Pub Date : 2023-12-14DOI: 10.3390/machines11121088
Didem Tekgun, B. Tekgun
This research examines how fluid damping loss affects the operation of a two-pole, 5.5 HP (4 kW) induction machine (IM) within the context of different slot opening configurations developed for downhole water pump applications. Since these motors operate with their cavities filled with fluid, the variations in fluid viscosity and density, compared to air, result in the occurrence of damping losses. Furthermore, this loss can be attributed to the motor’s stator and rotor surface geometry, as the liquid within the motor cavity moves unrestrictedly within the motor housing. This study involves the examination of the damping loss in a 24-slot IM under different stator slot indentations. The investigation utilizes computational fluid dynamics (CFD) finite element analysis (FEA) and is subsequently validated through experiments. The aim of this work is to emphasize the significance of fluid damping loss in submerged machines. Results reveal that the damping loss exceeds 8% of the motor output power when the stator surface has indentations, and it diminishes to 3.2% of the output power when a custom wedge structure is employed to eliminate these surface indentations.
{"title":"Investigating the Role of Stator Slot Indents in Minimizing Flooded Motor Fluid Damping Loss","authors":"Didem Tekgun, B. Tekgun","doi":"10.3390/machines11121088","DOIUrl":"https://doi.org/10.3390/machines11121088","url":null,"abstract":"This research examines how fluid damping loss affects the operation of a two-pole, 5.5 HP (4 kW) induction machine (IM) within the context of different slot opening configurations developed for downhole water pump applications. Since these motors operate with their cavities filled with fluid, the variations in fluid viscosity and density, compared to air, result in the occurrence of damping losses. Furthermore, this loss can be attributed to the motor’s stator and rotor surface geometry, as the liquid within the motor cavity moves unrestrictedly within the motor housing. This study involves the examination of the damping loss in a 24-slot IM under different stator slot indentations. The investigation utilizes computational fluid dynamics (CFD) finite element analysis (FEA) and is subsequently validated through experiments. The aim of this work is to emphasize the significance of fluid damping loss in submerged machines. Results reveal that the damping loss exceeds 8% of the motor output power when the stator surface has indentations, and it diminishes to 3.2% of the output power when a custom wedge structure is employed to eliminate these surface indentations.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"6 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138974697","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 : 2023-12-13DOI: 10.3390/machines11121087
Clarisse Lawson-Guidigbe, Kahina Amokrane-Ferka, Nicolas Louveton, Benoit Leblanc, Virgil Rousseaux, Jean-Marc André
The latest advances in car automation present new challenges in vehicle–driver interactions. Indeed, acceptance and adoption of high levels of automation (when full control of the driving task is given to the automated system) are conditioned by human factors such as user trust. In this work, we study the impact of anthropomorphic design on user trust in the context of a highly automated car. A virtual assistant was designed using two levels of anthropomorphic design: “voice-only” and “voice with visual appearance”. The visual appearance was a three-dimensional model, integrated as a hologram in the cockpit of a driving simulator. In a driving simulator study, we compared the three interfaces: two versions of the virtual assistant interface and the baseline interface with no anthropomorphic attributes. We measured trust versus perceived anthropomorphism. We also studied the evolution of trust throughout a range of driving scenarios. We finally analyzed participants’ reaction time to takeover request events. We found a significant correlation between perceived anthropomorphism and trust. However, the three interfaces tested did not significantly differentiate in terms of perceived anthropomorphism while trust converged over time across all our measurements. Finally, we found that the anthropomorphic assistant positively impacts reaction time for one takeover request scenario. We discuss methodological issues and implication for design and further research.
