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2016 IEEE International Symposium on Inertial Sensors and Systems

作者： Wei Li Kun Lu Dingbang Xiao Zhanqiang Hou Yan Shi Xuezhong Wu Yulie Wu College of Mechatronics Engineering and Automation National University of Defense Technology Changsha China Laboratory of Science and Technology on Integrated Logistics Support National University of Defense Technology Changsha China

This paper presents a novel micro shell resonator (MSR) with eight circular-distributed T-shape masses based on fused silica (FS), which is fabricated by combining micro blowing-torch process with high precise mold. FS is been heated instantaneously above the softening point by micro blowing-torch and flow down into the mold. The resonator shell is shaped using a pressure difference and surface tension whose precision is determined by the precision of mold. The key process is that eight T-shape masses are defined along the rim of resonator shell. Electrostatic transduction is used to detect spatial deformation of resonators by out-of-plane electrodes, which has wineglass modes at 10.27 k and 10.70 k with quality factors of 12558 and 6964. A large capacitance enabled by T-shape masses for driving and sensing is measured as 1.31pF~1.6pF, which improves out-of-plane transduction efficiency. Besides, it is more convenient to trim the frequency by adding or removing mass on the T-shape masses.

关键词： Electrodes Electrostatics Resonant frequency Fabrication Silicon compounds Capacitance Sensors

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Improving a two-equation eddy-viscosity turbulence model to predict the aerodynamic performance of thick wind turbine airfoils

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Journal of Physics: Conference Series 2018年第1期974卷

作者： Galih Bangga Tri Kusumadewi Go Hutomo Ahmad Sabila Taurista Syawitri Herlambang Setiadi Muhamad Faisal Raditya Wiranegara Yongki Hendranata Dwi Lastomo Louis Putra Stefanus Kristiadi Institute of Aerodynamics and Gas Dynamics University of Stuttgart Stuttgart Germany Mechanical Engineering Department Institut Teknologi Sepuluh Nopember Surabaya Indonesia School of Manufacturing System and Mechanical Engineering Sirindhorn International Institute of Technology Thammasat University Thailand Toyota SO Department Astra International Ltd. Indonesia Civil Engineering Department Universitas Brawijaya Malang Indonesia Mechanical Engineering Department Universitas Muhammadiyah Surakarta Surakarta Indonesia School of Information Technology & Electrical Engineering The University of Queensland Brisbane Australia Non-Installation Top Range Department Berca Schindler Lifts Ltd. Indonesia Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taiwan School of Aerospace Transport and Manufacturing Cranfield University United Kingdom Mechanical Engineering Department Texas A&M University College Station United States PUI-PT Mechatronics and Industrial Automation Research Center Intitut Teknologi Sepuluh Nopember Surabaya Indonesia Mechanical Engineering Department Politecnico di Milano Milan Italy Aeronautics Department Imperial College of Science Technology and Medicine London United Kingdom

Numerical simulations for relatively thick airfoils are carried out in the present studies. An attempt to improve the accuracy of the numerical predictions is done by adjusting the turbulent viscosity of the eddy-viscosity Menter Shear-Stress-Transport (SST) model. The modification involves the addition of a damping factor on the wall-bounded flows incorporating the ratio of the turbulent kinetic energy to its specific dissipation rate for separation detection. The results are compared with available experimental data and CFD simulations using the original Menter SST model. The present model improves the lift polar prediction even though the stall angle is still overestimated. The improvement is caused by the better prediction of separated flow under a strong adverse pressure gradient. The results show that the Reynolds stresses are damped near the wall causing variation of the logarithmic velocity profiles.

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Auxiliary error and probability density function based neuro-fuzzy model and its application in batch processes

Auxiliary error and probability density function based neuro...

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作者： Jia, Li Yuan, Kai Shanghai Key Laboratory of Power Station Automation Technology Department of Automation College of Mechatronics Engineering and Automation Shanghai University Shanghai200072 China

This paper focuses on resolving the identification problem of a neuro-fuzzy model (NFM) applied in batch processes. A hybrid learning algorithm is introduced to identify the proposed NFM with the idea of auxiliary error model and the identification principle based on the probability density function (PDF). The main contribution is that the NFM parameter updating approach is transformed into the shape control for the PDF of modeling error. More specifically, a virtual adaptive control system is constructed with the aid of the auxiliary error model and then the PDF shape control idea is used to tune NFM parameters so that the PDF of modeling error is controlled to follow a targeted PDF, which is in Gaussian or uniform distribution. Examples are used to validate the applicability of the proposed method and comparisons are made with the minimum mean square error based approaches. © 2015 Elsevier B.V.

