Hua Ding, Yanhong Huang, Jianqi Shi, Qi Shi, Yang Yang
Purpose Automatic guided vehicles (AGVs) are widely used in industrial fields. But most control strategies merely take the lateral force into consideration. This will reduce the accuracy, stability and robustness and will pay additional costs. Therefore, this paper aims to design a control strategy that initially considers lateral force. Thereby, it will improve the accuracy, stability and robustness and reduce the overall cost of AGV. Design/methodology/approach To achieve the goal of comprehensively improving AGV operating performance, this paper presents a new scheme, combining the dual-wheeled chassis model (DCM) using proportional–integral–differential (PID) control and a supporting quick response (QR) code navigation technology. DCM is the core, which analyzes the deviation caused by lateral force. Then, DCM with PID control by the control law is combined to suppress the errors. Meanwhile, QR code navigation technology provides effective data support for the control strategy. Findings Most AGV experiments are carried out in a standard environment. However, this study prepares unfavorable scenarios and operating conditions for the experiments that generate detailed data to demonstrate this study’s strategy, which can make an accurate, stable and robust operation process of AGV under various adverse environmental and mechanical factors. Originality/value This study proposed DCM, fully considering lateral force and converting the force into velocity. Subsequently, PID controls the speed of two wheels to reduce the error. QR code provides an efficient and low – cost way to obtain information. The three are cleverly combined as a novel industrial AGV control strategy, which can comprehensively improve the operating performance while reducing overall costs.
{"title":"A novel industrial AGV control strategy based on dual-wheel chassis model","authors":"Hua Ding, Yanhong Huang, Jianqi Shi, Qi Shi, Yang Yang","doi":"10.1108/aa-09-2021-0122","DOIUrl":"https://doi.org/10.1108/aa-09-2021-0122","url":null,"abstract":"\u0000Purpose\u0000Automatic guided vehicles (AGVs) are widely used in industrial fields. But most control strategies merely take the lateral force into consideration. This will reduce the accuracy, stability and robustness and will pay additional costs. Therefore, this paper aims to design a control strategy that initially considers lateral force. Thereby, it will improve the accuracy, stability and robustness and reduce the overall cost of AGV.\u0000\u0000\u0000Design/methodology/approach\u0000To achieve the goal of comprehensively improving AGV operating performance, this paper presents a new scheme, combining the dual-wheeled chassis model (DCM) using proportional–integral–differential (PID) control and a supporting quick response (QR) code navigation technology. DCM is the core, which analyzes the deviation caused by lateral force. Then, DCM with PID control by the control law is combined to suppress the errors. Meanwhile, QR code navigation technology provides effective data support for the control strategy.\u0000\u0000\u0000Findings\u0000Most AGV experiments are carried out in a standard environment. However, this study prepares unfavorable scenarios and operating conditions for the experiments that generate detailed data to demonstrate this study’s strategy, which can make an accurate, stable and robust operation process of AGV under various adverse environmental and mechanical factors.\u0000\u0000\u0000Originality/value\u0000This study proposed DCM, fully considering lateral force and converting the force into velocity. Subsequently, PID controls the speed of two wheels to reduce the error. QR code provides an efficient and low – cost way to obtain information. The three are cleverly combined as a novel industrial AGV control strategy, which can comprehensively improve the operating performance while reducing overall costs.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47061589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose The purpose of this paper is to propose a approach for data visualization and industrial process monitoring. Design/methodology/approach A deep enhanced t-distributed stochastic neighbor embedding (DESNE) neural network is proposed for data visualization and process monitoring. The DESNE is composed of two deep neural networks: stacked variant auto-encoder (SVAE) and a deep label-guided t-stochastic neighbor embedding (DLSNE) neural network. In the DESNE network, SVAE extracts informative features of the raw data set, and then DLSNE projects the extracted features to a two dimensional graph. Findings The proposed DESNE is verified on the Tennessee Eastman process and a real data set of blade icing of wind turbines. The results indicate that DESNE outperforms some visualization methods in process monitoring. Originality/value This paper has significant originality. A stacked variant auto-encoder is proposed for feature extraction. The stacked variant auto-encoder can improve the separation among classes. A deep label-guided t-SNE is proposed for visualization. A novel visualization-based process monitoring method is proposed.
