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Ensuring the Abrasive Jet Machining Efficiency Using a Nozzle with a Perforated Insert 使用带孔刀片的喷嘴确保喷砂加工效率

Machines Pub Date : 2024-05-16 DOI: 10.3390/machines12050347

Vadym Baha, Ivan Pavlenko, Kamil Židek, Olaf Ciszak

{"title":"Ensuring the Abrasive Jet Machining Efficiency Using a Nozzle with a Perforated Insert","authors":"Vadym Baha, Ivan Pavlenko, Kamil Židek, Olaf Ciszak","doi":"10.3390/machines12050347","DOIUrl":"https://doi.org/10.3390/machines12050347","url":null,"abstract":"Ejector-cleaning devices for abrasive jet machining have various practical applications. The working nozzle is one of the device’s key elements affecting the treated surface quality. There arises the necessity for new approaches to achieving an efficiency increase in abrasive jet equipment nozzles, namely their design improvement and further development of a new, relatively cheap but effective technology for their manufacturing and maintenance. This technology should allow for the high durability of nozzles without being essential for the hardness or wear resistance parameters of the material used for manufacturing. The nozzle should be designed as a long-length perforated insert to allow for radial airflow, forcing the abrasive material (river sand) from the inner walls of the nozzle’s working surface to reduce its friction with the abrasive material. This will result in new wear-out conditions, providing an essential decrease in the wear-out of a nozzle’s working surface. The article aims to develop a more effective design for the working nozzle based on the perforated insert application. The task was set to provide a more detailed experimental and theoretical study of the processes in perforated nozzles to improve their effectiveness. The research resulted in a new design for nozzles with higher efficiency.","PeriodicalId":509264,"journal":{"name":"Machines","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140967063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Objective Evaluation of Motion Cueing Algorithms for Vehicle Driving Simulator Based on Criteria Importance through Intercriteria Correlation (CRITIC) Weight Method Combined with Gray Correlation Analysis 基于标准间相关性（CRITIC）权重法和灰色关联分析的车辆驾驶模拟器运动提示算法的客观评估

Machines Pub Date : 2024-05-16 DOI: 10.3390/machines12050344

Xue Jiang, Xiafei Chen, Yiyang Jiao, Lijie Zhang

引用次数: 0

Determination of Mechanical Power Loss of the Output Mechanisms with Serially Arranged Rollers in Cycloidal Gears While Taking into Account Manufacturing Tolerances 在考虑制造公差的情况下，确定摆线齿轮中串列滚柱输出机构的机械功率损耗

Machines Pub Date : 2024-05-16 DOI: 10.3390/machines12050345

P. Antoniak, Sławomir Bednarczyk

{"title":"Determination of Mechanical Power Loss of the Output Mechanisms with Serially Arranged Rollers in Cycloidal Gears While Taking into Account Manufacturing Tolerances","authors":"P. Antoniak, Sławomir Bednarczyk","doi":"10.3390/machines12050345","DOIUrl":"https://doi.org/10.3390/machines12050345","url":null,"abstract":"Despite their complex design, cycloidal gearboxes are characterized by high efficiency. Nevertheless, due to friction, some power is lost during gearbox operation. Basically, these losses occur in two structural nodes: the cycloid gearing and the output mechanism. Since the first of these nodes has been well discussed in the literature, the output mechanism will be discussed in this article. The design of the output mechanism has a significant impact on mechanical power losses. There are several mechanism design solutions. One of them is a mechanism with serially arranged rollers. Three solutions that are different in design but work identically will be discussed. Due to this affinity, a single, common mathematical model will be used to determine the value of losses. As will be shown, the value of losses is directly affected by the backlash, number, and diameter of the rollers used in the output mechanism and indirectly by the ratio and eccentricity of the cycloidal gearbox. Sample calculations were carried out using the developed model of mechanical power losses in the output mechanism. This made it possible to analyze the distribution of backlash created by manufacturing tolerances. It was also shown that the backlash has a significant effect on the number of rollers involved in torque transmission, as well as on the distribution of loads, contact pressures, and mechanical power losses.","PeriodicalId":509264,"journal":{"name":"Machines","volume":"16 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140967835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mathematical Complexities in Modelling Damage in Spur Gears 支齿轮损坏建模的数学复杂性

