With the improvement of digitalization and intelligence in the power system, the safe operation of the power system is facing enormous challenges. The safe use of electricity on the load side is the key to achieving safe and reliable power system operation. The detection party needs amounts of human and material resources when the power network is attacked. In response to the current difficulties of low detection ability and high detection costs, this paper proposes an attack and defence game model that considers the differences between different nodes, ensuring the safety and economy of electricity consumption while reducing energy waste. At first, the structure of smart meters and the attack characteristics of intruders are summarized, and a basic attack and defence game model is constructed. The Nash equilibrium is then solved, and the optimal strategy for the game between the defender and the intruder is given to balance the relation between detection performance and energy consumption. In response to the differences generated by each node, strategies for attackers to launch attacks on different nodes and the setting of optimal thresholds for other nodes in the defence system are explored. Finally, case studies verify that the proposed model could reduce the cost of intruder detection while ensuring a specific detection rate.
{"title":"Analysis of safe electricity consumption on load side based on attack and defence game model","authors":"Xiaodong Wang, Feixiang Gong, Songsong Chen, Bowen Zheng, Ping Zhang, Liye Zhao, Linru Jiang, Dongdong Zhang, Pengcheng Du","doi":"10.1049/tje2.12380","DOIUrl":"https://doi.org/10.1049/tje2.12380","url":null,"abstract":"With the improvement of digitalization and intelligence in the power system, the safe operation of the power system is facing enormous challenges. The safe use of electricity on the load side is the key to achieving safe and reliable power system operation. The detection party needs amounts of human and material resources when the power network is attacked. In response to the current difficulties of low detection ability and high detection costs, this paper proposes an attack and defence game model that considers the differences between different nodes, ensuring the safety and economy of electricity consumption while reducing energy waste. At first, the structure of smart meters and the attack characteristics of intruders are summarized, and a basic attack and defence game model is constructed. The Nash equilibrium is then solved, and the optimal strategy for the game between the defender and the intruder is given to balance the relation between detection performance and energy consumption. In response to the differences generated by each node, strategies for attackers to launch attacks on different nodes and the setting of optimal thresholds for other nodes in the defence system are explored. Finally, case studies verify that the proposed model could reduce the cost of intruder detection while ensuring a specific detection rate.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":"124 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140765572","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}
Unmanned aerial vehicle (UAV) technology is experiencing strong growth in many fields such as military and civil. When operating around obstacles and in the proximity of walls or moving objects, the UAV is constrained to thrust and power consumption variation induced by several aerodynamic effects that can lead to severe flight instability. In this paper, a methodology based on multiple reference frames (MRF) is developed and applied to computational fluid dynamics (CFD) simulations on a Phantom DJI 3 propeller to reproduce the effect of fixed and moving wall proximity on the propeller aerodynamic performances. When hovering (3000 rpm) at 0.2 m above a moving obstacle (15 m/s), the results have shown a huge decrease in the thrust by 11.3% when compared to fixed obstacle thrust. This effect, however, is reduced when the propeller is hovering at 5000 rpm and neglected at 9550 rpm. Finally, the moving obstacle had a significant impact on the propeller's aerodynamic performance, resulting in a decrease in thrust force and power consumption at low hovering rotational velocities. Especially, when the obstacle is moving at a fast speed, the UAV could properly use high rotational velocity to maintain high power loading and ensure hovering stability.
