Machines最新文献_第2页

An Advanced Diagnostic Approach for Broken Rotor Bar Detection and Classification in DTC Controlled Induction Motors by Leveraging Dynamic SHAP Interaction Feature Selection (DSHAP-IFS) GBDT Methodology 利用动态 SHAP 交互特征选择（DSHAP-IFS）GBDT 方法检测和分类 DTC 控制感应电机转子断线的先进诊断方法

IF 2.1 3区工程技术

Machines Pub Date : 2024-07-22 DOI: 10.3390/machines12070495

Muhammad Amir Khan, B. Asad, T. Vaimann, A. Kallaste

{"title":"An Advanced Diagnostic Approach for Broken Rotor Bar Detection and Classification in DTC Controlled Induction Motors by Leveraging Dynamic SHAP Interaction Feature Selection (DSHAP-IFS) GBDT Methodology","authors":"Muhammad Amir Khan, B. Asad, T. Vaimann, A. Kallaste","doi":"10.3390/machines12070495","DOIUrl":"https://doi.org/10.3390/machines12070495","url":null,"abstract":"This paper introduces a sophisticated approach for identifying and categorizing broken rotor bars in direct torque-controlled (DTC) induction motors. DTC is implemented in industrial drive systems as a suitable control method to preserve torque control performance, which sometimes shows its impact on fault-representing frequencies. This is because of the DTC’s closed-loop control nature, whichtriesto reduce speed and torque ripples by changing the voltage profile. The proposed model utilizes the modified Shapley Additive exPlanations (SHAP) technique in combination with gradient-boosting decision trees (GBDT) to detect and classify the abnormalities in BRBs at diverse (0%, 25%, 50%, 75%, and 100%) loading conditions. To prevent overfitting of the proposed model, we used the adaptive fold cross-validation (AF-CV) technique, which can dynamically adjust the number of folds during the optimization process. By employing extensive feature engineering in the original dataset and then applying Shapely Additive exPlanations(SHAP)-based feature selection, our methodology effectively identifies informative features from signals (three-phase current, three-phase voltage, torque, and speed) and motor characteristics. The gradient-boosting decision tree (GBDT) classifier, trained using the given characteristics, extracts consistent and reliable classification performance under different loading circumstances and enables precise and accurate detection and classification of broken rotor bars. The proposed approach (SHAP-Fusion GBDT with AF-CV) is a major advancement in the field of machine learning in detecting motor anomalies at varying loading conditions and proved to be an effective mechanism for preventative maintenance and preventing faults in DTC-controlled induction motors byattaining an accuracy rate of 99% for all loading conditions.","PeriodicalId":48519,"journal":{"name":"Machines","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141815792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Friction Stir Channeling in Heat Sink Applications: Innovative Manufacturing Approaches and Performance Evaluation 散热器应用中的搅拌摩擦沟槽：创新制造方法和性能评估

IF 2.1 3区工程技术

Machines Pub Date : 2024-07-22 DOI: 10.3390/machines12070494

Sooraj Patel, Amit Arora

引用次数: 0

Fault Diagnosis Method for Tractor Transmission System Based on Improved Convolutional Neural Network–Bidirectional Long Short-Term Memory 基于改进型卷积神经网络-双向长短期记忆的拖拉机传动系统故障诊断方法

