Abstract Automatic pavement crack detection is essential for fast and efficient pavement maintenance and health measurement. And crack image data is the basis of crack detection. The existing data collection methods have disadvantages such as high cost, easy loss of frames, blurring, and loss of crack information. Therefore, a new method of data collection using target detection and perspective transformation is introduced. The CRACK2000 dataset with multiple complex backgrounds is constructed by this method. Also, a multiscale fully convolutional network by improving U‐Net, named U‐multiscale dilated network (U‐MDN), is proposed. The network uses U‐Net as the base network and introduces U‐multiscale dilated convolutional module (U‐MDM) after U‐Net downsampling. In addition, the U‐MDM is compared with U‐MCM and MDM, and the result shows that U‐MDM has a better effect. Finally, U‐MDN is compared with U‐Net, CrackSeg, DeeplabV3+, Basnet, and PDDF‐Net on CRACK2000 and other data sets, respectively. The experimental results demonstrate that the U‐MDN is better than other algorithms in terms of precision, recall, F1‐score, and AUC.
{"title":"Automated pavement crack detection based on multiscale fully convolutional network","authors":"Xin Wang, Yueming Wang, Lingjun Yu, Qi Li","doi":"10.1049/tje2.12317","DOIUrl":"https://doi.org/10.1049/tje2.12317","url":null,"abstract":"Abstract Automatic pavement crack detection is essential for fast and efficient pavement maintenance and health measurement. And crack image data is the basis of crack detection. The existing data collection methods have disadvantages such as high cost, easy loss of frames, blurring, and loss of crack information. Therefore, a new method of data collection using target detection and perspective transformation is introduced. The CRACK2000 dataset with multiple complex backgrounds is constructed by this method. Also, a multiscale fully convolutional network by improving U‐Net, named U‐multiscale dilated network (U‐MDN), is proposed. The network uses U‐Net as the base network and introduces U‐multiscale dilated convolutional module (U‐MDM) after U‐Net downsampling. In addition, the U‐MDM is compared with U‐MCM and MDM, and the result shows that U‐MDM has a better effect. Finally, U‐MDN is compared with U‐Net, CrackSeg, DeeplabV3+, Basnet, and PDDF‐Net on CRACK2000 and other data sets, respectively. The experimental results demonstrate that the U‐MDN is better than other algorithms in terms of precision, recall, F1‐score, and AUC.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135761983","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}
Zubaer Alam, Tushar Kanti Roy, Subarto Kumar Ghosh, Md Apel Mahmud
Abstract This paper presents a hybrid non‐linear voltage controller design approach for DC–DC buck converters where the hybridization is done by combining two non‐linear techniques: backstepping and sliding mode. In the proposed hybrid framework, the backstepping approach ensures the tracking of all states, while the sliding mode scheme with an enhanced reaching law is utilized for the finite‐time convergence of voltage and current in DC–DC buck converters. In this way, the proposed hybrid scheme offers two‐degree freedom instead of one‐degree in existing nonlinear approaches for controlling DC–DC converters, while guaranteeing the time‐time convergence that is not achievable with existing methods in the same application. In this work, the sliding surface is modified to capture changes in the load and supply voltage and the Lyapunov stability theory is used to assess the overall stability of DC–DC buck converters with the proposed controller. Simulation and experimental validations are conducted for evaluating the performance of this hybrid scheme, including a comparative study of an existing sliding mode controller in which the sliding surface is selected as the fast terminal one while avoiding the non‐singularity and incorporating the adaptation law.