{"title":"A comprehensive study on the aerodynamic influence of stationary and moving obstacles on an isolated phantom DJI 3 UAV propeller","authors":"C-F. Hage, T. Sophy, E. Aglzim","doi":"10.1049/tje2.12374","DOIUrl":"https://doi.org/10.1049/tje2.12374","url":null,"abstract":"Unmanned aerial vehicle (UAV) technology is experiencing strong growth in many fields such as military and civil. When operating around obstacles and in the proximity of walls or moving objects, the UAV is constrained to thrust and power consumption variation induced by several aerodynamic effects that can lead to severe flight instability. In this paper, a methodology based on multiple reference frames (MRF) is developed and applied to computational fluid dynamics (CFD) simulations on a Phantom DJI 3 propeller to reproduce the effect of fixed and moving wall proximity on the propeller aerodynamic performances. When hovering (3000 rpm) at 0.2 m above a moving obstacle (15 m/s), the results have shown a huge decrease in the thrust by 11.3% when compared to fixed obstacle thrust. This effect, however, is reduced when the propeller is hovering at 5000 rpm and neglected at 9550 rpm. Finally, the moving obstacle had a significant impact on the propeller's aerodynamic performance, resulting in a decrease in thrust force and power consumption at low hovering rotational velocities. Especially, when the obstacle is moving at a fast speed, the UAV could properly use high rotational velocity to maintain high power loading and ensure hovering stability.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":"392 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140762664","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}
Zhixin Zhang, Chenglong Xiao, Shanshan Wang, Weilun Yu, Yun Bai
Cable trees are primarily employed in industrial products to facilitate energy transfer and information exchange among various components. When utilizing machines for assembly, it is essential to convert the wiring plan into a sequence of cable insertion operations executed by the machine under various constraints. This poses a combinatorial optimization problem. In this domain, constraint programming (CP) solvers often exhibit outstanding performance by leveraging their robust problem‐modelling capabilities, excellent scalability, and precise solving capabilities. However, CP solvers may achieve various performances for different problem instances. Selecting the most suitable CP solver for each problem instance is crucial. This paper introduces an automatic selection algorithm for CP solvers to solve the cable tree wiring problem (CTW). Firstly, a scoring system is used to conduct an in‐depth analysis and compare four well‐known CP solvers: CPLEX, Chuffed, OR‐Tools, and Gurobi. The results indicate that OR‐Tools and CPLEX outperform other solvers in performance. Moreover, these two solvers exhibit complementary advantages in quickly finding optimal and feasible solutions within specified time limits. Therefore, CP and machine learning are ingeniously integrated, harnessing their complementary advantages. 4240 instances covering various scenarios are randomly generated to form the problem space. This method incorporates decision trees, random forests, K‐nearest neighbours, and naive Bayes, utilizing these four machine learning techniques. The proposed method can achieve better results than traditional single CP solvers. Among all the evaluated machining learning techniques, the automatic solver selection methods based on decision trees and random forests can achieve accuracy rates of 91.29% and 84.15%, respectively.
{"title":"Automatic constraint programming solver selection method based on machine learning for the cable tree wiring problem","authors":"Zhixin Zhang, Chenglong Xiao, Shanshan Wang, Weilun Yu, Yun Bai","doi":"10.1049/tje2.12368","DOIUrl":"https://doi.org/10.1049/tje2.12368","url":null,"abstract":"Cable trees are primarily employed in industrial products to facilitate energy transfer and information exchange among various components. When utilizing machines for assembly, it is essential to convert the wiring plan into a sequence of cable insertion operations executed by the machine under various constraints. This poses a combinatorial optimization problem. In this domain, constraint programming (CP) solvers often exhibit outstanding performance by leveraging their robust problem‐modelling capabilities, excellent scalability, and precise solving capabilities. However, CP solvers may achieve various performances for different problem instances. Selecting the most suitable CP solver for each problem instance is crucial. This paper introduces an automatic selection algorithm for CP solvers to solve the cable tree wiring problem (CTW). Firstly, a scoring system is used to conduct an in‐depth analysis and compare four well‐known CP solvers: CPLEX, Chuffed, OR‐Tools, and Gurobi. The results indicate that OR‐Tools and CPLEX outperform other solvers in performance. Moreover, these two solvers exhibit complementary advantages in quickly finding optimal and feasible solutions within specified time limits. Therefore, CP and machine learning are ingeniously integrated, harnessing their complementary advantages. 4240 instances covering various scenarios are randomly generated to form the problem space. This method incorporates decision trees, random forests, K‐nearest neighbours, and naive Bayes, utilizing these four machine learning techniques. The proposed method can achieve better results than traditional single CP solvers. Among all the evaluated machining learning techniques, the automatic solver selection methods based on decision trees and random forests can achieve accuracy rates of 91.29% and 84.15%, respectively.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":"147 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140276338","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}