{"title":"Industrial process data visualization based on a deep enhanced t-distributed stochastic neighbor embedding neural network","authors":"Weipeng Lu, Xue-feng Yan","doi":"10.1108/aa-09-2021-0123","DOIUrl":"https://doi.org/10.1108/aa-09-2021-0123","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to propose a approach for data visualization and industrial process monitoring.\u0000\u0000\u0000Design/methodology/approach\u0000A deep enhanced t-distributed stochastic neighbor embedding (DESNE) neural network is proposed for data visualization and process monitoring. The DESNE is composed of two deep neural networks: stacked variant auto-encoder (SVAE) and a deep label-guided t-stochastic neighbor embedding (DLSNE) neural network. In the DESNE network, SVAE extracts informative features of the raw data set, and then DLSNE projects the extracted features to a two dimensional graph.\u0000\u0000\u0000Findings\u0000The proposed DESNE is verified on the Tennessee Eastman process and a real data set of blade icing of wind turbines. The results indicate that DESNE outperforms some visualization methods in process monitoring.\u0000\u0000\u0000Originality/value\u0000This paper has significant originality. A stacked variant auto-encoder is proposed for feature extraction. The stacked variant auto-encoder can improve the separation among classes. A deep label-guided t-SNE is proposed for visualization. A novel visualization-based process monitoring method is proposed.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43484977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Changlong Ye, Yunfei Zang, Suyang Yu, Chun-ying Jiang
Purpose The purpose of this paper is to demonstrate a multipurpose inspection robot that can both walk on the ground and climb on poles. The structure design, size optimization, kinematics analysis, experiment and arithmetic of the robot are discussed in the paper. Design/methodology/approach The robot consists of three adjustable modules and a two-degree-of-freedom parallel mechanism in tandem, and the wheel-finger mechanism of each module can realize wheel-finger opening and closing for fast movement and obstacle crossing. This paper uses geometric analysis and simulation analysis to derive size optimization, and vector coordinate method to derive kinematics. Finally, the experiment is carried out by simulating the working environment of the robot. Findings The robot can realize ground walking and ground turning through the robot entity prototype experiment on the built working environment and efficiently realize 0°–90° pole climbing by the assemble design, optimization and machining. In addition, the robot can also smoothly complete the state transition process from 0° ground to 90° pole climbing. Furthermore, the robot shows good environmental self-adaptation and can complete daily inspection work. Originality/value The robot can pitch and yaw at a large angle and has six-legged characteristics. It is a multipurpose inspection robot that can walk on the ground and climb on poles. And through structure design, size optimization, kinematics analysis and simulation, the existing robots’ common shortcomings such as poor barrier-crossing ability and poor environmental adaptability are solved.
