Pub Date : 2023-12-04DOI: 10.3390/machines11121068
Donggyu Choi, Chang-eun Lee, Jaeuk Baek, Seungwon Do, Sungwoo Jun, Kwang-yong Kim, Young-guk Ha
Newly introduced vehicles come with various added functions, each time utilizing data from different sensors. One prominent related function is autonomous driving, which is performed in cooperation with multiple sensors. These sensors mainly include image sensors, depth sensors, and infrared detection technology for nighttime use, and they mostly generate data based on image processing methods. In this paper, we propose a model that utilizes a parallel transformer design to gradually reduce the size of input data in a manner similar to a stairway, allowing for the effective use of such data and efficient learning. In contrast to the conventional DETR, this model demonstrates its capability to be trained effectively with smaller datasets and achieves rapid convergence. When it comes to classification, it notably diminishes computational demands, scaling down by approximately 6.75 times in comparison to ViT-Base, all the while maintaining an accuracy margin of within ±3%. Additionally, even in cases where sensor positions may exhibit slight misalignment due to variations in data input for object detection, it manages to yield consistent results, unfazed by the differences in the field of view taken into consideration. The proposed model is named Stairwave and is characterized by a parallel structure that retains a staircase-like form.
{"title":"StairWave Transformer: For Fast Utilization of Recognition Function in Various Unmanned Vehicles","authors":"Donggyu Choi, Chang-eun Lee, Jaeuk Baek, Seungwon Do, Sungwoo Jun, Kwang-yong Kim, Young-guk Ha","doi":"10.3390/machines11121068","DOIUrl":"https://doi.org/10.3390/machines11121068","url":null,"abstract":"Newly introduced vehicles come with various added functions, each time utilizing data from different sensors. One prominent related function is autonomous driving, which is performed in cooperation with multiple sensors. These sensors mainly include image sensors, depth sensors, and infrared detection technology for nighttime use, and they mostly generate data based on image processing methods. In this paper, we propose a model that utilizes a parallel transformer design to gradually reduce the size of input data in a manner similar to a stairway, allowing for the effective use of such data and efficient learning. In contrast to the conventional DETR, this model demonstrates its capability to be trained effectively with smaller datasets and achieves rapid convergence. When it comes to classification, it notably diminishes computational demands, scaling down by approximately 6.75 times in comparison to ViT-Base, all the while maintaining an accuracy margin of within ±3%. Additionally, even in cases where sensor positions may exhibit slight misalignment due to variations in data input for object detection, it manages to yield consistent results, unfazed by the differences in the field of view taken into consideration. The proposed model is named Stairwave and is characterized by a parallel structure that retains a staircase-like form.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"29 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138604240","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}
Pub Date : 2023-12-04DOI: 10.3390/machines11121067
Ignacio Laraudogoitia Blanc, Christian Hamm, Maider García de Cortázar, Nils Kaiser, Oleksander Savysko, Franck Andrés Girot Mata
A comparative study is presented, focusing on three different bioinspired design methodologies applied to a large-scale aeronautical tooling use case. The study aims to optimize the structure in terms of the first vibration mode, minimizing mass, and supporting operational loads. The development of lightweight metallic components is of great importance for industries such as aerospace, automotive, and energy harvesting, where weight reduction can lead to significant improvements in performance, efficiency, and sustainability. Bioinspired design offers a promising approach to achieving these goals. The study begins with an introduction to natural selection and various bioinspired concepts. It proceeds with a thorough review of the selected bioinspired design methodologies and tools, which are then applied to the chosen use case. The outcomes for each methodology were explored with respect to the design requirements. Subsequently, the most suitable design was selected according to the success criteria defined and its validation is explained. The manufacturing of this design was carried out using an advanced and novel approach specifically tailored to accommodate the large dimensions and complexity of the structure. Finally, modal testing was performed to validate the entire process, and the results obtained demonstrate the potential effectiveness of bioinspired design methodologies in achieving lightweighting and optimizing vibration modes for large-scale aeronautical tooling.
