Pub Date : 2022-05-08DOI: 10.1080/21642583.2022.2071778
Xiaohui Wang, Shengpu Li
Garden balsam optimization (GBO) is a new proposed evolutionary algorithm based on swarm intelligence. Convergence and time complexity analyses are very important in evolutionary computation, but the research on GBO is still blank. Same as other evolutionary algorithms, the optimization process of the GBO algorithm can be regarded as a Markov process. In this paper, a Markov stochastic model of the GBO algorithm is defined and used to prove the convergence of GBO algorithm. Finally, the approximation region of the estimated convergence time of GBO algorithm is calculated, which characterizes the evolution of the evolutionary process of the proposed algorithm.
{"title":"Theoretical analysis of garden balsam optimization algorithm","authors":"Xiaohui Wang, Shengpu Li","doi":"10.1080/21642583.2022.2071778","DOIUrl":"https://doi.org/10.1080/21642583.2022.2071778","url":null,"abstract":"Garden balsam optimization (GBO) is a new proposed evolutionary algorithm based on swarm intelligence. Convergence and time complexity analyses are very important in evolutionary computation, but the research on GBO is still blank. Same as other evolutionary algorithms, the optimization process of the GBO algorithm can be regarded as a Markov process. In this paper, a Markov stochastic model of the GBO algorithm is defined and used to prove the convergence of GBO algorithm. Finally, the approximation region of the estimated convergence time of GBO algorithm is calculated, which characterizes the evolution of the evolutionary process of the proposed algorithm.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44100370","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 : 2022-05-08DOI: 10.1080/21642583.2022.2047123
Fourat Zribi, L. Sidhom, Mohamed Gharib, S. Refaat
The drill string is always exposed to various types of vibrations among which, stick slip is one of the most important types. It is a severe state of torsional vibrations. This phenomenon can decrease the rate of penetration of drilling, wear of expensive equipment prematurely and cause catastrophic failures. In this paper, a novel adaptive sliding mode (SM) controller is proposed to eliminate stick slip in drill string systems. This proposed algorithm has a more robust capacity than existing 1st-order SM schemes in the literature regarding the robustness to parametric uncertainties, variations in weight on bit (WOB), variations in reference velocity and measurement noise. Moreover, the proposed controller does not require a priori knowledge of the upper bounds of parametric uncertainties, external disturbances and can be easily applied for any operating mode of the drill rig. A proof of stability based on the Lyapunov criterion of the system is given. Simulation results show that the proposed algorithm suppresses the stick-slip while keeping good performances compared to other SM controllers. A comparative study between the proposed controller and classic SM controllers and other adaptive SM scheme is performed in order to assess the advantages of the proposed algorithm and illustrate the overall performance improvements. The obtained results show that the proposed controller succeeded to eliminate the stick-slip phenomenon with the best performance compared to the classic SM controllers. In fact, the proposed controller presented a reduction of nearly 26 in terms of overshoot and 1.6 times better settling time values while having the smoother input signal.
{"title":"New algorithm based active method to eliminate stick-slip vibrations in drill string systems","authors":"Fourat Zribi, L. Sidhom, Mohamed Gharib, S. Refaat","doi":"10.1080/21642583.2022.2047123","DOIUrl":"https://doi.org/10.1080/21642583.2022.2047123","url":null,"abstract":"The drill string is always exposed to various types of vibrations among which, stick slip is one of the most important types. It is a severe state of torsional vibrations. This phenomenon can decrease the rate of penetration of drilling, wear of expensive equipment prematurely and cause catastrophic failures. In this paper, a novel adaptive sliding mode (SM) controller is proposed to eliminate stick slip in drill string systems. This proposed algorithm has a more robust capacity than existing 1st-order SM schemes in the literature regarding the robustness to parametric uncertainties, variations in weight on bit (WOB), variations in reference velocity and measurement noise. Moreover, the proposed controller does not require a priori knowledge of the upper bounds of parametric uncertainties, external disturbances and can be easily applied for any operating mode of the drill rig. A proof of stability based on the Lyapunov criterion of the system is given. Simulation results show that the proposed algorithm suppresses the stick-slip while keeping good performances compared to other SM controllers. A comparative study between the proposed controller and classic SM controllers and other adaptive SM scheme is performed in order to assess the advantages of the proposed algorithm and illustrate the overall performance improvements. The obtained results show that the proposed controller succeeded to eliminate the stick-slip phenomenon with the best performance compared to the classic SM controllers. In fact, the proposed controller presented a reduction of nearly 26 in terms of overshoot and 1.6 times better settling time values while having the smoother input signal.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43299181","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 : 2022-05-08DOI: 10.1080/21642583.2022.2071779
