The Experts below are selected from a list of 267 Experts worldwide ranked by ideXlab platform
Jiaguo Feng - One of the best experts on this subject based on the ideXlab platform.
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The research of soft yoke Single Point Mooring tower system damage identification based on long-term monitoring data
Applied Ocean Research, 2018Co-Authors: Da Tang, Wang Shisheng, Qianjin Yue, Xianpeng Zeng, Wang Deyu, Yanlin Wang, Bingsen Wang, Bin Xie, Jiaguo FengAbstract:Abstract In this research, to identify the damage of the nonlinearity system under ambient loads, an intelligent damage identification method based on long-term monitoring data is proposed. The random decrement technique and the autocorrelation function algorithm are used to extract free decay of the structure from long-term monitoring data. The random decrement signatures, autocorrelation function, the frequency of free response and the peak Points of the frequency spectrum are used as the features of the structure. These features are then input into the Support Vector Machine (SVM) to classify the current state of the system and their identification accuracy is compared. The simulation experiments results show the extracted features are capable of representing the changes of the system inherent characteristics. Finally, the proposed method is applied to the data analysis of the soft yoke Single Point Mooring (SPM) tower system, and provide the reference for the damage identification of the soft yoke SPM tower system.
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Single Point Mooring system modal parameter identification based on empirical mode decomposition and time-varying autoregressive model
Applied Ocean Research, 2015Co-Authors: Da Tang, Zhongmin Shi, Qianjin Yue, Jiaguo FengAbstract:Abstract A method based on empirical mode decomposition (EMD) and time-varying autoregressive (TVAR) model is proposed here to identify the modal parameters of time-varying systems, such as the Floating Production Storage and Offloading (FPSO) Single Point Mooring system. For the EMD–TVAR method, the original signal is decomposed into a finite number of ‘intrinsic mode functions’ (IMFs) by the EMD. Each IMF can be represented as a TVAR model. Then, the time-varying modal parameters i.e., instantaneous frequency (IF) and modal dumping, can be obtained by the basis functions expansion method. The proposed EMD–TVAR method has good results in two experiments compared with the Huang–Hilbert transformation and Short Time Fourier Transform method, and it has been used to analysis the modal parameters of FPSO Single Point Mooring system successfully. The system's time-varying characteristic and its frequency distribution can be known from the modal analysis results.
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ICSAI - A data fusion method for the attitude of the floating production storage and offloading(FPSO) Single-Point Mooring system based on the monitoring data
The 2014 2nd International Conference on Systems and Informatics (ICSAI 2014), 2014Co-Authors: Dongmei Wang, Zhongmin Shi, Da Tang, Qianjin Yue, Jiaguo FengAbstract:Aiming at the sensor measurement data error of the Single Point Mooring attitude sensors in FPSO (floating production storage and offloading) during monitoring, this paper proposes a method of information fusion based on multi-sensor redundant monitoring. The method creates the multi-body dynamic motion equation of the FPSO Single-Point Mooring system and builds containment relationships among the redundancy data which is based on monitoring data of multi-sensors installed on FPSO hull and Mooring system. This method using nonlinear least square method can effectively correct the monitoring data error and improve the accuracy of the data constraints.
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A data fusion method for the attitude of the floating production storage and offloading(FPSO) Single-Point Mooring system based on the monitoring data
The 2014 2nd International Conference on Systems and Informatics (ICSAI 2014), 2014Co-Authors: Dongmei Wang, Zhongmin Shi, Da Tang, Qianjin Yue, Jiaguo FengAbstract:Aiming at the sensor measurement data error of the Single Point Mooring attitude sensors in FPSO (floating production storage and offloading) during monitoring, this paper proposes a method of information fusion based on multi-sensor redundant monitoring. The method creates the multi-body dynamic motion equation of the FPSO Single-Point Mooring system and builds containment relationships among the redundancy data which is based on monitoring data of multi-sensors installed on FPSO hull and Mooring system. This method using nonlinear least square method can effectively correct the monitoring data error and improve the accuracy of the data constraints.