Machines Pub Date : 2024-05-16 DOI: 10.3390/machines12050346

Aselimhe Oreavbiere, Muhammad Khan

{"title":"Mathematical Complexities in Modelling Damage in Spur Gears","authors":"Aselimhe Oreavbiere, Muhammad Khan","doi":"10.3390/machines12050346","DOIUrl":"https://doi.org/10.3390/machines12050346","url":null,"abstract":"Analytical modelling is an effective approach to obtaining a gear dynamic response or vibration pattern for health monitoring and useful life prediction. Many researchers have modelled this response with various fault conditions commonly observed in gears. The outcome of such models provides a good idea about the changes in the dynamic response available between different gear health states. Hence, a catalogue of the responses is currently available, which ought to aid predictions of the health of actual gears by their vibration patterns. However, these analytical models are limited in providing solutions to useful life prediction. This may be because a majority of these models used single fault conditions for modelling and are not valid to predict the remaining life of gears undergoing more than one fault condition. Existing reviews related to gear faults and dynamic modelling can provide an overview of fault modes, methods for modelling and health prediction. However, these reviews are unable to provide the critical similarities and differences in the single-fault dynamic models to ascertain the possibility of developing models under combined fault modes. In this paper, existing analytical models of spur gears are reviewed with their associated challenges to predict the gear health state. Recommendations for establishing more realistic models are made especially in the context of modelling combined faults and their possible impact on gear dynamic response and health prediction.","PeriodicalId":509264,"journal":{"name":"Machines","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140969948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Image-Based Interactive Training Method of an Upper Limb Rehabilitation Robot 基于图像的上肢康复机器人互动训练方法

Machines Pub Date : 2024-05-16 DOI: 10.3390/machines12050348

Changlong Ye, Zun Wang, Suyang Yu, Chunying Jiang

{"title":"An Image-Based Interactive Training Method of an Upper Limb Rehabilitation Robot","authors":"Changlong Ye, Zun Wang, Suyang Yu, Chunying Jiang","doi":"10.3390/machines12050348","DOIUrl":"https://doi.org/10.3390/machines12050348","url":null,"abstract":"Aimed at the problem of human–machine interaction between patients and robots in the process of using rehabilitation robots for rehabilitation training, this paper proposes a human–machine interactive control method based on an independently developed upper limb rehabilitation robot. In this method, the camera is used as a sensor, the human skeleton model is used to analyse the moving image, and the key points of the human body are extracted. Then, the three-dimensional coordinates of the key points of the human arm are extracted by depth estimation and spatial geometry, and then the real-time motion data are obtained, and the control instructions of the robot are generated from it to realise the real-time interactive control of the robot. This method can not only improve the adaptability of the system to individual patient differences, but also improve the robustness of the system, which is less affected by environmental changes. The experimental results show that this method can realise real-time control of the rehabilitation robot, and that the robot assists the patient to complete the action with high accuracy. The results show that this control method is effective and can be applied to the fields of robot control and robot-assisted rehabilitation training.","PeriodicalId":509264,"journal":{"name":"Machines","volume":"3 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140968536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting Tool Wear with ParaCRN-AMResNet: A Hybrid Deep Learning Approach 利用 ParaCRN-AMResNet 预测刀具磨损：混合深度学习方法

Machines Pub Date : 2024-05-15 DOI: 10.3390/machines12050341

Lian Guo, Yongguo Wang

{"title":"Predicting Tool Wear with ParaCRN-AMResNet: A Hybrid Deep Learning Approach","authors":"Lian Guo, Yongguo Wang","doi":"10.3390/machines12050341","DOIUrl":"https://doi.org/10.3390/machines12050341","url":null,"abstract":"In the manufacturing sector, tool wear substantially affects product quality and production efficiency. While traditional sequential deep learning models can handle time-series tasks, their neglect of complex temporal relationships in time-series data often leads to errors accumulating in continuous predictions, which reduces their forecasting accuracy for tool wear. For addressing these limitations, the parallel convolutional and recurrent neural networks with attention-modulated residual learning (ParaCRN-AMResNet) model is introduced. Compared with conventional deep learning models, ParaCRN-AMResNet markedly enhances the efficiency and precision of feature extraction from time-series data through its innovative parallel architecture. The model adeptly combines dilated convolution neural network and bidirectional gated recurrent units, effectively addressing distance dependencies and enriching the quantity and dimensions of extracted features. The strength of ParaCRN-AMResNet lies in its refined ability to capture the complex dynamics of time-series data, significantly boosting the model’s accuracy and generalization capability. The model’s efficacy was validated through comprehensive milling experiments and vibration signal analyses, showcasing ParaCRN-AMResNet’s superior performance. In evaluation metrics, the model achieved a MAE of 2.6015, MSE of 15.1921, R2 of 0.9897, and MAPE of 2.7997%, conclusively proving its efficiency and accuracy in the precise prediction of tool wear.","PeriodicalId":509264,"journal":{"name":"Machines","volume":"51 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140974642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electromagnetic Characterization of Permanent Magnet Eddy Current Structures Based on Backplane Distance Adjustment 基于背板间距调整的永磁涡流结构电磁特性分析

Machines Pub Date : 2024-05-15 DOI: 10.3390/machines12050343

Yipeng Wu, Teng Wang, Tao Song, Wenxiao Guo

引用次数: 0

A Remaining Useful Life Prediction Method of Mechanical Equipment Based on Particle Swarm Optimization-Convolutional Neural Network-Bidirectional Long Short-Term Memory 基于粒子群优化-卷积神经网络-双向长短期记忆的机械设备剩余使用寿命预测方法

