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Enhanced gear fault diagnosis via heterodyne downconversion: Theoretical verification and optimized ultrasonic signal acquisition

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Measurement 2025年 256卷

作者： Jingchao Zhang Shaoqun Zhang Yixue Dong Chen Li Guoqian Jiang Yingwei Li Xiaoli Li School of Information Science and Engineering Yanshan University Qinhuangdao 066004 China Hebei Key Laboratory of Information Transmission and Signal Processing Qinhuangdao 066004 China Intelligent Control System R&D Department Computer Application Technology Research Institute China Ordnance Industry Beijing 100089 China School of Electrical Engineering Yanshan University Qinhuangdao 066004 China School of Automation Science and Engineering South China University of Technology Guangzhou 510641 China Pazhou Lab Guangzhou 510330 China

Ultrasonic fault diagnosis has emerged as a promising technique for gear fault detection, owing to its capability to capture modulated high-frequency transients induced by incipient or localized defects. However, its practical application is constrained by the requirement for extremely high sampling rates. Heterodyne downconversion offers a potential solution by translating ultrasonic spectral components to lower frequencies, though its effectiveness in preserving diagnostic features remains insufficiently validated. This study conducts a theoretical analysis of the influence of heterodyne downconversion on ultrasonic signal characteristics and proposes an optimized heterodyne-based ultrasonic acquisition system with enhanced charge amplification and frequency conversion circuits. Experimental evaluations using a gear fault test platform demonstrate that the downconverted signals preserve the envelope spectral features of the original ultrasonic signals. Furthermore, comparative analyses indicate that the proposed method achieves superior fault detection sensitivity compared to conventional vibration-based techniques, particularly under high rotational speeds. These findings validate the feasibility and diagnostic advantages of the proposed heterodyne-based approach for efficient and accurate ultrasonic condition monitoring.

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Nonlinear Virtual Inertia Control of WTGs for Enhancing Primary Frequency Response and Suppressing Drive-Train Torsional Oscillations

arXiv

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arXiv 2020年

作者： Liu, Bi Huang, Qi Zhao, Junbo Milano, Federico Zhang, Yingchen Sichuan Provincial Key Lab of Power System Wide-area Measurement and Control University of Electronic Science and Technology of China Chengdu Sichuan611731 China Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States School of Electrical and Electronic Engineering University College Dublin Dublin Ireland National Renewable Energy Laboratory GoldenCO80401 United States

Virtual inertia controllers (VICs) for wind turbine generators (WTGs) have been recently developed to compensate the reduction of inertia in power systems. However, VICs can induce low frequency torsional oscillations of the drive train of WTGs. This paper addresses this issue and develops a new nonlinear VIC based on objective holographic feedbacks theory. This approach allows transforming the original nonlinear control into a completely controllable system of Brunovsky’s type. Simulation results under various scenarios demonstrate that the proposed method outperforms existing VICs in terms of suppression of low frequency drive-train torsional oscillations, enhancement of system frequency nadir as well as fast and smooth recovery of WTG rotor speed to the original MPP point before the disturbance. The proposed method is also able to coordinate multiple WTGs. Copyright © 2020, The Authors. All rights reserved.

关键词： Frequency response

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Virtual Transformer Control for DC-DC Interlinking Converters in DC Microgrids

Virtual Transformer Control for DC-DC Interlinking Converter...

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IEEE Energy Conversion Congress and Exposition

作者： Haixu Shi Kai Sun Yunwei Li Hongfei Wu State Key Lab of Power Systems Tsinghua University Beijing China Electrical and Computer Engineering University of Alberta Edmonton AB Canada Center for More-Electric-Aircraft Power System College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

In a DC microgrid, a converter connecting two DC buses is a DC-DC interlinking converter (ILC). In the ILCs, this paper proposes a simple control solution to handle two control issues simultaneously: a) high-voltage-side-series low-voltage-side-parallel (HSLP) modular ILC, b) control adaptability in different grid-working modes. Existing closed-loop control methods are complex and usually do not consider the two issues together. Open-loop controls feature very low cost for realization. Some open-loop controlled ILCs show good performances in the two issues: automatic voltage sharing in HSLP modules, good adaptability in different grid-working modes. The secret is that in these open-loop controlled ILCs: when the steady converter power changes, steady voltages of the two ports are nearly proportional. However, open-loop controls are restricted to certain converter topologies and they cannot modify the converter performances based on sampling feedback. For DC-DC ILCs, this paper proposes a very simple but comprehensive closed-loop control named `virtual transformer'. This control uses closed-loop feedback to learn the proportional-port-voltage feature from the open-loop controlled ILCs. Thus these good performances and the low cost are inherited, while the main shortcomings of open-loop controls are overcome.

