Research On Intelligent Condition Monitoring System For Autonomous Underwater Vehicle

Autonomous underwater vehicles (AUV) are the important carrying agents in the ocean resource development and underwater environment operation. Intelligence is one of the prominent features of AUV, as well as the basis and key technology for research and application of AUV.As a facility operating in the complicated sea environment, the capabilities in autonomy and security are fundamental requirements for AUV, and intelligent control is the core technology to realize its autonomous control and implement the required tasks. With the increasing development and enhancement of AUV function, the complexity of AUV system is also increasing with them, thus its security has been more and more paid attention to. Condition monitoring technology can guarantee the AUV safety. Therefore, it can be provided with theory research significance and application value to model and design intelligent condition monitoring and control system, as well as improve on relevant theoretic.The AUV condition monitoring technology is based on comprehensively identifying the monitored objects, and mastering their types, parameters and performance, etc. The key technologies of research are to model the monitored objects, deal with the collected information, select the appropriate method of feature extraction, establish the fault detection method and monitoring strategy, and diagnose degree of malfunction as well as analyze the running state.Art of the state of AUV system and fault diagnosis is overviewed in this thesis. While the key technology, mostly research results and existing issues of AUV condition monitoring are summarized.According to the basic components of AUV control processes, the intelligent condition monitoring system based on controller has been established on the basis of the fault mechanism of sensor system and thruster system, which constitutes the thruster fault detection subsystem, the AUV motion state detection subsystem, the residual fusion and condition assess subsystem. As a result, it is realized that the fused fault detection and condition evaluation based on multi-residual information, as well as the condition monitoring for the thruster system and the sensor system of AUV. For the intricate sea environment, the thesis presented the assess standard of AUV system design, a system structure that can be applicable to the AUV system, and the design method of hardware system, the center controller, thruster, sensor, power source and communication system.The condition model of AUV based on the improved dynamic recursion network and the thruster performance model based on the RBF network are developed, and the test platform of AUV is implemented and carry out the experiments in pond. From the experiment data, the learn sample is obtained that is requisite for setting up the AUV running state model and thruster performance model. Then, the thruster dynamic model is developed. Furthermore, the research has been made for simulating the thrusters and sensors fault, and the experiment in the pool of AUV thruster and sensors fault monitoring was carried out. The results prove that the models and methods developed in this thesis have been evaluated to be valid and feasible for AUV intelligent condition monitoring system.