{"title":"Anthropomorphic Design and Self-Reported Behavioral Trust: The Case of a Virtual Assistant in a Highly Automated Car","authors":"Clarisse Lawson-Guidigbe, Kahina Amokrane-Ferka, Nicolas Louveton, Benoit Leblanc, Virgil Rousseaux, Jean-Marc André","doi":"10.3390/machines11121087","DOIUrl":"https://doi.org/10.3390/machines11121087","url":null,"abstract":"The latest advances in car automation present new challenges in vehicle–driver interactions. Indeed, acceptance and adoption of high levels of automation (when full control of the driving task is given to the automated system) are conditioned by human factors such as user trust. In this work, we study the impact of anthropomorphic design on user trust in the context of a highly automated car. A virtual assistant was designed using two levels of anthropomorphic design: “voice-only” and “voice with visual appearance”. The visual appearance was a three-dimensional model, integrated as a hologram in the cockpit of a driving simulator. In a driving simulator study, we compared the three interfaces: two versions of the virtual assistant interface and the baseline interface with no anthropomorphic attributes. We measured trust versus perceived anthropomorphism. We also studied the evolution of trust throughout a range of driving scenarios. We finally analyzed participants’ reaction time to takeover request events. We found a significant correlation between perceived anthropomorphism and trust. However, the three interfaces tested did not significantly differentiate in terms of perceived anthropomorphism while trust converged over time across all our measurements. Finally, we found that the anthropomorphic assistant positively impacts reaction time for one takeover request scenario. We discuss methodological issues and implication for design and further research.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"162 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139006339","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 : 2023-12-13DOI: 10.3390/machines11121085
Silvia Buratti, Davide Deiana, A. Noccaro, Mattia Pinardi, G. di Pino, Domenico Formica, N. Jarrassé
Supernumerary robotic limbs are mainly designed to augment the physical capabilities of able-bodied individuals, in a wide range of contexts from body support to surgery. When they are worn as wearable devices, they naturally provide inherent feedback due to the mechanical coupling with the human body. The user can, thus, perceive the interaction with the environment by relying on a combination of visual and inherent feedback. However, these can be inefficient in accomplishing complex tasks, particularly in the case of visual occlusion or variation in the environment stiffness. Here, we investigated whether, in a force-regulation task using a wearable supernumerary robotic arm (SRA), additional vibrotactile feedback can increase the control performance of participants compared to the inherent feedback. Additionally, to make the scenario more realistic, we introduced variations in the SRA’s kinematic posture and in the environment stiffness. Notably, our findings revealed a statistically significant improvement in user performance over all the evaluated metrics while receiving additional vibrotactile feedback. Compared to inherent feedback alone, the additional vibrotactile feedback allowed participants to exert the required force faster (p < 0.01), to maintain it for longer (p < 0.001), and with lower errors (p < 0.001). No discernible effects related to the SRA’s posture or environment stiffness were observed. These results proved the benefits of providing the user with additional vibrotactile feedback to convey the SRA’s force during interaction tasks.
{"title":"Effect of Vibrotactile Feedback on the Control of the Interaction Force of a Supernumerary Robotic Arm","authors":"Silvia Buratti, Davide Deiana, A. Noccaro, Mattia Pinardi, G. di Pino, Domenico Formica, N. Jarrassé","doi":"10.3390/machines11121085","DOIUrl":"https://doi.org/10.3390/machines11121085","url":null,"abstract":"Supernumerary robotic limbs are mainly designed to augment the physical capabilities of able-bodied individuals, in a wide range of contexts from body support to surgery. When they are worn as wearable devices, they naturally provide inherent feedback due to the mechanical coupling with the human body. The user can, thus, perceive the interaction with the environment by relying on a combination of visual and inherent feedback. However, these can be inefficient in accomplishing complex tasks, particularly in the case of visual occlusion or variation in the environment stiffness. Here, we investigated whether, in a force-regulation task using a wearable supernumerary robotic arm (SRA), additional vibrotactile feedback can increase the control performance of participants compared to the inherent feedback. Additionally, to make the scenario more realistic, we introduced variations in the SRA’s kinematic posture and in the environment stiffness. Notably, our findings revealed a statistically significant improvement in user performance over all the evaluated metrics while receiving additional vibrotactile feedback. Compared to inherent feedback alone, the additional vibrotactile feedback allowed participants to exert the required force faster (p < 0.01), to maintain it for longer (p < 0.001), and with lower errors (p < 0.001). No discernible effects related to the SRA’s posture or environment stiffness were observed. These results proved the benefits of providing the user with additional vibrotactile feedback to convey the SRA’s force during interaction tasks.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"120 13","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139003829","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 : 2023-12-13DOI: 10.3390/machines11121086
S. Vanaei, Mohammadali Rastak, A. El Magri, H. Vanaei, K. Raissi, Abbas Tcharkhtchi
In Additive Manufacturing, wherein the construction of parts directly from 3D models is facilitated, a meticulous focus on enhancing the mechanical characteristics of these components becomes imperative. This study delves into the nuanced impact of the orientation of deposited layers on the mechanical properties of 3D printed Polylactic Acid (PLA) parts. Experimental testing, coupled with predictive modeling using Tsai–Hill and Tsai–Wu criteria, forms the crux of our investigation. The predicted ultimate strength from both criteria exhibits commendable agreement with the 3D printed specimens across a spectrum of orientation angles. Concurrently, Finite Element Simulations are meticulously executed to forecast mechanical behavior, taking into account the observed elasticity and plasticity in various orientations. Our observations reveal a significant augmentation in Young’s modulus and ductility/elongation—40% and 70%, respectively—when transitioning from θ = 0° to θ = 90°. Furthermore, the ultimate strength experiences a notable increase, leading to varied failure modes contingent upon θ. These findings underscore the pivotal role played by the orientation of printed layers in shaping the anisotropic behavior of 3D printed PLA parts, thereby integrating key process variables for optimization objectives. This study contributes valuable insights for professionals in the engineering, design, and manufacturing domains who seek to harness the advantages of 3D printing technology while ensuring that the mechanical integrity of 3D printed parts aligns with their functional requisites. It emphasizes the critical consideration of orientation as a design parameter in the pursuit of optimization objectives.