{"title":"Bioinspired Design for Lightweighting and Vibration Behavior Optimization in Large-Scale Aeronautical Tooling: A Comparative Study","authors":"Ignacio Laraudogoitia Blanc, Christian Hamm, Maider García de Cortázar, Nils Kaiser, Oleksander Savysko, Franck Andrés Girot Mata","doi":"10.3390/machines11121067","DOIUrl":"https://doi.org/10.3390/machines11121067","url":null,"abstract":"A comparative study is presented, focusing on three different bioinspired design methodologies applied to a large-scale aeronautical tooling use case. The study aims to optimize the structure in terms of the first vibration mode, minimizing mass, and supporting operational loads. The development of lightweight metallic components is of great importance for industries such as aerospace, automotive, and energy harvesting, where weight reduction can lead to significant improvements in performance, efficiency, and sustainability. Bioinspired design offers a promising approach to achieving these goals. The study begins with an introduction to natural selection and various bioinspired concepts. It proceeds with a thorough review of the selected bioinspired design methodologies and tools, which are then applied to the chosen use case. The outcomes for each methodology were explored with respect to the design requirements. Subsequently, the most suitable design was selected according to the success criteria defined and its validation is explained. The manufacturing of this design was carried out using an advanced and novel approach specifically tailored to accommodate the large dimensions and complexity of the structure. Finally, modal testing was performed to validate the entire process, and the results obtained demonstrate the potential effectiveness of bioinspired design methodologies in achieving lightweighting and optimizing vibration modes for large-scale aeronautical tooling.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"61 10","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138604874","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}
Pub Date : 2023-12-01DOI: 10.3390/machines11121065
Axel Coronado-Andrade, Alejandra de la Guerra, Luis Alvarez-Icaza
An observer is proposed for a trapezoidal brushless DC motor composed of a cascade connection of a reduced-order Luenberger observer and a high-order sliding mode (HOSM) differentiator. This configuration can estimate the angular velocity and reconstruct the load torque, key elements for the control of this type of motor, under the mild assumption that the variable load torque and its k-th time derivatives are bounded. The proposed observer was tested on an experimental test bench based on Texas Instruments (TI) High Voltage Digital Motor Control (HVMTR Kit) using a Delfino F28379D micro controller. The results show that the velocity and load torque can be properly estimated, despite the presence of noise in the current measurements.
{"title":"Load Torque Observer for BLDC Motors Based on a HOSM Differentiator","authors":"Axel Coronado-Andrade, Alejandra de la Guerra, Luis Alvarez-Icaza","doi":"10.3390/machines11121065","DOIUrl":"https://doi.org/10.3390/machines11121065","url":null,"abstract":"An observer is proposed for a trapezoidal brushless DC motor composed of a cascade connection of a reduced-order Luenberger observer and a high-order sliding mode (HOSM) differentiator. This configuration can estimate the angular velocity and reconstruct the load torque, key elements for the control of this type of motor, under the mild assumption that the variable load torque and its k-th time derivatives are bounded. The proposed observer was tested on an experimental test bench based on Texas Instruments (TI) High Voltage Digital Motor Control (HVMTR Kit) using a Delfino F28379D micro controller. The results show that the velocity and load torque can be properly estimated, despite the presence of noise in the current measurements.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"3 1‐6","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138624459","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}
Pub Date : 2023-12-01DOI: 10.3390/machines11121066
Zhengping Ding, Yingcheng Xu, Kai Zhong
Local Fisher discriminant analysis (LFDA) has been widely applied to dimensionality reduction and fault classification fields. However, it often suffers from small sample size (SSS) problem and incorporates all process variables without emphasizing the key faulty ones, thus leading to degraded fault diagnosis performance and poor model interpretability. To this end, this paper develops the sparse variables selection based exponential local Fisher discriminant analysis (SELFDA) model, which can overcome the two limitations of basic LFDA concurrently. First, the responsible faulty variables are identified automatically through the least absolute shrinkage and selection operator, and the current optimization problem are subsequently recast as an iterative convex optimization problem and solved by the minimization-maximization method. After that, the matrix exponential strategy is implemented on LFDA, it can essentially overcome the SSS problem by ensuring that the within-class scatter matrix is always full-rank, thus more practical in real industrial practices, and the margin between different categories is enlarged due to the distance diffusion mapping, which is benefit for the enhancement of classification accuracy. Finally, the Tennessee Eastman process and a real-world diesel working process are employed to validate the proposed SELFDA method, experimental results prove that the SELFDA framework is more excellent than the other approaches.
