Pub Date : 2023-03-01DOI: 10.1177/00202940221092030
Changhong Chen, Shaofeng Wang, Shunzhou Huang
In view of the complex multi-scale target detection environment of ultrasonic atlas of weld defect and the poor detection performance of existing algorithms for the multiple small target defects, the Faster RCNN convolution neural network is applied to weld defect detection, and a Fast RCNN deep learning network is proposed in combination with an improved ResNet 50. Based on the coexistence of multiple small targets and multi-scale target detection, this paper proposes to combine deformable network, FPN network and ResNet50 to improve the detection performance of the algorithm for multi-scale targets, especially small targets. Based on the efficiency and accuracy of candidate frame selection, K-means clustering algorithm and ROI Align algorithm are proposed, and the anchors points and candidate frames suitable for weld defect data sets are customized for accurate positioning. Through the self-made ultrasonic atlas data set of weld defects and experimental verification of the improved algorithm in this paper, the overall mean average precision has reaches 93.72%, and the average precision of small target defects such as “stoma” and “crack” has reaches 92.5% and 88.9% respectively, which is 4.8% higher than the original Faster RCNN algorithm. At the same time, through the ablation experiments and comparison experiments with other mainstream target detection algorithms, it is proved that the improved method proposed in this paper improves the detection performance and is superior to other algorithms. The actual industrial detection scene proves that it basically meets the requirements of weld defect detection, and can provide a reference for the intelligent detection method of weld defects.
{"title":"An improved faster RCNN-based weld ultrasonic atlas defect detection method","authors":"Changhong Chen, Shaofeng Wang, Shunzhou Huang","doi":"10.1177/00202940221092030","DOIUrl":"https://doi.org/10.1177/00202940221092030","url":null,"abstract":"In view of the complex multi-scale target detection environment of ultrasonic atlas of weld defect and the poor detection performance of existing algorithms for the multiple small target defects, the Faster RCNN convolution neural network is applied to weld defect detection, and a Fast RCNN deep learning network is proposed in combination with an improved ResNet 50. Based on the coexistence of multiple small targets and multi-scale target detection, this paper proposes to combine deformable network, FPN network and ResNet50 to improve the detection performance of the algorithm for multi-scale targets, especially small targets. Based on the efficiency and accuracy of candidate frame selection, K-means clustering algorithm and ROI Align algorithm are proposed, and the anchors points and candidate frames suitable for weld defect data sets are customized for accurate positioning. Through the self-made ultrasonic atlas data set of weld defects and experimental verification of the improved algorithm in this paper, the overall mean average precision has reaches 93.72%, and the average precision of small target defects such as “stoma” and “crack” has reaches 92.5% and 88.9% respectively, which is 4.8% higher than the original Faster RCNN algorithm. At the same time, through the ablation experiments and comparison experiments with other mainstream target detection algorithms, it is proved that the improved method proposed in this paper improves the detection performance and is superior to other algorithms. The actual industrial detection scene proves that it basically meets the requirements of weld defect detection, and can provide a reference for the intelligent detection method of weld defects.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"1 1","pages":"832 - 843"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80748767","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}
Pub Date : 2023-03-01DOI: 10.1177/00202940221126036
{"title":"RETRACTION NOTICE: Analysis of voltage and current magnification in resonant circuits on hyperspectral signal processing","authors":"","doi":"10.1177/00202940221126036","DOIUrl":"https://doi.org/10.1177/00202940221126036","url":null,"abstract":"","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"119 1","pages":"891 - 891"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77955841","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}
Pub Date : 2023-03-01DOI: 10.1177/00202940221131454
