Pub Date : 2024-07-11DOI: 10.1088/1361-6501/ad6206
Wentao Zhao, Chao Zhang, Jianguo Wang, Fengshou Gu, Oscar García Peyrano, Shuai Wang, Da Lv
One of the key critical technologies in the digital revolution of measurement technology is digital twin. The literature now in publication indicates that the advancement and use of digital twin technology will raise the bar for improvement in the measuring sector. The current literature on the creation and use of digital twin technology is reviewed first, followed by a list of recognized definitions and a summary of the three main categories of digital twin models for easy reference. The main drawbacks of conventional measurement technology in the application process are enumerated here: direct measurement is challenging, measuring multiple parameters at once is challenging, sensors' influence cannot be disregarded, and the accuracy of measurement results is not satisfactory. To address these issues, this review outlines the benefits and potential uses of digital twin technology in measurement, as well as a summary of six significant contributions. Strong application and robustness, the ability to visualize the process of changing a measurement parameter, simultaneous measurement of many parameters, cheap measurement costs, data security, integrity, high availability, and intelligent measurement are only a few of these features. It is explored where digital twin research in measurement technology is headed in the future. A new digital solution and path for measuring technology development are offered by the digital twin and virtual sensor simulation methods.
{"title":"Application and research trend of digital twin in measurement technology","authors":"Wentao Zhao, Chao Zhang, Jianguo Wang, Fengshou Gu, Oscar García Peyrano, Shuai Wang, Da Lv","doi":"10.1088/1361-6501/ad6206","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6206","url":null,"abstract":"\u0000 One of the key critical technologies in the digital revolution of measurement technology is digital twin. The literature now in publication indicates that the advancement and use of digital twin technology will raise the bar for improvement in the measuring sector. The current literature on the creation and use of digital twin technology is reviewed first, followed by a list of recognized definitions and a summary of the three main categories of digital twin models for easy reference. The main drawbacks of conventional measurement technology in the application process are enumerated here: direct measurement is challenging, measuring multiple parameters at once is challenging, sensors' influence cannot be disregarded, and the accuracy of measurement results is not satisfactory. To address these issues, this review outlines the benefits and potential uses of digital twin technology in measurement, as well as a summary of six significant contributions. Strong application and robustness, the ability to visualize the process of changing a measurement parameter, simultaneous measurement of many parameters, cheap measurement costs, data security, integrity, high availability, and intelligent measurement are only a few of these features. It is explored where digital twin research in measurement technology is headed in the future. A new digital solution and path for measuring technology development are offered by the digital twin and virtual sensor simulation methods.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141657278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.1088/1361-6501/ad6205
Yaofu Yu, Zhen Zhang, Weiguo Lin
Compressed sensing (CS) has shown a huge advantage on data compressing and transmission, and designing a suitable measurement matrix is helpful for performance of the CS. Recently, traditional CS measurement matrices have been well applied in many fields, however, there are still problems, such as long construction time, large storage space, and poor real-time performance. Aiming at above problems, combining the advantages of sparse measurement matrix and identity matrix, a new construction method of measurement matrix named Block Sparse Random Measurement Matrix (BSRMM) is proposed. The proposed matrix satisfies restricted isometry property (RIP) with high probability, has faster construction speed, smaller storage space, and is easy to implement. Finally, the compressed sampling process with the BSRMM is implemented on a wireless sensor node with microprocessor STM32F407, and a good reconstruction effect is achieved on the simulated leak signals from a small gas pipeline network, which verifies the effectiveness of the BSRMM.