{"title":"Structure design and optimization of ground moving and pole climbing inspection robot","authors":"Changlong Ye, Yunfei Zang, Suyang Yu, Chun-ying Jiang","doi":"10.1108/aa-12-2021-0168","DOIUrl":"https://doi.org/10.1108/aa-12-2021-0168","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to demonstrate a multipurpose inspection robot that can both walk on the ground and climb on poles. The structure design, size optimization, kinematics analysis, experiment and arithmetic of the robot are discussed in the paper.\u0000\u0000\u0000Design/methodology/approach\u0000The robot consists of three adjustable modules and a two-degree-of-freedom parallel mechanism in tandem, and the wheel-finger mechanism of each module can realize wheel-finger opening and closing for fast movement and obstacle crossing. This paper uses geometric analysis and simulation analysis to derive size optimization, and vector coordinate method to derive kinematics. Finally, the experiment is carried out by simulating the working environment of the robot.\u0000\u0000\u0000Findings\u0000The robot can realize ground walking and ground turning through the robot entity prototype experiment on the built working environment and efficiently realize 0°–90° pole climbing by the assemble design, optimization and machining. In addition, the robot can also smoothly complete the state transition process from 0° ground to 90° pole climbing. Furthermore, the robot shows good environmental self-adaptation and can complete daily inspection work.\u0000\u0000\u0000Originality/value\u0000The robot can pitch and yaw at a large angle and has six-legged characteristics. It is a multipurpose inspection robot that can walk on the ground and climb on poles. And through structure design, size optimization, kinematics analysis and simulation, the existing robots’ common shortcomings such as poor barrier-crossing ability and poor environmental adaptability are solved.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45280554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Y. Zhu, Jun Yang, Hongwei Zhang, Wenmin Zhu, Jie Wang, Zelin Zhou
Purpose Marking and inspecting are key steps in hull structure construction. However, currently most marking and inspecting operations are still carried out manually, which leads to low assembly efficiency and quality. This paper aims to solve these problems through the application of digital technology: the optical projection and machine vision. Design/methodology/approach First, the assembly process model of hull construction is established in 3D design environment. Second, the process information is presented to workers in a virtual form through optical projector, which provides accurate guidance for the manual operation. On this basis, the workers can complete welding and assembly operations readily. Finally, the machine vision method is used to check the assembly results, which can decrease the subjective errors. Findings A rapid and accurate assembly positioning for hull structure construction is realized based on optical projection, which can avoid the pollution caused by the marking machine and the error caused by human. Originality/value This paper combines the advantages of optical projection and machine vision to the field of shipbuilding. The shortcomings of the traditional marking and inspection methods is effectively solved, which may provide a new way for enhancing the assembly efficiency and quality.
{"title":"Intelligent assembly assistance for hull structure construction based on optical projection","authors":"Y. Zhu, Jun Yang, Hongwei Zhang, Wenmin Zhu, Jie Wang, Zelin Zhou","doi":"10.1108/aa-05-2021-0061","DOIUrl":"https://doi.org/10.1108/aa-05-2021-0061","url":null,"abstract":"\u0000Purpose\u0000Marking and inspecting are key steps in hull structure construction. However, currently most marking and inspecting operations are still carried out manually, which leads to low assembly efficiency and quality. This paper aims to solve these problems through the application of digital technology: the optical projection and machine vision.\u0000\u0000\u0000Design/methodology/approach\u0000First, the assembly process model of hull construction is established in 3D design environment. Second, the process information is presented to workers in a virtual form through optical projector, which provides accurate guidance for the manual operation. On this basis, the workers can complete welding and assembly operations readily. Finally, the machine vision method is used to check the assembly results, which can decrease the subjective errors.\u0000\u0000\u0000Findings\u0000A rapid and accurate assembly positioning for hull structure construction is realized based on optical projection, which can avoid the pollution caused by the marking machine and the error caused by human.\u0000\u0000\u0000Originality/value\u0000This paper combines the advantages of optical projection and machine vision to the field of shipbuilding. The shortcomings of the traditional marking and inspection methods is effectively solved, which may provide a new way for enhancing the assembly efficiency and quality.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43332110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This paper aims to study the boundary disturbance rejection control design for a flexible Timoshenko robot arm to diminish external disturbances and achieve desired angle tracking, with system vibration and elastic deformation considered. Design/methodology/approach This study introduces disturbance observer and disturbance rejection mechanism into the boundary control design for flexible Timoshenko robot arm systems. The uniform bounded stability of controlled systems is proved via Lyapunov analysis without any simplification of the infinite-dimensional system dynamics. Findings The proposed boundary disturbance rejection control scheme can effectively suppress vibrations and shear deformations, achieve the required angular positioning and reject external disturbances. Numerical simulations developed by the finite difference method are adapted to demonstrate the validity of the designed controller. Originality/value The originality of this study is to design boundary disturbance rejection control to suppress vibrations and shear deformations for the flexible Timoshenko robot arm, thereby improving the performance and control accuracy of the system.