关键词： Voltage control Microgrids Medium voltage Prototypes Topology Bridge circuits

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OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines

arXiv

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arXiv 2022年

作者： Babier, Aaron Mahmood, Rafid Zhang, Binghao Alves, Victor G.L. Barragán-Montero, Ana Maria Beaudry, Joel Cardenas, Carlos E. Chang, Yankui Chen, Zijie Chun, Jaehee Diaz, Kelly Eraso, Harold David Faustmann, Erik Gaj, Sibaji Gay, Skylar Gronberg, Mary Guo, Bingqi He, Junjun Heilemann, Gerd Hira, Sanchit Huang, Yuliang Ji, Fuxin Jiang, Dashan Giraldo, Jean Carlo Jimenez Lee, Hoyeon Lian, Jun Liu, Shuolin Liu, Keng-Chi Marrugo, José Miki, Kentaro Nakamura, Kunio Netherton, Tucker Nguyen, Dan Nourzadeh, Hamidreza Osman, Alexander F.I. Peng, Zhao Muñoz, José Darío Quinto Ramsl, Christian Rhee, Dong Joo Rodriguez, Juan David Shan, Hongming Siebers, Jeffrey V. Soomro, Mumtaz H. Sun, Kay Hoyos, Andrés Usuga Valderrama, Carlos Verbeek, Rob Wang, Enpei Willems, Siri Wu, Qi Xu, Xuanang Yang, Sen Yuan, Lulin Zhu, Simeng Zimmermann, Lukas Moore, Kevin L. Purdie, Thomas G. McNiven, Andrea L. Chan, Timothy C.Y. Department Of Mechanical And Industrial Engineering University Of Toronto TorontoON Canada Vector Institute TorontoON Canada Department Of Radiation Oncology University Of Virginia Health System CharlottesvilleVA United States Department Of Molecular Imaging Radiation Oncology UCLouvain Louvain-la-Neuve Belgium Department Of Radiation Oncology Memorial Sloan Kettering Cancer Center New YorkNY United States Department Of Radiation Oncology The University Of Alabama At Birmingham BirminghamAL United States Department Of Engineering And Applied Physics University Of Science And Technology Of China Hefei China Shenying Medical Technology Co. Ltd. Guangdong Shenzhen China Department Of Radiation Oncology Yonsei University Seoul Korea Republic of Department Of Physics National University Of Colombia Medellín Colombia Atominstitut Vienna University Of Technology Vienna Austria Department Of Biomedical Engineering Cleveland Clinic ClevelandOH United States Department Of Radiation Physics The University Of Texas MD Anderson Cancer Center HoustonTX United States Department Of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Department Of Radiation Oncology Medical University Of Vienna Vienna Austria Department Of Biomedical Engineering Johns Hopkins University BaltimoreMD United States Department Of Radiation Oncology Peking University Cancer Hospital And Institute Beijing China Department Of Electrical Engineering And Automation Anhui University Hefei China Department Of Radiation Oncology Massachusetts General Hospital BostonMA United States Department Of Radiation Oncology University Of North Carolina At Chapel Hill Chapel HillNC United States Department Of Medical Imaging Taiwan AI Labs Taipei Taiwan Department Of Biomedical And Health Sciences Hiroshima University Hiroshima Japan Laboratory Department Of Radiation Oncology The University Of Texas Southwestern Medical Center DallasTX United States Department Of Radiatio

We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients with head-and-neck cancer and high-quality dose predictions from 19 KBP models that were developed by different research groups during the OpenKBP Grand Challenge. The dose predictions were input to four optimization models to form 76 unique KBP pipelines that generated 7600 plans. The predictions and plans were compared to the reference plans via: dose score, which is the average mean absolute voxel-by-voxel difference in dose a model achieved;the deviation in dosevolume histogram (DVH) criterion;and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models. The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50 to 0.62, which indicates that the quality of the predictions is generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBPgenerated plans performed significantly better (P © 2022, CC BY.

