Malhar Khan, Muhammad Amir Raza, Muhammed Faheem, Shahjahan Alias Sarang, Madeeha Panhwar, T. Jumani
The increasing global need for renewable energy sources, driven by environmental concerns and the limited availability of traditional energy, highlights the significance of solar energy. However, weather fluctuations challenge the efficiency of solar systems, making maximum power point tracking (MPPT) systems crucial for optimal energy harvesting. This study compares ten MPPT approaches, including both conventional and artificial intelligence (AI)‐based techniques. These controllers were designed and implemented using MATLAB Simulink, and their performance was evaluated under real environmental conditions with fluctuating irradiance and temperature. The results demonstrate that conventional techniques, such as incremental conductance (INC), Perturb and Observe (P&O), Incremental conductance and Particle Swam Optimization (INC‐PSO), Fuzzy Logic Control and Particle Swam Optimization (FLC‐PSO), and Perturb and Observe and Particle Swam Optimization (P&O‐PSO), achieved accuracies of 94%, 97.6%, 98.9%, 98.7%, and 99.3% respectively. In contrast, AI‐based intelligent techniques, including Artificial Neural Network (ANN), Artificial Neural Fuzzy Interference System (ANFIS), Fuzzy Logic Control (FLC), Particle Swam Optimization (PSO), and Artificial Neural Network and Particle Swam Optimization (ANN‐PSO), outperform achieving higher accuracies of 97.8%, 99.9%, 98.9%, 99.2%, and 99%, respectively. Compared to available research, which often reports lower accuracies for conventional techniques, our study highlights the enhanced performance of AI‐based methods. This study provides a comprehensive comparative analysis, delivering critical analysis and practical guidance for engineers and researchers in selecting the most effective MPPT controller optimized to specific environmental conditions. By improving the efficiency and reliability of solar power systems, our research supports the advancement of sustainable energy solutions.
{"title":"Conventional and artificial intelligence based maximum power point tracking techniques for efficient solar power generation","authors":"Malhar Khan, Muhammad Amir Raza, Muhammed Faheem, Shahjahan Alias Sarang, Madeeha Panhwar, T. Jumani","doi":"10.1002/eng2.12963","DOIUrl":"https://doi.org/10.1002/eng2.12963","url":null,"abstract":"The increasing global need for renewable energy sources, driven by environmental concerns and the limited availability of traditional energy, highlights the significance of solar energy. However, weather fluctuations challenge the efficiency of solar systems, making maximum power point tracking (MPPT) systems crucial for optimal energy harvesting. This study compares ten MPPT approaches, including both conventional and artificial intelligence (AI)‐based techniques. These controllers were designed and implemented using MATLAB Simulink, and their performance was evaluated under real environmental conditions with fluctuating irradiance and temperature. The results demonstrate that conventional techniques, such as incremental conductance (INC), Perturb and Observe (P&O), Incremental conductance and Particle Swam Optimization (INC‐PSO), Fuzzy Logic Control and Particle Swam Optimization (FLC‐PSO), and Perturb and Observe and Particle Swam Optimization (P&O‐PSO), achieved accuracies of 94%, 97.6%, 98.9%, 98.7%, and 99.3% respectively. In contrast, AI‐based intelligent techniques, including Artificial Neural Network (ANN), Artificial Neural Fuzzy Interference System (ANFIS), Fuzzy Logic Control (FLC), Particle Swam Optimization (PSO), and Artificial Neural Network and Particle Swam Optimization (ANN‐PSO), outperform achieving higher accuracies of 97.8%, 99.9%, 98.9%, 99.2%, and 99%, respectively. Compared to available research, which often reports lower accuracies for conventional techniques, our study highlights the enhanced performance of AI‐based methods. This study provides a comprehensive comparative analysis, delivering critical analysis and practical guidance for engineers and researchers in selecting the most effective MPPT controller optimized to specific environmental conditions. By improving the efficiency and reliability of solar power systems, our research supports the advancement of sustainable energy solutions.","PeriodicalId":502604,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646529","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}
To address the optimal solution problem of loop‐free paths in software‐defined optical networks with multiple complex logical relationships, a unified constraint expression is utilized to describe the constraints. The logical relationships of complex constraints are dissected and simplified, differentiating between “AND” and “OR” constraints. An optimal path calculation method is proposed, involving the transformation of the network topology based on various constraints. This transformation includes layering the topology, removing specific links, and adding necessary links to portray the different complex constraints onto the original network structure. Following the topology transformation, an enhanced K‐shortest path algorithm is employed to compute the route satisfying the combination of multiple complex constraints, resulting in the global optimal solution. Experimental results demonstrate that this method can determine the optimal path under intricate constraints in a single computational iteration without requiring prior knowledge of the optimal constraint sequence. Therefore, it offers significant practical value compared to existing algorithms.