Machines Pub Date : 2024-05-15 DOI: 10.3390/machines12050342

Yong Liu, Jiaqi Liu, Han Wang, Mingshun Yang, Xinqin Gao, Shujuan Li

{"title":"A Remaining Useful Life Prediction Method of Mechanical Equipment Based on Particle Swarm Optimization-Convolutional Neural Network-Bidirectional Long Short-Term Memory","authors":"Yong Liu, Jiaqi Liu, Han Wang, Mingshun Yang, Xinqin Gao, Shujuan Li","doi":"10.3390/machines12050342","DOIUrl":"https://doi.org/10.3390/machines12050342","url":null,"abstract":"In industry, forecast prediction and health management (PHM) is used to improve system reliability and efficiency. In PHM, remaining useful life (RUL) prediction plays a key role in preventing machine failures and reducing operating costs, especially for reliability requirements such as critical components in aviation as well as for costly equipment. With the development of deep learning techniques, many RUL prediction methods employ convolutional neural network (CNN) and long short-term memory (LSTM) networks and demonstrate superior performance. In this paper, a novel two-stream network based on a bidirectional long short-term memory neural network (BiLSTM) is proposed to establish a two-stage residual life prediction model for mechanical devices using CNN as the feature extractor and BiLSTM as the timing processor, and finally, a particle swarm optimization (PSO) algorithm is used to adjust and optimize the network structural parameters for the initial data. Under the condition of lack of professional knowledge, the adaptive extraction of the features of the data accumulated by the enterprise and the effective processing of a large amount of timing data are achieved. Comparing the prediction results with other models through examples, it shows that the model established in this paper significantly improves the accuracy and efficiency of equipment remaining life prediction.","PeriodicalId":509264,"journal":{"name":"Machines","volume":"58 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140973727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Geometric Error-Based Multi-Source Error Identification and Compensation Strategy for Five-Axis Side Milling 基于几何误差的五轴侧铣多源误差识别和补偿策略

Machines Pub Date : 2024-05-14 DOI: 10.3390/machines12050340

Ziwen Zhao, Jian Mao, Xingchi Wei

{"title":"Geometric Error-Based Multi-Source Error Identification and Compensation Strategy for Five-Axis Side Milling","authors":"Ziwen Zhao, Jian Mao, Xingchi Wei","doi":"10.3390/machines12050340","DOIUrl":"https://doi.org/10.3390/machines12050340","url":null,"abstract":"Based on a multi-source error model, this paper discusses the principle of error element identification and uses the mirror bias method to compensate the geometric errors of a process system. Firstly, a nine-line measurement method to determine the geometric error of the linear feed axes of machine tools is introduced, and the geometric error identification model based on the “nine-line method” is established. Then, using a ballbar mounted in the axial, tangential, and radial directions of the machine, the geometric error elements of the rotation axis are identified by three simple measurements in each direction. Subsequently, for the more common flat vise clamping workpiece in actual production, the workpiece position error is identified by using the traditional process of dimensional chain, and the workpiece attitude error is identified by fitting the angle between the positioning plane and the horizontal plane by the least squares method. Finally, based on the tool position points and tool axis vectors obtained from the multi-source error model, the error compensation value is solved using inverse machine tool kinematics to offset the machining error by mirroring the error value of the same size, and based on the “S-shaped specimen” to compensate the processing experiments, after compensation, the processing error is reduced by 30~45%, verifying the effectiveness of the compensation method.","PeriodicalId":509264,"journal":{"name":"Machines","volume":"32 51","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Natural Characteristics of a Marine Two-Stage Tandem Hybrid Planetary System 海洋双级串联混合行星系统的自然特征

Machines Pub Date : 2024-05-14 DOI: 10.3390/machines12050338

Xingfu Zhao, Z. Yue, Jianjun Qu, Marmysh Dzianis, Yanzhong Wang

{"title":"Natural Characteristics of a Marine Two-Stage Tandem Hybrid Planetary System","authors":"Xingfu Zhao, Z. Yue, Jianjun Qu, Marmysh Dzianis, Yanzhong Wang","doi":"10.3390/machines12050338","DOIUrl":"https://doi.org/10.3390/machines12050338","url":null,"abstract":"This study focuses on a marine two-stage tandem hybrid planetary system. Natural frequencies and vibration modes are determined using a translational–torsional coupled dynamic model. Based on the motion characteristics of the transmission system, free vibration is categorized into three typical modes. The parameter sensitivity of natural frequencies is computed, and the effects of structural parameters such as unequally spaced planet, mesh stiffness, planet mass and rotational inertia on the natural frequencies are analyzed. Utilizing the coupling factor, the mode transition criterion for the natural frequencies response to parameters is formulated. The results demonstrate that the vibration modes of the two-stage tandem hybrid planetary system can be classified as the fixed-axis train vibration mode, the differential train vibration mode, and the coupled vibration mode. Unequally spaced planet primarily disrupts vibration modes without significantly affecting natural frequencies. In contrast, the effects of mesh stiffness, planet mass and rotational inertia on the modes are opposite to those of unequally spaced planets. The validity of the parameter sensitivity and mode transition criterion is substantiated through illustrative examples.","PeriodicalId":509264,"journal":{"name":"Machines","volume":"29 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140981293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0