Model based design of electro-hydraulic motion control systems for offshore pipe handling equipment

Abstract

Despite the fact that hydraulics, in general, is considered a mature technology, design of hydraulic systems still offers a number of challenges for both component suppliers and manufacturers of hydraulically actuated machines such as offshore pipe handling equipment. This type of equipment is characterized by high price, high level of system complexity and low production numbers. It requires a great level of skill and experience to develop the equipment and the focus on production and development costs is constantly increasing. Therefore design engineers continuously have to improve their procedures for decision making regarding choice of principal solutions, components and materials in order to reach the best possible trade-off between a wide range of design criteria as fast as possible. In this dissertation methods for modeling, parameter identification, design and optimization of a selected piece of offshore pipe handling equipment, a knuckle boom crane, are put forward and treated in details in five appended papers. Modeling of mechanical multi-body systems with attention to structural flexibility is treated in papers I and IV. Modeling, testing and parameter identification of directional control valves with main focus on dynamic characteristics are treated in paper II and also discussed in papers III and IV. Modeling of counterbalance valves with main focus on steady-state characteristics is treated in papers III and IV. In paper IV also modeling of hydraulic cylinders is discussed and a procedure for parameter identification for models of hydraulic-mechanical systems is presented. Steady-state design procedures for hydraulic systems are discussed in paper III and a design optimization method for reduction of oscillations is presented. Paper V deals with dynamic considerations in design of electro-hydraulic motion control systems for offshore pipe handling equipment. All the presented methods are developed to accommodate the needs of the system designer. They take into account the limited access to component data and time available for model development and design optimization, which are the main challenges for the system designer. The methods also address the problem of required knowledge within several disciplines, e.g., by suggesting modeling assumptions and experimental work suitable for system design.