{"title":"RETRACTION NOTICE: Pareto-based allocations of multi-type flexible AC transmission system devices for optimal reactive power dispatch using Kinetic Gas Molecule Optimization algorithm","authors":"","doi":"10.1177/00202940221131454","DOIUrl":"https://doi.org/10.1177/00202940221131454","url":null,"abstract":"","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"41 1","pages":"897 - 897"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84710528","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}
Pub Date : 2023-02-27DOI: 10.1177/00202940231157422
Yueping Chen, Bo Tan, Linan Zeng
To address the problems of long run times, long path length and low efficiencies of traditional intelligent algorithms to optimise free-form surface inspection path algorithms, this paper proposes a method based on an improved cuckoo search algorithm. Since the basic cuckoo search algorithm suffers from problems such as low search efficiency and the tendency to fall into local optimum solutions, the basic cuckoo search algorithm is improved by using a parameter adaptive adjustment strategy and dynamic neighbourhood search strategy, so that the improved cuckoo search algorithm can obtain the optimised inspection path stably and quickly. The local composition of the free-form surface inspection path and the corresponding mathematical model are first analysed, and then traditional intelligent algorithms and the improved cuckoo search algorithm are applied to optimise the mathematical model. The results of inspection experiments conducted with an engine impeller showed that the improved cuckoo search algorithm reduced the length of the optimised inspection path by at least 8.6%, reduced the algorithm run time by at least 35%, and improved the inspection efficiency by at least 1.2% compared to those of the genetic algorithm, simulated annealing algorithm, and ant colony Optimisation algorithm. The improved cuckoo search algorithm allows for effective free-form surface inspection path Optimisation and an improved inspection efficiency.
{"title":"Inspection path planning of free-form surfaces based on improved cuckoo search algorithm","authors":"Yueping Chen, Bo Tan, Linan Zeng","doi":"10.1177/00202940231157422","DOIUrl":"https://doi.org/10.1177/00202940231157422","url":null,"abstract":"To address the problems of long run times, long path length and low efficiencies of traditional intelligent algorithms to optimise free-form surface inspection path algorithms, this paper proposes a method based on an improved cuckoo search algorithm. Since the basic cuckoo search algorithm suffers from problems such as low search efficiency and the tendency to fall into local optimum solutions, the basic cuckoo search algorithm is improved by using a parameter adaptive adjustment strategy and dynamic neighbourhood search strategy, so that the improved cuckoo search algorithm can obtain the optimised inspection path stably and quickly. The local composition of the free-form surface inspection path and the corresponding mathematical model are first analysed, and then traditional intelligent algorithms and the improved cuckoo search algorithm are applied to optimise the mathematical model. The results of inspection experiments conducted with an engine impeller showed that the improved cuckoo search algorithm reduced the length of the optimised inspection path by at least 8.6%, reduced the algorithm run time by at least 35%, and improved the inspection efficiency by at least 1.2% compared to those of the genetic algorithm, simulated annealing algorithm, and ant colony Optimisation algorithm. The improved cuckoo search algorithm allows for effective free-form surface inspection path Optimisation and an improved inspection efficiency.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"57 1","pages":"1321 - 1332"},"PeriodicalIF":0.0,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88263475","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}
Pub Date : 2023-02-23DOI: 10.1177/00202940231154856
Haoyue Zhang, Shihong Ding
We consider a hypersonic vehicle optimal flight control problem. The problem is modeled as an optimal control problem of switched systems (OCPSS), which can become a parameter optimization problem (POP). Following that, to achieve the globally optimal solution of the POP, an improved continuous filled function (CFF) algorithm including one adjusting parameter is proposed based on a penalty function, in which the CFF is differentiable, excludes logarithmic terms or exponential terms, and does not require to minimize the cost function. Numerical results show that the proposed algorithm is effective.