为了解决具有多种复杂逻辑关系的软件定义光网络中无环路路径的最优解问题，我们采用了统一的约束表达式来描述约束。通过区分 "AND "和 "OR "约束，对复杂约束的逻辑关系进行了剖析和简化。提出了一种最优路径计算方法，涉及根据各种约束条件对网络拓扑结构进行转换。这种转换包括拓扑分层、移除特定链接和添加必要链接，以便在原始网络结构上描绘不同的复杂约束条件。拓扑改造后，采用增强型 K 最短路径算法计算满足多个复杂约束条件组合的路由，从而得出全局最优解。实验结果表明，这种方法可以在一次计算迭代中确定复杂约束条件下的最优路径，而无需事先了解最优约束序列。因此，与现有算法相比，它具有重要的实用价值。
{"title":"Optimal path calculation method of optical network under complex constraints","authors":"Peng Zhu, Hong Sun, Qian Xiang, Zhenming Zhang","doi":"10.1002/eng2.12962","DOIUrl":"https://doi.org/10.1002/eng2.12962","url":null,"abstract":"To address the optimal solution problem of loop‐free paths in software‐defined optical networks with multiple complex logical relationships, a unified constraint expression is utilized to describe the constraints. The logical relationships of complex constraints are dissected and simplified, differentiating between “AND” and “OR” constraints. An optimal path calculation method is proposed, involving the transformation of the network topology based on various constraints. This transformation includes layering the topology, removing specific links, and adding necessary links to portray the different complex constraints onto the original network structure. Following the topology transformation, an enhanced K‐shortest path algorithm is employed to compute the route satisfying the combination of multiple complex constraints, resulting in the global optimal solution. Experimental results demonstrate that this method can determine the optimal path under intricate constraints in a single computational iteration without requiring prior knowledge of the optimal constraint sequence. Therefore, it offers significant practical value compared to existing algorithms.","PeriodicalId":502604,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141664678","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}
The perception of unmanned surface vehicles is significantly influenced by the detection of navigable areas in narrow rivers. Conventional semantic segmentation networks are unable to resolve the numerous interferences on the water's surface, including highlights and inverted images. To solve this problem, a river surface image reflection removal generative adversarial network (RRGAN) is proposed to eliminate the interference of harsh water surface environment. The proposed RRGAN only uses a single generator to reduce the number of parameters. By adding AdaLIN layers in the generator to enhance the ability to generate low‐reflection images, the AdaLIN encoder (AdaLINE) is proposed to automatically generate normalized affine parameters. In addition, a cycle semantic consistency loss function with a single generator is proposed to ensure that the water region of the generated images remains unchanged. Finally, a two‐stage method for detecting navigable areas is proposed. In the first stage, the RRGAN is used to remove the interference on the water surface environment. In the second stage, the semantic segmentation network is used to segment the water body from the denoised image to determine the navigable areas on the water surface. The experimental results demonstrate that, in the complex and varied narrow river environment, the suggested RRGAN method can significantly reduce the reflection interference of the water surface and improve the accuracy of the water segmentation after the reflection is removed.
