Subsea manifold system is a complex system that occupies a pivotal role in contemporary ocean engineering and has a significant impact on the safety of marine resource exploitation. Reliability technology plays a significant role in ensuring the safe operation of the subsea manifold system. To perform a comprehensive analysis of the reliability of complex systems, a combination method of FMECA-FFTA (Failure Modes, Effects and Criticality Analysis - Fuzzy Fault Tree Analysis) is introduced in this study. Firstly, FMECA is used to accomplish a qualitative analysis of system reliability considering multifactorial failure modes, which included analyzing potential failure modes, causes of system failure, and evaluating the degree of hazard to the system through a risk matrix diagram. Then, FFTA is applied to build a fault tree model to divide the system into “system-subsystem-component” and determine the minimal cut sets for quantitative analysis of system reliability. In addition, fuzzy set theory is incorporated to improve the accuracy of handling uncertainty in quantitative reliability analysis. Finally, a qualitative and quantitative reliability analysis is conducted by using FMECA-FFTA method for subsea manifold system. The failure modes of the subsea manifold system are clearly identified, including high-risk modes such as external leakage, medium-high-risk modes such as fail to close/lock on demand, and medium-risk modes such as leakage of critical location, plugged, and effective measures should be taken to focus on preventive protection and regular testing for the high risk, medium-high risk and medium risk modes.

With the further exploitation of offshore resources, there are more and more offshore oil and gas fields which cannot meet the production capacity requirements. So, it becomes extremely urgent to pay attention to the decommissioning of the exploitation equipment in abandoned offshore fields. A new decommissioning solution is offered by the double-ship integrated offshore platform decommissioning equipment comes. However, as the equipment will inevitably bear the combined actions of various dynamic and static loads during operation, the strength and stability of the overall unit and the connections between different modules will be greatly challenged by the complex ocean. Firstly, the dynamic characteristics of the integrated decommissioning system are analyzed in this paper. Mathematical modeling of the lifting arm system is established based on the unit characteristics matrix, and a dynamic equation of the flexible lifting arm unit and system is developed based on Lagrange’s equation and solved through numerical calculation. Secondly, modal analysis and transient analysis of the lifting arm in specific working conditions are performed according to the prototype parameters of the designed decommissioning system. Finally, according to the principle of similitude, a hydrodynamic experiment method is proposed with an integrated decommissioning multi-dimensional vibration test bench. The decommissioning system model test bench is designed and built to perform the dynamic response test, and this paper compares the test results and the simulation results for verification. The comparison verifies that the theoretical analysis and the tests prove each other valid and the results are accurate, meaning this work provides a powerful theoretical reference and offers effective research methods for future studies on super-large-scale integrated decommissioning equipment.

The drill pipe handling system is characterized by large working load, wide range of load variation and high control accuracy requirements, which put certain requirements on the stability and reliability of the hydraulic system. In this paper, the research on the optimized control of electro-hydraulic servo system of drill pipe handling system is mainly conducted. Firstly, the mathematical model of the electro-hydraulic servo system is established and the transfer function of the electro-hydraulic servo system is solved. Secondly, the Cauchy mutation mechanism is introduced to improve the traditional particle swarm optimization (PSO) algorithm for the defects of local optimum, and the algorithm is verified by a series of experiments. The results show that the improved PSO has faster convergence speed and higher convergence accuracy, and the solution performance is greatly improved. Finally, Simulink is used to build a simulation model and the improved PSO algorithm is applied to the optimization of PID parameters. It is found that the improved PSO algorithm obtains better control effect through simulation.