Positioning Accuracy Determination of the Servo Axes for Grinding Wavy-Tilt-Dam Seals Using a Four-Axis Grinder

The wavy-tilt-dam (WTD) seal is considered to be one of the ideal sealing patterns used in nuclear reactor coolant pumps (RCPs). Grinding such seals with a four-axis grinder had been proposed and six grinding implementation strategies were described in our previous studies. However, another important issue is to determine the positioning accuracy of each servo axis so that the high-precision moving components can be selected properly. In the present paper, the positioning accuracy analysis is carried out to seek a balance between the manufacturing cost and the accuracy requirements. First, a geometric model is established for investigating the error sensitivity of each axis and setting reasonable accuracy allocation of the four axes. Subsequently, the combined influence of all four axes is assessed based on multi-body system (MBS) theory and homogeneous transformation matrix (HTM). According to the results calculated, positioning errors of the X-axis, Z-axis, B-axis, and C-axis within ±10 μm, ±0.1 μm, ±1 arcsec and ±60 arcsec are acceptable, respectively. Meanwhile, the form error calculated of the ground wavy face is no more than 109.74 nm. It is indicated that the accuracy level of the moving components is achievable by modern manufacturing techniques. The present paper is expected to serve as a theoretical basis for the design and development of the four-axis grinder.

State of Science Assessment of Remote Sensing of Great Lakes Coastal Wetlands: Responding to an Operational Requirement

The purpose of this research was to develop a state of science synthesis of remote sensing technologies that could be used to track changes in Great Lakes coastal vegetation for the Great Lakes-St. Lawrence River Adaptive Management (GLAM) Committee. The mapping requirements included a minimum mapping unit (MMU) of either 2 × 2 m or 4 × 4 m, a digital elevation model (DEM) accuracy in x and y of 2 m, a “z” value or vertical accuracy of 1–5 cm, and an accuracy of 90% for the classes of interest. To determine the appropriate remote sensing sensors, we conducted an extensive literature review. The required high degree of accuracy resulted in the elimination of many of the remote sensing sensors used in other wetland mapping applications including synthetic aperture radar (SAR) and optical imagery with a resolution >1 m. Our research showed that remote sensing sensors that could at least partially detect the different types of wetland vegetation in this study were the following types: (1) advanced airborne “coastal” Airborne Light Detection and Ranging (LiDAR) with either a multispectral or a hyperspectral sensor, (2) colour-infrared aerial photography (airplane) with (optimum) 8 cm resolution, (3) colour-infrared unmanned aerial vehicle (UAV) photography with vertical accuracy determination rated at 10 cm, (4) colour-infrared UAV photography with high vertical accuracy determination rated at 3–5 cm, (5) airborne hyperspectral imagery, and (6) very high-resolution optical satellite data with better than 1 m resolution.