{"title":"A Compressed Sensing Random Measurement Matrix Construction Method: Block Sparse Random Measurement Matrix","authors":"Yaofu Yu, Zhen Zhang, Weiguo Lin","doi":"10.1088/1361-6501/ad6205","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6205","url":null,"abstract":"\u0000 Compressed sensing (CS) has shown a huge advantage on data compressing and transmission, and designing a suitable measurement matrix is helpful for performance of the CS. Recently, traditional CS measurement matrices have been well applied in many fields, however, there are still problems, such as long construction time, large storage space, and poor real-time performance. Aiming at above problems, combining the advantages of sparse measurement matrix and identity matrix, a new construction method of measurement matrix named Block Sparse Random Measurement Matrix (BSRMM) is proposed. The proposed matrix satisfies restricted isometry property (RIP) with high probability, has faster construction speed, smaller storage space, and is easy to implement. Finally, the compressed sampling process with the BSRMM is implemented on a wireless sensor node with microprocessor STM32F407, and a good reconstruction effect is achieved on the simulated leak signals from a small gas pipeline network, which verifies the effectiveness of the BSRMM.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141656324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the booming development of modern industrial technology, rotating machinery fault diagnosis is of great significance to improve the safety, efficiency and sustainable development of industrial production. Machine learning as an effective solution for fault identification, has advantages over traditional fault diagnosis solutions in processing complex data, achieving automation and intelligence, adapting to different fault types, and continuously optimizing. It has high application value and broad development prospects in the field of fault diagnosis of rotating machinery. Therefore, this article reviews machine learning and its applications in intelligent fault diagnosis technology and covers advanced topics in emerging deep learning techniques and optimization methods. Firstly, this article briefly introduces the theories of several main machine learning methods, including Extreme Learning Machines (ELM), Support Vector Machines (SVM), Convolutional Neural Networks (CNN), Deep Belief Networks (DBN) and related emerging deep learning technologies such as Transformer, adversarial neural network (GAN) and graph neural network (GNN) in recent years. The optimization techniques for diagnosing faults in rotating machinery are subsequently investigated. Then, a brief introduction is given to the papers on the application of these machine learning methods in the field of rotating machinery fault diagnosis, and the application characteristics of various methods are summarized. Finally, this survey discusses the problems to be solved by machine learning in fault diagnosis of rotating machinery and proposes an outlook.
{"title":"A Survey on Fault Diagnosis of Rotating Machinery Based on Machine Learning","authors":"Qi Wang, Rui Huang, Jianbin Xiong, Xiangjun Dong, Jianxiang Yang, Yipeng Wu, Yinbo Wu, Tiantian Lu","doi":"10.1088/1361-6501/ad6203","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6203","url":null,"abstract":"\u0000 With the booming development of modern industrial technology, rotating machinery fault diagnosis is of great significance to improve the safety, efficiency and sustainable development of industrial production. Machine learning as an effective solution for fault identification, has advantages over traditional fault diagnosis solutions in processing complex data, achieving automation and intelligence, adapting to different fault types, and continuously optimizing. It has high application value and broad development prospects in the field of fault diagnosis of rotating machinery. Therefore, this article reviews machine learning and its applications in intelligent fault diagnosis technology and covers advanced topics in emerging deep learning techniques and optimization methods. Firstly, this article briefly introduces the theories of several main machine learning methods, including Extreme Learning Machines (ELM), Support Vector Machines (SVM), Convolutional Neural Networks (CNN), Deep Belief Networks (DBN) and related emerging deep learning technologies such as Transformer, adversarial neural network (GAN) and graph neural network (GNN) in recent years. The optimization techniques for diagnosing faults in rotating machinery are subsequently investigated. Then, a brief introduction is given to the papers on the application of these machine learning methods in the field of rotating machinery fault diagnosis, and the application characteristics of various methods are summarized. Finally, this survey discusses the problems to be solved by machine learning in fault diagnosis of rotating machinery and proposes an outlook.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141657690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.1088/1361-6501/ad6207
Xiaoxia Zhang, Dong-e Zhao, Yayun Ma, Xuefeng Yang, W. Chu
The distortion degree of the interference pattern of vortex light is measured to achieve high-precision measurement of small angles. In this paper, a regression prediction model based on the Stacking ensemble learning algorithm is constructed. Firstly, by altering the optical axis at small angles within the range of 0.0006° to 0.3° in a vortex optical conjugate interference system, corresponding interference patterns were obtained. The angle formed by the centroids of the upper two petals of the deformed interference patterns and the center was extracted as a feature for dataset construction. The dataset was randomly split into training and testing sets in a 7:3 ratio. Secondly, four models, including SVR, PSO-BP, GPR, and Stacking ensemble algorithm, were optimized for hyperparameters, trained, and evaluated. Comparative analysis of prediction performance was conducted using coefficients of determination, root mean square errors, and mean absolute errors. Based on multiple random splits of the dataset for training and prediction, it was observed that compared to single learners, the ensemble model reduced the average relative error by 0.2829%, demonstrating better prediction performance and stronger stability by combining the advantages of primary learners. Additionally, the Stacking model achieved a measurement accuracy of 0.0006°, with the relative error maintained within 0.6%, indicating the feasibility of high-precision measurement of optical axis micro-angles using machine learning and vortex optical conjugate interference systems.
