词： High-altitude Test Facility Pressure Control Extremum-Seeking Nonlinear PID

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A Comparison Study of Tracking Differentiator and Robust Exact Differentiator

A Comparison Study of Tracking Differentiator and Robust Exa...

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Chinese Automation Congress (CAC)

作者： Juan Wang Hehong Zhang Gaoxi Xiao Zhihong Dan Song Zhang Yunde Xie College of Mathematics and Computer Science Fuzhou University Fuzhou China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Singapore Science and Technology on Altitude Simulation Laboratory AECC Sichuan Gas Turbine Establishment of China Mianyang China Beijing Rail Transit Technology Equipment Group Co. Ltd Beijing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

This paper presents a comparison study of two commonly-used differentiators, namely tracking differentiator (TD) and robust exact differentiator (RED) in both the frequency and the time domains. Specifically, we compare their performances in filtering and differentiation estimation for a large number of inputs with different levels of noises. Meanwhile, the parameter adaptability regarding different inputs for the two differentiators is tested. Furthermore, the efficiency of the two algorithms are evaluated respectively by the hardware. The results show that TD outperforms RED in quickness, smoothness, and noise-tolerance with no overshoots, while RED has advantageous exactness and robustness in the filtering and algorithm's simplicity. Also, TD has a better parameter adaptability and tolerance to signal frequency's variations whereas the performance of RED is heavily dependent on parameter setting. To overcome the overshoot problem in RED, an enhancement by adoption of the transition function is proposed. These results shall provide useful tips for selecting appropriate differentiators in real-life engineering, and designing new differentiators as well.

关键词： Estimation Signal to noise ratio Time-frequency analysis Time-domain analysis Signal processing algorithms Frequency estimation Turbines

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EFFECT OF THE RIM SEAL CONFIGURATIONS ON THE HOT GAS INGESTION INTO THE ROTOR-STATOR CAVITY

EFFECT OF THE RIM SEAL CONFIGURATIONS ON THE HOT GAS INGESTI...

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第三届中国国际透平机械学术会议

作者： Xing-yun Jia Jie Zhou Qun Zheng Hai Zhang College of Power and Energy Engineering Harbin Engineering UniversityHarbin 150001China Science and Technology on Altitude Simulation Laboratory China Gas Turbine EstablishmentChina Aviat

The effect of rim seal configurations on the flow and heat transfer characteristics in a turbine cavity and the rim seal clearance flow are computed by using a numerical method for conjugate heat transfer.A radial clearance at high radius can properly block the ingestion air and purge flow into the rim clearance region,leading to a better temperature distribution of the turbine disc and cavity with approximately 3-10%increase in seal effectiveness when compared to an axial clearance rim seal at high *** radial-axial clearance rim seal keeps the advantages of a radial-clearance,further reducing the negative effect of ingestion gas on the temperature of the rotor and stator *** the condition of minimum sealant flow rate for the radial-axial clearance rim seal,the seal effectiveness of the radial-axial clearance rim seal is 5.29%higher than that of the axial-clearance rim seal,and the air-cooling aerodynamic efficiency of the radial-axial clearance rim seal is 1.8%higher than that of the axial-clearance.

关键词： Rim seal Radial-axial clearance rim seal Hot gas ingestion Rotor-stator cavity Conjugate heat transfer

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