{"title":"Orientation-Dependent Mechanical Behavior of 3D Printed Polylactic Acid Parts: An Experimental–Numerical Study","authors":"S. Vanaei, Mohammadali Rastak, A. El Magri, H. Vanaei, K. Raissi, Abbas Tcharkhtchi","doi":"10.3390/machines11121086","DOIUrl":"https://doi.org/10.3390/machines11121086","url":null,"abstract":"In Additive Manufacturing, wherein the construction of parts directly from 3D models is facilitated, a meticulous focus on enhancing the mechanical characteristics of these components becomes imperative. This study delves into the nuanced impact of the orientation of deposited layers on the mechanical properties of 3D printed Polylactic Acid (PLA) parts. Experimental testing, coupled with predictive modeling using Tsai–Hill and Tsai–Wu criteria, forms the crux of our investigation. The predicted ultimate strength from both criteria exhibits commendable agreement with the 3D printed specimens across a spectrum of orientation angles. Concurrently, Finite Element Simulations are meticulously executed to forecast mechanical behavior, taking into account the observed elasticity and plasticity in various orientations. Our observations reveal a significant augmentation in Young’s modulus and ductility/elongation—40% and 70%, respectively—when transitioning from θ = 0° to θ = 90°. Furthermore, the ultimate strength experiences a notable increase, leading to varied failure modes contingent upon θ. These findings underscore the pivotal role played by the orientation of printed layers in shaping the anisotropic behavior of 3D printed PLA parts, thereby integrating key process variables for optimization objectives. This study contributes valuable insights for professionals in the engineering, design, and manufacturing domains who seek to harness the advantages of 3D printing technology while ensuring that the mechanical integrity of 3D printed parts aligns with their functional requisites. It emphasizes the critical consideration of orientation as a design parameter in the pursuit of optimization objectives.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"11 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139004751","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 : 2023-12-13DOI: 10.3390/machines11121084
Hui Li, Haiyang Liu, Xianying Feng, Yandong Liu, Ming Yao, Anning Wang
The dual drive sliding feed system can obtain a uniform and stable resolution at extremely low speeds and significantly reduce the system’s nonlinear friction. However, the numerous thermal sources within the system and the multipoint sliding contact during transmission result in a significant temperature rise, leading to considerable thermal deformation and errors. Moreover, the responsive mechanism of the thermal characteristics needs to be clarified. Therefore, firstly, a frictional torque model of the engagement of the screw and nut is established, and the heat generation, heat transfer, and thermal contact resistance (TCR) are solved. Then, based on the solution, a finite element thermal simulation model of the dual drive sliding feed system is established, and experiments are performed for validation. The results show that the error in temperature at the measuring point is less than 2.1 °C, and the axial thermal elongation of the screw is less than 6.2 µm. Finally, the thermal characteristics of the feeding system under various operating conditions are analyzed. The results show that the established thermal simulated model can effectively describe the dynamic thermal characteristics of the dual drive sliding feed system during operation. The effects of the rotational speed and ambient temperature on the dynamic thermal characteristics of the dual drive sliding feed system are investigated separately. The temperature increase in each part of the screw during the operation is characterized.