{"title":"Research on high-precision angular measurement based on machine learning and optical vortex interference technology","authors":"Xiaoxia Zhang, Dong-e Zhao, Yayun Ma, Xuefeng Yang, W. Chu","doi":"10.1088/1361-6501/ad6207","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6207","url":null,"abstract":"\u0000 The distortion degree of the interference pattern of vortex light is measured to achieve high-precision measurement of small angles. In this paper, a regression prediction model based on the Stacking ensemble learning algorithm is constructed. Firstly, by altering the optical axis at small angles within the range of 0.0006° to 0.3° in a vortex optical conjugate interference system, corresponding interference patterns were obtained. The angle formed by the centroids of the upper two petals of the deformed interference patterns and the center was extracted as a feature for dataset construction. The dataset was randomly split into training and testing sets in a 7:3 ratio. Secondly, four models, including SVR, PSO-BP, GPR, and Stacking ensemble algorithm, were optimized for hyperparameters, trained, and evaluated. Comparative analysis of prediction performance was conducted using coefficients of determination, root mean square errors, and mean absolute errors. Based on multiple random splits of the dataset for training and prediction, it was observed that compared to single learners, the ensemble model reduced the average relative error by 0.2829%, demonstrating better prediction performance and stronger stability by combining the advantages of primary learners. Additionally, the Stacking model achieved a measurement accuracy of 0.0006°, with the relative error maintained within 0.6%, indicating the feasibility of high-precision measurement of optical axis micro-angles using machine learning and vortex optical conjugate interference systems.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141658134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.1088/1361-6501/ad6204
zhengliang zhu, Cong Hu, Weiwang Chen, Xinzhi Wang
The environment of buildings and outdoor transportation in urban areas is becoming increasingly complex. This poses a challenge for rescue pathfinding once an emergency occurs, which relies on the generation of road network models. To better balance efficiency and accuracy in pathfinding, a three-dimensional integrated road network model (3D-IRNM) derived from grid and topological road network models was developed in this study. Firstly, a cross-platform data loading method from BIM to Geographic Information Systems (GIS) is proposed, to serve as a data source for road network model generation and visual enhancement. Then, the topological and grid road network models are generated in indoor spaces of different functions, with IRNM obtained by the integration strategy. The 3D-IRNM can be formed by extracting indoor vertical paths from the stairs, and connecting them with the IRNM of each floor. To further combine the 3D-IRNM with outdoor environments, a CrossNode model is then proposed. Besides, an adaptive pathfinding algorithm is also proposed. Finally, the construction of an emergency path-finding system based on GIS technology is achieved. The pathfinding algorithm and the structure of 3D-IRNM helps the pathfinding both efficiency and accuracy. The practicability of the designed 3D-IRNM together with its pathfinding algorithm is well verified.
{"title":"Integration of two different road network models for emergency rescue pathfinding in indoor and outdoor environments","authors":"zhengliang zhu, Cong Hu, Weiwang Chen, Xinzhi Wang","doi":"10.1088/1361-6501/ad6204","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6204","url":null,"abstract":"\u0000 The environment of buildings and outdoor transportation in urban areas is becoming increasingly complex. This poses a challenge for rescue pathfinding once an emergency occurs, which relies on the generation of road network models. To better balance efficiency and accuracy in pathfinding, a three-dimensional integrated road network model (3D-IRNM) derived from grid and topological road network models was developed in this study. Firstly, a cross-platform data loading method from BIM to Geographic Information Systems (GIS) is proposed, to serve as a data source for road network model generation and visual enhancement. Then, the topological and grid road network models are generated in indoor spaces of different functions, with IRNM obtained by the integration strategy. The 3D-IRNM can be formed by extracting indoor vertical paths from the stairs, and connecting them with the IRNM of each floor. To further combine the 3D-IRNM with outdoor environments, a CrossNode model is then proposed. Besides, an adaptive pathfinding algorithm is also proposed. Finally, the construction of an emergency path-finding system based on GIS technology is achieved. The pathfinding algorithm and the structure of 3D-IRNM helps the pathfinding both efficiency and accuracy. The practicability of the designed 3D-IRNM together with its pathfinding algorithm is well verified.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141657537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-10DOI: 10.1088/1361-6501/ad6175
Peng Xu, Yan Li, Gaoge Hu, Guangle Gao
A reliable and autonomous navigation system is crucial for the achievement of high survivability of spacecraft. As a novel autonomous navigation system, inertial/spectral redshift(INS/SRS) integrated navigation system can correct the navigation error of INS through redshift and direction vector information from celestial body. However, Since SRS need to obtain the position measurement by integrating the velocity information of the spacecraft, the position error from INS/SRS is diverged. Thus, this paper investigates a direction vector assisted INS/SRS integrated navigation system for the spacecraft. In this paper, the relationship among the position of spacecraft, redshift and direction vector from celestial body are investigated. And then a direction vector assisted SRS is proposed which can solve the position information of spacecraft directly by redshift and direction vector information. Finally, the direction vector assisted SRS has been combined with INS as the direction vector assisted INS/SRS integrated navigation system. Simulations and comprehensive analysis have demonstrated the proposed integrated navigation system has better navigation performance than INS/SRS integrated navigation system.