{"title":"Exponential Local Fisher Discriminant Analysis with Sparse Variables Selection: A Novel Fault Diagnosis Scheme for Industry Application","authors":"Zhengping Ding, Yingcheng Xu, Kai Zhong","doi":"10.3390/machines11121066","DOIUrl":"https://doi.org/10.3390/machines11121066","url":null,"abstract":"Local Fisher discriminant analysis (LFDA) has been widely applied to dimensionality reduction and fault classification fields. However, it often suffers from small sample size (SSS) problem and incorporates all process variables without emphasizing the key faulty ones, thus leading to degraded fault diagnosis performance and poor model interpretability. To this end, this paper develops the sparse variables selection based exponential local Fisher discriminant analysis (SELFDA) model, which can overcome the two limitations of basic LFDA concurrently. First, the responsible faulty variables are identified automatically through the least absolute shrinkage and selection operator, and the current optimization problem are subsequently recast as an iterative convex optimization problem and solved by the minimization-maximization method. After that, the matrix exponential strategy is implemented on LFDA, it can essentially overcome the SSS problem by ensuring that the within-class scatter matrix is always full-rank, thus more practical in real industrial practices, and the margin between different categories is enlarged due to the distance diffusion mapping, which is benefit for the enhancement of classification accuracy. Finally, the Tennessee Eastman process and a real-world diesel working process are employed to validate the proposed SELFDA method, experimental results prove that the SELFDA framework is more excellent than the other approaches.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"52 8","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138626884","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}
Pub Date : 2023-11-30DOI: 10.3390/machines11121063
Trung-Kien Hoang, Lionel Vido, Celia Tchuanlong
This article investigates the comparison between two configurations of 20 MW offshore synchronous wind generators using ferrite and rare-earth permanent magnets. The optimization-based comparison concerns the torque ripple and active mass, which are two crucial criteria for offshore wind generators. Both generators adopt surface-mounted permanent magnet type with direct-drive technology to avoid problems associated with the gearboxes. The result shows that at the full-load condition, the ferrite permanent magnet generator can reduce the torque ripple to as much as 0.12%, while the rare-earth counterpart can be about 2.5 times lighter than the former one.
{"title":"Torque Ripple and Mass Comparison between 20 MW Rare-Earth and Ferrite Permanent Magnet Wind Generators","authors":"Trung-Kien Hoang, Lionel Vido, Celia Tchuanlong","doi":"10.3390/machines11121063","DOIUrl":"https://doi.org/10.3390/machines11121063","url":null,"abstract":"This article investigates the comparison between two configurations of 20 MW offshore synchronous wind generators using ferrite and rare-earth permanent magnets. The optimization-based comparison concerns the torque ripple and active mass, which are two crucial criteria for offshore wind generators. Both generators adopt surface-mounted permanent magnet type with direct-drive technology to avoid problems associated with the gearboxes. The result shows that at the full-load condition, the ferrite permanent magnet generator can reduce the torque ripple to as much as 0.12%, while the rare-earth counterpart can be about 2.5 times lighter than the former one.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"136 ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139204854","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}
Pub Date : 2023-11-30DOI: 10.3390/machines11121064
Tsvetan Zhivkov, Elizabeth Sklar, Duncan Botting, Simon Pearson
Global food security is a critical issue today, strained by a wide range of factors including global warming, carbon emissions, sociopolitical and economic challenges, traditional workforce decline and population growth. Technical innovations that address food security, like agricultural robotics, are gaining traction in industry settings, moving from controlled labs and experimental test facilities to real-world environments. Such technologies require sufficient network infrastructure to support in-field operations; thus, there is increased urgency to establish reliable, high-speed wireless communication networking solutions that enable deployment of autonomous agri-robots. The work presented here includes two contributions at the intersection of network infrastructure and in-field agricultural robotics. First, the physical performance of a private 5G-SA system in an agri-robotics application is evaluated and in-field experimental results are presented. These results are compared (using the same experimental setup) against public 4G and private WiFi6 (a newly emerging wireless communication standard). Second, a simulated experiment was performed to assess the “real-time” operational delay in critical tasks that may require quick turnaround between in-field robot and off-board processing. The results demonstrate that public 4G cannot be used in the agricultural domain for applications that require high throughput and reliable communication; that private 5G-SA greatly outperforms public 4G in all performance metrics (as expected); and that private WiFi6, though limited in range, is a fast and very reliable alternative in specific settings. While a single wireless solution does not currently exist for the agricultural domain, multiple technologies can be combined in a hybrid solution that meets the communications requirements.