Eduardo Trutié-Carrero, D. Seuret-Jiménez, J. Nieto-Jalil, J. Escobedo-Alatorre, J. A. Marbán-Salgado, A. Zamudio-Lara
Failures in photovoltaic systems are a major problem since they cause a decrease in the production of electrical energy. It is a challenge for the scientific community to obtain algorithms that adapt to existing systems, reducing the probability density of false positives. This paper solves this problem, presenting two contributions aimed at detecting faults in photovoltaic systems. The first contribution is aimed at a new algorithm based on non-coherent detection. Such algorithm is adaptable to any photovoltaic system and uses the box-counting procedure to estimate the fractal dimension of the normalized signal. The second contribution are to two equations that allow calculating the detection threshold under a failure prediction of suchalgorithm. The prediction of failures is based on a probability density of false positives set a priori. The algorithm was experimentally validated using 300 signals acquired from a photovoltaic system in series and parallel configurations. The results show that the algorithm had a behaviour, under a probability density of false positives of 2%, higher than those reported in the literature.
{"title":"I–V characteristic and its fractal dimension for performance’s fault detection","authors":"Eduardo Trutié-Carrero, D. Seuret-Jiménez, J. Nieto-Jalil, J. Escobedo-Alatorre, J. A. Marbán-Salgado, A. Zamudio-Lara","doi":"10.1080/21642583.2022.2071779","DOIUrl":"https://doi.org/10.1080/21642583.2022.2071779","url":null,"abstract":"Failures in photovoltaic systems are a major problem since they cause a decrease in the production of electrical energy. It is a challenge for the scientific community to obtain algorithms that adapt to existing systems, reducing the probability density of false positives. This paper solves this problem, presenting two contributions aimed at detecting faults in photovoltaic systems. The first contribution is aimed at a new algorithm based on non-coherent detection. Such algorithm is adaptable to any photovoltaic system and uses the box-counting procedure to estimate the fractal dimension of the normalized signal. The second contribution are to two equations that allow calculating the detection threshold under a failure prediction of suchalgorithm. The prediction of failures is based on a probability density of false positives set a priori. The algorithm was experimentally validated using 300 signals acquired from a photovoltaic system in series and parallel configurations. The results show that the algorithm had a behaviour, under a probability density of false positives of 2%, higher than those reported in the literature.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47584744","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 : 2022-05-04DOI: 10.1080/21642583.2022.2068167
Jiajin Lang, Jiafa Mao, Ronghua Liang
With the development of computer vision technology, target measurement methods have been widely used in robot automatic obstacle avoidance, vehicle-assisted driving and other systems. There are many target measurement technologies available, but most of them are based on binocular or trinocular vision, or based on monocular vision with other auxiliary equipment, or based on monocular vision to measure horizontal target. The first two technologies achieve precise positioning by increasing the amount of data and sacrificing processing speed, while the third only studies the measurement method of the horizontal target. To address the complexity of the multi-equipment measurement methods and the limitation of the monocular measurement methods for horizontal target, this paper proposes a novel monocular vision measurement method for the non-horizontal target. According to the principle of camera imaging, internal and external parameters of the camera and analogue-to-digital conversion principle, the imaging relationship model for measuring the relative height and target distance of non-horizontal target is deduced, and the solvability of the model is demonstrated by mathematics. The experimental results verify the correctness and feasibility of this method.