{"title":"Numerical algorithm for hypersonic vehicle optimal flight control","authors":"Haoyue Zhang, Shihong Ding","doi":"10.1177/00202940231154856","DOIUrl":"https://doi.org/10.1177/00202940231154856","url":null,"abstract":"We consider a hypersonic vehicle optimal flight control problem. The problem is modeled as an optimal control problem of switched systems (OCPSS), which can become a parameter optimization problem (POP). Following that, to achieve the globally optimal solution of the POP, an improved continuous filled function (CFF) algorithm including one adjusting parameter is proposed based on a penalty function, in which the CFF is differentiable, excludes logarithmic terms or exponential terms, and does not require to minimize the cost function. Numerical results show that the proposed algorithm is effective.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"9 1","pages":"1308 - 1320"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85133736","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}
Pub Date : 2023-02-15DOI: 10.1177/00202940221098051
A. Castriota, M. De Giorgi, Fabio Manco, A. Morabito, R. Nobile
In this work, the authors aim at developing a reliable and fast methodology to evaluate the wear evolution in tire starting from a complete optical 3D scanning. Starting from a data cloud, a semi-automatic methodology was implemented in MATLAB to extract mean tread radial profiles in correspondence of the desired angular position of the tire. These profiles could be numerically evaluated to establish the presence of irregular wear and the characteristic parameter of the groove depth. The reliability and the robustness of this methodology was firstly tested by applying it to several synthetic case studies modeled in CATIA V5®, where ovalization and presence of defects were also simulated. The groove depth was determined with an error lower than 1% for the ideal model, while the introduction of ovalization and defects leaded to an error of 2.6% in the worst condition. In a second time, the methodology has been successfully applied to experimental measurements carried out in two different wear life of the tire, allowing the tracking of the wear phenomena through the evaluation of the progressive lowering of tread radial profiles.
{"title":"A semi-automatic methodology for tire’s wear evaluation","authors":"A. Castriota, M. De Giorgi, Fabio Manco, A. Morabito, R. Nobile","doi":"10.1177/00202940221098051","DOIUrl":"https://doi.org/10.1177/00202940221098051","url":null,"abstract":"In this work, the authors aim at developing a reliable and fast methodology to evaluate the wear evolution in tire starting from a complete optical 3D scanning. Starting from a data cloud, a semi-automatic methodology was implemented in MATLAB to extract mean tread radial profiles in correspondence of the desired angular position of the tire. These profiles could be numerically evaluated to establish the presence of irregular wear and the characteristic parameter of the groove depth. The reliability and the robustness of this methodology was firstly tested by applying it to several synthetic case studies modeled in CATIA V5®, where ovalization and presence of defects were also simulated. The groove depth was determined with an error lower than 1% for the ideal model, while the introduction of ovalization and defects leaded to an error of 2.6% in the worst condition. In a second time, the methodology has been successfully applied to experimental measurements carried out in two different wear life of the tire, allowing the tracking of the wear phenomena through the evaluation of the progressive lowering of tread radial profiles.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"66 1","pages":"1292 - 1307"},"PeriodicalIF":0.0,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76061489","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}
Pub Date : 2023-02-14DOI: 10.1177/00202940231153205
Ayber Eray Algüner, H. Ergezer
Electromyography (EMG) signal classification is vital to diagnose musculoskeletal abnormalities and control devices by motion intention detection. Machine learning assists both areas by classifying conditions or motion intentions. This paper proposes a novel window length insensitive EMG classification method utilizing the Entropy feature. The main goal of this study is to show that entropy can be used as the only feature for fast real-time classification of EMG signals of hand gestures. The main goal of this study is to show that entropy can be used as the only feature for fast real-time classification of EMG signals of hand gestures. Additionally, the entropy feature can classify feature vectors of different sliding window lengths without including them in the training data. Many kinds of entropy feature succeeded in electroencephalography (EEG) and electrocardiography (ECG) classification research. However, to the best of our knowledge, the Entropy Feature proposed by Shannon stays untested for EMG classification to this day. All the machine learning models are tested on datasets NinaPro DB5 and the newly collected SingleMyo. As an initial analysis to test the entropy feature, classic Machine Learning (ML) models are trained on the NinaPro DB5 dataset. This stage showed that except for the K Nearest Neighbor (kNN) with high inference time, Support Vector Machines (SVM) gave the best validation accuracy. Later, SVM models trained with feature vectors created by 1 s (200 samples) sliding windows are tested on feature vectors created by 250 ms (50 samples) to 1500 ms (300 samples) sliding windows. This experiment resulted in slight accuracy differences through changing window length, indicating that the Entropy feature is insensitive to this parameter. Lastly, Locally Parsed Histogram (LPH), typical in standard entropy functions, makes learning hard for ML methods. Globally Parsed Histogram (GPH) was proposed, and classification accuracy increased from 60.35% to 89.06% while window length insensitivity is preserved. This study shows that Shannon’s entropy is a compelling feature with low window length sensitivity for EMG hand gesture classification. The effect of the GPH approach against an easy-to-make mistake LPH is shown. A real-time classification algorithm for the entropy features is tested on the newly created SingleMyo dataset.