{"title":"5G on the Farm: Evaluating Wireless Network Capabilities and Needs for Agricultural Robotics","authors":"Tsvetan Zhivkov, Elizabeth Sklar, Duncan Botting, Simon Pearson","doi":"10.3390/machines11121064","DOIUrl":"https://doi.org/10.3390/machines11121064","url":null,"abstract":"Global food security is a critical issue today, strained by a wide range of factors including global warming, carbon emissions, sociopolitical and economic challenges, traditional workforce decline and population growth. Technical innovations that address food security, like agricultural robotics, are gaining traction in industry settings, moving from controlled labs and experimental test facilities to real-world environments. Such technologies require sufficient network infrastructure to support in-field operations; thus, there is increased urgency to establish reliable, high-speed wireless communication networking solutions that enable deployment of autonomous agri-robots. The work presented here includes two contributions at the intersection of network infrastructure and in-field agricultural robotics. First, the physical performance of a private 5G-SA system in an agri-robotics application is evaluated and in-field experimental results are presented. These results are compared (using the same experimental setup) against public 4G and private WiFi6 (a newly emerging wireless communication standard). Second, a simulated experiment was performed to assess the “real-time” operational delay in critical tasks that may require quick turnaround between in-field robot and off-board processing. The results demonstrate that public 4G cannot be used in the agricultural domain for applications that require high throughput and reliable communication; that private 5G-SA greatly outperforms public 4G in all performance metrics (as expected); and that private WiFi6, though limited in range, is a fast and very reliable alternative in specific settings. While a single wireless solution does not currently exist for the agricultural domain, multiple technologies can be combined in a hybrid solution that meets the communications requirements.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"33 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139196674","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}
Pub Date : 2023-11-29DOI: 10.3390/machines11121060
M. Garrosa, M. Ceccarelli, Vicente Díaz, Matteo Russo
This paper presents an analysis of the risk of neck injury in vehicle occupants as a consequence of an impact. A review of the formulation of indexes that are used in the assessment and investigation of neck injury risk is discussed with the aim of providing a new, more appropriate index using suitable sensorized equipment. An experimental analysis is proposed with a new driver monitoring device using low-cost sensors. The system consists of wearable units for the head, neck, and torso where inertial measurement sensors (IMU) are installed to record data concerning the occupant’s head, neck, and torso accelerations while the vehicle moves. Two laser infrared distance sensors are also installed on the vehicle’s steering wheel to record the position data of the head and neck, as well as an additional IMU for vehicle acceleration values. To validate both the device and the new index, experiments are designed in which different sensorized volunteers reproduce an emergency braking maneuver with an instrumented vehicle at speeds of 10, 20, and 30 km/h before the beginning of any braking action. The neck is particularly sensitive to sudden changes in acceleration, so a sudden braking maneuver is enough to constitute a potential risk of cervical spine injury. During the experiments, large accelerations and displacements were recorded as the test speed increased. The largest accelerations were obtained in the experimental test at a speed of 30 km/h with values of 19.17, 9.57, 9.28, and 5.09 m/s2 in the head, torso, neck, and vehicle, respectively. In the same experiment, the largest displacement of the head was 0.33 m and that of the neck was 0.27 m. Experimental results have verified that the designed device can be effectively used to characterize the biomechanical response of the neck in car impacts. The new index is also able to quantify a neck injury risk by taking into account the dynamics of a vehicle and the kinematics of the occupant’s head, neck, and torso. The numerical value of the new index is inversely proportional to the acceleration experienced by the vehicle occupant, so that small values indicate risky conditions.