{"title":"A method for detecting navigable areas in narrow rivers under complex reflection conditions","authors":"Kai Zhang, Min Hu, Daoyang Yu, Yanwei Bao","doi":"10.1002/eng2.12959","DOIUrl":"https://doi.org/10.1002/eng2.12959","url":null,"abstract":"The perception of unmanned surface vehicles is significantly influenced by the detection of navigable areas in narrow rivers. Conventional semantic segmentation networks are unable to resolve the numerous interferences on the water's surface, including highlights and inverted images. To solve this problem, a river surface image reflection removal generative adversarial network (RRGAN) is proposed to eliminate the interference of harsh water surface environment. The proposed RRGAN only uses a single generator to reduce the number of parameters. By adding AdaLIN layers in the generator to enhance the ability to generate low‐reflection images, the AdaLIN encoder (AdaLINE) is proposed to automatically generate normalized affine parameters. In addition, a cycle semantic consistency loss function with a single generator is proposed to ensure that the water region of the generated images remains unchanged. Finally, a two‐stage method for detecting navigable areas is proposed. In the first stage, the RRGAN is used to remove the interference on the water surface environment. In the second stage, the semantic segmentation network is used to segment the water body from the denoised image to determine the navigable areas on the water surface. The experimental results demonstrate that, in the complex and varied narrow river environment, the suggested RRGAN method can significantly reduce the reflection interference of the water surface and improve the accuracy of the water segmentation after the reflection is removed.","PeriodicalId":502604,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141670347","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}
Jesús Eduardo Rodríguez-Gutiérrez, Brenda Ríos‐Fuentes, José Luis Altamirano‐Corona, A. Estrada-Baltazar, L. F. Fuentes-Cortés
This work addresses the multi‐objective design of water, energy and food supply systems in isolated rural communities using local resources. The approach used considers objective functions based on life cycle analysis such as water and carbon footprint, as well as economic performance considering the application and integration of normalized metrics to address the water‐energy‐environment‐food nexus. The results show that it is possible to build robust and accessible metrics for the analysis of problems with various design objective functions in decision‐making environments. The optimization problem considers decision variables associated with the sizing of units such as photovoltaic panels, wind turbines, thermal and electrical energy storage, wood‐fired boilers and the integration of food production systems involving aquaculture and local corn production. Water management is associated with domestic activities and crop irrigation.
{"title":"Multi‐objective assessment of the water‐energy‐environment‐food nexus involving a life cycle assessment approach","authors":"Jesús Eduardo Rodríguez-Gutiérrez, Brenda Ríos‐Fuentes, José Luis Altamirano‐Corona, A. Estrada-Baltazar, L. F. Fuentes-Cortés","doi":"10.1002/eng2.12957","DOIUrl":"https://doi.org/10.1002/eng2.12957","url":null,"abstract":"This work addresses the multi‐objective design of water, energy and food supply systems in isolated rural communities using local resources. The approach used considers objective functions based on life cycle analysis such as water and carbon footprint, as well as economic performance considering the application and integration of normalized metrics to address the water‐energy‐environment‐food nexus. The results show that it is possible to build robust and accessible metrics for the analysis of problems with various design objective functions in decision‐making environments. The optimization problem considers decision variables associated with the sizing of units such as photovoltaic panels, wind turbines, thermal and electrical energy storage, wood‐fired boilers and the integration of food production systems involving aquaculture and local corn production. Water management is associated with domestic activities and crop irrigation.","PeriodicalId":502604,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141670639","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}
Yongling Chen, Hu Yang, Chun Zhan, Wei Zhang, Jia Wang, Dan Xie, Wei Wei, Ciren Lamu
Yangshan gold belt (YSGB) in Gansu Province is a super‐large orogenic gold deposit located in the middle section of the Mianxian‐Lueyang arcuate suture zone (Mian‐Lue suture zone). The YSGB is mainly divided into the Gejiaowan, Anba, and Gaoloushan mine sections. The ore veins are strictly controlled by strong strain zones in the fracture zone and secondary fractures superimposed on the inherited activity and are vein‐like in general and lenticular in localities. For a long time, there have been different understandings regarding its ore‐controlling factors and mineral genesis. By utilizing controlled‐source audio‐frequency magnetotellurics (CSAMT) technology to conduct electrical characteristic studies, the deep electrical structural characteristics of the Gaoloushan section are identified, and a tectonically‐controlled geoelectric model of the deposit is established, which provides geophysical evidence for the view that the Yangshan gold mine is a tectonically‐controlled low‐temperature hydrothermal deposit in altered rock, guiding the arrangement of exploration work and identifying prospective mining areas, and thereby providing a geophysical exploration paradigm for deep exploration of large orogenic gold deposits.