{"title":"Vibration and position tracking control for a flexible Timoshenko robot arm with disturbance rejection mechanism","authors":"Yan Yang, Jun Shi, Zhijie Liu, Shuangyin Liu","doi":"10.1108/aa-11-2021-0154","DOIUrl":"https://doi.org/10.1108/aa-11-2021-0154","url":null,"abstract":"\u0000Purpose\u0000This paper aims to study the boundary disturbance rejection control design for a flexible Timoshenko robot arm to diminish external disturbances and achieve desired angle tracking, with system vibration and elastic deformation considered.\u0000\u0000\u0000Design/methodology/approach\u0000This study introduces disturbance observer and disturbance rejection mechanism into the boundary control design for flexible Timoshenko robot arm systems. The uniform bounded stability of controlled systems is proved via Lyapunov analysis without any simplification of the infinite-dimensional system dynamics.\u0000\u0000\u0000Findings\u0000The proposed boundary disturbance rejection control scheme can effectively suppress vibrations and shear deformations, achieve the required angular positioning and reject external disturbances. Numerical simulations developed by the finite difference method are adapted to demonstrate the validity of the designed controller.\u0000\u0000\u0000Originality/value\u0000The originality of this study is to design boundary disturbance rejection control to suppress vibrations and shear deformations for the flexible Timoshenko robot arm, thereby improving the performance and control accuracy of the system.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48552800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chenlong Li, Changshun Yuan, Xiaoshu Ma, Wen-Liang Chen, Jun Wang
Purpose This paper aims to provide a novel integrated fault detection method for industrial process monitoring. Design/methodology/approach A novel integrated fault detection method based on the combination of Mallat (MA) algorithm, weight-elimination (WE) algorithm, conjugate gradient (CG) algorithm and multi-dimensional Taylor network (MTN) dynamic model, namely, MA-WE-CG-MTN, is proposed in this paper. First, MA algorithm is taken as data pre-processing. Second, in virtue of approximation ability and low computation complexity owing to the simple structure of MTN, MTN dynamic models are constructed for each frequency band. Furthermore, the CG algorithm is used to discipline the model parameters and the outputs of MTN model of each frequency band are gained. Third, the authors introduce the WE algorithm to cut down the number of middle layer nodes of MTN, reducing the complexity of the network. Finally, the outputs of MTN model for each frequency band are superimposed to achieve outputs of MTN model, and fault detection is proceeded by the residual error generator based on the difference between the output of MTN model and the actual output. Findings The novel proposed method is used to perform fault detection for industrial process monitoring effectively, such as the Benchmark Simulation Model 1 wastewater treatment process. Originality/value The novel proposed method has generality and provides considerably improved performance and effectiveness, which is used to perform fault detection for industrial process monitoring. The proposed method has good robustness, low complexity and easy implementation.
{"title":"Integrated fault detection for industrial process monitoring based on multi-dimensional Taylor network","authors":"Chenlong Li, Changshun Yuan, Xiaoshu Ma, Wen-Liang Chen, Jun Wang","doi":"10.1108/aa-06-2021-0076","DOIUrl":"https://doi.org/10.1108/aa-06-2021-0076","url":null,"abstract":"\u0000Purpose\u0000This paper aims to provide a novel integrated fault detection method for industrial process monitoring.\u0000\u0000\u0000Design/methodology/approach\u0000A novel integrated fault detection method based on the combination of Mallat (MA) algorithm, weight-elimination (WE) algorithm, conjugate gradient (CG) algorithm and multi-dimensional Taylor network (MTN) dynamic model, namely, MA-WE-CG-MTN, is proposed in this paper. First, MA algorithm is taken as data pre-processing. Second, in virtue of approximation ability and low computation complexity owing to the simple structure of MTN, MTN dynamic models are constructed for each frequency band. Furthermore, the CG algorithm is used to discipline the model parameters and the outputs of MTN model of each frequency band are gained. Third, the authors introduce the WE algorithm to cut down the number of middle layer nodes of MTN, reducing the complexity of the network. Finally, the outputs of MTN model for each frequency band are superimposed to achieve outputs of MTN model, and fault detection is proceeded by the residual error generator based on the difference between the output of MTN model and the actual output.\u0000\u0000\u0000Findings\u0000The novel proposed method is used to perform fault detection for industrial process monitoring effectively, such as the Benchmark Simulation Model 1 wastewater treatment process.\u0000\u0000\u0000Originality/value\u0000The novel proposed method has generality and provides considerably improved performance and effectiveness, which is used to perform fault detection for industrial process monitoring. The proposed method has good robustness, low complexity and easy implementation.