Changyin Sun - One of the best experts on this subject based on the ideXlab platform.
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three dimensional vibrations control design for a Single Point Mooring line system with input saturation
International Conference on Neural Information Processing, 2017Co-Authors: Weijie Xiang, Changyin SunAbstract:This paper presents a boundary control design for a Single Point Mooring line system with input saturation in three-dimensional (3D) space. The system is described by some partial differential equations (PDEs) and ordinary differential equations (ODEs). The control strategy proposed in this paper at the tip payload of the Mooring line and the control design uses Lyapunov’s direct method (LDM) to ensure the stability of the system. In order to compensate the input saturation, we propose an auxiliary system. With the proposed boundary control, the Mooring system’s uniform boundedness under the effect of external environment is obtained. The presented boundary control is implementable with feasible equipment because all information in the system can be gained and calculated through various sensors or by applying a backward difference algorithm. Simulation results are provided to prove that the controller is effective in regulating the vibration of the system.
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ICONIP (6) - Three-Dimensional Vibrations Control Design for a Single Point Mooring Line System with Input Saturation
Neural Information Processing, 2017Co-Authors: Weijie Xiang, Changyin SunAbstract:This paper presents a boundary control design for a Single Point Mooring line system with input saturation in three-dimensional (3D) space. The system is described by some partial differential equations (PDEs) and ordinary differential equations (ODEs). The control strategy proposed in this paper at the tip payload of the Mooring line and the control design uses Lyapunov’s direct method (LDM) to ensure the stability of the system. In order to compensate the input saturation, we propose an auxiliary system. With the proposed boundary control, the Mooring system’s uniform boundedness under the effect of external environment is obtained. The presented boundary control is implementable with feasible equipment because all information in the system can be gained and calculated through various sensors or by applying a backward difference algorithm. Simulation results are provided to prove that the controller is effective in regulating the vibration of the system.
Weijie Xiang - One of the best experts on this subject based on the ideXlab platform.
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three dimensional vibrations control design for a Single Point Mooring line system with input saturation
International Conference on Neural Information Processing, 2017Co-Authors: Weijie Xiang, Changyin SunAbstract:This paper presents a boundary control design for a Single Point Mooring line system with input saturation in three-dimensional (3D) space. The system is described by some partial differential equations (PDEs) and ordinary differential equations (ODEs). The control strategy proposed in this paper at the tip payload of the Mooring line and the control design uses Lyapunov’s direct method (LDM) to ensure the stability of the system. In order to compensate the input saturation, we propose an auxiliary system. With the proposed boundary control, the Mooring system’s uniform boundedness under the effect of external environment is obtained. The presented boundary control is implementable with feasible equipment because all information in the system can be gained and calculated through various sensors or by applying a backward difference algorithm. Simulation results are provided to prove that the controller is effective in regulating the vibration of the system.
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ICONIP (6) - Three-Dimensional Vibrations Control Design for a Single Point Mooring Line System with Input Saturation
Neural Information Processing, 2017Co-Authors: Weijie Xiang, Changyin SunAbstract:This paper presents a boundary control design for a Single Point Mooring line system with input saturation in three-dimensional (3D) space. The system is described by some partial differential equations (PDEs) and ordinary differential equations (ODEs). The control strategy proposed in this paper at the tip payload of the Mooring line and the control design uses Lyapunov’s direct method (LDM) to ensure the stability of the system. In order to compensate the input saturation, we propose an auxiliary system. With the proposed boundary control, the Mooring system’s uniform boundedness under the effect of external environment is obtained. The presented boundary control is implementable with feasible equipment because all information in the system can be gained and calculated through various sensors or by applying a backward difference algorithm. Simulation results are provided to prove that the controller is effective in regulating the vibration of the system.
Da Tang - One of the best experts on this subject based on the ideXlab platform.