{"title":"Mineralization based on CSAMT data: A case study on the Gaoloushan section of Yangshan gold belt","authors":"Yongling Chen, Hu Yang, Chun Zhan, Wei Zhang, Jia Wang, Dan Xie, Wei Wei, Ciren Lamu","doi":"10.1002/eng2.12961","DOIUrl":"https://doi.org/10.1002/eng2.12961","url":null,"abstract":"Yangshan gold belt (YSGB) in Gansu Province is a super‐large orogenic gold deposit located in the middle section of the Mianxian‐Lueyang arcuate suture zone (Mian‐Lue suture zone). The YSGB is mainly divided into the Gejiaowan, Anba, and Gaoloushan mine sections. The ore veins are strictly controlled by strong strain zones in the fracture zone and secondary fractures superimposed on the inherited activity and are vein‐like in general and lenticular in localities. For a long time, there have been different understandings regarding its ore‐controlling factors and mineral genesis. By utilizing controlled‐source audio‐frequency magnetotellurics (CSAMT) technology to conduct electrical characteristic studies, the deep electrical structural characteristics of the Gaoloushan section are identified, and a tectonically‐controlled geoelectric model of the deposit is established, which provides geophysical evidence for the view that the Yangshan gold mine is a tectonically‐controlled low‐temperature hydrothermal deposit in altered rock, guiding the arrangement of exploration work and identifying prospective mining areas, and thereby providing a geophysical exploration paradigm for deep exploration of large orogenic gold deposits.","PeriodicalId":502604,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141671610","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}
Maintenance manuals are crucial information sources for maintenance and repair. Prior studies explored factual knowledge extraction from textual documents. However, maintenance knowledge in manuals is more task‐centric rather than factual knowledge and often documented in an unstructured Portable Document Format (PDF), posing challenges for knowledge extraction. Addressing this, this research develops effective methods to extract task‐centric maintenance knowledge from unstructured PDF manuals. A new Task‐centric Knowledge Graph (TCKG) schema centralized on maintenance task components (MTCs) is proposed to address the need for structured knowledge representation. A method (Heterogeneous Graph‐based Method, HGM) for knowledge extraction is then proposed, which is enhanced by incorporating visual and spatial information. In the experiments, the proposed HGM exhibits robust performance in the knowledge extraction process, surpassing the baseline Graph‐based Interaction Model with a Tracker (GIT) method in MTCs extraction by 13.3%, and the baseline Translate Embedding (TransE) method in MTCs' relation extraction by 3.8%. A series of ablation studies also prove that including visual and spatial information through the proposed method can improve the relation extraction performance by over 10%. This research supplies valuable insights for future developments in information extraction from maintenance manuals.
{"title":"A task‐centric knowledge graph construction method based on multi‐modal representation learning for industrial maintenance automation","authors":"Zengkun Liu, Yuqian Lu","doi":"10.1002/eng2.12952","DOIUrl":"https://doi.org/10.1002/eng2.12952","url":null,"abstract":"Maintenance manuals are crucial information sources for maintenance and repair. Prior studies explored factual knowledge extraction from textual documents. However, maintenance knowledge in manuals is more task‐centric rather than factual knowledge and often documented in an unstructured Portable Document Format (PDF), posing challenges for knowledge extraction. Addressing this, this research develops effective methods to extract task‐centric maintenance knowledge from unstructured PDF manuals. A new Task‐centric Knowledge Graph (TCKG) schema centralized on maintenance task components (MTCs) is proposed to address the need for structured knowledge representation. A method (Heterogeneous Graph‐based Method, HGM) for knowledge extraction is then proposed, which is enhanced by incorporating visual and spatial information. In the experiments, the proposed HGM exhibits robust performance in the knowledge extraction process, surpassing the baseline Graph‐based Interaction Model with a Tracker (GIT) method in MTCs extraction by 13.3%, and the baseline Translate Embedding (TransE) method in MTCs' relation extraction by 3.8%. A series of ablation studies also prove that including visual and spatial information through the proposed method can improve the relation extraction performance by over 10%. This research supplies valuable insights for future developments in information extraction from maintenance manuals.","PeriodicalId":502604,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141670528","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}
N. A. Tunio, A. Hashmani, Suhail Khokhar, Mohsin Ali Tunio, Muhammed Faheem
Faults in transmission lines cause instability of power system and result in degrading end users sophisticated equipment. Therefore, in case of fault and for the quick restoration of problematic phases, reliable and accurate fault detection and classification techniques are required to categorize the faults in a minimum time. In this work, 500 kV transmission line (Jamshoro‐New Karachi), Sindh, Pakistan has been modeled in MATLAB. The discrete wavelet transform (DWT) has been used to extract features from the transient current signal for different faults in 500 kV transmission line under various parameters such as fault location, fault inception angle, ground resistance and fault resistance and time series data has been obtained for fault classification. Moreover, the temporal convolutional neural network (TCN) is used for fault classification in 500 kV transmission network due to its robust framework. From simulation results, it is found that faults in 500 kV transmission line are classified with 99.9% accuracy. Furthermore, the simulation results of the TCN model compared to bidirectional long short‐term memory (BiLSTM) and Gated Recurrent Unit (GRU) and it has been found that TCN model is capable of classifying faults in 500 kV transmission line with high accuracy due to its ability to handle long receptive field size, less memory requirement and parallel processing due to dilated causal convolutions. Through this work, the meantime to repair of 500 kV transmission line can be reduced.