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47006745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This paper aims to save time spent on manufacturing the data set and make the intelligent grasping system easy to deploy into a practical industrial environment. Due to the accuracy and robustness of the convolutional neural network, the success rate of the gripping operation reached a high level. Design/Methodology/Approach The proposed system comprises two diverse kinds of convolutional neuron network (CNN) algorithms used in different stages and a binocular eye-in-hand system on the end effector, which detects the position and orientation of workpiece. Both algorithms are trained by the data sets containing images and annotations, which are generated automatically by the proposed method. Findings The approach can be successfully applied to standard position-controlled robots common in the industry. The algorithm performs excellently in terms of elapsed time. Procession of a 256 × 256 image spends less than 0.1 s without relying on high-performance GPUs. The approach is validated in a series of grasping experiments. This method frees workers from monotonous work and improves factory productivity. Originality/Value The authors propose a novel neural network whose performance is tested to be excellent. Moreover, experimental results demonstrate that the proposed second level is extraordinary robust subject to environmental variations. The data sets are generated automatically which saves time spent on manufacturing the data set and makes the intelligent grasping system easy to deploy into a practical industrial environment. Due to the accuracy and robustness of the convolutional neural network, the success rate of the gripping operation reached a high level.
{"title":"An industrial intelligent grasping system based on convolutional neural network","authors":"Jiang Daqi, Wang Hong, Zhou Bin, Wei Chunfeng","doi":"10.1108/aa-03-2021-0036","DOIUrl":"https://doi.org/10.1108/aa-03-2021-0036","url":null,"abstract":"\u0000Purpose\u0000This paper aims to save time spent on manufacturing the data set and make the intelligent grasping system easy to deploy into a practical industrial environment. Due to the accuracy and robustness of the convolutional neural network, the success rate of the gripping operation reached a high level.\u0000\u0000\u0000Design/Methodology/Approach\u0000The proposed system comprises two diverse kinds of convolutional neuron network (CNN) algorithms used in different stages and a binocular eye-in-hand system on the end effector, which detects the position and orientation of workpiece. Both algorithms are trained by the data sets containing images and annotations, which are generated automatically by the proposed method.\u0000\u0000\u0000Findings\u0000The approach can be successfully applied to standard position-controlled robots common in the industry. The algorithm performs excellently in terms of elapsed time. Procession of a 256 × 256 image spends less than 0.1 s without relying on high-performance GPUs. The approach is validated in a series of grasping experiments. This method frees workers from monotonous work and improves factory productivity.\u0000\u0000\u0000Originality/Value\u0000The authors propose a novel neural network whose performance is tested to be excellent. Moreover, experimental results demonstrate that the proposed second level is extraordinary robust subject to environmental variations. The data sets are generated automatically which saves time spent on manufacturing the data set and makes the intelligent grasping system easy to deploy into a practical industrial environment. Due to the accuracy and robustness of the convolutional neural network, the success rate of the gripping operation reached a high level.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44364384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This paper aims to propose a deployment optimization and efficient synchronous acquisition method for compressive stress sensors used by stress distribution law research based on the genetic algorithm and numerical simulations. The authors established a new method of collecting the mining compressive stress-strain distribution data to address the problem of the number of sensors and to optimize the sensor locations in physical similarity simulations to improve the efficiency and accuracy of data collection. Design/methodology/approach First, numerical simulations were used to obtain the compressive stress distribution curve under specific mining conditions. Second, by comparing the mean square error between a fitted curve and simulation data for different numbers of sensors, a genetic algorithm was used to optimize the three-dimensional (3D) spatial deployment of sensors. Third, the authors designed an efficient synchronous acquisition module to allow distributed sensors to achieve synchronous and efficient acquisition of hundreds of data points through a built-in on-board database and a synchronous sampling communication structure. Findings The sensor deployment scheme was established through the genetic algorithm, A synchronous and selective data acquisition method was established for reduced the amount of sensor data required under synchronous acquisition and improved the system acquisition efficiency. The authors obtained a 3D compressive stress distribution when the advancement was 200 m on a large-scale 3D physical similarity simulation platform. Originality/value The proposed method provides a new optimization method for sensor deployment in physical similarity simulations, which improves the efficiency and accuracy of system data acquisition, providing accurate acquisition data for experimental data analysis.