{"title":"Non-horizontal target measurement method based on monocular vision","authors":"Jiajin Lang, Jiafa Mao, Ronghua Liang","doi":"10.1080/21642583.2022.2068167","DOIUrl":"https://doi.org/10.1080/21642583.2022.2068167","url":null,"abstract":"With the development of computer vision technology, target measurement methods have been widely used in robot automatic obstacle avoidance, vehicle-assisted driving and other systems. There are many target measurement technologies available, but most of them are based on binocular or trinocular vision, or based on monocular vision with other auxiliary equipment, or based on monocular vision to measure horizontal target. The first two technologies achieve precise positioning by increasing the amount of data and sacrificing processing speed, while the third only studies the measurement method of the horizontal target. To address the complexity of the multi-equipment measurement methods and the limitation of the monocular measurement methods for horizontal target, this paper proposes a novel monocular vision measurement method for the non-horizontal target. According to the principle of camera imaging, internal and external parameters of the camera and analogue-to-digital conversion principle, the imaging relationship model for measuring the relative height and target distance of non-horizontal target is deduced, and the solvability of the model is demonstrated by mathematics. The experimental results verify the correctness and feasibility of this method.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44988039","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 : 2022-05-04DOI: 10.1080/21642583.2022.2063200
C. Xue, Wen Wen, Shumin Li
In order to explore how cross-border e-commerce and logistics companies make decisions during synergy in a dynamic environment, this paper first establishes an evolutionary game model to study the influencing factors of enterprises’ strategies in the process of synergy in a dynamic environment. Then the study uses sensitivity analysis and numerical simulation to analyse the impact of different enterprises’ strategies on synergy. Finally, the synergistic strategies of enterprises in different dynamic environments are discussed. We found that: (1) capital and labour input of cross-border e-commerce platforms will affect the synergy. In a highly dynamic environment, the influences are greater. (2) There is a positive correlation between the technical level of the platform and synergistic degree, while the high technical level of logistics enterprises will inhibit synergy. However, in an unstable environment, the positive effect still exists, and the change in the logistics enterprise technology level has little effect on synergy. (3) The technical level of the cross-border e-commerce platform has the greatest impact on the benefits of both parties, and then is the lower cost of labour and capital input, while the technical level of logistics companies has little impact.
{"title":"Enterprise strategy analysis of synergy between cross-border e-commerce and logistics in a dynamic environment","authors":"C. Xue, Wen Wen, Shumin Li","doi":"10.1080/21642583.2022.2063200","DOIUrl":"https://doi.org/10.1080/21642583.2022.2063200","url":null,"abstract":"In order to explore how cross-border e-commerce and logistics companies make decisions during synergy in a dynamic environment, this paper first establishes an evolutionary game model to study the influencing factors of enterprises’ strategies in the process of synergy in a dynamic environment. Then the study uses sensitivity analysis and numerical simulation to analyse the impact of different enterprises’ strategies on synergy. Finally, the synergistic strategies of enterprises in different dynamic environments are discussed. We found that: (1) capital and labour input of cross-border e-commerce platforms will affect the synergy. In a highly dynamic environment, the influences are greater. (2) There is a positive correlation between the technical level of the platform and synergistic degree, while the high technical level of logistics enterprises will inhibit synergy. However, in an unstable environment, the positive effect still exists, and the change in the logistics enterprise technology level has little effect on synergy. (3) The technical level of the cross-border e-commerce platform has the greatest impact on the benefits of both parties, and then is the lower cost of labour and capital input, while the technical level of logistics companies has little impact.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45635130","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 : 2022-05-01DOI: 10.1080/21642583.2022.2068165
D. Kataev, E. Y. Kutyakov
This paper introduces a finite-time generalization of Lyapunov modal contributions (LMC) – a technique for energy-based selective modal analysis. The main focus is a case study involving a system with physically meaningful squared output and considering its unforced movement as transferring excessive energy towards its environment. This problem statement leads to LMCs estimating energy transfers measured in joules. The results facilitate solutions to several issues that occur in applications of methods based on Gramian spectral decomposition.
