Based on dynamic response signals a damage detection algorithm is developed for marine risers. Damage detection methods based on numerous modal properties have encountered issues in the researches in offshore oil comm...Based on dynamic response signals a damage detection algorithm is developed for marine risers. Damage detection methods based on numerous modal properties have encountered issues in the researches in offshore oil community. For example, significant increase in structure mass due to marine plant/animal growth and changes in modal properties by equipment noise are not the result of damage for riser structures. In an attempt to eliminate the need to determine modal parameters, a data-based method is developed. The implementation of the method requires that vibration data are first standardized to remove the influence of different loading conditions and the autoregressive moving average(ARMA) model is used to fit vibration response signals. In addition, a damage feature factor is introduced based on the autoregressive(AR) parameters. After that, the Euclidean distance between ARMA models is subtracted as a damage indicator for damage detection and localization and a top tensioned riser simulation model with different damage scenarios is analyzed using the proposed method with dynamic acceleration responses of a marine riser as sensor data. Finally, the influence of measured noise is analyzed. According to the damage localization results, the proposed method provides accurate damage locations of risers and is robust to overcome noise effect.展开更多
In the exploitation of ocean oil and gas, many offshore structures may be damaged due to the severe environment, so an effective method of diagnosing structural damage is urgently needed to locate the damage and evalu...In the exploitation of ocean oil and gas, many offshore structures may be damaged due to the severe environment, so an effective method of diagnosing structural damage is urgently needed to locate the damage and evaluate its severity. Genetic algorithms have become some of the most important global optimization tools and been widely used in many fields in recent years because of their simple operation and strong robustness. Based on the natural frequencies and mode shapes of the structure, the damage diagnosis of a jacket offshore platform is attributed to an optimization problem and studied by using a genetic algorithm. According to the principle that the structural stiffness of a certain direction can be greatly affected only when the brace bar in the corresponding direction is damaged, an improved objective function was proposed in this paper targeting measurement noise and the characteristics of modal identification for offshore platforms. This function can be used as fitness function of a genetic algorithm, and both numerical simulation and physical model test results show that the improved method may locate the structural damage and evaluate the severity of a jacket offshore platform satisfactorily while improving the robustness of evolutionary searching and the reliability of damage diagnosis.展开更多
基金financially supported by the 973 Project (Grant No. 2011CB013704)by the National Natural Science Foundation of China (Grant Nos. 51379005, 51009093)
文摘Based on dynamic response signals a damage detection algorithm is developed for marine risers. Damage detection methods based on numerous modal properties have encountered issues in the researches in offshore oil community. For example, significant increase in structure mass due to marine plant/animal growth and changes in modal properties by equipment noise are not the result of damage for riser structures. In an attempt to eliminate the need to determine modal parameters, a data-based method is developed. The implementation of the method requires that vibration data are first standardized to remove the influence of different loading conditions and the autoregressive moving average(ARMA) model is used to fit vibration response signals. In addition, a damage feature factor is introduced based on the autoregressive(AR) parameters. After that, the Euclidean distance between ARMA models is subtracted as a damage indicator for damage detection and localization and a top tensioned riser simulation model with different damage scenarios is analyzed using the proposed method with dynamic acceleration responses of a marine riser as sensor data. Finally, the influence of measured noise is analyzed. According to the damage localization results, the proposed method provides accurate damage locations of risers and is robust to overcome noise effect.
基金Supported by the National Natural Science Fundation of China (51079136)(51179179)
文摘In the exploitation of ocean oil and gas, many offshore structures may be damaged due to the severe environment, so an effective method of diagnosing structural damage is urgently needed to locate the damage and evaluate its severity. Genetic algorithms have become some of the most important global optimization tools and been widely used in many fields in recent years because of their simple operation and strong robustness. Based on the natural frequencies and mode shapes of the structure, the damage diagnosis of a jacket offshore platform is attributed to an optimization problem and studied by using a genetic algorithm. According to the principle that the structural stiffness of a certain direction can be greatly affected only when the brace bar in the corresponding direction is damaged, an improved objective function was proposed in this paper targeting measurement noise and the characteristics of modal identification for offshore platforms. This function can be used as fitness function of a genetic algorithm, and both numerical simulation and physical model test results show that the improved method may locate the structural damage and evaluate the severity of a jacket offshore platform satisfactorily while improving the robustness of evolutionary searching and the reliability of damage diagnosis.