{"title":"Multi-sensor optimal deployment based efficient and synchronous data acquisition in large three-dimensional physical similarity simulation","authors":"Yuyu Hao, Shugang Li, Tian-cai Zhang","doi":"10.1108/aa-06-2021-0074","DOIUrl":"https://doi.org/10.1108/aa-06-2021-0074","url":null,"abstract":"\u0000Purpose\u0000This paper aims to propose a deployment optimization and efficient synchronous acquisition method for compressive stress sensors used by stress distribution law research based on the genetic algorithm and numerical simulations. The authors established a new method of collecting the mining compressive stress-strain distribution data to address the problem of the number of sensors and to optimize the sensor locations in physical similarity simulations to improve the efficiency and accuracy of data collection.\u0000\u0000\u0000Design/methodology/approach\u0000First, numerical simulations were used to obtain the compressive stress distribution curve under specific mining conditions. Second, by comparing the mean square error between a fitted curve and simulation data for different numbers of sensors, a genetic algorithm was used to optimize the three-dimensional (3D) spatial deployment of sensors. Third, the authors designed an efficient synchronous acquisition module to allow distributed sensors to achieve synchronous and efficient acquisition of hundreds of data points through a built-in on-board database and a synchronous sampling communication structure.\u0000\u0000\u0000Findings\u0000The sensor deployment scheme was established through the genetic algorithm, A synchronous and selective data acquisition method was established for reduced the amount of sensor data required under synchronous acquisition and improved the system acquisition efficiency. The authors obtained a 3D compressive stress distribution when the advancement was 200 m on a large-scale 3D physical similarity simulation platform.\u0000\u0000\u0000Originality/value\u0000The proposed method provides a new optimization method for sensor deployment in physical similarity simulations, which improves the efficiency and accuracy of system data acquisition, providing accurate acquisition data for experimental data analysis.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42888342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose In this study, a physical similarity simulation plays a significant role in the study of crack evolution and the gas migration mechanism. A sensor is deployed inside a comparable artificial rock formation to assure the accuracy of the experiment results. During the building of the simulated rock formation, a huge volume of acidic gas is released, causing numerous sensor measurement mistakes. Additionally, the gas concentration estimation approach is subject to uncertainty because of the complex rock formation environment. As a result, the purpose of this study is to introduce an adaptive Kalman filter approach to reduce observation noise, increase the accuracy of the gas concentration estimation model and, finally, determine the gas migration law. Design/methodology/approach First, based on the process of gas floatation-diffusion and seepage, the gas migration model is established according to Fick’s second law, and a simplified modeling method using diffusion flux instead of gas concentration is presented. Second, an adaptive Kalman filter algorithm is introduced to establish a gas concentration estimation model, taking into account the model uncertainty and the unknown measurement noise. Finally, according to a large-scale physical similarity simulation platform, a thorough experiment about gas migration is carried out to extract gas concentration variation data with certain ventilation techniques and to create a gas chart of the time-changing trend. Findings This approach is used to determine the changing process of gas distribution for a certain ventilation mode. The results match the rock fissure distribution condition derived from the microseismic monitoring data, proving the effectiveness of the approach. Originality/value For the first time in large-scale three-dimensional physical similarity simulations, the adaptive Kalman filter data processing method based on the inverse Wishart probability density function is used to solve the problem of an inaccurate process and measurement noise, laying the groundwork for studying the gas migration law and determining the gas migration mechanism.