可靠的自主导航系统对于实现航天器的高生存能力至关重要。作为一种新型自主导航系统，惯性/光谱红移（INS/SRS）综合导航系统可以通过天体的红移和方向矢量信息纠正 INS 的导航误差。然而，由于 SRS 需要通过整合航天器的速度信息来获得位置测量值，因此 INS/SRS 的位置误差是有偏差的。因此，本文研究了一种方向矢量辅助 INS/SRS 集成导航系统。本文研究了航天器位置、红移和来自天体的方向矢量之间的关系。然后提出了一种方向矢量辅助 SRS，它可以直接通过红移和方向矢量信息来解决航天器的位置信息。最后，方向矢量辅助 SRS 与 INS 相结合，成为方向矢量辅助 INS/SRS 集成导航系统。仿真和综合分析表明，所提出的综合导航系统比 INS/SRS 综合导航系统具有更好的导航性能。
{"title":"The Direction Vector Assisted INS/Spectral Redshift Integrated Navigation System for Spacecraft","authors":"Peng Xu, Yan Li, Gaoge Hu, Guangle Gao","doi":"10.1088/1361-6501/ad6175","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6175","url":null,"abstract":"\u0000 A reliable and autonomous navigation system is crucial for the achievement of high survivability of spacecraft. As a novel autonomous navigation system, inertial/spectral redshift(INS/SRS) integrated navigation system can correct the navigation error of INS through redshift and direction vector information from celestial body. However, Since SRS need to obtain the position measurement by integrating the velocity information of the spacecraft, the position error from INS/SRS is diverged. Thus, this paper investigates a direction vector assisted INS/SRS integrated navigation system for the spacecraft. In this paper, the relationship among the position of spacecraft, redshift and direction vector from celestial body are investigated. And then a direction vector assisted SRS is proposed which can solve the position information of spacecraft directly by redshift and direction vector information. Finally, the direction vector assisted SRS has been combined with INS as the direction vector assisted INS/SRS integrated navigation system. Simulations and comprehensive analysis have demonstrated the proposed integrated navigation system has better navigation performance than INS/SRS integrated navigation system.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141659136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-10DOI: 10.1088/1361-6501/ad6172
Zhen Lyu, Weiwei Cai, Yingzheng Liu
This paper reports a high-frequency event-triggered background-oriented schlieren (BOS) technique using a combination of an event-triggered camera and dynamic projection. To combine the advantages of continuous and pulsed illumination for the event-triggered camera, a novel background pattern is first developed to incorporate static and dynamic textures generated through projection utilizing a dynamic mirror device (DMD). Then, a specific post-processing algorithm is proposed to reconstruct frames with high time accuracy from event data. This technique allows for the continuous observation and capturing of flows at 4000 frames per second (FPS) with a very low cost, breaking through the short operating times of current high-frame-rate BOS. Moreover, the proposed BOS technique can visualize the flow in real-time with high temporal accuracy, a capability that is challenging to achieve with traditional BOS. To examine the proposed technique, BOS experiments were conducted on a sweeping jet actuator with various inlet pressure. The sweeping dynamics and the start-up process of the sweeping jet at various inlet pressure were visualized and investigated. It is found that the proposed event-triggered BOS can continuously visualize and record the jet flow at a resolution of 1280 × 720 pixels with an equivalent frame rate of up to 4000 FPS. The oscillation frequency of the sweeping jet was found to increase linearly with increasing inlet pressure. It reaches 117.2 Hz at an inlet pressure of 0.5 Mpa. Within the first ten milliseconds or so of start-up, the shape of the sweep was found to be symmetrical. Within the next hundred milliseconds, the jet commences to sweep and saturates. The start-up time of the sweeping jet was quantitatively measured and was observed to decrease with increased inlet pressures.