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The research of soft yoke Single Point Mooring tower system damage identification based on long-term monitoring data
Applied Ocean Research, 2018Co-Authors: Da Tang, Wang Shisheng, Qianjin Yue, Xianpeng Zeng, Wang Deyu, Yanlin Wang, Bingsen Wang, Bin Xie, Jiaguo FengAbstract:Abstract In this research, to identify the damage of the nonlinearity system under ambient loads, an intelligent damage identification method based on long-term monitoring data is proposed. The random decrement technique and the autocorrelation function algorithm are used to extract free decay of the structure from long-term monitoring data. The random decrement signatures, autocorrelation function, the frequency of free response and the peak Points of the frequency spectrum are used as the features of the structure. These features are then input into the Support Vector Machine (SVM) to classify the current state of the system and their identification accuracy is compared. The simulation experiments results show the extracted features are capable of representing the changes of the system inherent characteristics. Finally, the proposed method is applied to the data analysis of the soft yoke Single Point Mooring (SPM) tower system, and provide the reference for the damage identification of the soft yoke SPM tower system.
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Single Point Mooring system modal parameter identification based on empirical mode decomposition and time-varying autoregressive model
Applied Ocean Research, 2015Co-Authors: Da Tang, Zhongmin Shi, Qianjin Yue, Jiaguo FengAbstract:Abstract A method based on empirical mode decomposition (EMD) and time-varying autoregressive (TVAR) model is proposed here to identify the modal parameters of time-varying systems, such as the Floating Production Storage and Offloading (FPSO) Single Point Mooring system. For the EMD–TVAR method, the original signal is decomposed into a finite number of ‘intrinsic mode functions’ (IMFs) by the EMD. Each IMF can be represented as a TVAR model. Then, the time-varying modal parameters i.e., instantaneous frequency (IF) and modal dumping, can be obtained by the basis functions expansion method. The proposed EMD–TVAR method has good results in two experiments compared with the Huang–Hilbert transformation and Short Time Fourier Transform method, and it has been used to analysis the modal parameters of FPSO Single Point Mooring system successfully. The system's time-varying characteristic and its frequency distribution can be known from the modal analysis results.
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ICSAI - A data fusion method for the attitude of the floating production storage and offloading(FPSO) Single-Point Mooring system based on the monitoring data
The 2014 2nd International Conference on Systems and Informatics (ICSAI 2014), 2014Co-Authors: Dongmei Wang, Zhongmin Shi, Da Tang, Qianjin Yue, Jiaguo FengAbstract:Aiming at the sensor measurement data error of the Single Point Mooring attitude sensors in FPSO (floating production storage and offloading) during monitoring, this paper proposes a method of information fusion based on multi-sensor redundant monitoring. The method creates the multi-body dynamic motion equation of the FPSO Single-Point Mooring system and builds containment relationships among the redundancy data which is based on monitoring data of multi-sensors installed on FPSO hull and Mooring system. This method using nonlinear least square method can effectively correct the monitoring data error and improve the accuracy of the data constraints.
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A data fusion method for the attitude of the floating production storage and offloading(FPSO) Single-Point Mooring system based on the monitoring data
The 2014 2nd International Conference on Systems and Informatics (ICSAI 2014), 2014Co-Authors: Dongmei Wang, Zhongmin Shi, Da Tang, Qianjin Yue, Jiaguo FengAbstract:Aiming at the sensor measurement data error of the Single Point Mooring attitude sensors in FPSO (floating production storage and offloading) during monitoring, this paper proposes a method of information fusion based on multi-sensor redundant monitoring. The method creates the multi-body dynamic motion equation of the FPSO Single-Point Mooring system and builds containment relationships among the redundancy data which is based on monitoring data of multi-sensors installed on FPSO hull and Mooring system. This method using nonlinear least square method can effectively correct the monitoring data error and improve the accuracy of the data constraints.