{"title":"A hybrid non‐linear voltage controller design for DC–DC buck converters","authors":"Zubaer Alam, Tushar Kanti Roy, Subarto Kumar Ghosh, Md Apel Mahmud","doi":"10.1049/tje2.12318","DOIUrl":"https://doi.org/10.1049/tje2.12318","url":null,"abstract":"Abstract This paper presents a hybrid non‐linear voltage controller design approach for DC–DC buck converters where the hybridization is done by combining two non‐linear techniques: backstepping and sliding mode. In the proposed hybrid framework, the backstepping approach ensures the tracking of all states, while the sliding mode scheme with an enhanced reaching law is utilized for the finite‐time convergence of voltage and current in DC–DC buck converters. In this way, the proposed hybrid scheme offers two‐degree freedom instead of one‐degree in existing nonlinear approaches for controlling DC–DC converters, while guaranteeing the time‐time convergence that is not achievable with existing methods in the same application. In this work, the sliding surface is modified to capture changes in the load and supply voltage and the Lyapunov stability theory is used to assess the overall stability of DC–DC buck converters with the proposed controller. Simulation and experimental validations are conducted for evaluating the performance of this hybrid scheme, including a comparative study of an existing sliding mode controller in which the sliding surface is selected as the fast terminal one while avoiding the non‐singularity and incorporating the adaptation law.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135922216","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}
Abstract The integration of modular multilevel converters (MMCs) with high voltage direct current (HVDC) transmission systems is an efficient method for transporting electricity from distant renewable energy sources to demand centres. However, MMC‐HVDC systems face reliability challenges during DC overcurrent faults, often caused by component failures that can lead to HVDC network shutdowns. Consequently, a reliable fault location approach is crucial for grid protection and restoration, aiding in fault isolation and alternate power flow identification. Conventional fault location methods struggle with manual protective threshold setting, susceptibility to fault resistance and noise, and the need for communication channels, resulting in signal delays. In multi‐terminal HVDC networks, fault location becomes even more complex due to poor selectivity and sensitivity in traditional schemes. This study proposes a robust fault location approach based on bidirectional long short‐term memory (bi‐LSTM). The method offers a simplified decision‐making model with low computational requirements, utilizing fault features from one end of the network, eliminating the need for a communication channel. Remarkably, this approach achieves high fault location accuracy, even with varying fault types, resistances, and noise levels, as demonstrated by an MSE of 0.006 and a percentage error below 1% in simulations conducted using a real‐time simulator with MATLAB/Simulink.
{"title":"A novel fault location strategy based on Bi‐LSTM for MMC‐HVDC systems","authors":"Jude Inwumoh, Craig Baguley, Udaya Madawala, Kosala Gunawardane","doi":"10.1049/tje2.12310","DOIUrl":"https://doi.org/10.1049/tje2.12310","url":null,"abstract":"Abstract The integration of modular multilevel converters (MMCs) with high voltage direct current (HVDC) transmission systems is an efficient method for transporting electricity from distant renewable energy sources to demand centres. However, MMC‐HVDC systems face reliability challenges during DC overcurrent faults, often caused by component failures that can lead to HVDC network shutdowns. Consequently, a reliable fault location approach is crucial for grid protection and restoration, aiding in fault isolation and alternate power flow identification. Conventional fault location methods struggle with manual protective threshold setting, susceptibility to fault resistance and noise, and the need for communication channels, resulting in signal delays. In multi‐terminal HVDC networks, fault location becomes even more complex due to poor selectivity and sensitivity in traditional schemes. This study proposes a robust fault location approach based on bidirectional long short‐term memory (bi‐LSTM). The method offers a simplified decision‐making model with low computational requirements, utilizing fault features from one end of the network, eliminating the need for a communication channel. Remarkably, this approach achieves high fault location accuracy, even with varying fault types, resistances, and noise levels, as demonstrated by an MSE of 0.006 and a percentage error below 1% in simulations conducted using a real‐time simulator with MATLAB/Simulink.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135605631","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}
Abstract Price‐based demand response (PBDR) programs can push consumers to reconsider their electricity demand regarding the electricity price in the market. The load profile of the whole network can be reshaped in response, which can directly affect the network investment decisions. The decision‐maker had to consider this effect in order to reach an optimal plan for the network. Here, a mixed‐integer linear programming (MILP) model considering a price‐based demand response (PBDR) program is developed for transmission expansion planning (TEP) of wind‐integrated networks and the problem is constrained by the conditional value at risk (CVaR) measure to model the risk of planning and investments for both sides. The proposed model is an originally bi‐level problem with different objective functions in both layers. These objectives are as follows, minimizing the total cost of TEP, consumer payments, and wind curtailment in the first layer, and minimizing the network operational costs in the second layer. Then, using an innovative formulation to overcome the non‐linearities, and using KKT conditions of the second layer problem, the problem recast into a single‐layer mixed integer non‐linear program (MINLP) problem which is called a mathematical program with equilibrium constraints (MPEC) with primal‐dual formulation. The proposed model had been applied to IEEE standard 24‐bus RTS and IEEE standard 118‐bus test systems to show its efficiency.