{"title":"An event-triggered background-oriented schlieren technique combined with dynamic projection using dynamic mirror device","authors":"Zhen Lyu, Weiwei Cai, Yingzheng Liu","doi":"10.1088/1361-6501/ad6172","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6172","url":null,"abstract":"\u0000 This paper reports a high-frequency event-triggered background-oriented schlieren (BOS) technique using a combination of an event-triggered camera and dynamic projection. To combine the advantages of continuous and pulsed illumination for the event-triggered camera, a novel background pattern is first developed to incorporate static and dynamic textures generated through projection utilizing a dynamic mirror device (DMD). Then, a specific post-processing algorithm is proposed to reconstruct frames with high time accuracy from event data. This technique allows for the continuous observation and capturing of flows at 4000 frames per second (FPS) with a very low cost, breaking through the short operating times of current high-frame-rate BOS. Moreover, the proposed BOS technique can visualize the flow in real-time with high temporal accuracy, a capability that is challenging to achieve with traditional BOS. To examine the proposed technique, BOS experiments were conducted on a sweeping jet actuator with various inlet pressure. The sweeping dynamics and the start-up process of the sweeping jet at various inlet pressure were visualized and investigated. It is found that the proposed event-triggered BOS can continuously visualize and record the jet flow at a resolution of 1280 × 720 pixels with an equivalent frame rate of up to 4000 FPS. The oscillation frequency of the sweeping jet was found to increase linearly with increasing inlet pressure. It reaches 117.2 Hz at an inlet pressure of 0.5 Mpa. Within the first ten milliseconds or so of start-up, the shape of the sweep was found to be symmetrical. Within the next hundred milliseconds, the jet commences to sweep and saturates. The start-up time of the sweeping jet was quantitatively measured and was observed to decrease with increased inlet pressures.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141660538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-10DOI: 10.1088/1361-6501/ad6173
A. D’Alessandro, A. Meoni, Ruben Rodríguez Romero, E. García-Macías, Marco Viviani, F. Ubertini
Civil constructions significantly contribute to greenhouse gas emissions and entail extensive energy and resource consumption, leading to a substantial ecological footprint. Research into eco-friendly engineering solutions is therefore currently imperative, particularly to mitigate the impact of concrete technology. Among potential alternatives, shot-earth-concrete, which combines cement and earth as a binder matrix and is applied via spraying, emerges as a promising option. Furthermore, this composite material allows for the incorporation of nano and micro-fillers, thereby providing room for enhancing mechanical properties and providing multifunctional capabilities. This paper investigates the damage detection capabilities of a novel smart shot-earth concrete with carbon microfibers, by investigating the strain sensing performance of a full-scale vault with a span of 4 meters, mechanically tested until failure. The material's strain and damage sensing capabilities involve its capacity to produce an electrical response (manifested as a relative change in resistance) corresponding to the applied strain in its uncracked state, as well as to exhibit a significant alteration in electrical resistance upon cracking. A detailed multiphysics numerical (i.e. mechanical and electrical) model is also developed to aid the interpretation of the experimental results. The experimental test was conducted by the application of an increasing vertical load at a quarter of the span, while modelling of the element was carried out by considering a piezoresistive material, with coupled mechanical and electrical constitutive properties, including a new law to reproduce the degradation of the electrical conductivity with tensile cracking. Another notable aspect of the simulation was the consideration of the effects of the electrical conduction through the rebars, which was found critical to accurately reproduce the full-scale electromechanical response of the vault. By correlating the outcomes from external displacement transducers with the self-monitoring features inherent in the proposed material, significant insights were gleaned. The findings indicated that the proposed smart-earth composite, besides being well suited for structural applications, also exhibits a distinctive electromechanical behaviour that enables the early detection of damage initiation. The results of the paper represent an important step toward the real application of smart earth-concrete in the construction field, demonstrating the effectiveness and feasibility of full-scale strain and damage monitoring even in the presence of steel reinforcement.