关键词： Probability density function

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Enhancing BEM simulations of a stalled wind turbine using a 3D correction model

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Journal of Physics: Conference Series 2018年第1期974卷

作者： Galih Bangga Go Hutomo Taurista Syawitri Tri Kusumadewi Winda Oktavia Ahmad Sabila Herlambang Setiadi Muhamad Faisal Yongki Hendranata Dwi Lastomo Louis Putra Stefanus Kristiadi Ilmi Bumi Institute of Aerodynamics and Gas Dynamics University of Stuttgart Stuttgart Germany Mechanical Engineering Department Institut Teknologi Sepuluh Nopember Surabaya Indonesia Toyota SO Department Astra International Ltd. Indonesia Mechanical Engineering Department Universitas Muhammadiyah Surakarta Surakarta Indonesia School of Manufacturing System and Mechanical Engineering Sirindhorn International Institute of Technology Thammasat University Thailand Project Support and Cost Control Division Indoturbine Ltd. Jakarta Indonesia Civil Engineering Department Universitas Brawijaya Malang Indonesia School of Information Technology & Electrical Engineering The University of Queensland Brisbane Australia Non-Installation Top Range Department Berca Schindler Lifts Ltd. Indonesia Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taiwan Mechanical Engineering Department Texas A&M University College Station United States PUI-PT Mechatronics and Industrial Automation Research Center Intitut Teknologi Sepuluh Nopember Surabaya Indonesia Mechanical Engineering Department Politecnico di Milano Milan Italy Aeronautics Department Imperial College of Science Technology and Medicine London United Kingdom Materials Engineering Department Institut Teknologi Sepuluh Nopember Surabaya Indonesia

Nowadays wind turbine rotors are usually employed with pitch control mechanisms to avoid deep stall conditions. Despite that, wind turbines often operate under pitch fault situation causing massive flow separation to occur. Pure Blade Element Momentum (BEM) approaches are not designed for this situation and inaccurate load predictions are already expected. In the present studies, BEM predictions are improved through the inclusion of a stall delay model for a wind turbine rotor operating under pitch fault situation of -2.3° towards stall. The accuracy of the stall delay model is assessed by comparing the results with available Computational Fluid Dynamics (CFD) simulations data.

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Corrigendum to “Empirical research on evolutionary behavior of covert network with preference measurement” [Physica A 471 (2017) 33–43]

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Physica A: Statistical Mechanics and its Applications 2017年 480卷 79-79页

作者： Bo Li Duoyong Sun Guanghan Bai Department of Management College of Information System and Management National University of Defense Technology Changsha 410072 China Science and Technology on Integrated Logistics Support Laboratory College of Mechatronics Engineering and Automation National University of Defense Technology Changsha 410072 China

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Synchronization of fractional-order drive-response complex dynamical networks using scalar signals 34

Synchronization of fractional-order drive-response complex d...

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第三十四届中国控制会议

作者： ZHAO Xiao-Wen WU Yonghong ZHANG Xian-He LIU Feng GUAN Zhi-Hong College of Automation Huazhong University of Science and Technology School of Science Wuhan University of Technology College of Mechatronics and Control Engineering Hubei Normal University School of Automation China University of Geosciences

ISBN: (纸本)9781467374439

In this paper, synchronization of drive-response complex dynamical networks with fractional-order dynamical nodes is discussed. Only scalar signals as the feedback variable are required to be transmitted from the driving network to the response network, which can save a lot of channel resources and has more significant meanings in engineering applications. Based on the Jordan canonical transformation method, some criteria for synchronization of fractional-order drive-response complex dynamical networks are given in the form of normal algebraic inequalities, which can greatly decrease the original computational ***, a numerical simulation is provided to validate the effectiveness and feasibility of the proposed synchronization criteria.