{"title":"Experimental Validation of a Driver Monitoring System","authors":"M. Garrosa, M. Ceccarelli, Vicente Díaz, Matteo Russo","doi":"10.3390/machines11121060","DOIUrl":"https://doi.org/10.3390/machines11121060","url":null,"abstract":"This paper presents an analysis of the risk of neck injury in vehicle occupants as a consequence of an impact. A review of the formulation of indexes that are used in the assessment and investigation of neck injury risk is discussed with the aim of providing a new, more appropriate index using suitable sensorized equipment. An experimental analysis is proposed with a new driver monitoring device using low-cost sensors. The system consists of wearable units for the head, neck, and torso where inertial measurement sensors (IMU) are installed to record data concerning the occupant’s head, neck, and torso accelerations while the vehicle moves. Two laser infrared distance sensors are also installed on the vehicle’s steering wheel to record the position data of the head and neck, as well as an additional IMU for vehicle acceleration values. To validate both the device and the new index, experiments are designed in which different sensorized volunteers reproduce an emergency braking maneuver with an instrumented vehicle at speeds of 10, 20, and 30 km/h before the beginning of any braking action. The neck is particularly sensitive to sudden changes in acceleration, so a sudden braking maneuver is enough to constitute a potential risk of cervical spine injury. During the experiments, large accelerations and displacements were recorded as the test speed increased. The largest accelerations were obtained in the experimental test at a speed of 30 km/h with values of 19.17, 9.57, 9.28, and 5.09 m/s2 in the head, torso, neck, and vehicle, respectively. In the same experiment, the largest displacement of the head was 0.33 m and that of the neck was 0.27 m. Experimental results have verified that the designed device can be effectively used to characterize the biomechanical response of the neck in car impacts. The new index is also able to quantify a neck injury risk by taking into account the dynamics of a vehicle and the kinematics of the occupant’s head, neck, and torso. The numerical value of the new index is inversely proportional to the acceleration experienced by the vehicle occupant, so that small values indicate risky conditions.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"44 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139212497","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}
Pub Date : 2023-11-29DOI: 10.3390/machines11121059
Mengyuan Zhang, Mark Sutcliffe, P. I. Nicholson, Qingping Yang
Within the domain of robotic non-destructive testing (NDT) of complex structures, the existing methods typically utilise an offline robot-path-planning strategy. Commonly, for robotic inspection, this will involve full coverage of the component. An NDT probe oriented normal to the component surface is deployed in a raster scan pattern. Here, digital models are used, with the user decomposing complex structures into manageable scan path segments, while carefully avoiding obstacles and other geometric features. This is a manual process that requires a highly skilled robotic operator, often taking several hours or days to refine. This introduces several challenges to NDT, including the need for an accurate model of the component (which, for NDT inspection, is often not available), the requirement of skilled personnel, and careful consideration of both the NDT inspection method and the geometric structure of the component. This paper addresses the specific challenge of scanning complex surfaces by using an automated approach. An algorithm is presented, which is able to learn an efficient scan path by taking into account the dimensional constraints of the footprint of an ultrasonic phased-array probe (a common inspection method for NDT) and the surface geometry. The proposed solution harnesses a digital model of the component, which is decomposed into a series of connected nodes representing the NDT inspection points within the NDT process—this step utilises graph theory. The connections to other nodes are determined using nearest neighbour with KD-Tree optimisation to improve the efficiency of node traversal. This enables a trade-off between simplicity and efficiency. Next, movement restrictions are introduced to allow the robot to navigate the surface of a component in a three-dimensional space, defining obstacles as prohibited areas, explicitly. Our solution entails a two-stage planning process, as follows: a modified three-dimensional flood fill is combined with Dijkstra’s shortest path algorithm. The process is repeated iteratively until the entire surface is covered. The efficiency of this proposed approach is evaluated through simulations. The technique presented in this paper provides an improved and automated method for NDT robotic inspection, reducing the requirement of skilled robotic path-planning personnel while ensuring full component coverage.
