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Bearing Fault Diagnosis in Induction Motors Using Low-Cost Triaxial ADXL355 Accelerometer and a Hybrid CWT-DCNN-LSTM Model

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IEEE Access 2025年 13卷 101037-101050页

作者： Muhammad Ahsan Jose Rodriguez Mohamed Abdelrahem Department of Measurements and Control Systems Silesian University of Technology Gliwice Poland Director Center for Energy Transition Universidad San Sebastián Santiago Chile Chair of High-Power Converter Systems Technical University of Munich Munich Germany Electrical Engineering Department Assiut University Assiut Egypt

This paper presents a novel approach for bearing fault diagnosis in induction motor utilizing an improved hybrid Continuous Wavelet Transform-Deep Convolutional Neural Network-Long Short-Term Memory (CWT-DCNN-LSTM) model. The vibration data, recorded using an low-cost ADXL355 accelerometer, was preprocessed by converting the one-dimensional (1D) signals into two-dimensional (2D) images using Continuous Wavelet Transform (CWT). The dataset, comprising 13 classes with varying fault conditions, was segmented and shuffled before model training. Three datasets, corresponding to different load conditions (100W, 200W, and 300W), were used to evaluate the model’s performance. Experimental results demonstrated high training accuracy of 100% and validation accuracies of 96.43%, 97.47%, and 95.06% for the 100W, 200W, and 300W load conditions, respectively. Validation losses were recorded at 12.33%, 9.81%, and 20.33% for the respective loads. Furthermore, performance results using accuracy, sensitivity, specificity, balanced accuracy and geometric mean were computed for all three load conditions. The results indicate the robustness and effectiveness of the proposed CWT-DCNN-LSTM model for bearing fault diagnosis of induction motor using low-cost ADXL335 accelerometer, highlighting its potential for real-world industrial applications.

关键词： Vibrations Continuous wavelet transforms Fault diagnosis Accelerometers Micromechanical devices Sensors Machinery Accuracy Feature extraction Induction motors

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An Integrated Observer Framework Based Mechanical Parameters Identification for Adaptive control of Permanent Magnet Synchronous Motor

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Complex System Modeling and Simulation 2022年第4期2卷 354-367页

作者： Zhong Liao Zhaohua Liu Lei Chen Mingyang Lyu Dian Wang Faming Wu Zhengheng Wang Hualiang Wei the School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China the Wind Power Business Division CRRC Zhuzhou Institute Co.Ltd.Zhuzhou 412001China. the Department of Automatic Control and Systems Engineering University of SheffieldSheffieldS13JDUK.

An integrated observer framework based mechanical parameters identification approach for adaptive control of permanent magnet synchronous motors is proposed in this ***,an integrated observer framework is established for mechanical parameters’estimation,which consists of an extended sliding mode observer(ESMO)and a Luenberger *** at minimizing the influence of parameters coupling,the viscous friction and the moment of inertia are obtained by ESMO and the load torque is identified by Luenberger observer *** obtaining estimates of the mechanical parameters,the optimal proportional integral(PI)parameters of the speed-loop are determined according to third-order best design *** a result,the controller can adjust the PI parameters in real time according to the parameter changes to realize the adaptive control of the ***,the disturbance is compensated according to the ***,the experiments were carried out on simulation platform,and the experimental results validated the reliability of parameter identification and the efficiency of the adaptive control strategy presented in this paper.

关键词： parameter identification permanent magnet synchronous motor adaptive control extended sliding mode observer Luenberger observer

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Facile construction of N-doped TiO2 nanohybrids with enriched oxygen vacancies for enhanced photocatalytic green hydrogen production

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Ceramics International 2025年

作者： Tao, Zichen Zhang, Bin Chen, Wenxin Cao, Ruwen Liu, Jie Wang, Lidong Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control Department of Environmental Science and Engineering North China Electric Power University Baoding071003 China MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environmental Science and Engineering North China Electric Power University Beijing102206 China