{"title":"Full-scale testing and multiphysics modeling of a reinforced shot-earth concrete vault with self-sensing properties","authors":"A. D’Alessandro, A. Meoni, Ruben Rodríguez Romero, E. García-Macías, Marco Viviani, F. Ubertini","doi":"10.1088/1361-6501/ad6173","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6173","url":null,"abstract":"\u0000 Civil constructions significantly contribute to greenhouse gas emissions and entail extensive energy and resource consumption, leading to a substantial ecological footprint. Research into eco-friendly engineering solutions is therefore currently imperative, particularly to mitigate the impact of concrete technology. Among potential alternatives, shot-earth-concrete, which combines cement and earth as a binder matrix and is applied via spraying, emerges as a promising option. Furthermore, this composite material allows for the incorporation of nano and micro-fillers, thereby providing room for enhancing mechanical properties and providing multifunctional capabilities. This paper investigates the damage detection capabilities of a novel smart shot-earth concrete with carbon microfibers, by investigating the strain sensing performance of a full-scale vault with a span of 4 meters, mechanically tested until failure. The material's strain and damage sensing capabilities involve its capacity to produce an electrical response (manifested as a relative change in resistance) corresponding to the applied strain in its uncracked state, as well as to exhibit a significant alteration in electrical resistance upon cracking. A detailed multiphysics numerical (i.e. mechanical and electrical) model is also developed to aid the interpretation of the experimental results. The experimental test was conducted by the application of an increasing vertical load at a quarter of the span, while modelling of the element was carried out by considering a piezoresistive material, with coupled mechanical and electrical constitutive properties, including a new law to reproduce the degradation of the electrical conductivity with tensile cracking. Another notable aspect of the simulation was the consideration of the effects of the electrical conduction through the rebars, which was found critical to accurately reproduce the full-scale electromechanical response of the vault. By correlating the outcomes from external displacement transducers with the self-monitoring features inherent in the proposed material, significant insights were gleaned. The findings indicated that the proposed smart-earth composite, besides being well suited for structural applications, also exhibits a distinctive electromechanical behaviour that enables the early detection of damage initiation. The results of the paper represent an important step toward the real application of smart earth-concrete in the construction field, demonstrating the effectiveness and feasibility of full-scale strain and damage monitoring even in the presence of steel reinforcement.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141662916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The unique hysteretic characteristic of rubber bellows and the nonlinear flow of internal airflow in the system results in the significant nonlinear dynamic characteristic of throttling orifice type air damping air springs. To solve the problem of mathematical representation of dynamic characteristic and key parameters optimization of throttling orifice type air damping air spring, this paper comprehensively considers the hysteretic characteristic of rubber bellows under variable pressure, the nonlinear dynamic characteristic model and linear model of throttling orifice type air damping air spring are established based on the concepts of gas thermodynamics and fluid mechanics. The static and dynamic characteristic tests of the throttling orifice type air damping air spring are conducted, to verify the accuracy and effectiveness of the proposed model, and to reveal the influence laws of excitation amplitude, excitation frequency, and throttling orifice diameter on the quantitative characterization indexes. Finally, a complete throttling orifice diameter optimization method is proposed based on the eight-degree-of-freedom model of the entire vehicle. Optimization results illustrate that the RMS values of the vertical acceleration of the body and the vertical acceleration of the driver are decreased by 19.02% and 38.44%, respectively. Overall, the outcomes of this paper can provide the design idea and theoretical basis for air damping matching and active suspension control.
