In the hydropower industry, in situ maintenance work of turbine runners to address issues such as cavitation damage and cracking is mainly performed manually. Alternatively, the entire turbine requires disassembly and is repaired off site at greater cost. This paper presents the development and fundamentals of robotic technology designed to perform work in situ on hydroelectric equipment. A second paper surveys field implementations carried out with the technology over the past 15 years. A new portable manipulator was designed with unique track-based kinematics well suited to accessing turbine blades in a confined space. The robot is driven by position-controlled stepper motors but relies on a hybrid force/position controller to perform processes in contact with the work piece, such as grinding. A major obstacle for robotic repair is excessive programming time. As most work is done on curved surfaces, the robot relies on a model of curvilinear space for trajectory generation. The robot is coupled to an accurate measurement system to scan surface topography in three dimensions. It has been equipped to perform several processes, such as welding and grinding, to facilitate the manufacture and maintenance of hydropower equipment. Despite the robot's inaccuracy and flexibility, surface profiles may be reconstructed with great accuracy through the use of a controlled metal removal rate strategy that relies on an innovative dynamic model of the grinding process. C

Field repair work on large hydropower equipment is rarely automated due to the high complexity of the task. Generally, the work is done manually or the equipment is dismantled and repaired off site at greatly added cost and time. This paper surveys work carried out with the SCOMPI robot in the field on large hydropower equipment. SCOMPI is a small, portable, multiprocess, track-based robot. This paper is the continuation of another paper in which the fundamentals of the robot technology are described in greater detail. Over the past 15 years, SCOMPIs have been extensively employed for a variety of field applications on equipment such as turbines, head gates, spillway gates, and penstocks. Initially designed to repair cavitation damage to turbines, the robots are now applied to reinforce turbines or to improve their performance in terms of efficiency. More recently, they have been used for the refurbishment of gates and for the construction of penstocks. C 2011 Wiley Periodicals, Inc.

Robot manipulators play an im portant role in industrial automation. Various aspects of robotic systems were subject of intensive investigations in the past, but the vibration problems in robotic machining processes have been rarely treated in the available literature. In this paper we present dynamic modeling of an ongoing research to study chatter vibration in robotic grinding process using a portable manipulator for rectifying the surfaces of hydro-electric equipments.This special-purpose robot manipulator was developed to automate on-site repairs such as grinding of eroded surfaces, depositing overlay welding and hammer peening. In this study, the structure of robot as the tool holder mechanism of the machining operation is modeled by articulated rigid bodies with flexible joints. The dynamic equations of the 6DOF flexiblejoint manipulator are established using Lagrangian formulation. 1mpulsive grinding forces and periodically perturbed excitations existing in the process are exerted on the model to simulate its response. As an intuitive estimation for joints' stiffness parameters of the model, payload test experiments were performed on the robot. To validate predictions of the dynamic model regarding vibratory behavior, modal testing experiments were performed and measured natural frequencies and mode shapes were compared to their analytical equivalents. Some future trends of the research work are also addressed.

This paper presents the experimental characterization and vibration control of a flexible robotic system. For this work, a test bench was built to characterize the harmonic drive (HD) and joint components, while control algorithms were designed and compared to minimize vibration. Encoder accuracy was critical since the difference in the measurements between two encoders was used to evaluate the vibrational behavior of the test set-up. Therefore, a laser tracker was used to characterize the error of the output encoder. Real-time compensation using this technique achieved an angular position accuracy of 50 µrad. Four rosette strain gauges were fixed to the HD’s flexible spline to determine its torsion. To reduce torque ripple, a real-time correcting function was applied. It was thus possible to reduce the error to 0.3% of the full-scale error. Two vibration control strategies were developed, namely, singular perturbation and feed-forward control. Simulation results showed that both control strategies greatly reduced vibration response compared to a common rigid control. However, test results showed that good vibration control could only be achieved with the feed-forward approach: the singular perturbation technique generated too much torque ripple to the motor. A feed-forward controller can quickly stabilize the link, achieving the same settling time as with the rigid control algorithm.

This paper presents a method for the extraction of modal parameters for identification of time-varying systems using Data-Driven Stochastic Subspace Identification (SSI-DATA). In practical applications of SSI-DATA, both the modal parameters and computational ones are mixed together in the identified results. In order to differentiate the structural ones from computational ones, a new method based on the eigen-decomposition of the state matrix constructed in SSI-DATA is proposed. The efficiency of the proposed method is demonstrated through numerical simulation of a lumped-mass system and experimental test of a moving robot for extracting excited natural frequencies of the system.