关键词： Forecasting

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Control of Nonlinear Constrained Ultra-Supercritical Boiler–Turbine Units Using Offset-Free Output-Feedback Stable MPC

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IFAC-PapersOnLine 2018年第28期51卷 155-160页

作者： Chen, Chen Pan, Lei Shen, Jiong Lee, Kwang Y. Zhang, Fan Sun, Li Wu, Xiao Zhang, Junli Xue, Wenchao Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education Southeast University Nanjing210096 China Department of Electrical and Computer Engineering Baylor University One Bear Place #97356 WacoTX76798-7356 United States State Key Lab of Power System Department of Energy and Power Engineering Tsinghua University Beijing100084 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

It is extremely challenging to control ultra-supercritical boiler–turbine unit on account of its nonlinearity, coupling among multi-variables, hard input constraints, and unknown disturbances. An offset-free output-feedback stable model predictive control (MPC) (OFOF-SMPC) for nonlinear constrained ultra-supercritical boiler-turbine units is investigated. It is shown that the OFOF-SMPC is composed of a disturbance and state observer, a steady-state target calculator as well as a stable MPC, which can remove unknown disturbances from output channels and ensure the stability of the closed-loop system with input constraints. Simulation results demonstrate the effectiveness of the proposed algorithm. © 2018

关键词： Feedback

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A Benchmark system for Hardware-in-The-Loop Testing of Distributed Energy Resources

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IEEE power and Energy Technology systems Journal 2018年第3期5卷 94-103页

作者： Kotsampopoulos, Panos Lagos, Dimitris Hatziargyriou, Nikos Faruque, M. Omar Lauss, Georg Nzimako, Onyi Forsyth, Paul Steurer, Michael Ponci, F. Monti, A. Dinavahi, V. Strunz, Kai Smart Grids Research Unit School of Electrical and Computer Engineering National Technical University of Athens Zografou15780 Greece Department of Electrical and Computer Engineering Center for Advanced Power Systems Florida State University TallahasseeFL32310 United States Energy Department Austrian Institute of Technology Vienna1210 Austria RTDS Inc. WinnipegMBR3T 2E1 Canada Institute for Automation of Complex Power Systems E.ON Energy Research Center RWTH Aachen University Aachen52074 Germany Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2V4 Canada SENSE Lab Berlin University of Technology Berlin10587 Germany

In order to overcome challenges associated with the integration of distributed energy resources (DER) into state-of-The-art and future power grids, a common basis for testing using appropriate benchmark systems is required. Real-time hardware-in-The-loop (HIL) simulation has proven to be an advanced and efficient tool for the analysis and validation of electric power systems and DER components. However, a common methodology for HIL testing of DER along with the required set of reference systems has not yet been developed. This task-force paper proposes a benchmark system for HIL testing incorporating DER into the real-time simulation environment. A low-voltage benchmark system with detailed HIL setup is proposed for the testing of DER performance. The modeling of DER for real-time applications is discussed, and the detailed laboratory procedures and setups for both controller HIL (CHIL) and power HIL (PHIL) are provided. Results from CHIL simulation related to the centralized controls and experimental results of PHIL simulation related to local control on the benchmark system substantiate the suitability of the proposed real-time simulation approach. © 2014 IEEE.

关键词： Hardware-in-the-loop simulation

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OpenHI2 - Open source histopathological image platform

OpenHI2 - Open source histopathological image platform

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Pargorn Puttapirat Haichuan Zhang Jingyi Deng Yuxin Dong Jiangbo Shi Hongyu He Zeyu Gao Chunbao Wang Xiangrong Zhang Chen Li National Engineering Lab for Big Data Analytics Xi'an Jiao tong University Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Tech. R&D Xi'an Jiaotong University Department of Power System and Automation School of Electrical Engineering Xi'an Jiaotong University Department of Pathology the First Affiliated Hospital of Xi'an Jiaotong University Institute of Intelligent Information Processing Xidian University

ISBN: (纸本)9781728118680

Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine. Pathological diagnoses are sensitive to many external factors and is known to be subjective. Only systems that can meet strict requirements in pathology would be able to run along pathological routines and eventually digitized the area, and the developed platform should comply with existing pathological routines and international standards. Currently, there are a number of available software tools which can perform histopathological tasks including virtual slide viewing, annotating, and basic image analysis, however, none of them can serve as a digital platform for pathology. Here we describe OpenHI2, an enhanced version Open Histopathological Image platform which is capable of supporting all basic pathological tasks and file formats;ready to be deployed in medical institutions on a standard server environment or cloud computing infrastructure. In this paper, we also describe the development decisions for the platform and propose solutions to overcome technical challenges including responsive region retrieval and viewing, virtual slide magnification, recording of diagnostic areas. These factors would promote OpenHI2 be used as a platform for histopathological images in real-world clinical settings. Furthermore, in research, OpenHI2 inherited the annotation functionality from the previous version, thus acquired annotations can be directly utilized by the newly added machine learning module which include popular machine learning models to perform tasks such as histology image classification and segmentation in the same environment. Addition can be made to the platform since each component is modularized and fully documented. OpenHI2 is free, open-source, and available at .

