Proposal of redundant drive wire mechanism for producing motions with high acceleration and high precision

A new wire mechanism called Redundant Drive Wire Mechanism (RDWM) is proposed. The purpose of this paper is to build up the theory of a RDWM with fast motion and fine motion. First, the basic concepts of the proposed mechanism is presented. Second, the vector closure condition for the proposed mechanism is developed. Next, we present the basic equations, propose the basic structure of RDWM with the Internal DOF module, Double Actuation Modules and Precision Modules together with the properties of the mechanism. Finally, we conduct the simulation to show the validity of the RDWM.

Kinematical analysis of redundant drive wire mechanisms with velocity constraint

In this paper, we propose a new velocity constraint type for Redundant Drive Wire Mechanisms. The purpose of this paper is to demonstrate that the proposed velocity constraint module can fix the orientation of the movable part and to use the kinematical analysis method to obtain the moving direction of the movable part. First, we discuss the necessity of using this velocity constraint type and the possible applications of the proposed mechanism. Second, we derive the basic equations of a wire mechanism with this constraint type. Next, we present a method of motion analysis on active and passive constraint spaces, which is used to find the moving direction of a movable part. Finally, we apply the above analysis method on a wire mechanism with a velocity constraint module and on a wire mechanism with four double actuator modules. By evaluating the results, we prove the validity of the proposed constraint type.

Assessment of a 1 hour gridded precipitation dataset to drive a hydrological model: a case study of the summer 2007 floods in the Upper Severn, UK

In this study a gridded hourly 1-km precipitation dataset for a meso-scale catchment (4,062 km2) of the Upper Severn River, UK was constructed using rainfall radar data to disaggregate a daily precipitation (rain gauge) dataset. The dataset was compared to an hourly precipitation dataset created entirely from rainfall radar data. Results found that when assessed against gauge readings and as input to the Lisflood-RR hydrological model, the rain gauge/radar disaggregated dataset performed the best suggesting that this simple method of combining rainfall radar data with rain gauge readings can provide temporally detailed precipitation datasets for calibrating hydrological models.