Qianjin Yue - One of the best experts on this subject based on the ideXlab platform.
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The research of soft yoke Single Point Mooring tower system damage identification based on long-term monitoring data
Applied Ocean Research, 2018Co-Authors: Da Tang, Wang Shisheng, Qianjin Yue, Xianpeng Zeng, Wang Deyu, Yanlin Wang, Bingsen Wang, Bin Xie, Jiaguo FengAbstract:Abstract In this research, to identify the damage of the nonlinearity system under ambient loads, an intelligent damage identification method based on long-term monitoring data is proposed. The random decrement technique and the autocorrelation function algorithm are used to extract free decay of the structure from long-term monitoring data. The random decrement signatures, autocorrelation function, the frequency of free response and the peak Points of the frequency spectrum are used as the features of the structure. These features are then input into the Support Vector Machine (SVM) to classify the current state of the system and their identification accuracy is compared. The simulation experiments results show the extracted features are capable of representing the changes of the system inherent characteristics. Finally, the proposed method is applied to the data analysis of the soft yoke Single Point Mooring (SPM) tower system, and provide the reference for the damage identification of the soft yoke SPM tower system.
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Single Point Mooring system modal parameter identification based on empirical mode decomposition and time-varying autoregressive model
Applied Ocean Research, 2015Co-Authors: Da Tang, Zhongmin Shi, Qianjin Yue, Jiaguo FengAbstract:Abstract A method based on empirical mode decomposition (EMD) and time-varying autoregressive (TVAR) model is proposed here to identify the modal parameters of time-varying systems, such as the Floating Production Storage and Offloading (FPSO) Single Point Mooring system. For the EMD–TVAR method, the original signal is decomposed into a finite number of ‘intrinsic mode functions’ (IMFs) by the EMD. Each IMF can be represented as a TVAR model. Then, the time-varying modal parameters i.e., instantaneous frequency (IF) and modal dumping, can be obtained by the basis functions expansion method. The proposed EMD–TVAR method has good results in two experiments compared with the Huang–Hilbert transformation and Short Time Fourier Transform method, and it has been used to analysis the modal parameters of FPSO Single Point Mooring system successfully. The system's time-varying characteristic and its frequency distribution can be known from the modal analysis results.
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ICSAI - A data fusion method for the attitude of the floating production storage and offloading(FPSO) Single-Point Mooring system based on the monitoring data
The 2014 2nd International Conference on Systems and Informatics (ICSAI 2014), 2014Co-Authors: Dongmei Wang, Zhongmin Shi, Da Tang, Qianjin Yue, Jiaguo FengAbstract:Aiming at the sensor measurement data error of the Single Point Mooring attitude sensors in FPSO (floating production storage and offloading) during monitoring, this paper proposes a method of information fusion based on multi-sensor redundant monitoring. The method creates the multi-body dynamic motion equation of the FPSO Single-Point Mooring system and builds containment relationships among the redundancy data which is based on monitoring data of multi-sensors installed on FPSO hull and Mooring system. This method using nonlinear least square method can effectively correct the monitoring data error and improve the accuracy of the data constraints.
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A data fusion method for the attitude of the floating production storage and offloading(FPSO) Single-Point Mooring system based on the monitoring data
The 2014 2nd International Conference on Systems and Informatics (ICSAI 2014), 2014Co-Authors: Dongmei Wang, Zhongmin Shi, Da Tang, Qianjin Yue, Jiaguo FengAbstract:Aiming at the sensor measurement data error of the Single Point Mooring attitude sensors in FPSO (floating production storage and offloading) during monitoring, this paper proposes a method of information fusion based on multi-sensor redundant monitoring. The method creates the multi-body dynamic motion equation of the FPSO Single-Point Mooring system and builds containment relationships among the redundancy data which is based on monitoring data of multi-sensors installed on FPSO hull and Mooring system. This method using nonlinear least square method can effectively correct the monitoring data error and improve the accuracy of the data constraints.