{"title":"Efficient Autonomous Path Planning for Ultrasonic Non-Destructive Testing: A Graph Theory and K-Dimensional Tree Optimisation Approach","authors":"Mengyuan Zhang, Mark Sutcliffe, P. I. Nicholson, Qingping Yang","doi":"10.3390/machines11121059","DOIUrl":"https://doi.org/10.3390/machines11121059","url":null,"abstract":"Within the domain of robotic non-destructive testing (NDT) of complex structures, the existing methods typically utilise an offline robot-path-planning strategy. Commonly, for robotic inspection, this will involve full coverage of the component. An NDT probe oriented normal to the component surface is deployed in a raster scan pattern. Here, digital models are used, with the user decomposing complex structures into manageable scan path segments, while carefully avoiding obstacles and other geometric features. This is a manual process that requires a highly skilled robotic operator, often taking several hours or days to refine. This introduces several challenges to NDT, including the need for an accurate model of the component (which, for NDT inspection, is often not available), the requirement of skilled personnel, and careful consideration of both the NDT inspection method and the geometric structure of the component. This paper addresses the specific challenge of scanning complex surfaces by using an automated approach. An algorithm is presented, which is able to learn an efficient scan path by taking into account the dimensional constraints of the footprint of an ultrasonic phased-array probe (a common inspection method for NDT) and the surface geometry. The proposed solution harnesses a digital model of the component, which is decomposed into a series of connected nodes representing the NDT inspection points within the NDT process—this step utilises graph theory. The connections to other nodes are determined using nearest neighbour with KD-Tree optimisation to improve the efficiency of node traversal. This enables a trade-off between simplicity and efficiency. Next, movement restrictions are introduced to allow the robot to navigate the surface of a component in a three-dimensional space, defining obstacles as prohibited areas, explicitly. Our solution entails a two-stage planning process, as follows: a modified three-dimensional flood fill is combined with Dijkstra’s shortest path algorithm. The process is repeated iteratively until the entire surface is covered. The efficiency of this proposed approach is evaluated through simulations. The technique presented in this paper provides an improved and automated method for NDT robotic inspection, reducing the requirement of skilled robotic path-planning personnel while ensuring full component coverage.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"58 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139214231","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}
Pub Date : 2023-11-29DOI: 10.3390/machines11121062
S. Iliev, Z. Ivanov, R. Dimitrov, V. Mihaylov, D. Ivanov, Stoyan Stoyanov, Slavena Atanasova
Propanol isomers, which are oxygen-rich fuels, possess superior octane ratings and energy density in comparison to methanol and ethanol. Recently, due to advancements in fermentation techniques, these propanol isomers have garnered increased interest as additives for engines. They are being explored to decrease emissions and reduce the usage of conventional fossil fuels. This study delves into this emerging field. One of the alternatives is the use of alcohol fuels in their pure state or as additives to traditional fuels. Alcohols, due to their higher volumetric energy density, are better fuels for spark ignition engines than hydrogen and biogas. Alcohol-blended fuels or alcohol fuels in their pure state may be used in gasoline engines to reduce exhaust emissions. The current research emphasizes the effect of isopropanol gasoline blends on the performance and emissions characteristics of a gasoline direct injection (GDI) engine. This investigation was conducted with different blends of isopropanol and gasoline (by volume: 10% isopropanol [IP10], 20% isopropanol [IP10], 30% isopropanol [IP30], 40% isopropanol [IP40], and 50% isopropanol [IP50]). The reviewed results showed that with increasing isopropanol in the fuel blends, engine brake power increased while BSFC decreased. In terms of emissions, with the increase in isopropanol in the fuel blends, CO and HC emissions decreased while CO2 and NOx emissions increased.