{"title":"Dynamic Characteristic Analysis and Key Parameter Optimization of Throttling Orifice Type Air Damping Air Spring","authors":"Junjie Chen, Ziqi Huang, Sheng Kang, Qin Yang, Xianju Yuan, Peng Huang, Yu Feng Gan","doi":"10.1088/1361-6501/ad6177","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6177","url":null,"abstract":"\u0000 The unique hysteretic characteristic of rubber bellows and the nonlinear flow of internal airflow in the system results in the significant nonlinear dynamic characteristic of throttling orifice type air damping air springs. To solve the problem of mathematical representation of dynamic characteristic and key parameters optimization of throttling orifice type air damping air spring, this paper comprehensively considers the hysteretic characteristic of rubber bellows under variable pressure, the nonlinear dynamic characteristic model and linear model of throttling orifice type air damping air spring are established based on the concepts of gas thermodynamics and fluid mechanics. The static and dynamic characteristic tests of the throttling orifice type air damping air spring are conducted, to verify the accuracy and effectiveness of the proposed model, and to reveal the influence laws of excitation amplitude, excitation frequency, and throttling orifice diameter on the quantitative characterization indexes. Finally, a complete throttling orifice diameter optimization method is proposed based on the eight-degree-of-freedom model of the entire vehicle. Optimization results illustrate that the RMS values of the vertical acceleration of the body and the vertical acceleration of the driver are decreased by 19.02% and 38.44%, respectively. Overall, the outcomes of this paper can provide the design idea and theoretical basis for air damping matching and active suspension control.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141659625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-10DOI: 10.1088/1361-6501/ad6174
Feng Cao, Ruirong Dang, Bo Dang, Huifeng Zheng, A. Ji, Zhanjun Chen
Gas-liquid counter-current flow in vertical annulus is involved in multiple industrial fields such as petroleum engineering. For instance, in coalbed methane wells where liquid pumping is utilized, obtaining real-time gas-liquid flow in the annulus is crucial for the development and management of coalbed methane wells. However, due to complex flow conditions, this requirement is difficult to achieve through traditional flow measurement means. Therefore, this paper proposes a flow prediction method based on multiple sets of differential pressure signals and machine learning techniques. Experiments on air-water two-phase flow were conducted on a vertical annulus pipe with an inner/outer diameter of 75mm/125mm and adjustable eccentricity. The probability density function and power spectral density function of three sets of differential pressure signals collected at different heights in the annulus pipe were used as model inputs, and gas-liquid flow rate as output. A gas-liquid two-phase flow prediction model was constructed based on the artificial neural network model, and the hyper-parameters of the model were optimized using Bayesian optimization. The results show that on a test dataset of 440 combinations of conditions with air superficial velocity of 0.06~5.04m/s, water superficial velocity of 0.03~0.25m/s, and pipe eccentricity of 0, 0.25, 0.5, 0.75, 1, the model can achieve average prediction errors of 9.12% and 29.34% for gas and water flow, respectively. This indicates that the method can be applied to non-throttling, non-intrusive measurement of phase flow under annulus gas-liquid counter-current flow conditions.
{"title":"Measurement of Air-Water Counter-Current Flow Rates in Vertical Annulus Using Multiple Differential Pressure Signals and Machine Learning","authors":"Feng Cao, Ruirong Dang, Bo Dang, Huifeng Zheng, A. Ji, Zhanjun Chen","doi":"10.1088/1361-6501/ad6174","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6174","url":null,"abstract":"\u0000 Gas-liquid counter-current flow in vertical annulus is involved in multiple industrial fields such as petroleum engineering. For instance, in coalbed methane wells where liquid pumping is utilized, obtaining real-time gas-liquid flow in the annulus is crucial for the development and management of coalbed methane wells. However, due to complex flow conditions, this requirement is difficult to achieve through traditional flow measurement means. Therefore, this paper proposes a flow prediction method based on multiple sets of differential pressure signals and machine learning techniques. Experiments on air-water two-phase flow were conducted on a vertical annulus pipe with an inner/outer diameter of 75mm/125mm and adjustable eccentricity. The probability density function and power spectral density function of three sets of differential pressure signals collected at different heights in the annulus pipe were used as model inputs, and gas-liquid flow rate as output. A gas-liquid two-phase flow prediction model was constructed based on the artificial neural network model, and the hyper-parameters of the model were optimized using Bayesian optimization. The results show that on a test dataset of 440 combinations of conditions with air superficial velocity of 0.06~5.04m/s, water superficial velocity of 0.03~0.25m/s, and pipe eccentricity of 0, 0.25, 0.5, 0.75, 1, the model can achieve average prediction errors of 9.12% and 29.34% for gas and water flow, respectively. This indicates that the method can be applied to non-throttling, non-intrusive measurement of phase flow under annulus gas-liquid counter-current flow conditions.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141661683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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