{"title":"Physically meaningful Lyapunov modal contributions in linear systems","authors":"D. Kataev, E. Y. Kutyakov","doi":"10.1080/21642583.2022.2068165","DOIUrl":"https://doi.org/10.1080/21642583.2022.2068165","url":null,"abstract":"This paper introduces a finite-time generalization of Lyapunov modal contributions (LMC) – a technique for energy-based selective modal analysis. The main focus is a case study involving a system with physically meaningful squared output and considering its unforced movement as transferring excessive energy towards its environment. This problem statement leads to LMCs estimating energy transfers measured in joules. The results facilitate solutions to several issues that occur in applications of methods based on Gramian spectral decomposition.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47329332","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 : 2022-04-26DOI: 10.1080/21642583.2022.2068166
Lars Brockmann, Hanjie Wang, K. Hunt
To investigate the time dependence of the heart rate variability (HRV) during treadmill running, a feedback control loop was implemented to eliminate the potentially confounding influence of cardiovascular drift. Without cardiovascular drift, observed changes in HRV can be directly attributed to time only and not to drift-related increases in heart rate. To quantify the time-dependence of HRV, standard HRV metrics for two consecutive windows of equal duration (12.5 min) were computed and compared. Eight participants were included. The outcome measures showed an overall tendency to decrease over time. Seven of the 10 HRV metrics were significantly lower (p<0.05); three HRV metrics showed moderate evidence of decrease over time, viz. average control power (p = 0.053), very-low frequency power (VLF) of the RR-signal (p = 0.072) and low frequency power (LF) of the RR-signal (p = 0.12). Taken together, these results provide evidence of a decrease in HRV over time during treadmill running; the employment of feedback control of heart rate is important as cardiovascular drift was eliminated. Further work is required to optimize the experimental design and to use a larger sample size to improve the statistical power of the results.
{"title":"Time dependence of heart rate variability during treadmill running","authors":"Lars Brockmann, Hanjie Wang, K. Hunt","doi":"10.1080/21642583.2022.2068166","DOIUrl":"https://doi.org/10.1080/21642583.2022.2068166","url":null,"abstract":"To investigate the time dependence of the heart rate variability (HRV) during treadmill running, a feedback control loop was implemented to eliminate the potentially confounding influence of cardiovascular drift. Without cardiovascular drift, observed changes in HRV can be directly attributed to time only and not to drift-related increases in heart rate. To quantify the time-dependence of HRV, standard HRV metrics for two consecutive windows of equal duration (12.5 min) were computed and compared. Eight participants were included. The outcome measures showed an overall tendency to decrease over time. Seven of the 10 HRV metrics were significantly lower (p<0.05); three HRV metrics showed moderate evidence of decrease over time, viz. average control power (p = 0.053), very-low frequency power (VLF) of the RR-signal (p = 0.072) and low frequency power (LF) of the RR-signal (p = 0.12). Taken together, these results provide evidence of a decrease in HRV over time during treadmill running; the employment of feedback control of heart rate is important as cardiovascular drift was eliminated. Further work is required to optimize the experimental design and to use a larger sample size to improve the statistical power of the results.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48910050","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 : 2022-04-22DOI: 10.1080/21642583.2022.2057370
Kaijie Zhang, Chao Wang, X. Yu, A. Zheng, M. Gao, Zhenggao Pan, Guo-ji Chen, Zhiqi Shen
Vehicle tracking detection, recognition and counting is an important part of vehicle analysis. Designing such a model with excellent performance is difficult. The traditional target detection algorithm based on artificial features has poor generalization ability and robustness. In order to take use the deep learning method for vehicle tracking detection, recognition and counting, this paper proposes a vehicle detection method based on yolov5. This method uses the deep learning technology, takes the running vehicles video as the research object, analysis the target detection algorithm, proposes a vehicle detection framework and platform. The relevant detection algorithm of the platform designed in this paper has great adaptability, when displayed under various conditions, such as heavy traffic, night environment, multiple vehicles overlap with each other, partial loss of vehicles, etc. it has good performance. The experimental results show that the algorithm can accurately segment and identify vehicles according to the edge contour of vehicles. It can take use the materials includes pictures, videos, and real-time monitoring, and has a high recognition rate in real-time performance.