Wenle Song, Lei Wang, Xiangyu Hao, Le Wan, Chenyang Li
To improve the economy of offshore oil production platform shore‐based power transmission mode, the reactive power capacity allocation technology of offshore oil production platform shore‐based power supply system based on different network topology reliability measures was proposed. The optimization model of power supply system network topology and the structure model of voltage source converter high voltage direct current transmission system were established, the start and stop control scheme of flexible direct current (DC) transmission system was designed, and the operation parameters of converter station and DC line were monitored in real time. The topological structure of offshore oil production platform shore‐based power supply system is constructed, the mathematical model of flexible DC transmission system is established when the alternating current side voltage is balanced, the reactive power capacity configuration of offshore oil production platform shore‐based power supply system is optimized, and the life cycle cost results are calculated. The experimental results show that the algorithm proposed in this paper can obtain the optimal solution only after 26 calculations, with high optimization efficiency and good convergence effect. Reactive capacity configuration of shore‐based power supply system for offshore production platform can reduce failure rate and life cycle cost.
{"title":"Reactive power capacity allocation technology of shore‐based power supply system of offshore oil production platform under different network topology reliability measures","authors":"Wenle Song, Lei Wang, Xiangyu Hao, Le Wan, Chenyang Li","doi":"10.1049/tje2.12365","DOIUrl":"https://doi.org/10.1049/tje2.12365","url":null,"abstract":"To improve the economy of offshore oil production platform shore‐based power transmission mode, the reactive power capacity allocation technology of offshore oil production platform shore‐based power supply system based on different network topology reliability measures was proposed. The optimization model of power supply system network topology and the structure model of voltage source converter high voltage direct current transmission system were established, the start and stop control scheme of flexible direct current (DC) transmission system was designed, and the operation parameters of converter station and DC line were monitored in real time. The topological structure of offshore oil production platform shore‐based power supply system is constructed, the mathematical model of flexible DC transmission system is established when the alternating current side voltage is balanced, the reactive power capacity configuration of offshore oil production platform shore‐based power supply system is optimized, and the life cycle cost results are calculated. The experimental results show that the algorithm proposed in this paper can obtain the optimal solution only after 26 calculations, with high optimization efficiency and good convergence effect. Reactive capacity configuration of shore‐based power supply system for offshore production platform can reduce failure rate and life cycle cost.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":"70 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140271801","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 recent years, there has been a notable increase in the frequency and intensity of natural disasters related to global warming. Large‐scale blackouts caused by natural disasters demonstrate the extreme vulnerability of power systems to these devastations. Resilience planning is the key to preparing power systems for natural disasters by enhancing the vital infrastructure's robustness. This paper proposes a new resilience improvement framework based on resiliency assessment and optimal hardening to improve the distribution system's resiliency against hurricanes. The main goal is to find the optimal distribution system line hardening solution according to reconfiguration potentials after the hurricane to minimize the distribution system cost of energy not supplied. Fragility curves and Monte Carlo simulations are used for the distribution system resilience assessment. Poles and conductors are vulnerable components of distribution system lines; therefore, two hardening strategies have been outlined using measures like replacing old poles with new poles, upgrading pole classes, and vegetation management. This method is modelled as an optimization program considering budget limitations and load priorities and implemented by a genetic algorithm on the IEEE 33‐bus standard network. The results show that optimal line hardening according to network reconfiguration potentials significantly increased the distribution system's resilience.