A series of N-doped TiO2 nanohybrids (xN-TiO2) were successfully prepared via a facile solvothermal route by using oleylamine as N source, for enhancing photocatalytic hydrogen evolution reaction (HER). The doped-N atoms induced the generation of abundant oxygen vacancies (OVs). The resulted impurity and defect levels in xN-TiO2 contributed to their narrowed band gap, enhanced visible light response, and promoted separation and transfer of photogenerated carrier. Moreover, the N-doping optimized the distribution of OVs, and therefore affect the conduction band (CB) location of catalyst. Herein, the 3N-TiO2 catalyst with excellent photoelectric properties and appropriate CB location, showed the photocatalytic HER rate of 3984.71 μmol h−1 g−1 under the simulated sunlight irradiation, which was 5.5 and 29.0 times that of the undoped TiO2 and commercial P25, respectively. Meanwhile, the 3N-TiO2 catalyst exhibited the excellent stability and salt-resistance. This work provides a novel insight for the band alignment of photocatalysts by defects regulation, and opens the new possibility for synthesizing N-doped TiO2 catalyst by a more practical and safe method. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Hydrogen evolution reaction

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Development of Digital Pressure Observer in Hydraulic Cylinders for Vertical Balancing of Rolling Stand Spindles

Development of Digital Pressure Observer in Hydraulic Cylind...

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2023 Russian Workshop on power engineering and Automation of Metallurgy Industry: Research and Practice, PEAMI 2023

作者： Loginov, B.M. Gasiyarova, O.A. Khramshin, V.R. Voronin, S.S. Pjsc Magnitogorsk Iron and Steel Works Magnitogorsk Russia Llc Npp Uchtekh-Profi Department of Material Science Chelyabinsk Russia Nosov Magnitogorsk State Technical University Power Engineering and Automated Systems Institute Magnitogorsk Russia Moscow Polytechnic University Department of Automation and Control Moscow Russia

ISBN: (纸本)9798350322156

A literature review showed that the causes of accidents frequently occuring at rolling mills are fatigue failures of spindle heads or necks of mill rollers. This confirms the relevance of developing the systems for monitoring the wear degree of the spindle joint components directly during the rolling process. This is relevant for thick plate rolling mills operating under shock load application. As a diagnostic feature, it is proposed to use pressure in hydraulic cylinders of spindle vertical balancing. It has been experimentally proved that the process of fatigue failure development increases such pressure;that is why it is an informative criterion in terms of defect growth. The observer structure is proposed;at the observer output the variable pressure component is restored, and an emergency signal is generated. The algorithm for virtual observer configuration is implemented in the Matlab Simulink package. The proposed algorithm has been implemented in pilot operation on a thick plate mill 5000. The authors give an example of a pre-emergency situation on-line monitoring. The timely emergency warning has been registered and confirmed which proves the technical and economic efficiency of the observer adoption. © 2023 IEEE.

关键词： Cylinders (shapes)

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Suppression of Phase Current Ripple and Torque Harmonics in Four-Module PMSM with Asymmetric Mutual Inductance

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IEEE Transactions on power Electronics 2025年

作者： Liu, Kaiyuan Li, Chi Zheng, Zedong Li, Yongdong Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Department of Electrical Engineering Beijing100084 China

In N-module motors, uniform carrier phase shifting (UCPS) by 2π/N between modules can effectively suppress torque harmonics caused by high-frequency switching of power devices. In multi-module motors with fractional-slot concentrated winding, the mutual inductance between adjacent windings is higher than that between non-adjacent windings. Although the conventional UCPS can reduce the torque sideband harmonics synthesized by the four modules, this asymmetric mutual inductance (AMI) paradoxically increases phase current ripple in each sub-module, leading to higher system losses. Aiming at this problem, this paper derives the mathematical model of N-module motor with AMI, analyzes the limitations of the traditional UCPS method that increases the phase current ripple. For different optimization objectives, two carrier phaseshifting angle optimized strategies are proposed to achieve integrated suppression of torque sideband harmonics and intramodule phase current ripples, with a genetic algorithm improving optimization speed. A threshold coefficient is introduced to achieve a tradeoff between phase current ripple and q-axis current harmonics, which can be adjusted to prioritize objectives based on user requirements. To enhance algorithm adaptability, the paper further investigates model variations under uneven torque distribution in sub-healthy states and proposes an improved comprehensive optimization algorithm, limiting torque sideband harmonics and current ripple in both healthy and sub-healthy conditions. Finally, the proposed algorithm is validated experimentally by a four-module permanent magnet synchronous motor. © 2025 IEEE.