关键词： OpenHI digital pathology histopathological image analysis open source software open source software pathology Platform Software Tools open source Religious Missions External factors images

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Cascaded PI Controller Tuning for power Plant Superheated Steam Temperature based on Multi-Objective Optimization

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IFAC-PapersOnLine 2017年第1期50卷 3227-3231页

作者： Fu H. Pan L. Xue Y.L. Sun L. Li D.H. Lee K.Y. Wu Z.L. He T. Zheng S. Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education Southeast University Nanjing 210096 China State Key Lab of Power System Department of Thermal Engineering Tsinghua University Beijing China Department of Electrical and Computer Engineering Baylor University Waco TX 76798 United States Department of Automation Fuzhou University Fuzhou 350000 China

To improve the superheated steam temperature (SST) control performance, this paper considers the conflicting objectives in SST control, multi-objective optimization (MOO) algorithm is employed in this paper. Firstly, the inner-loop PI controller is optimized by considering the objectives of set-point tracking and disturbance rejection, with and without constraints on robustness level. It is found that robustness constraint is essential in the optimization. Secondly, the regulation performance of the outer-loop PI controller is addressed by optimizing the disturbance rejection and robustness simultaneously. The parameter are determined based on the simulation comparison between the non-dominated solutions. The simulation results demonstrate a promising prospect of promoting the proposed strategy to more industrial practices. © 2017

关键词： Disturbance rejection Pareto optimization power plant control Robustness Superheated steam temperature

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Design of hybrid damping controller based on multi-target gravitational search optimization algorithm in a multi-machine power system with high penetration of PV park

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Journal of Central South University 2016年第5期23卷 1163-1175页

作者： Y.Hashemi H.Shayeghi M.Moradzadeh A.Safari Technical Engineering Department University of Mohaghegh Ardabili Centre of Excellence for Power System Automation and Operation Department of Electrical EngineeringIran University of Science and Technology Centre for Engineering Innovation Department of Electrical and Computer EngineeringUniversity of Windsor Electrical Energy Laboratory Department of Electrical EnergySystems and AutomationGhent University Department of Electrical Engineering Azarbaijan Shahid Madani University

A mathematical approach was proposed to investigate the impact of high penetration of large-scale photovoltaic park(LPP) on small-signal stability of a power network and design of hybrid controller for these units.A systematic procedure was performed to obtain the complete model of a multi-machine power network including *** damping of oscillations focusing on inter-area oscillatory modes,a hybrid controller for LPP was *** performance of the suggested controller was tested using a 16-machine 5-area *** results indicate that the proposed hybrid controller for LPP provides sufficient damping to the low-frequency modes of power system for a wide range of operating *** method presented in this work effectively indentifies the impact of increased PV penetration and its controller on dynamic performance of multi-machine power network containing *** results demonstrate that the model presented can be used in designing of essential controllers for LPP.

关键词： hybrid controller multi-objective optimization large-scale photovoltaic park small-signal scrutiny

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Hybrid Symbiotic Organisms Search for Optimal Fuzzified Joint Reconfiguration and Capacitor Placement in Electric Distribution systems

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INAE Letters 2017年第3期2卷 107-121页

作者： Mostafa Sedighizadeh Masoud Esmaili Amir Eisapour-Moarref Faculty of Electrical and Computer Engineering Shahid Beheshti University Tehran Iran Department of Electrical Engineering West Tehran Branch Islamic Azad University Tehran Iran Centre of Excellence for Power System Automation and Operation Iran University of Science and Technology Tehran Iran

Network reconfiguration and capacitor allocation are two valuable tools to optimally manage distribution systems. In the present work, an efficient algorithm is proposed for the joint problem of reconfiguration and capacitor placement in distribution systems. The multi-objective problem is formulated to minimize objective functions of total network power losses, bus voltage violation, and branch loading deviations subject to different technical and operational constraints. To enhance exploration ability, the Symbiotic Organisms Search algorithm is strengthened with Particle Swarm Optimization capabilities to develop the Hybrid Symbiotic Organisms Search algorithm, which is applied to solve the proposed problem. Objective functions are fuzzified and aggregated by a geometric mean operator to have the same scales. The proposed joint optimization problem is solved with the introduced Hybrid Symbiotic Organisms Search algorithm in two different case studies of balanced and unbalanced test systems. According to obtained results that are compared with some well-known evolutionary algorithms, the superiority of the Hybrid Symbiotic Organisms Search algorithm is confirmed in terms of solution optimality and convergence speed.

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