{"title":"Window length insensitive real-time EMG hand gesture classification using entropy calculated from globally parsed histograms","authors":"Ayber Eray Algüner, H. Ergezer","doi":"10.1177/00202940231153205","DOIUrl":"https://doi.org/10.1177/00202940231153205","url":null,"abstract":"Electromyography (EMG) signal classification is vital to diagnose musculoskeletal abnormalities and control devices by motion intention detection. Machine learning assists both areas by classifying conditions or motion intentions. This paper proposes a novel window length insensitive EMG classification method utilizing the Entropy feature. The main goal of this study is to show that entropy can be used as the only feature for fast real-time classification of EMG signals of hand gestures. The main goal of this study is to show that entropy can be used as the only feature for fast real-time classification of EMG signals of hand gestures. Additionally, the entropy feature can classify feature vectors of different sliding window lengths without including them in the training data. Many kinds of entropy feature succeeded in electroencephalography (EEG) and electrocardiography (ECG) classification research. However, to the best of our knowledge, the Entropy Feature proposed by Shannon stays untested for EMG classification to this day. All the machine learning models are tested on datasets NinaPro DB5 and the newly collected SingleMyo. As an initial analysis to test the entropy feature, classic Machine Learning (ML) models are trained on the NinaPro DB5 dataset. This stage showed that except for the K Nearest Neighbor (kNN) with high inference time, Support Vector Machines (SVM) gave the best validation accuracy. Later, SVM models trained with feature vectors created by 1 s (200 samples) sliding windows are tested on feature vectors created by 250 ms (50 samples) to 1500 ms (300 samples) sliding windows. This experiment resulted in slight accuracy differences through changing window length, indicating that the Entropy feature is insensitive to this parameter. Lastly, Locally Parsed Histogram (LPH), typical in standard entropy functions, makes learning hard for ML methods. Globally Parsed Histogram (GPH) was proposed, and classification accuracy increased from 60.35% to 89.06% while window length insensitivity is preserved. This study shows that Shannon’s entropy is a compelling feature with low window length sensitivity for EMG hand gesture classification. The effect of the GPH approach against an easy-to-make mistake LPH is shown. A real-time classification algorithm for the entropy features is tested on the newly created SingleMyo dataset.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"12 1","pages":"1278 - 1291"},"PeriodicalIF":0.0,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88960630","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}
Pub Date : 2023-02-12DOI: 10.1177/00202940221143851
Tianlei Wang, Nanlin Tan, Jiongzhi Qiu, Z. Zheng, Chengmin Lin, Hongmin Wang
To achieve stabilisation control of an underactuated bridge crane system, a new robust control strategy for the sliding mode is proposed in this paper. It can realise finite-time-convergent stabilisation control under the conditions of model uncertainty, parameter perturbation and external interference. In contrast to the existing methods, our method does not need prior information of the dynamic characteristics of the bridge crane system, and can make the system converge to the equilibrium state at the preset time. Specifically, the nonlinear model of the bridge crane system is linearised with partial feedback, and adaptive signals are introduced. Then, according to the form of the transformed system, a fast terminal sliding mode surface is constructed, and an adaptive terminal sliding mode controller is designed. According to strict analysis, the proposed control law ensures that the system converges to the equilibrium point in finite time and provides the convergence time. Finally, the effectiveness and robustness of the proposed control method are verified by comparing the simulation and experimental results with existing methods.