{"title":"Fault detection and classification in overhead transmission lines through comprehensive feature extraction using temporal convolution neural network","authors":"N. A. Tunio, A. Hashmani, Suhail Khokhar, Mohsin Ali Tunio, Muhammed Faheem","doi":"10.1002/eng2.12950","DOIUrl":"https://doi.org/10.1002/eng2.12950","url":null,"abstract":"Faults in transmission lines cause instability of power system and result in degrading end users sophisticated equipment. Therefore, in case of fault and for the quick restoration of problematic phases, reliable and accurate fault detection and classification techniques are required to categorize the faults in a minimum time. In this work, 500 kV transmission line (Jamshoro‐New Karachi), Sindh, Pakistan has been modeled in MATLAB. The discrete wavelet transform (DWT) has been used to extract features from the transient current signal for different faults in 500 kV transmission line under various parameters such as fault location, fault inception angle, ground resistance and fault resistance and time series data has been obtained for fault classification. Moreover, the temporal convolutional neural network (TCN) is used for fault classification in 500 kV transmission network due to its robust framework. From simulation results, it is found that faults in 500 kV transmission line are classified with 99.9% accuracy. Furthermore, the simulation results of the TCN model compared to bidirectional long short‐term memory (BiLSTM) and Gated Recurrent Unit (GRU) and it has been found that TCN model is capable of classifying faults in 500 kV transmission line with high accuracy due to its ability to handle long receptive field size, less memory requirement and parallel processing due to dilated causal convolutions. Through this work, the meantime to repair of 500 kV transmission line can be reduced.","PeriodicalId":502604,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141706937","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}
To solve the problem of optical path difference velocity (OPDV) stability in the Fourier spectrometer, a Cerebellar Model Articulation Controller‐Proportional‐Integral‐Derivative (CMAC‐PID) composite control strategy is proposed. The relationship between the angular velocity of the rotary‐type voice coil motor (RT‐VCM) and the OPDV was studied, along with a mathematical model of the parallel rotating mirror interferometer system. CMAC‐PID is designed and simulated on this basis to suppress the disturbance of nonlinear factors in the system model. The simulation results demonstrate that the steady‐state fluctuation error of the CMAC‐PID controller is 90.1% less than that of the PID controller. The experimental results indicate that compared to the PID controller, the CMAC‐PID controller improves the stability of the OPDV by 1.25%, which means that time‐varying disturbances are effectively suppressed.
{"title":"Modeling and simulation of the control system for the plane mirror rotating interferometer","authors":"Yusheng Qin, Xiang-xian Li, Xin Han, Jingjing Tong, Minguang Gao","doi":"10.1002/eng2.12942","DOIUrl":"https://doi.org/10.1002/eng2.12942","url":null,"abstract":"To solve the problem of optical path difference velocity (OPDV) stability in the Fourier spectrometer, a Cerebellar Model Articulation Controller‐Proportional‐Integral‐Derivative (CMAC‐PID) composite control strategy is proposed. The relationship between the angular velocity of the rotary‐type voice coil motor (RT‐VCM) and the OPDV was studied, along with a mathematical model of the parallel rotating mirror interferometer system. CMAC‐PID is designed and simulated on this basis to suppress the disturbance of nonlinear factors in the system model. The simulation results demonstrate that the steady‐state fluctuation error of the CMAC‐PID controller is 90.1% less than that of the PID controller. The experimental results indicate that compared to the PID controller, the CMAC‐PID controller improves the stability of the OPDV by 1.25%, which means that time‐varying disturbances are effectively suppressed.","PeriodicalId":502604,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141344191","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}
In this study, we investigate the vibration and dynamic stability of a thick rectangular plate that is restrained on four edges by simple clamps. Nonlocal elasticity based on high‐order shear theories is used to model the structure, which takes into account not only shear flow along the thickness, but also different distributions of shear deformations. The inclusion of rotational inertia also significantly impacts the accuracy of the results. The aerodynamic flow on the plate surface is modeled using the linear piston theory, which relates the incoming load from the aerodynamic flow to the transversal deformation of the plate. By utilizing Hamilton's principle, the governing equations for the system are obtained and solved using the weighted residual method. The results are validated by comparing them to previous studies. The effects of various parameters, such as the plate's geometrical properties, the impact of different theories, heat, electric voltage, and nonlocal variables, on the vibration and flutter behavior of the plate are examined. Additionally, it is found that the application of negative voltage increases the critical aerodynamic pressure by creating a traction force, and that a suitable thermal load can avoid instability caused by aerodynamic load. By applying voltage and heat, it is possible to increase the flutter threshold and delay it.