{"title":"Distribution system resilience improvement against hurricanes: optimal line hardening according to reconfiguration potentials","authors":"Navid Talaei Pashiri, Sasan Azad, M. Ameli","doi":"10.1049/tje2.12364","DOIUrl":"https://doi.org/10.1049/tje2.12364","url":null,"abstract":"In recent years, there has been a notable increase in the frequency and intensity of natural disasters related to global warming. Large‐scale blackouts caused by natural disasters demonstrate the extreme vulnerability of power systems to these devastations. Resilience planning is the key to preparing power systems for natural disasters by enhancing the vital infrastructure's robustness. This paper proposes a new resilience improvement framework based on resiliency assessment and optimal hardening to improve the distribution system's resiliency against hurricanes. The main goal is to find the optimal distribution system line hardening solution according to reconfiguration potentials after the hurricane to minimize the distribution system cost of energy not supplied. Fragility curves and Monte Carlo simulations are used for the distribution system resilience assessment. Poles and conductors are vulnerable components of distribution system lines; therefore, two hardening strategies have been outlined using measures like replacing old poles with new poles, upgrading pole classes, and vegetation management. This method is modelled as an optimization program considering budget limitations and load priorities and implemented by a genetic algorithm on the IEEE 33‐bus standard network. The results show that optimal line hardening according to network reconfiguration potentials significantly increased the distribution system's resilience.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":"9 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140268395","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}
Steady‐state visual evoked potentials (SSVEP), significant in brain‐computer interfaces (BCI) and medical diagnostics, benefit from enhanced signal processing for improved analysis and interpretation. This study introduces a novel enhancement algorithm for SSVEP electroencephalogram (EEG) signals, employing fractional‐order differentiation operators combined with image processing techniques. Utilizing fractional‐order differentiation within a Laplace pyramid framework, the algorithm achieves hierarchical signal enhancement, facilitating detailed feature extraction and emphasizing SSVEP signal characteristics. This innovative approach merges the precision of fractional calculus with the structural benefits of the Laplace pyramid, leading to enhanced signal clarity and feature discrimination. The efficacy of this method was validated using canonical correlation analysis (CCA), filter bank CCA (FBCCA), and task‐related component analysis (TRCA) on a public dataset. Compared to conventional methods, our algorithm not only mitigates trend components in SSVEP signals but also significantly boosts the recognition accuracy of CCA, FBCCA, and TRCA algorithms. Experimental results indicate a marked improvement in recognition precision, underscoring the algorithm's potential to advance SSVEP‐based BCI research.
{"title":"Research on SSVEP‐EEG feature enhancement algorithm based on fractional differentiation","authors":"Zenghui Li, Wei Wang, Saijie Yuan, Junpeng Pei, Qianqian Yang, Yousong Wang","doi":"10.1049/tje2.12363","DOIUrl":"https://doi.org/10.1049/tje2.12363","url":null,"abstract":"Steady‐state visual evoked potentials (SSVEP), significant in brain‐computer interfaces (BCI) and medical diagnostics, benefit from enhanced signal processing for improved analysis and interpretation. This study introduces a novel enhancement algorithm for SSVEP electroencephalogram (EEG) signals, employing fractional‐order differentiation operators combined with image processing techniques. Utilizing fractional‐order differentiation within a Laplace pyramid framework, the algorithm achieves hierarchical signal enhancement, facilitating detailed feature extraction and emphasizing SSVEP signal characteristics. This innovative approach merges the precision of fractional calculus with the structural benefits of the Laplace pyramid, leading to enhanced signal clarity and feature discrimination. The efficacy of this method was validated using canonical correlation analysis (CCA), filter bank CCA (FBCCA), and task‐related component analysis (TRCA) on a public dataset. Compared to conventional methods, our algorithm not only mitigates trend components in SSVEP signals but also significantly boosts the recognition accuracy of CCA, FBCCA, and TRCA algorithms. Experimental results indicate a marked improvement in recognition precision, underscoring the algorithm's potential to advance SSVEP‐based BCI research.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":"56 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140087274","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}
This paper introduces a new approach for analyzing the dynamics of DC–DC converters. Currently, the primary widely accepted method for examining dynamic processes is the Small Signal Analysis technique. However, when applied to modern complex converters, this method poses additional challenges in formulating and solving systems of differential equations. The method proposed in this paper is based on its application to the analysis of dynamic modes of energy functions—Lagrangians. These functions make it possible to define simple criteria to describe the course of dynamic processes, and in the end define an equivalent (approximating) conventional converter identical to the original one with respect to the course of dynamics. If the magnetic and electrical energies in the Lagrangians of both the converters are equal, the outcome is practically identical transient processes. These findings were confirmed by both theoretical analysis and experimentally modelling the dynamics of the initial converter and an equivalent to it in the Matlab–Simscape program. An additional possibility of using the transfer functions of a conventional boost converter for the theoretical analysis of the converters of much greater orders is also discussed. The authors’ experiments confirm the correctness of their theoretical conclusions.