关键词： Genetic algorithms

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Machine Learning for Analyzing Concrete Cover Separation in Externally Bonded FRP RC Beams

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Procedia Structural Integrity 2024年 64卷 1524-1531页

作者： Manish Prasad Cristina Barris Mehdi Aghabagloo Beatriz López Ricardo Perera Marta Baena Analysis and Advanced Materials for Structural Design AMADE University of Girona Girona 17003 Spain Control Engineering and Intelligent Systems EXIT University of Girona Girona 17003 Spain Department of Mechanical Engineering Technical University of Madrid 28006 Madrid Spain

Strengthening of concrete structures with Externally Bonded (EB) Fiber Reinforced Polymer (FRP) is one the most cost effective, efficient, and sustainable rehabilitation techniques. However, usually the ultimate tensile strength of the FRP cannot be achieved due to the premature debonding of the FRP or delamination of the concrete cover. In this last case, known as concrete cover separation (CCS), high stress concentration at the free end of FRP laminate, in combination with the shear stress at that section, cause the initiation of a shear crack that, if not controlled by the shear reinforcement, propagates in concrete just below internal reinforcement. Various analytical and empirical models have been developed to predict this phenomenon but none of them could give a failure load with reasonable accuracy. On the other hand, Machine Learning (ML) has been proved very effective in predicting behaviors that are difficult to quantify using mechanics. This paper explores ML algorithms to predict the failure load of flexural elements that undergo CCS. To this end, a database has been collected that comprises 140 four-point bending tests on beams reinforced with EB CFRP that failed by CCS. K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF) and extreme gradient boosting (XGBOOST) algorithms have been applied and then ranked based on their R-squared score. R-squared scores obtained from ML are the highest compared to the analytical models described in this paper. Moreover, the mean values and standard deviation of the ratio of experimental failure load and that of calculated by the ML model are the lowest compared to the analytical models. The predictions from the ML models are found more aligned with the experimental results than the analytical models. KNN is chosen as the best ML algorithm for the prediction of failure load with an R-squared score of 0.97.

关键词： Fiber Reinforced Polymer Concrete cover separation Machine Learning

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Research on operation and control of low voltage photovoltaic-energy storage DC building system 18

Research on operation and control of low voltage photovoltai...

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18th International Conference on AC and DC power Transmission, ACDC 2022

作者： Guo, Peiqian Yuan, Zhichang Han, Xuejiao Wu, Aijun Wang, Yuxuan Jiang, Zhilin State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China Energy Internet Research Institute Tsinghua University Beijing China

ISBN: (数字)9781839537615

ISBN: (纸本)9781839537615

The spread of the power electronics, both for control and power applications, in the realization of apparatuses the DC transformation in building distribution and utilization system. Currently, the research and discussion of the operation scheme and control strategy for low voltage photovoltaic-energy storage DC building system, LVPESDCBS, are relatively less. Focusing on these, in-depth research and analysis for control and operation scheme are conducted, and the related application possibility for different types LVPESDCBSs is discussed in this paper. At the start, the existing operational control strategies for the DC system are summarized. Following this, the centralized operational control scheme, which applies to the existing buildings that need to be renovated to DC type, and the decentralized operational control scheme for newly built DC buildings are studied respectively. Taking these conclusions into consideration, a ±375V LVPESDCBS digital model with various types of AC/DC power electronic devices is established in PSCAD/EMTDC. The proposed control strategy and operational scheme are verified through normal operation and single-pole operation of this LVPESDCBS. Finally, extended marketability requirement discussions of future DC building based on three perspectives: data drives, converter devices, and the application of DC technology are presented. © ACDC 2022. All rights reserved.