{"title":"A gas migration law study of a large-scale 3D physical similarity simulation with an adaptive Kalman filter algorithm","authors":"Yuyu Hao, Shugang Li, Tian-cai Zhang","doi":"10.1108/aa-06-2021-0084","DOIUrl":"https://doi.org/10.1108/aa-06-2021-0084","url":null,"abstract":"\u0000Purpose\u0000In this study, a physical similarity simulation plays a significant role in the study of crack evolution and the gas migration mechanism. A sensor is deployed inside a comparable artificial rock formation to assure the accuracy of the experiment results. During the building of the simulated rock formation, a huge volume of acidic gas is released, causing numerous sensor measurement mistakes. Additionally, the gas concentration estimation approach is subject to uncertainty because of the complex rock formation environment. As a result, the purpose of this study is to introduce an adaptive Kalman filter approach to reduce observation noise, increase the accuracy of the gas concentration estimation model and, finally, determine the gas migration law.\u0000\u0000\u0000Design/methodology/approach\u0000First, based on the process of gas floatation-diffusion and seepage, the gas migration model is established according to Fick’s second law, and a simplified modeling method using diffusion flux instead of gas concentration is presented. Second, an adaptive Kalman filter algorithm is introduced to establish a gas concentration estimation model, taking into account the model uncertainty and the unknown measurement noise. Finally, according to a large-scale physical similarity simulation platform, a thorough experiment about gas migration is carried out to extract gas concentration variation data with certain ventilation techniques and to create a gas chart of the time-changing trend.\u0000\u0000\u0000Findings\u0000This approach is used to determine the changing process of gas distribution for a certain ventilation mode. The results match the rock fissure distribution condition derived from the microseismic monitoring data, proving the effectiveness of the approach.\u0000\u0000\u0000Originality/value\u0000For the first time in large-scale three-dimensional physical similarity simulations, the adaptive Kalman filter data processing method based on the inverse Wishart probability density function is used to solve the problem of an inaccurate process and measurement noise, laying the groundwork for studying the gas migration law and determining the gas migration mechanism.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48512038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose To solve the above problems and ensure the stability of the ad hoc network node topology in the process of wireless signal transmission, this paper aims to design a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system. Design/methodology/approach This paper designs a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system. Findings The simulation results show that the amorphous flat wireless self-organizing network system has good nonlinear distortion fault-tolerant correction ability under the feedback control of the designed controller, and the system has the asymptotically stable convergence ability; the test results show: the node topology of the self-organizing network structural stability is significantly improved, which provides a foundation for the subsequent realization of long-distance transmission of ad hoc network nodes. Research limitations/implications Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further. Originality/value The controller can extract the fault information caused by nonlinear distortion in the wireless signal transmission process, and at the same time, its feedback matrix K can gradually converge the generated wireless signal error to zero, to realize the stable transmission of the wireless signal.
{"title":"Research on robust adaptive sliding film fault-tolerant control under nonlinear distortion of signal transmission in amorphous flat air-to-ground wireless ad-hoc network system","authors":"Zhifang Wang, Jianguo Yu, Shangjing Lin","doi":"10.1108/aa-04-2021-0045","DOIUrl":"https://doi.org/10.1108/aa-04-2021-0045","url":null,"abstract":"\u0000Purpose\u0000To solve the above problems and ensure the stability of the ad hoc network node topology in the process of wireless signal transmission, this paper aims to design a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system.\u0000\u0000\u0000Design/methodology/approach\u0000This paper designs a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system.\u0000\u0000\u0000Findings\u0000The simulation results show that the amorphous flat wireless self-organizing network system has good nonlinear distortion fault-tolerant correction ability under the feedback control of the designed controller, and the system has the asymptotically stable convergence ability; the test results show: the node topology of the self-organizing network structural stability is significantly improved, which provides a foundation for the subsequent realization of long-distance transmission of ad hoc network nodes.\u0000\u0000\u0000Research limitations/implications\u0000Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.\u0000\u0000\u0000Originality/value\u0000The controller can extract the fault information caused by nonlinear distortion in the wireless signal transmission process, and at the same time, its feedback matrix K can gradually converge the generated wireless signal error to zero, to realize the stable transmission of the wireless signal.\u0000","PeriodicalId":55448,"journal":{"name":"Assembly Automation","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2022-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42993347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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