{"title":"Equivalent converter method for analyzing complex DC–DC converting systems","authors":"Sagi Orel Moshe, Yefim Berkovich","doi":"10.1049/tje2.12359","DOIUrl":"https://doi.org/10.1049/tje2.12359","url":null,"abstract":"This paper introduces a new approach for analyzing the dynamics of DC–DC converters. Currently, the primary widely accepted method for examining dynamic processes is the Small Signal Analysis technique. However, when applied to modern complex converters, this method poses additional challenges in formulating and solving systems of differential equations. The method proposed in this paper is based on its application to the analysis of dynamic modes of energy functions—Lagrangians. These functions make it possible to define simple criteria to describe the course of dynamic processes, and in the end define an equivalent (approximating) conventional converter identical to the original one with respect to the course of dynamics. If the magnetic and electrical energies in the Lagrangians of both the converters are equal, the outcome is practically identical transient processes. These findings were confirmed by both theoretical analysis and experimentally modelling the dynamics of the initial converter and an equivalent to it in the Matlab–Simscape program. An additional possibility of using the transfer functions of a conventional boost converter for the theoretical analysis of the converters of much greater orders is also discussed. The authors’ experiments confirm the correctness of their theoretical conclusions.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":"65 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140280692","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}
Subramaniam Thangavel, C. Maheswari, E. Bhaskaran Priyanka, Albert Alexander Stonier, Geno Peter, Vivekananda Ganji
The present research work focused on optimizing the input parameters of the automated TIG welding process of SS304 metal. Since SS304 possesses high inter‐granular toughness and corrosion resistance with increased lifespan in the pressure vessel and automobile sector, SS304 is mainly referred for gas arc welding compared with SS 202. The SS304 workpieces of 60 mm × 40 mm × 4 mm with dimension are utilized in the experiment and the same metal has been used as the filler material. The TIG welding experimental lab‐scale setup utilizes a 2‐axis servo workbench programmed with PLC to perform an automatic trajectory path using Taguchi design of optimization to obtain the optimal welding parameters for the SS304 welding process. To analyze the influence of welding current, welding speed, gas flow rate, and welding arc length on the tensile strength and hardness based on predicted R‐squared, p‐value and co‐efficient of the sum of squares from are verified. From the regression analysis, the predicted model R‐squared value holds 95.78% and 94.83% for the hardness and tensile strength respectively associating with the actual coefficient confirming the model which has maximum precision. Further, it is inferred that on increasing welding current and welding speed, the hardness of the welded joints seems to increase whereas when the minimum gas flow rate is maintained, the tensile strength of the SS304 decreases drastically. Overall, among the four input factors, the welding current is a major influencing parameter on the SS304 which is directly proportional to tensile strength and hardness.