{"title":"Thermal Model and Thermal Analysis of the Dual Drive Sliding Feed System","authors":"Hui Li, Haiyang Liu, Xianying Feng, Yandong Liu, Ming Yao, Anning Wang","doi":"10.3390/machines11121084","DOIUrl":"https://doi.org/10.3390/machines11121084","url":null,"abstract":"The dual drive sliding feed system can obtain a uniform and stable resolution at extremely low speeds and significantly reduce the system’s nonlinear friction. However, the numerous thermal sources within the system and the multipoint sliding contact during transmission result in a significant temperature rise, leading to considerable thermal deformation and errors. Moreover, the responsive mechanism of the thermal characteristics needs to be clarified. Therefore, firstly, a frictional torque model of the engagement of the screw and nut is established, and the heat generation, heat transfer, and thermal contact resistance (TCR) are solved. Then, based on the solution, a finite element thermal simulation model of the dual drive sliding feed system is established, and experiments are performed for validation. The results show that the error in temperature at the measuring point is less than 2.1 °C, and the axial thermal elongation of the screw is less than 6.2 µm. Finally, the thermal characteristics of the feeding system under various operating conditions are analyzed. The results show that the established thermal simulated model can effectively describe the dynamic thermal characteristics of the dual drive sliding feed system during operation. The effects of the rotational speed and ambient temperature on the dynamic thermal characteristics of the dual drive sliding feed system are investigated separately. The temperature increase in each part of the screw during the operation is characterized.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"134 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139004269","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 : 2023-12-12DOI: 10.3390/machines11121083
Binayak Bhandari, Prakash Manandhar
This paper focuses on the development of an integrated system that can rapidly and accurately extract the geometrical dimensions of a physical object assisted by a robotic hand and generate a 3D model of an object in a popular commercial Computer-Aided Design (CAD) software using computer vision. Two sets of experiments were performed: one with a simple cubical object and the other with a more complex geometry that needed photogrammetry to redraw it in the CAD system. For the accurate positioning of the object, a robotic hand was used. An Internet of Things (IoT) based camera unit was used for capturing the image and wirelessly transmitting it over the network. Computer vision algorithms such as GrabCut, Canny edge detector, and morphological operations were used for extracting border points of the input. The coordinates of the vertices of the solids were then transferred to the Computer-Aided Design (CAD) software via a macro to clean and generate the border curve. Finally, a 3D solid model is generated by linear extrusion based on the curve generated in CATIA. The results showed excellent regeneration of an object. This research makes two significant contributions. Firstly, it introduces an integrated system designed to achieve precise dimension extraction from solid objects. Secondly, it presents a method for regenerating intricate 3D solids with consistent cross-sections. The proposed system holds promise for a wide range of applications, including automatic 3D object reconstruction and quality assurance of 3D-printed objects, addressing potential defects arising from factors such as shrinkage and calibration, all with minimal user intervention.
{"title":"Integrating Computer Vision and CAD for Precise Dimension Extraction and 3D Solid Model Regeneration for Enhanced Quality Assurance","authors":"Binayak Bhandari, Prakash Manandhar","doi":"10.3390/machines11121083","DOIUrl":"https://doi.org/10.3390/machines11121083","url":null,"abstract":"This paper focuses on the development of an integrated system that can rapidly and accurately extract the geometrical dimensions of a physical object assisted by a robotic hand and generate a 3D model of an object in a popular commercial Computer-Aided Design (CAD) software using computer vision. Two sets of experiments were performed: one with a simple cubical object and the other with a more complex geometry that needed photogrammetry to redraw it in the CAD system. For the accurate positioning of the object, a robotic hand was used. An Internet of Things (IoT) based camera unit was used for capturing the image and wirelessly transmitting it over the network. Computer vision algorithms such as GrabCut, Canny edge detector, and morphological operations were used for extracting border points of the input. The coordinates of the vertices of the solids were then transferred to the Computer-Aided Design (CAD) software via a macro to clean and generate the border curve. Finally, a 3D solid model is generated by linear extrusion based on the curve generated in CATIA. The results showed excellent regeneration of an object. This research makes two significant contributions. Firstly, it introduces an integrated system designed to achieve precise dimension extraction from solid objects. Secondly, it presents a method for regenerating intricate 3D solids with consistent cross-sections. The proposed system holds promise for a wide range of applications, including automatic 3D object reconstruction and quality assurance of 3D-printed objects, addressing potential defects arising from factors such as shrinkage and calibration, all with minimal user intervention.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"54 S1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139009706","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 : 2023-12-11DOI: 10.3390/machines11121081
Dairon Pleasant, Connor Gavin, Garrett Redden, Jacquelyn K. S. Nagel, Hao Zhang
This research explores the enhancement of mechanical properties in material architectures, such as strength-to-weight ratio and resilience, through the inspiration of natural systems. Historically, designs for additive manufacturing have relied on simple, repetitive structures like honeycombs, often leading to unnecessary material expenditure. This study aims to examine the compressive mechanical attributes of designs inspired by natural systems, including bird nests, cocoons, and the layered structure of skull bones. Through a comparative analysis, we assessed peak load capacity, strength-to-weight ratio, and resilience between these bioinspired architectures and a standard 3D infill pattern utilized in additive manufacturing. Findings indicate that structures inspired by sandwiched bone layers excel in resilience and peak load, whereas those based on bird nests are notably lighter and, in some cases, exhibit the highest strength-to-weight ratio. The insights provided here will help design engineers with empirically backed mechanical properties of bioinspired architectures, offering a novel methodology for the development of material systems influenced by biological paradigms.