IF 2.1 3区工程技术

Machines Pub Date : 2024-07-21 DOI: 10.3390/machines12070492

Liyou Xu, Guoxiang Zhao, Sixia Zhao, Yiwei Wu, Xiaoliang Chen

{"title":"Fault Diagnosis Method for Tractor Transmission System Based on Improved Convolutional Neural Network–Bidirectional Long Short-Term Memory","authors":"Liyou Xu, Guoxiang Zhao, Sixia Zhao, Yiwei Wu, Xiaoliang Chen","doi":"10.3390/machines12070492","DOIUrl":"https://doi.org/10.3390/machines12070492","url":null,"abstract":"In response to the problems of limited algorithms and low diagnostic accuracy for fault diagnosis in large tractor transmission systems, as well as the high noise levels in tractor working environments, a defect detection approach for tractor transmission systems is proposed using an enhanced convolutional neural network (CNN) and a bidirectional long short-term memory neural network (BILSTM). This approach uses a one-dimensional convolutional neural network (1DCNN) to create three feature extractors of varying scales, directly extracting feature information from different levels of the raw vibration signals. Simultaneously, in order to enhance the model’s predicted accuracy and learn the data features more effectively, it presents the multi-head attention mechanism (MHA). To overcome the issue of high noise levels in tractor working environments and enhance the model’s robustness, an adaptive soft threshold is introduced. Finally, to recognize and classify faults, the fused feature data are fed into a classifier made up of bidirectional long short-term memory (BILSTM) and fully linked layers. The analytical findings demonstrate that the fault recognition accuracy of the method described in this article is over 98%, and it also has better performance in noisy environments.","PeriodicalId":48519,"journal":{"name":"Machines","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141818059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Industrial Robot Trajectory Optimization Based on Improved Sparrow Search Algorithm 基于改进的麻雀搜索算法的工业机器人轨迹优化

IF 2.1 3区工程技术

Machines Pub Date : 2024-07-20 DOI: 10.3390/machines12070490

Fei Ma, Weiwei Sun, Zhouxiang Jiang, Shuangfu Suo, Xiao Wang, Yue Liu

{"title":"Industrial Robot Trajectory Optimization Based on Improved Sparrow Search Algorithm","authors":"Fei Ma, Weiwei Sun, Zhouxiang Jiang, Shuangfu Suo, Xiao Wang, Yue Liu","doi":"10.3390/machines12070490","DOIUrl":"https://doi.org/10.3390/machines12070490","url":null,"abstract":"This paper proposes an enhanced multi-strategy sparrow search algorithm to optimize the trajectory of a six-axis industrial robot, addressing issues of low efficiency and high vibration impact on joints during operation. Initially, the improved D-H parametric method is employed to establish both forward and inverse kinematic models of the robot. Subsequently, a 3-5-3 mixed polynomial interpolation trajectory planning approach is applied to the robot. Building upon the conventional sparrow algorithm, a two-dimensional Logistic chaotic system initializes the population. Additionally, a Levy flight strategy and nonlinear adaptive weighting are introduced to refine the discoverer position update operator, while an inverse learning strategy enhances the vigilante position update operator. These modifications boost both the local and global search capabilities of the algorithm. The improved sparrow algorithm, based on 3-5-3 hybrid polynomial trajectory planning, is then used for the time-optimal trajectory planning of the robot. This is compared with traditional sparrow search algorithm and particle swarm algorithm optimization results. The findings indicate that the proposed enhanced sparrow search algorithm outperforms both the standard sparrow algorithm and the particle swarm algorithm in terms of convergence speed and accuracy for robot trajectory optimization. This can lead to the increased work efficiency and performance of the robot.","PeriodicalId":48519,"journal":{"name":"Machines","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141819985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction and Dynamic Simulation Verification of Output Characteristics of Radial Piston Motors Based on Neural Networks 基于神经网络的径向活塞发动机输出特性预测与动态模拟验证

IF 2.1 3区工程技术

Machines Pub Date : 2024-07-20 DOI: 10.3390/machines12070491

Chunjin Li, Zhengwen Xia, Yongjie Tang

{"title":"Prediction and Dynamic Simulation Verification of Output Characteristics of Radial Piston Motors Based on Neural Networks","authors":"Chunjin Li, Zhengwen Xia, Yongjie Tang","doi":"10.3390/machines12070491","DOIUrl":"https://doi.org/10.3390/machines12070491","url":null,"abstract":"Radial piston motors are executive components in hydraulic systems, tasked with providing appropriate torque and speed according to load requirements in practical applications. The purpose of this study is to predict the output torque of radial piston hydraulic motors and confirm their suitable operating conditions. Efficiency determination experiments were conducted on physical models, yielding thirty sets of performance data. Torque (output torque) and mechanical efficiency from the experimental data were selected as prediction targets and fitted using two methods: multiple linear regression and neural networks. A dynamic simulation model was built using Adams2020 software to obtain theoretical torque values, enabling the verification of the alignment between the predicted values and simulation results. The results indicate that the error between the theoretical torque of the dynamic model and the physical experiments is 1.9%, with the error of the neural network predictions being within 2%. The dynamic simulation model can yield highly accurate theoretical torque values, providing a reference for the external load of hydraulic motors; additionally, neural networks offer accurate predictions of output torque, thus reducing experimental testing costs.","PeriodicalId":48519,"journal":{"name":"Machines","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigation of the Electrical Impedance Signal Behavior in Rolling Element Bearings as a New Approach for Damage Detection 研究滚动体轴承中的电阻抗信号行为作为检测损坏的新方法