{"title":"Risk‐constrained expansion planning of wind integrated networks using innovative MPEC primal‐dual formulation for directly involving price‐based demand response in MILP problem","authors":"Saman Baharvandi, Pouria Maghouli","doi":"10.1049/tje2.12314","DOIUrl":"https://doi.org/10.1049/tje2.12314","url":null,"abstract":"Abstract Price‐based demand response (PBDR) programs can push consumers to reconsider their electricity demand regarding the electricity price in the market. The load profile of the whole network can be reshaped in response, which can directly affect the network investment decisions. The decision‐maker had to consider this effect in order to reach an optimal plan for the network. Here, a mixed‐integer linear programming (MILP) model considering a price‐based demand response (PBDR) program is developed for transmission expansion planning (TEP) of wind‐integrated networks and the problem is constrained by the conditional value at risk (CVaR) measure to model the risk of planning and investments for both sides. The proposed model is an originally bi‐level problem with different objective functions in both layers. These objectives are as follows, minimizing the total cost of TEP, consumer payments, and wind curtailment in the first layer, and minimizing the network operational costs in the second layer. Then, using an innovative formulation to overcome the non‐linearities, and using KKT conditions of the second layer problem, the problem recast into a single‐layer mixed integer non‐linear program (MINLP) problem which is called a mathematical program with equilibrium constraints (MPEC) with primal‐dual formulation. The proposed model had been applied to IEEE standard 24‐bus RTS and IEEE standard 118‐bus test systems to show its efficiency.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134978509","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}
Pranto Halder, Md. Mehedi Hassan, A. K. Z. Rasel Rahman, Laboni Akter, Abu Shakil Ahmed, Shakir Khan, Sajib Chatterjee, M. Raihan
Abstract As 4G technology served as a foundation, the emergence of 5G is now underway, ushering in a new era of connectivity. With the growing demand for seamless internet experiences, particularly in the face of escalating internet subscribers, the networking domain must evolve. Developing nations strive to align with this dynamic landscape, necessitating an upgrade that integrates internet of things (IoT), natural language processing (NLP), and artificial intelligence (AI) with network infrastructure. By enhancing networking systems with lower latency and improved scalability, 5G addresses congestion issues. This is achieved by coupling mm‐wave technology with the 5G framework through the 3rd Generation Partnership Project, significantly amplifying channel bandwidth. However, the comprehensive analysis underscores challenges in 5G implementation, encompassing aspects like distance, orientation, non‐line‐of‐sight conditions, protocol utilization, and server positioning. Drawing from a dataset provided by the University of Minnesota that illuminates the limitations of 5G implementation in select US cities, this paper extends its focus to densely populated regions in developing countries of the sub‐continent. Employing a machine learning approach, the paper delves into the constraints of 5G deployment in such areas. Ultimately, this research aims to shed light on the intricacies of 5G's implementation challenges, contributing to the discourse on enhancing network infrastructure in the evolving landscape of global connectivity.