{"title":"Vibration and flutter analysis of piezoelectric plates in an electrothermal field using higher order theories","authors":"Mohammad Javad Khoshgoftar","doi":"10.1002/eng2.12919","DOIUrl":"https://doi.org/10.1002/eng2.12919","url":null,"abstract":"In this study, we investigate the vibration and dynamic stability of a thick rectangular plate that is restrained on four edges by simple clamps. Nonlocal elasticity based on high‐order shear theories is used to model the structure, which takes into account not only shear flow along the thickness, but also different distributions of shear deformations. The inclusion of rotational inertia also significantly impacts the accuracy of the results. The aerodynamic flow on the plate surface is modeled using the linear piston theory, which relates the incoming load from the aerodynamic flow to the transversal deformation of the plate. By utilizing Hamilton's principle, the governing equations for the system are obtained and solved using the weighted residual method. The results are validated by comparing them to previous studies. The effects of various parameters, such as the plate's geometrical properties, the impact of different theories, heat, electric voltage, and nonlocal variables, on the vibration and flutter behavior of the plate are examined. Additionally, it is found that the application of negative voltage increases the critical aerodynamic pressure by creating a traction force, and that a suitable thermal load can avoid instability caused by aerodynamic load. By applying voltage and heat, it is possible to increase the flutter threshold and delay it.","PeriodicalId":502604,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141342581","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}
Izaak Stanton, K. Munir, Ahsan Ikram, Murad El‐Bakry
In the aviation industry, predictive maintenance is vital to minimise Unscheduled faults and maintain the operational availability of aircraft. However, the amount of open data available for research is limited due to the proprietary nature of aircraft data. In this work, six time‐series datasets are synthesised using the DoppelGANger model trained on real Airbus datasets from landing gear systems. The synthesised datasets contain no proprietary information, but maintain the shape and patterns present in the original, making them suitable for testing novel PdM models. They can be used by researchers outside of the industry to explore a more diverse selection of aircraft systems, and the proposed methodology can be replicated by industry data scientists to synthesise and release more data to the public. The results of this study demonstrate the feasibility and effectiveness of using the DoppelGANger model from the Gretel.ai library to generate new time series data that can be used to train predictive maintenance models for industry problems. These synthetic datasets were subject to fidelity testing using six metrics. The six datasets are available on the UWE Library service.
{"title":"Data augmentation for predictive maintenance: Synthesising aircraft landing gear datasets","authors":"Izaak Stanton, K. Munir, Ahsan Ikram, Murad El‐Bakry","doi":"10.1002/eng2.12946","DOIUrl":"https://doi.org/10.1002/eng2.12946","url":null,"abstract":"In the aviation industry, predictive maintenance is vital to minimise Unscheduled faults and maintain the operational availability of aircraft. However, the amount of open data available for research is limited due to the proprietary nature of aircraft data. In this work, six time‐series datasets are synthesised using the DoppelGANger model trained on real Airbus datasets from landing gear systems. The synthesised datasets contain no proprietary information, but maintain the shape and patterns present in the original, making them suitable for testing novel PdM models. They can be used by researchers outside of the industry to explore a more diverse selection of aircraft systems, and the proposed methodology can be replicated by industry data scientists to synthesise and release more data to the public. The results of this study demonstrate the feasibility and effectiveness of using the DoppelGANger model from the Gretel.ai library to generate new time series data that can be used to train predictive maintenance models for industry problems. These synthetic datasets were subject to fidelity testing using six metrics. The six datasets are available on the UWE Library service.","PeriodicalId":502604,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141339483","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}
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