{"title":"Research on mine vehicle tracking and detection technology based on YOLOv5","authors":"Kaijie Zhang, Chao Wang, X. Yu, A. Zheng, M. Gao, Zhenggao Pan, Guo-ji Chen, Zhiqi Shen","doi":"10.1080/21642583.2022.2057370","DOIUrl":"https://doi.org/10.1080/21642583.2022.2057370","url":null,"abstract":"Vehicle tracking detection, recognition and counting is an important part of vehicle analysis. Designing such a model with excellent performance is difficult. The traditional target detection algorithm based on artificial features has poor generalization ability and robustness. In order to take use the deep learning method for vehicle tracking detection, recognition and counting, this paper proposes a vehicle detection method based on yolov5. This method uses the deep learning technology, takes the running vehicles video as the research object, analysis the target detection algorithm, proposes a vehicle detection framework and platform. The relevant detection algorithm of the platform designed in this paper has great adaptability, when displayed under various conditions, such as heavy traffic, night environment, multiple vehicles overlap with each other, partial loss of vehicles, etc. it has good performance. The experimental results show that the algorithm can accurately segment and identify vehicles according to the edge contour of vehicles. It can take use the materials includes pictures, videos, and real-time monitoring, and has a high recognition rate in real-time performance.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42938947","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 : 2022-04-20DOI: 10.1080/21642583.2022.2047124
Wanping Song, Zengqiang Chen, Mingwei Sun, Qinglin Sun
To address the position control problem of a six degrees of freedom autonomous underwater vehicle (AUV), the disturbance is observed by an observer and compensated by a controller in this paper. To ensure the vehicle reaches the specified position quickly, the sine cosine algorithm with individual memory is used to find suitable parameters for different controllers. The simulation results show that the observer can extract the system's internal and external uncertainty information in real-time, reduce the phase lag and improve the stability of AUV position control. For a system with complex nonlinearity such as AUV, the observer proposed in this paper has stronger applicability and better robustness.
{"title":"Observation reconstruction and disturbance compensation-based position control for autonomous underwater vehicle","authors":"Wanping Song, Zengqiang Chen, Mingwei Sun, Qinglin Sun","doi":"10.1080/21642583.2022.2047124","DOIUrl":"https://doi.org/10.1080/21642583.2022.2047124","url":null,"abstract":"To address the position control problem of a six degrees of freedom autonomous underwater vehicle (AUV), the disturbance is observed by an observer and compensated by a controller in this paper. To ensure the vehicle reaches the specified position quickly, the sine cosine algorithm with individual memory is used to find suitable parameters for different controllers. The simulation results show that the observer can extract the system's internal and external uncertainty information in real-time, reduce the phase lag and improve the stability of AUV position control. For a system with complex nonlinearity such as AUV, the observer proposed in this paper has stronger applicability and better robustness.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41971701","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 : 2022-04-20DOI: 10.1080/21642583.2022.2063202
Dan-Ni Yang, Jingyi Lu, Hongli Dong, Zhongrui Hu
This paper considers the problem of effective feature extraction of acoustic signals from oil and gas pipelines under different working conditions. A feature extraction of pipeline leakage detection method is proposed based on multi-feature entropy fusion and local linear embedding (LLE). First, seven kinds of commonly used entropy which can reflect the characteristics of the signal better are extracted from the pipeline signal through experiments, including permutation entropy, envelope entropy, approximate entropy, fuzzy entropy, energy entropy, sample entropy and dispersion entropy. The seven-dimensional feature vectors are obtained by feature fusion. Second, the LLE algorithm is used to reduce the dimension of the feature vector to complete the secondary feature extraction. Finally, the support vector machine (SVM) is used to identify the working conditions of the pipeline. The experimental results show that, compared with other dimensionality reduction methods, single-feature entropy method and multi-feature entropy fusion method, the proposed method can identify the types of pipeline working conditions effectively and reduce the problems of false negatives and false positives in pipeline leakage detection.
{"title":"Pipeline signal feature extraction method based on multi-feature entropy fusion and local linear embedding","authors":"Dan-Ni Yang, Jingyi Lu, Hongli Dong, Zhongrui Hu","doi":"10.1080/21642583.2022.2063202","DOIUrl":"https://doi.org/10.1080/21642583.2022.2063202","url":null,"abstract":"This paper considers the problem of effective feature extraction of acoustic signals from oil and gas pipelines under different working conditions. A feature extraction of pipeline leakage detection method is proposed based on multi-feature entropy fusion and local linear embedding (LLE). First, seven kinds of commonly used entropy which can reflect the characteristics of the signal better are extracted from the pipeline signal through experiments, including permutation entropy, envelope entropy, approximate entropy, fuzzy entropy, energy entropy, sample entropy and dispersion entropy. The seven-dimensional feature vectors are obtained by feature fusion. Second, the LLE algorithm is used to reduce the dimension of the feature vector to complete the secondary feature extraction. Finally, the support vector machine (SVM) is used to identify the working conditions of the pipeline. The experimental results show that, compared with other dimensionality reduction methods, single-feature entropy method and multi-feature entropy fusion method, the proposed method can identify the types of pipeline working conditions effectively and reduce the problems of false negatives and false positives in pipeline leakage detection.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48438866","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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