本研究工作的重点是优化 SS304 金属自动氩弧焊工艺的输入参数。由于 SS304 具有较高的晶间韧性和耐腐蚀性，在压力容器和汽车领域的使用寿命较长，因此与 SS 202 相比，SS304 主要用于气弧焊。实验中使用了尺寸为 60 mm × 40 mm × 4 mm 的 SS304 工件，并使用相同的金属作为填充材料。实验室规模的氩弧焊实验装置使用了一个由 PLC 编程的双轴伺服工作台，利用田口优化设计执行自动轨迹路径，以获得 SS304 焊接工艺的最佳焊接参数。根据预测的 R 方、P 值和平方和系数，分析焊接电流、焊接速度、气体流量和焊接电弧长度对拉伸强度和硬度的影响。通过回归分析，硬度和拉伸强度的预测模型 R 平方值分别为 95.78% 和 94.83%，与实际系数相关联，证实该模型具有最高精度。此外，还可以推断出，随着焊接电流和焊接速度的增加，焊点的硬度似乎会增加，而当保持最小气体流量时，SS304 的抗拉强度会急剧下降。总之，在四个输入因素中，焊接电流是影响 SS304 的主要参数，它与抗拉强度和硬度成正比。
{"title":"Analysis and optimization of the automated TIG welding process parameters on SS304 incorporating Taguchi optimization technique","authors":"Subramaniam Thangavel, C. Maheswari, E. Bhaskaran Priyanka, Albert Alexander Stonier, Geno Peter, Vivekananda Ganji","doi":"10.1049/tje2.12373","DOIUrl":"https://doi.org/10.1049/tje2.12373","url":null,"abstract":"The present research work focused on optimizing the input parameters of the automated TIG welding process of SS304 metal. Since SS304 possesses high inter‐granular toughness and corrosion resistance with increased lifespan in the pressure vessel and automobile sector, SS304 is mainly referred for gas arc welding compared with SS 202. The SS304 workpieces of 60 mm × 40 mm × 4 mm with dimension are utilized in the experiment and the same metal has been used as the filler material. The TIG welding experimental lab‐scale setup utilizes a 2‐axis servo workbench programmed with PLC to perform an automatic trajectory path using Taguchi design of optimization to obtain the optimal welding parameters for the SS304 welding process. To analyze the influence of welding current, welding speed, gas flow rate, and welding arc length on the tensile strength and hardness based on predicted R‐squared, p‐value and co‐efficient of the sum of squares from are verified. From the regression analysis, the predicted model R‐squared value holds 95.78% and 94.83% for the hardness and tensile strength respectively associating with the actual coefficient confirming the model which has maximum precision. Further, it is inferred that on increasing welding current and welding speed, the hardness of the welded joints seems to increase whereas when the minimum gas flow rate is maintained, the tensile strength of the SS304 decreases drastically. Overall, among the four input factors, the welding current is a major influencing parameter on the SS304 which is directly proportional to tensile strength and hardness.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":"6 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140268756","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}
This work presents the design, development, and performance evaluation of a cost‐effective and practical single‐phase power quality analyzer (SPPQA) using Pyboard microcontroller and Python‐to‐Python interface. The SPPQA offers comprehensive measurements, including voltage/current harmonics up to the seventh order, frequency, voltage and current root mean square values, total power, active/reactive power, power factor, voltage and current crest factor, as well as voltage/current total harmonic distortion. To ensure the accuracy of the SPPQA, a testing procedure was conducted using a test bench equipped with a non‐linear load and a 220‐V power source operating at a frequency of 50 Hz. The obtained results, such as and , are compared with measurements obtained from classical approaches and devices, validating the authenticity and reliability of the SPPQA's performance. The SPPQA demonstrates considerable accuracy and reliability in its measurements, establishing it as an efficient and practical tool for power quality assessment. The ability to measure the seven harmonics of voltage and current, alongside other critical parameters, positions the SPPQA as a practical asset in the academic, industrial, and commercial sectors. The affordability and practicality of the SPPQA make it practical in both academic research and practical scenarios. Utilizers can gain deeper information into power quality through its measurements and harmonics analysis, while also enhancing industrial processes and ensuring a reliable power supply in commercial settings.