IF 2.1 3区工程技术

Machines Pub Date : 2024-07-19 DOI: 10.3390/machines12070487

F. Becker-Dombrowsky, Johanna Schink, Julian Frischmuth, E. Kirchner

{"title":"Investigation of the Electrical Impedance Signal Behavior in Rolling Element Bearings as a New Approach for Damage Detection","authors":"F. Becker-Dombrowsky, Johanna Schink, Julian Frischmuth, E. Kirchner","doi":"10.3390/machines12070487","DOIUrl":"https://doi.org/10.3390/machines12070487","url":null,"abstract":"The opportunities of impedance-based condition monitoring for rolling bearings have been shown earlier by the authors: Changes in the impedance signal and the derived features enable the detection of pitting damages. Localizing and measuring the pitting length in the raceway direction is possible. Furthermore, the changes in features behavior are physically explainable. These investigations were focused on a single bearing type and only one load condition. Different bearing types and load angles were not considered yet. Thus, the impedance signals and their features of different bearing types under different load angles are investigated and compared. The signals are generated in fatigue tests on a rolling bearing test rig with conventional integrated vibration analysis based on structural borne sound. The rolling bearing impedance is gauged using an alternating current measurement bridge. Significant changes in the vibration signals mark the end of the fatigue tests. Therefore, comparing the response time of the impedance can be compared to the vibration signal response time. It can be shown that the rolling bearing impedance is an instrument for condition monitoring, independently from the bearing type. In case of pure radial loads, explicit changes in the impedance signal are detectable, which indicate a pitting damage. Under combined loads, the signal changes are detectable as well, but not as significant as under radial load. Damage-indicating signal changes occur later compared to pure radial loads, but nevertheless enable an early detection. Therefore, the rolling bearing impedance is an instrument for pitting damage detection, independently from bearing type and load angle.","PeriodicalId":48519,"journal":{"name":"Machines","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Damage Mechanism Analysis of the Connecting Screw of Turbine Disk-Drum Assembly 涡轮机盘鼓组件连接螺杆的损伤机理分析

IF 2.1 3区工程技术

Machines Pub Date : 2024-07-19 DOI: 10.3390/machines12070489

Haijun Wang, Shengxu Wang, Pu Xue, Yongxin Guo, Liang Jiang

{"title":"Damage Mechanism Analysis of the Connecting Screw of Turbine Disk-Drum Assembly","authors":"Haijun Wang, Shengxu Wang, Pu Xue, Yongxin Guo, Liang Jiang","doi":"10.3390/machines12070489","DOIUrl":"https://doi.org/10.3390/machines12070489","url":null,"abstract":"The turbine disk-drum is one of the key components of an aero-engine and its assembly is connected with high-strength refined screws. But due to the uncoordinated rotation and deformation, the screws have abnormal wear damage. Through detailed contact stress analysis of screw body and component level using the finite element method, combined with experimental observation, the mechanism of wear damage of screw surface in screws is determined. It mainly includes the following: Firstly, the finite element method is used to calculate the deformation and stress distribution of the connecting screw of the turbine disk-drum assembly. Then, after the overspeed test, the morphology of the screws disassembled from the disk-drum assembly is evaluated. It was found that the wear degree in the circumferential direction and axial direction of the screw was quite different, that is, the screw wear experiment was consistent with the finite element analysis results. Finally, the influence of different rotation states and screw tightening states on screw wear was compared and analyzed. Conclusions obtained in this paper will be helpful to improve the assembly reliability of turbine drum.","PeriodicalId":48519,"journal":{"name":"Machines","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Coupled Wing Morphing of Ornithopters Improves Attitude Control and Agile Flight 鸟翼飞行器的耦合机翼变形可改善姿态控制和敏捷飞行