{"title":"Bioinspired Design of Material Architecture for Additive Manufacturing","authors":"Dairon Pleasant, Connor Gavin, Garrett Redden, Jacquelyn K. S. Nagel, Hao Zhang","doi":"10.3390/machines11121081","DOIUrl":"https://doi.org/10.3390/machines11121081","url":null,"abstract":"This research explores the enhancement of mechanical properties in material architectures, such as strength-to-weight ratio and resilience, through the inspiration of natural systems. Historically, designs for additive manufacturing have relied on simple, repetitive structures like honeycombs, often leading to unnecessary material expenditure. This study aims to examine the compressive mechanical attributes of designs inspired by natural systems, including bird nests, cocoons, and the layered structure of skull bones. Through a comparative analysis, we assessed peak load capacity, strength-to-weight ratio, and resilience between these bioinspired architectures and a standard 3D infill pattern utilized in additive manufacturing. Findings indicate that structures inspired by sandwiched bone layers excel in resilience and peak load, whereas those based on bird nests are notably lighter and, in some cases, exhibit the highest strength-to-weight ratio. The insights provided here will help design engineers with empirically backed mechanical properties of bioinspired architectures, offering a novel methodology for the development of material systems influenced by biological paradigms.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"17 10","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138979918","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 : 2023-12-11DOI: 10.3390/machines11121082
E. Brescia, Patrizia Vergallo, Pietro Serafino, Massimo Tipaldi, Davide Cascella, G. L. Cascella, Francesca Romano, Andrea Polichetti
Condition monitoring and fault management approaches can help with timely maintenance planning, assure industry-wide continuous production, and enhance both performance and safety in complex industrial operations. At the moment, data-driven approaches for condition monitoring and fault detection are the most attractive being conceived, developed, and applied with less of a need for sophisticated expertise and detailed knowledge of the addressed plant. Among them, Gaussian mixture model (GMM) methods can offer some advantages. However, conventional GMM solutions need the number of Gaussian components to be defined in advance and suffer from the inability to detect new types of faults and identify new operating modes. To address these issues, this paper presents a novel data-driven method, based on automated GMM (AutoGMM) and decision trees (DTree), for the online condition monitoring of electrical industrial loads. By leveraging the benefits of the AutoGMM and the DTree, after the training phase, the proposed approach allows the clustering and time allocation of nominal operating conditions, the identification of both already-classified and new anomalous conditions, and the acknowledgment of new operating modes of the monitored industrial asset. The proposed method, implemented on a commercial cloud-computing platform, is validated on a real industrial plant with electrical loads, characterized by a daily periodic working cycle, by using active power consumption data.