{"title":"Prospects and setbacks for migrating towards 5G wireless access in developing Bangladesh: A comparative study","authors":"Pranto Halder, Md. Mehedi Hassan, A. K. Z. Rasel Rahman, Laboni Akter, Abu Shakil Ahmed, Shakir Khan, Sajib Chatterjee, M. Raihan","doi":"10.1049/tje2.12319","DOIUrl":"https://doi.org/10.1049/tje2.12319","url":null,"abstract":"Abstract As 4G technology served as a foundation, the emergence of 5G is now underway, ushering in a new era of connectivity. With the growing demand for seamless internet experiences, particularly in the face of escalating internet subscribers, the networking domain must evolve. Developing nations strive to align with this dynamic landscape, necessitating an upgrade that integrates internet of things (IoT), natural language processing (NLP), and artificial intelligence (AI) with network infrastructure. By enhancing networking systems with lower latency and improved scalability, 5G addresses congestion issues. This is achieved by coupling mm‐wave technology with the 5G framework through the 3rd Generation Partnership Project, significantly amplifying channel bandwidth. However, the comprehensive analysis underscores challenges in 5G implementation, encompassing aspects like distance, orientation, non‐line‐of‐sight conditions, protocol utilization, and server positioning. Drawing from a dataset provided by the University of Minnesota that illuminates the limitations of 5G implementation in select US cities, this paper extends its focus to densely populated regions in developing countries of the sub‐continent. Employing a machine learning approach, the paper delves into the constraints of 5G deployment in such areas. Ultimately, this research aims to shed light on the intricacies of 5G's implementation challenges, contributing to the discourse on enhancing network infrastructure in the evolving landscape of global connectivity.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135811850","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}
Travelling salesman problem (TSP) is one of the most famous problems in graph theory, as well as one of the typical nondeterministic polynomial time (NP)‐hard problems in combinatorial optimization. Reinforcement learning (RL) has been widely regarded as an effective tool for solving combinatorial optimization problems. This paper attempts to solve the TSP problem using different reinforcement learning algorithms and evaluated the performance of three RL algorithms (Q‐Learning, SARSA, and Double Q‐Learning) under different reward functions, ε‐greedy decay strategies, and running times. A comprehensive analysis and comparison of the three algorithms mentioned above were conducted in the experiment. First, the experimental results indicate that the Double Q‐Learning algorithm is the best algorithm. Among the eight TSP instances, the Double Q‐Learning algorithm outperforms the other two algorithms in five instances. Additionally, it has shorter runtimes compared to the SARSA algorithm and similar runtimes to the Q‐Learning algorithm across all instances. Second, upon analysing the results, it was found that using the reward strategy contributes to obtaining the best results for all algorithms. Among the 24 combinations of 3 algorithms and 8 instances, 17 combinations achieved the best results when the reward strategy was set to .
{"title":"Reinforcement learning for the traveling salesman problem: Performance comparison of three algorithms","authors":"Jiaying Wang, Chenglong Xiao, Shanshan Wang, Yaqi Ruan","doi":"10.1049/tje2.12303","DOIUrl":"https://doi.org/10.1049/tje2.12303","url":null,"abstract":"Travelling salesman problem (TSP) is one of the most famous problems in graph theory, as well as one of the typical nondeterministic polynomial time (NP)‐hard problems in combinatorial optimization. Reinforcement learning (RL) has been widely regarded as an effective tool for solving combinatorial optimization problems. This paper attempts to solve the TSP problem using different reinforcement learning algorithms and evaluated the performance of three RL algorithms (Q‐Learning, SARSA, and Double Q‐Learning) under different reward functions, ε‐greedy decay strategies, and running times. A comprehensive analysis and comparison of the three algorithms mentioned above were conducted in the experiment. First, the experimental results indicate that the Double Q‐Learning algorithm is the best algorithm. Among the eight TSP instances, the Double Q‐Learning algorithm outperforms the other two algorithms in five instances. Additionally, it has shorter runtimes compared to the SARSA algorithm and similar runtimes to the Q‐Learning algorithm across all instances. Second, upon analysing the results, it was found that using the reward strategy contributes to obtaining the best results for all algorithms. Among the 24 combinations of 3 algorithms and 8 instances, 17 combinations achieved the best results when the reward strategy was set to .","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74662201","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}
An experimental study was conducted to investigate the phenomenon of UAV attitude instability caused by large vibrations affecting single‐rotor UAV airborne equipment. Appropriate measurement points were selected to collect vibration signals from the unmanned aerial platform during takeoff and flight of the drone. The time‐domain response and power spectral density of the unmanned aerial platform were then obtained. Establish a dynamic model of the vibration reduction system for an unmanned aerial platform and design a two‐stage vibration reduction structure for the unmanned aerial platform. Through field flight tests of unmanned aerial vehicles, it has been demonstrated that the maximum time domain response of the platform after vibration reduction is 8.75 g (less than 50 g), and the maximum root mean square value of the power spectral density (PSD) is 1.82 g (less than 3 g). The designed secondary vibration reduction structure can serve as a reference for the design of vibration reduction in unmanned aerial vehicles.