{"title":"An Experimental Investigation into the Performance and Emission Characteristics of a Gasoline Direct Injection Engine Fueled with Isopropanol Gasoline Blends","authors":"S. Iliev, Z. Ivanov, R. Dimitrov, V. Mihaylov, D. Ivanov, Stoyan Stoyanov, Slavena Atanasova","doi":"10.3390/machines11121062","DOIUrl":"https://doi.org/10.3390/machines11121062","url":null,"abstract":"Propanol isomers, which are oxygen-rich fuels, possess superior octane ratings and energy density in comparison to methanol and ethanol. Recently, due to advancements in fermentation techniques, these propanol isomers have garnered increased interest as additives for engines. They are being explored to decrease emissions and reduce the usage of conventional fossil fuels. This study delves into this emerging field. One of the alternatives is the use of alcohol fuels in their pure state or as additives to traditional fuels. Alcohols, due to their higher volumetric energy density, are better fuels for spark ignition engines than hydrogen and biogas. Alcohol-blended fuels or alcohol fuels in their pure state may be used in gasoline engines to reduce exhaust emissions. The current research emphasizes the effect of isopropanol gasoline blends on the performance and emissions characteristics of a gasoline direct injection (GDI) engine. This investigation was conducted with different blends of isopropanol and gasoline (by volume: 10% isopropanol [IP10], 20% isopropanol [IP10], 30% isopropanol [IP30], 40% isopropanol [IP40], and 50% isopropanol [IP50]). The reviewed results showed that with increasing isopropanol in the fuel blends, engine brake power increased while BSFC decreased. In terms of emissions, with the increase in isopropanol in the fuel blends, CO and HC emissions decreased while CO2 and NOx emissions increased.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"24 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139210241","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}
Motor faults not only damage the motor body but also affect the entire production system. When the motor runs in a steady state, the characteristic frequency of the fault current is close to the fundamental frequency, so it is difficult to effectively extract the fault current components, such as the broken rotor bar. In this paper, according to the characteristics of electromagnetic force and vibration, when the rotor eccentricity and the broken bar occur, the vibration signal is used to analyze and diagnose the fault. Firstly, the frequency, order, and amplitude characteristics of electromagnetic force under rotor eccentricity and broken bar fault are analyzed. Then, the fault vibration acceleration value collected by a one-dimensional dilated convolution pair is extracted, and the SeLU activation function and residual connection are introduced to solve the problem of gradient disappearance and network degradation, and the fault motor model is established by combining average ensemble learning and SoftMax multi-classifier. Finally, experiments of normal rotor eccentricity and broken bar faults are carried out on 4-pole asynchronous motors. The experimental results show that the accuracy of the proposed method for motor fault detection can reach 99%, which meets the requirements of fault motor detection and is helpful for further application.
电机故障不仅会损坏电机本体，还会影响整个生产系统。电机在稳定状态下运行时，故障电流的特征频率接近基频，因此很难有效提取故障电流成分，如转子断棒等。本文根据电磁力和振动的特点，在转子偏心和断条发生时，利用振动信号对故障进行分析和诊断。首先，分析转子偏心和断杆故障下电磁力的频率、阶次和振幅特征。然后，提取一维扩张卷积对采集的故障振动加速度值，引入 SeLU 激活函数和残差连接解决梯度消失和网络退化问题，并结合平均集合学习和 SoftMax 多分类器建立故障电机模型。最后，在 4 极异步电机上进行了正常转子偏心和断条故障的实验。实验结果表明，所提出的电机故障检测方法的准确率可达 99%，满足了电机故障检测的要求，有助于进一步的应用。
{"title":"Vibration Analysis for Fault Diagnosis in Induction Motors Using One-Dimensional Dilated Convolutional Neural Networks","authors":"Xiaopeng Liu, Jianfeng Hong, Kang Zhao, Bingxiang Sun, Weige Zhang, Jiuchun Jiang","doi":"10.3390/machines11121061","DOIUrl":"https://doi.org/10.3390/machines11121061","url":null,"abstract":"Motor faults not only damage the motor body but also affect the entire production system. When the motor runs in a steady state, the characteristic frequency of the fault current is close to the fundamental frequency, so it is difficult to effectively extract the fault current components, such as the broken rotor bar. In this paper, according to the characteristics of electromagnetic force and vibration, when the rotor eccentricity and the broken bar occur, the vibration signal is used to analyze and diagnose the fault. Firstly, the frequency, order, and amplitude characteristics of electromagnetic force under rotor eccentricity and broken bar fault are analyzed. Then, the fault vibration acceleration value collected by a one-dimensional dilated convolution pair is extracted, and the SeLU activation function and residual connection are introduced to solve the problem of gradient disappearance and network degradation, and the fault motor model is established by combining average ensemble learning and SoftMax multi-classifier. Finally, experiments of normal rotor eccentricity and broken bar faults are carried out on 4-pole asynchronous motors. The experimental results show that the accuracy of the proposed method for motor fault detection can reach 99%, which meets the requirements of fault motor detection and is helpful for further application.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139211460","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}
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