{"title":"A novel model-free adaptive terminal sliding mode controller for bridge cranes","authors":"Tianlei Wang, Nanlin Tan, Jiongzhi Qiu, Z. Zheng, Chengmin Lin, Hongmin Wang","doi":"10.1177/00202940221143851","DOIUrl":"https://doi.org/10.1177/00202940221143851","url":null,"abstract":"To achieve stabilisation control of an underactuated bridge crane system, a new robust control strategy for the sliding mode is proposed in this paper. It can realise finite-time-convergent stabilisation control under the conditions of model uncertainty, parameter perturbation and external interference. In contrast to the existing methods, our method does not need prior information of the dynamic characteristics of the bridge crane system, and can make the system converge to the equilibrium state at the preset time. Specifically, the nonlinear model of the bridge crane system is linearised with partial feedback, and adaptive signals are introduced. Then, according to the form of the transformed system, a fast terminal sliding mode surface is constructed, and an adaptive terminal sliding mode controller is designed. According to strict analysis, the proposed control law ensures that the system converges to the equilibrium point in finite time and provides the convergence time. Finally, the effectiveness and robustness of the proposed control method are verified by comparing the simulation and experimental results with existing methods.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"1 1","pages":"1217 - 1230"},"PeriodicalIF":0.0,"publicationDate":"2023-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88786449","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}
Pub Date : 2023-02-12DOI: 10.1177/00202940221143584
Yahia Salwa, Bedoui Saida, K. Abderrahim
Over the past few decades, there have been increasing research activities in fault diagnosis (FD) and fault-tolerant control (FTC) for switched hybrid systems. This paper addresses the problem of active-fault tolerant control (AFTC) for switched hybrid systems subject to actuator faults to enhance system security and keep system stability. The proposed FTC is designed by adding the state feedback control with integral action to an additive control law which requires accurate fault estimation to compensate for the fault effect. Thus, a data-based projection method (DPM) is extended (EDPM) based on inputs and outputs measures to estimate the fault without using mathematical models. The synthesis of the state feedback control with integral action is proposed for recovering the desired performances. It integrates a set of controllers corresponding to a set of partial models to design a set of switching control laws. Indeed, new linear matrix inequalities (LMIs) using Lyapunov stability analysis are proposed to find the optimal values of the control gains matrices and keeping system stability. A comparative study of the proposed FTC with existing work is given to show the effectiveness of the proposed technique.
{"title":"Diagnosis and fault tolerant control against actuator fault for a class of hybrid dynamic systems","authors":"Yahia Salwa, Bedoui Saida, K. Abderrahim","doi":"10.1177/00202940221143584","DOIUrl":"https://doi.org/10.1177/00202940221143584","url":null,"abstract":"Over the past few decades, there have been increasing research activities in fault diagnosis (FD) and fault-tolerant control (FTC) for switched hybrid systems. This paper addresses the problem of active-fault tolerant control (AFTC) for switched hybrid systems subject to actuator faults to enhance system security and keep system stability. The proposed FTC is designed by adding the state feedback control with integral action to an additive control law which requires accurate fault estimation to compensate for the fault effect. Thus, a data-based projection method (DPM) is extended (EDPM) based on inputs and outputs measures to estimate the fault without using mathematical models. The synthesis of the state feedback control with integral action is proposed for recovering the desired performances. It integrates a set of controllers corresponding to a set of partial models to design a set of switching control laws. Indeed, new linear matrix inequalities (LMIs) using Lyapunov stability analysis are proposed to find the optimal values of the control gains matrices and keeping system stability. A comparative study of the proposed FTC with existing work is given to show the effectiveness of the proposed technique.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"4 1","pages":"1240 - 1250"},"PeriodicalIF":0.0,"publicationDate":"2023-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82076258","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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