{"title":"Research of the single‐rotor UAV gimbal vibration test","authors":"Guangchen Xu, Zhenliang Yu, Guangming Liu","doi":"10.1049/tje2.12306","DOIUrl":"https://doi.org/10.1049/tje2.12306","url":null,"abstract":"An experimental study was conducted to investigate the phenomenon of UAV attitude instability caused by large vibrations affecting single‐rotor UAV airborne equipment. Appropriate measurement points were selected to collect vibration signals from the unmanned aerial platform during takeoff and flight of the drone. The time‐domain response and power spectral density of the unmanned aerial platform were then obtained. Establish a dynamic model of the vibration reduction system for an unmanned aerial platform and design a two‐stage vibration reduction structure for the unmanned aerial platform. Through field flight tests of unmanned aerial vehicles, it has been demonstrated that the maximum time domain response of the platform after vibration reduction is 8.75 g (less than 50 g), and the maximum root mean square value of the power spectral density (PSD) is 1.82 g (less than 3 g). The designed secondary vibration reduction structure can serve as a reference for the design of vibration reduction in unmanned aerial vehicles.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78198351","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}
Hasanain B. Altalebi, Alaa A. Atiyah, Saad B. H. Farid
Abstract Here, the eligibility of silicone rubber‐nanoceramic composites as flexible substrates for sub‐6 GHz 5G antennas is investigated. Two different composites are prepared using the solution mixing method, namely mono and hybrid composites. The reflection and transmission coefficient (S‐parameters) of composites are measured using a rectangular waveguide‐based transmission line technique in conjunction with a Vector Network Analyzer (VNA) at C‐band frequencies (4–8 GHz). The Nicolson–Ross–Weir (NRW) algorithm is adopted to extract the complex permittivity and loss tangent of the material under test. Due to the synergetic effect, the silicone rubber hybrid composite (0.12BiVO 4 +0.12LaNbO 4 ) exhibits the advantage of a lowered loss tangent while retaining a good dielectric constant at 5.78 GHz. A rectangular microstrip patch antenna is designed and simulated with CST software using 0.12BVO/0.12LNO/0.76SR composite as a substrate. Moreover, based on the simulation, the antenna with the proposed substrate has acceptable performance at 5.78 GHz with the return loss, directivity, and gain of −25.05 dB, 5.46 dBi and 2.74 dBi, respectively. As a result, the composite material's ability to act as a suitable substrate for a 5 GHz Wi‐Fi antenna is confirmed.
{"title":"Silicone rubber‐nanoceramic composites for 5G antenna substrates","authors":"Hasanain B. Altalebi, Alaa A. Atiyah, Saad B. H. Farid","doi":"10.1049/tje2.12312","DOIUrl":"https://doi.org/10.1049/tje2.12312","url":null,"abstract":"Abstract Here, the eligibility of silicone rubber‐nanoceramic composites as flexible substrates for sub‐6 GHz 5G antennas is investigated. Two different composites are prepared using the solution mixing method, namely mono and hybrid composites. The reflection and transmission coefficient (S‐parameters) of composites are measured using a rectangular waveguide‐based transmission line technique in conjunction with a Vector Network Analyzer (VNA) at C‐band frequencies (4–8 GHz). The Nicolson–Ross–Weir (NRW) algorithm is adopted to extract the complex permittivity and loss tangent of the material under test. Due to the synergetic effect, the silicone rubber hybrid composite (0.12BiVO 4 +0.12LaNbO 4 ) exhibits the advantage of a lowered loss tangent while retaining a good dielectric constant at 5.78 GHz. A rectangular microstrip patch antenna is designed and simulated with CST software using 0.12BVO/0.12LNO/0.76SR composite as a substrate. Moreover, based on the simulation, the antenna with the proposed substrate has acceptable performance at 5.78 GHz with the return loss, directivity, and gain of −25.05 dB, 5.46 dBi and 2.74 dBi, respectively. As a result, the composite material's ability to act as a suitable substrate for a 5 GHz Wi‐Fi antenna is confirmed.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135389400","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}
Umar Musa, Shaharil Mohd Shah, Huda A Majid, Ismail Ahmat Mahadi, Kamal A Rahim Mohamad, Muhammad Sani Yahya, Zuhairiah Zainal Abidin