{"title":"Online Condition Monitoring of Industrial Loads Using AutoGMM and Decision Trees","authors":"E. Brescia, Patrizia Vergallo, Pietro Serafino, Massimo Tipaldi, Davide Cascella, G. L. Cascella, Francesca Romano, Andrea Polichetti","doi":"10.3390/machines11121082","DOIUrl":"https://doi.org/10.3390/machines11121082","url":null,"abstract":"Condition monitoring and fault management approaches can help with timely maintenance planning, assure industry-wide continuous production, and enhance both performance and safety in complex industrial operations. At the moment, data-driven approaches for condition monitoring and fault detection are the most attractive being conceived, developed, and applied with less of a need for sophisticated expertise and detailed knowledge of the addressed plant. Among them, Gaussian mixture model (GMM) methods can offer some advantages. However, conventional GMM solutions need the number of Gaussian components to be defined in advance and suffer from the inability to detect new types of faults and identify new operating modes. To address these issues, this paper presents a novel data-driven method, based on automated GMM (AutoGMM) and decision trees (DTree), for the online condition monitoring of electrical industrial loads. By leveraging the benefits of the AutoGMM and the DTree, after the training phase, the proposed approach allows the clustering and time allocation of nominal operating conditions, the identification of both already-classified and new anomalous conditions, and the acknowledgment of new operating modes of the monitored industrial asset. The proposed method, implemented on a commercial cloud-computing platform, is validated on a real industrial plant with electrical loads, characterized by a daily periodic working cycle, by using active power consumption data.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"15 21","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138980975","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 : 2023-12-11DOI: 10.3390/machines11121080
Andrei S. Maliuk, Zahoor Ahmad, Jong-Myon Kim
This paper proposes a new method for bearing fault diagnosis using wavelet packet transform (WPT)-based signal representation and informative factor linear discriminant analysis (IF-LDA). Time–frequency domain approaches for analyzing bearing vibration signals have gained wide acceptance due to their effectiveness in extracting information related to bearing health. WPT is a prominent method in this category, offering a balanced approach between short-time Fourier transform and empirical mode decomposition. However, the existing methods for bearing fault diagnosis often overlook the limitations of WPT regarding its dependence on the mother wavelet parameters for feature extraction. This work addresses this issue by introducing a novel signal representation method that employs WPT with a new rule for selecting the mother wavelet based on the power spectrum energy-to-entropy ratio of the reconstructed coefficients and a combination of the nodes from different WPT trees. Furthermore, an IF-LDA feature preprocessing technique is proposed, resulting in a highly sensitive set of features for bearing condition assessment. The k-nearest neighbors algorithm is employed as the classifier, and the proposed method is evaluated using datasets from Paderborn and Case Western Reserve universities. The performance of the proposed method demonstrates its effectiveness in bearing fault diagnosis, surpassing existing techniques in terms of fault identification and diagnosis performance.
{"title":"A Technique for Bearing Fault Diagnosis Using Novel Wavelet Packet Transform-Based Signal Representation and Informative Factor LDA","authors":"Andrei S. Maliuk, Zahoor Ahmad, Jong-Myon Kim","doi":"10.3390/machines11121080","DOIUrl":"https://doi.org/10.3390/machines11121080","url":null,"abstract":"This paper proposes a new method for bearing fault diagnosis using wavelet packet transform (WPT)-based signal representation and informative factor linear discriminant analysis (IF-LDA). Time–frequency domain approaches for analyzing bearing vibration signals have gained wide acceptance due to their effectiveness in extracting information related to bearing health. WPT is a prominent method in this category, offering a balanced approach between short-time Fourier transform and empirical mode decomposition. However, the existing methods for bearing fault diagnosis often overlook the limitations of WPT regarding its dependence on the mother wavelet parameters for feature extraction. This work addresses this issue by introducing a novel signal representation method that employs WPT with a new rule for selecting the mother wavelet based on the power spectrum energy-to-entropy ratio of the reconstructed coefficients and a combination of the nodes from different WPT trees. Furthermore, an IF-LDA feature preprocessing technique is proposed, resulting in a highly sensitive set of features for bearing condition assessment. The k-nearest neighbors algorithm is employed as the classifier, and the proposed method is evaluated using datasets from Paderborn and Case Western Reserve universities. The performance of the proposed method demonstrates its effectiveness in bearing fault diagnosis, surpassing existing techniques in terms of fault identification and diagnosis performance.","PeriodicalId":48519,"journal":{"name":"Machines","volume":"30 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139010528","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 : 2023-12-09DOI: 10.3390/machines11121079
Norbert Markó, Ernő Horváth, István Szalay, K. Enisz
In a vehicle, wheel speed sensors and inertial measurement units (IMUs) are present onboard, and their raw data can be used for localization estimation. Both wheel sensors and IMUs encounter challenges such as bias and measurement noise, which accumulate as errors over time. Even a slight inaccuracy or minor error can render the localization system unreliable and unusable in a matter of seconds. Traditional algorithms, such as the extended Kalman filter (EKF), have been applied for a long time in non-linear systems. These systems have white noise in both the system and in the estimation model. These approaches require deep knowledge of the non-linear noise characteristics of the sensors. On the other hand, as a subset of artificial intelligence (AI), neural network-based (NN) algorithms do not necessarily have these strict requirements. The current paper proposes an AI-based long short-term memory (LSTM) localization approach and evaluates its performance against the ground truth.
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