IF 2.1 3区工程技术

Machines Pub Date : 2024-07-19 DOI: 10.3390/machines12070486

Yu Cai, Guangfa Su, Jiannan Zhao, Shuang Feng

{"title":"The Coupled Wing Morphing of Ornithopters Improves Attitude Control and Agile Flight","authors":"Yu Cai, Guangfa Su, Jiannan Zhao, Shuang Feng","doi":"10.3390/machines12070486","DOIUrl":"https://doi.org/10.3390/machines12070486","url":null,"abstract":"Bird wings are exquisite mechanisms integrated with multiple morphological deformation joints. The larger avian species are particularly adept at utilizing their wings’ flapping, folding, and twisting motions to control the wing angle and area. These motions mainly involve different types of spanwise folding and chordwise twisting. It is wondered whether the agile maneuverability of birds is based on the complex coupling of these wing morphing changes. To investigate this issue, we designed a two-section wing structure ornithopter capable of simultaneously controlling both spanwise folding and chordwise twisting and applied it to research on heading control. The experimental data collected from outdoor flights describe the differing flight capabilities between the conventional and two-section active twist wing states, indicating that incorporating an active twist structure enhances the agility and maneuverability of this novel flapping aircraft. In the experiments on yaw control, we observed some peculiar phenomena: although the twisting motion of the active twist ornithopter wings resembles that of a fixed-wing aileron control, due to the intricate coupling of the wing flapping and folding, the ornithopter, under the control of active twist structures, exhibited a yaw direction opposite to the expected direction (directly applying the logic assumed by the fixed-wing aileron control). Addressing this specific phenomenon, we provide a plausible model explanation. In summary, our study with active twist mechanisms on ornithopters corroborates the positive impact of active deformation on their attitude agility, which is beneficial for the design of similar bio-inspired aircraft in the future.","PeriodicalId":48519,"journal":{"name":"Machines","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrated Control of a Wheel–Track Hybrid Vehicle Based on Adaptive Model Predictive Control 基于自适应模型预测控制的轮轨混合动力车集成控制

IF 2.1 3区工程技术

Machines Pub Date : 2024-07-19 DOI: 10.3390/machines12070485

Boyuan Li, Zhengyu Pan, Junhua Liu, Shiyu Zhou, Shaoxun Liu, Shouyuan Chen, Rongrong Wang

{"title":"Integrated Control of a Wheel–Track Hybrid Vehicle Based on Adaptive Model Predictive Control","authors":"Boyuan Li, Zhengyu Pan, Junhua Liu, Shiyu Zhou, Shaoxun Liu, Shouyuan Chen, Rongrong Wang","doi":"10.3390/machines12070485","DOIUrl":"https://doi.org/10.3390/machines12070485","url":null,"abstract":"Hybrid wheel–track systems have found extensive applications due to the advantages a combination of wheels and tracks. However, the coupling influence between the wheeled and tracked mechanisms poses a challenge to stable and efficient controller design and implementation. This paper focuses on the lateral dynamic control of a vehicle in scenarios where both tracks and wheels are in contact with the ground. A dynamic model of a vehicle is first established based on the tire brush model and linearized general track model. Based on the dynamic model, a novel adaptive model predictive control (AMPC) method is designed considering the coupling and nonlinearity of the wheels and tracks to simultaneously regulate both mechanisms. Compared with traditional model predictive control approaches, the AMPC controller takes the side-slip angle and slip ratio as constraints to prevent the vehicle from reaching unstable states. Simulations are conducted to validate the effectiveness of the controller, and the results indicate that the controller has the capacity to optimize the objective’s yaw-rate response while maintaining lateral vehicle stability and preventing slip by imposing constraints.","PeriodicalId":48519,"journal":{"name":"Machines","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Topology Analysis and Structural Optimization of Air Suspension Mechanical-Vibration-Reduction Wheels 空气悬架机械减震轮的拓扑分析与结构优化

IF 2.1 3区工程技术

Machines Pub Date : 2024-07-19 DOI: 10.3390/machines12070488

Xiao Meng, Xianying Feng, Peihua Liu, Xinhua Sun

引用次数: 0