Abstract In this work, the nonlinearity of PIN diode on frequency reconfigurable patch antenna is investigated. To perform frequency reconfiguration, the proposed design makes use of the switching capabilities of a PIN diode. The antenna has a dimension of 41 × 44 mm 2 corresponding to 0.33 λ 0 × 0.35 λ 0 , where λ 0 represents the wavelength in free space at 2.4 GHz fabricated on Rogers Duroid RO3003 TM material. In the OFF state of the PIN diode, a single resonance (ISM 5.8 GHz) is achieved. However, in the ON state of the PIN diode, a dual‐resonance (ISM 5.8 GHz and 2.4 GHz) is achieved. A directional and bidirectional radiation pattern can be observed in the E ‐plane at 5.8 GHz and 2.4 GHz, respectively, and omnidirectional radiation patterns can be viewed in the H ‐plane for both 5.8 GHz and 2.4 GHz. The gain is measured to be 4.84 dBi at 2.4 GHz and 5.87 dBi at 5.8 GHz, with total efficiencies of 91.8% and 92.5% at 5.8 GHz and 2.4 GHz, respectively. Two‐tone nonlinear measurements at 2.4 GHz and 5.8 GHz are used to evaluate the PIN diode. Several third‐order intermodulation distortion products (IMD3) frequencies are observed with input powers between 0 and 20 dBm. The IMD3 at 2.4 GHz is −36.18 dBm, while at 5.8 GHz is −47.19 dBm and the third‐order input intercept point (IIP3) of +66.65 dBm is obtained at 2.4 GHz, while +22.69 dBm at 5.8 GHz. Additionally, at 2.4 GHz, the 1‐dB gain compression (P 1‐dB ) could not be identified, showing that the antenna behaves linearly within the spectrum of input power. Similarly, the P 1‐dB is detected at 14.8 dBm input power at 5.8 GHz. The proposed antenna works in the linear region up to an input power level of 15 dBm, where the received signal strength of the IMD3 is minimal, according to the measurement of the nonlinearity caused by the PIN diode. The nonlinearity results confirm that the active reconfigurable antenna designed and implemented in this work is suitable for use in the 2.4 GHz and 5.8 GHz bands for indoor and short‐range communication applications. Furthermore, the assessment of nonlinearity provides a deeper understanding of and helps mitigate the negative effects of nonlinearity on the proposed antenna. This measurement assists in refining biasing, selecting suitable linearization methods, improving the design, and evaluating performance at the system level. Ultimately, it enhances antenna performance and expands frequency reconfigurability by enabling optimization across multiple aspects.
{"title":"Investigation of the nonlinearity of PIN diode on frequency reconfigurable patch antenna","authors":"Umar Musa, Shaharil Mohd Shah, Huda A Majid, Ismail Ahmat Mahadi, Kamal A Rahim Mohamad, Muhammad Sani Yahya, Zuhairiah Zainal Abidin","doi":"10.1049/tje2.12308","DOIUrl":"https://doi.org/10.1049/tje2.12308","url":null,"abstract":"Abstract In this work, the nonlinearity of PIN diode on frequency reconfigurable patch antenna is investigated. To perform frequency reconfiguration, the proposed design makes use of the switching capabilities of a PIN diode. The antenna has a dimension of 41 × 44 mm 2 corresponding to 0.33 λ 0 × 0.35 λ 0 , where λ 0 represents the wavelength in free space at 2.4 GHz fabricated on Rogers Duroid RO3003 TM material. In the OFF state of the PIN diode, a single resonance (ISM 5.8 GHz) is achieved. However, in the ON state of the PIN diode, a dual‐resonance (ISM 5.8 GHz and 2.4 GHz) is achieved. A directional and bidirectional radiation pattern can be observed in the E ‐plane at 5.8 GHz and 2.4 GHz, respectively, and omnidirectional radiation patterns can be viewed in the H ‐plane for both 5.8 GHz and 2.4 GHz. The gain is measured to be 4.84 dBi at 2.4 GHz and 5.87 dBi at 5.8 GHz, with total efficiencies of 91.8% and 92.5% at 5.8 GHz and 2.4 GHz, respectively. Two‐tone nonlinear measurements at 2.4 GHz and 5.8 GHz are used to evaluate the PIN diode. Several third‐order intermodulation distortion products (IMD3) frequencies are observed with input powers between 0 and 20 dBm. The IMD3 at 2.4 GHz is −36.18 dBm, while at 5.8 GHz is −47.19 dBm and the third‐order input intercept point (IIP3) of +66.65 dBm is obtained at 2.4 GHz, while +22.69 dBm at 5.8 GHz. Additionally, at 2.4 GHz, the 1‐dB gain compression (P 1‐dB ) could not be identified, showing that the antenna behaves linearly within the spectrum of input power. Similarly, the P 1‐dB is detected at 14.8 dBm input power at 5.8 GHz. The proposed antenna works in the linear region up to an input power level of 15 dBm, where the received signal strength of the IMD3 is minimal, according to the measurement of the nonlinearity caused by the PIN diode. The nonlinearity results confirm that the active reconfigurable antenna designed and implemented in this work is suitable for use in the 2.4 GHz and 5.8 GHz bands for indoor and short‐range communication applications. Furthermore, the assessment of nonlinearity provides a deeper understanding of and helps mitigate the negative effects of nonlinearity on the proposed antenna. This measurement assists in refining biasing, selecting suitable linearization methods, improving the design, and evaluating performance at the system level. Ultimately, it enhances antenna performance and expands frequency reconfigurability by enabling optimization across multiple aspects.