关键词： Digital storage

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Decentralized Dynamic Disturbance Compensation control Strategy for Multiple Parallel Inverters in Microgrid 1

Decentralized Dynamic Disturbance Compensation Control Strat...

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1st IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2022

作者： Luo, Shanna Peng, Kaixiang Hu, Changbin Shi, Xiangyi Lu, Heng School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China School of Electrical and Control Engineering North China University of Technology Beijing China Tianjin Electric Power Design Institute Co. Ltd China Energy Engineering Group Tianjin China Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg47057 Germany

ISBN: (纸本)9798350398069

In order to enhance the anti-disturbance capability of voltage fluctuation during microgrid island operation, a decentralized dynamic disturbance compensation control strategy for multiple inverters in parallel based on robust residual generator is proposed. First, a parallel state space model of multiple inverters with line parameters under quasi-stationary line conditions is established. Secondly, for the double closed loop control structure of the inverter, a dynamic compensation controller Q(s) is designed from the perspective of disturbance cancellation, and its control signal is applied to the input terminal of the current loop to realize superposition with the original system current given signal. Then, a residual generator and a dynamic compensation controller Qi(s) are added to each parallel inverter to realize mutual influence among multiple inverters further decoupling. Finally, hardware-in-the-loop experiment on three inverters in parallel are designed on the RTDS platform to verify the effectiveness of the proposed strategy. © 2022 IEEE.

关键词： controllers

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Cooling the Car while Parking Under the Sun 19

Cooling the Car while Parking Under the Sun

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19th IEEE International Multi-Conference on systems, Signals and Devices, SSD 2022

作者： Saif, Abdul-Wahid A. Aldhaifallah, Mujahed Mysorewala, Muhammad Altowairqi, Faisal Alraygi, Abdullah for Smart Mobility and Logistics Saudi Arabia for Renewable Energy and Power Systems Saudi Arabia King Fahd University of Petroleum & Minerals Control and Instrumentation Engineering Department Dhahran31261 Saudi Arabia

ISBN: (数字)9781665471084

ISBN: (纸本)9781665471084

With the increasing demand to provide green and efficient energy with an Inexhaustible source like the sun, we decided to get benefit by using the solar panel at the top of the car. Saudi Arabia is considered one of the countries that have hot weather, and that causes lots of problems during office hours, damaging car's accessories and burning of combustible material like batteries. In this work, we propose a coolant system for a car when parking under the sun. The work tries to give a design of the proposed system with a brief description of each part of the project like the solar panel, and the most suitable type for our project, the water radiator that is the future of the AC. © 2022 IEEE.

关键词： Solar concentrators

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Data-driven modeling of heat pumps and thermal storage units for MPC

Data-driven modeling of heat pumps and thermal storage units...

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2023 International Conference on the Built Environment in Transition, CISBAT 2023

作者： Brandes, M. Cai, H. Vivian, J. Croci, L. Heer, P. Smith, R. Urban Energy Systems Laboratory Empa Dübendorf Switzerland Dept. of Industrial Engineering University of Padova Padua Italy Dept. of Power System Development Ricerca Sistema Energetico SpA Milan Italy Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zurich Switzerland

Heat pumps can play a crucial role in the European energy strategy 2050, which aims to achieve net-zero greenhouse gas emissions. When coupled with thermal energy storage and integrated with advanced control strategies, heat pump operation can be optimized to reduce carbon footprint and respond to the needs of system operators. However, to scale in a multitude of buildings, the transferability of the modeling into heterogeneous systems is crucial. In this paper, two different interpretable linear models, a hybrid (grey-box) and a fully data-driven (black-box) model are investigated. Specifically, two regression-based identification methods (SINDYc and DMDc) are used for dynamic models and the LASSO regression is used for static models. The transferability of the approach is evaluated using two real-world facilities with heterogeneous sizing and configuration. The results show a similar simulation performance for both cases with a maximum normalized RMSE of 0.41 and 0.60, respectively. This confirms the transferability of the approach that is necessary for large-scale implementation. © 2023 Institute of Physics Publishing. All rights reserved.

关键词： Carbon footprint

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