{"title":"Design and implementation of a cost‐effective practical single‐phase power quality analyzer using pyboard microcontroller and python‐to‐python interface","authors":"Mehran Sabahi, Ashkan Safari, Morteza Nazari‐Heris","doi":"10.1049/tje2.12360","DOIUrl":"https://doi.org/10.1049/tje2.12360","url":null,"abstract":"This work presents the design, development, and performance evaluation of a cost‐effective and practical single‐phase power quality analyzer (SPPQA) using Pyboard microcontroller and Python‐to‐Python interface. The SPPQA offers comprehensive measurements, including voltage/current harmonics up to the seventh order, frequency, voltage and current root mean square values, total power, active/reactive power, power factor, voltage and current crest factor, as well as voltage/current total harmonic distortion. To ensure the accuracy of the SPPQA, a testing procedure was conducted using a test bench equipped with a non‐linear load and a 220‐V power source operating at a frequency of 50 Hz. The obtained results, such as and , are compared with measurements obtained from classical approaches and devices, validating the authenticity and reliability of the SPPQA's performance. The SPPQA demonstrates considerable accuracy and reliability in its measurements, establishing it as an efficient and practical tool for power quality assessment. The ability to measure the seven harmonics of voltage and current, alongside other critical parameters, positions the SPPQA as a practical asset in the academic, industrial, and commercial sectors. The affordability and practicality of the SPPQA make it practical in both academic research and practical scenarios. Utilizers can gain deeper information into power quality through its measurements and harmonics analysis, while also enhancing industrial processes and ensuring a reliable power supply in commercial settings.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":"48 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139966572","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}
This paper studies the effect of the number of switching (NOS) per day of capacitor banks on loss reduction in radial distribution systems. To this aim, the daytime (more precisely, 24 h) is divided into different numbers of time segments (equal to the same NOS) for capacitors’ size switching. The resulting non‐linear programming with discontinuous derivatives (called DNLP) model is solved subject to related constraints. The results reveal the impact of hourly switching of capacitor banks on further loss reduction (namely 118.4435, 83.7856, and 101.738 MWh for three IEEE systems) and higher net savings (i.e. k$5.6067, k$4.2772, and k$5.3542 for the same systems) of radial distribution systems compared to daily switching. Then, the hyper‐tuned Random Forest model is trained based on the IEEE 69‐bus network, fine‐tuned by the IEEE 10‐bus network, and fitted by the IEEE 33‐bus network to have an intelligent multi‐classification task with the highest accuracy. Numerical simulation, in both classic and intelligent parts, is presented to demonstrate the performance of DeepOptaCap. For the final step, DeepOptaCast is compared to other intelligent models of Light Gradient Boosting Method (LGBM), Decision Tree, and XGBoost, regarding KPIs of mean absolute percentage error, root mean squared percentage error, mean absolute error, root mean squared error, and coefficient of determination to demonstrate the model's superiority.
{"title":"Net saving improvement of capacitor banks in power distribution systems by increasing daily size switching number: A comparative result analysis by artificial intelligence","authors":"Omid Sadeghian, Ashkan Safari","doi":"10.1049/tje2.12357","DOIUrl":"https://doi.org/10.1049/tje2.12357","url":null,"abstract":"This paper studies the effect of the number of switching (NOS) per day of capacitor banks on loss reduction in radial distribution systems. To this aim, the daytime (more precisely, 24 h) is divided into different numbers of time segments (equal to the same NOS) for capacitors’ size switching. The resulting non‐linear programming with discontinuous derivatives (called DNLP) model is solved subject to related constraints. The results reveal the impact of hourly switching of capacitor banks on further loss reduction (namely 118.4435, 83.7856, and 101.738 MWh for three IEEE systems) and higher net savings (i.e. k$5.6067, k$4.2772, and k$5.3542 for the same systems) of radial distribution systems compared to daily switching. Then, the hyper‐tuned Random Forest model is trained based on the IEEE 69‐bus network, fine‐tuned by the IEEE 10‐bus network, and fitted by the IEEE 33‐bus network to have an intelligent multi‐classification task with the highest accuracy. Numerical simulation, in both classic and intelligent parts, is presented to demonstrate the performance of DeepOptaCap. For the final step, DeepOptaCast is compared to other intelligent models of Light Gradient Boosting Method (LGBM), Decision Tree, and XGBoost, regarding KPIs of mean absolute percentage error, root mean squared percentage error, mean absolute error, root mean squared error, and coefficient of determination to demonstrate the model's superiority.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":"65 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139966692","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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