关键词： Complex dynamical networks,Fractional-order,Synchronization,Scalar signal

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Realize Almost Sure Optimal Consensus with Quantized Gossip-Type Subgradient Algorithms 34

Realize Almost Sure Optimal Consensus with Quantized Gossip-...

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第三十四届中国控制会议

作者： HU Bin JIANG Xiao-Wei ZHANG Ding-Xue LI Tao GUAN Zhi-Hong College of Automation Huazhong University of Science and Technology College of Mechatronics and Control Engineering Hubei Normal University Petroleum Engineering College Yangtze University School of Electronics and Information Yangtze University

ISBN: (纸本)9781467374439

This paper concerns with the optimal consensus problem of multi-agent networks under imperfect *** the network issues, we resort to an integrated scheme of the standard gossip algorithm and the subgradient method for multiagent cooperative control. Under the proposed control strategy, agents are supposed to transfer desirable information through a quantized mechanism, and the dithering technique is adopted to deal with the triggered quantization errors. Detailed convergence analysis is carried out by the stochastic approximation method. It is demonstrated that multi-agent networks can achieve almost sure optimal consensus under the proposed algorithm through quantized communication. Related simulation work is further given to validate the derived theoretical results.

关键词： Multi-agent networks,Optimal consensus,Gossip algorithm,Subgradient method,Quantization

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Measurement on the mechanical properties of SiC thin films based on square thin films theory

Measurement on the mechanical properties of SiC thin films b...

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16th Annual Conference and 5th International Conference on Chinese Society of Micro-Nano Technology, CSMNT 2014

作者： Chen, Yaomin Dong, Peitao Wu, Xuezong Wu, Yulie College of Mechatronics Engineering and Automation National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783038354628

SiC films made of different methods may have different mechanical properties, so their mechanical properties need to be determined by mechanical property measurement [1]. Since SiC films have stable chemical properties, it's very difficult to be etched [2]. This paper introduce a method for SiC films mechanical property testing without processing SiC. Moreover, in view of the lack of square SiC films' mechanical properties research, this paper also do simulation on it. © (2015) Trans Tech Publications, Switzerland.

关键词： Silicon carbide

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Research on Assembly Data Mining Technology of Complex Mechanical System

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Procedia CIRP 2016年 44卷 97-101页

作者： Kai Zhang Guoxi Li JingZhong Gong Meng Zhang College of Mechatronics Engineering and Automation National University of Defense Technology No.109 Deya Street Changsha 410073 P.R. China School of Mechanical Engineering Hunan International Economics University No.822 Fenglin Street Changsha 410073 P.R. China

The discipline between the assembly process and the final performance of complex mechanical system is unclear and the performance target is usually reached by experienced technicians. To find out the discipline and obtain the knowledge which may be hiding in the experience of technician, data mining technology is put forward to analyze the assembly data. By establishing the structure and procedure of the data mining process and encapsulating the data mining template of the assembly data, the knowledge of the discipline and assembly experience can be extracted through a case study. These knowledge can be used for assembly quality prediction, parameter optimization, process improvement and success rate increase.

关键词： Assembly data assembly process design data mining priori knowledge

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An online anomaly detection method for stream data using isolation principle and statistic histogram

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International Journal of Modeling, Simulation, and Scientific Computing 2015年第2期6卷 85-106页

作者： Zhiguo Ding Minrui Fei Dajun Du Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronics Engineering and Automation Shanghai University Shanghai 200072 P.R.China College of Mathematics Physics and Information Engineering Zhejiang Normal University JinhuaZhejiang 321004P.R.China

Online anomaly detection for stream data has been explored recently,where the detector is supposed to be able to perform an accurate and timely judgment for the upcoming ***,due to the inherent complex characteristics of stream data,such as quick generation,tremendous volume and dynamic evolution distribution,how to develop an effective online anomaly detection method is a *** main objective of this paper is to propose an adaptive online anomaly detection method for stream *** is achieved by combining isolation principle with online ensemble learning,which is then optimized by statistic *** main algorithms are developed,i.e.,online detector building algorithm,anomaly detecting algorithm and adaptive detector updating *** evaluate our proposed method,four massive datasets from the UCI machine learning repository recorded from real events were *** simulations based on these datasets show that our method is effective and robust against different scenarios.

关键词： Online anomaly detection stream data isolation principle ensemble learning statistic histogram

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