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135304856","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}
Establishing effective feature descriptors is a crucial step in 3D point cloud registration task. Existing manual‐based methods are noise‐susceptible and time‐consuming when running on low‐cost edge computing devices. To this end, the authors proposed a Local Reference Frame (LRF) based approach that can quickly and robustly register point clouds by using a novel lightweight local‐spherical grid weighted descriptor (LSGWD). Firstly, the LRF of the proposed algorithm is established by the covariance matrix eigenvector of KeyPoint's spherical support set and the centroid vector's projection on its orthogonal plane. Then the spherical support is grided to 32 bins, and the 4D geometric features of each subset are constructed by the centroid moment and the cosine value of the angles between the centroid vector and axes of LRF. Secondly, to restrain the insufficient discriminative information presented in the purely geometric features, the Gaussian projection and gradient mapping are proposed to calculate the smooth density and the correlation of structural characteristics, which are obtained as the distribution information of each bin to weigh the feature representation. Finally, the 32 × 4‐dimensional KeyPoint descriptor is obtained and used in the 3D point cloud registration framework. Experiments are carried out on three test datasets and real scene data. Compared to previous baselines, our descriptor achieves the state‐of‐the‐art performance in terms of efficiency and accuracy owing to its compact structure and noise robustness. The proposed method enhances the recognition and registration performance of 3D point cloud matching in low‐cost edge computing applications.
{"title":"A weighted local‐spherical grid based lightweight descriptor for 3D point cloud registration","authors":"Shouquan Che, Cong‐Wang Bao, Jian‐Feng Lu","doi":"10.1049/tje2.12304","DOIUrl":"https://doi.org/10.1049/tje2.12304","url":null,"abstract":"Establishing effective feature descriptors is a crucial step in 3D point cloud registration task. Existing manual‐based methods are noise‐susceptible and time‐consuming when running on low‐cost edge computing devices. To this end, the authors proposed a Local Reference Frame (LRF) based approach that can quickly and robustly register point clouds by using a novel lightweight local‐spherical grid weighted descriptor (LSGWD). Firstly, the LRF of the proposed algorithm is established by the covariance matrix eigenvector of KeyPoint's spherical support set and the centroid vector's projection on its orthogonal plane. Then the spherical support is grided to 32 bins, and the 4D geometric features of each subset are constructed by the centroid moment and the cosine value of the angles between the centroid vector and axes of LRF. Secondly, to restrain the insufficient discriminative information presented in the purely geometric features, the Gaussian projection and gradient mapping are proposed to calculate the smooth density and the correlation of structural characteristics, which are obtained as the distribution information of each bin to weigh the feature representation. Finally, the 32 × 4‐dimensional KeyPoint descriptor is obtained and used in the 3D point cloud registration framework. Experiments are carried out on three test datasets and real scene data. Compared to previous baselines, our descriptor achieves the state‐of‐the‐art performance in terms of efficiency and accuracy owing to its compact structure and noise robustness. The proposed method enhances the recognition and registration performance of 3D point cloud matching in low‐cost edge computing applications.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79669375","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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