Objectives Options associated with geothermal drilling operations are generally limited by factors such as formation temperature and rock strength. The objective of the research is to expand the "tool box" available to the geothermal driller by furthering the development of a high-temperature drilling motor that can be used in directional drilling applications for drilling high temperature geothermal formations. The motor is specifically designed to operate in conjunction with a pneumatic down-the-hole-hammer. It provides a more compact design compared to traditional drilling motors such as PDMs (positive displacement motors). The packaging can help to enhance directional drilling capabilities. It uses no elastomeric components, which enables it to operate in higher temperatures (greater than 250 degrees F). Current work on the motor has shown that is a capable of operating under pneumatic power with a down-the-hole-hammer. Further development work will include continued testing and refining motor components and evaluating motor capabilities. Targets/Milestones Complete testing current motor - 12/31/2010 Make final material and design decisions - 01/31/2011 Build and test final prototype - 04/31/2011 Final demonstration - 07/31/2011 Impacts The development of the motor will help to achieve program technical objectives by improving well construction capabilities. This includes enabling high-temperature drilling as well as enhancing directional drilling. A key component in the auto indexer is the drive motor. It is an air-driven vane motor that converts the energy stored in the compressed air to mechanical energy. The motor is attached to hammer-like components which impart an impulsive load onto the drive shaft. The impulsive force on the drive shaft in turn creates an indexing action. A controlled test was performed to characterize the performance of the the vane motor for a given pressure. The Sandia dynamometer test station was used to determine the performance of the motor for a given input pressure.

Wind turbine condition monitoring (CM) can potentially help the wind industry reduce turbine downtime and operation and maintenance (O&M) cost. NREL CM research has investigated various condition-monitoring techniques such as acoustic emission (AE specifically stress wave), vibration, electrical signature, lubricant and debris monitoring based on the Gearbox Reliability Collaborative dynamometer and field tests, and other test turbines and resources accessible by NREL. During the past several years, NREL CM research has shown that there are very few validation and verification efforts on commercial wind turbine CM systems. One of the reasons might be limited benchmarking datasets accessible by stakeholders. To fill this gap, NREL executed a data collection effort. The targeted users of these datasets include those investigating vibration-based wind turbine CM research, evaluating commercially available vibration-based CM systems, or testing prototyped vibration-based CM systems. NREL collected data from a healthy and a damaged gearbox of the same design tested by the GRC. Vibration data were collected by accelerometers along with high-speed shaft RPM signals during the dynamometer testing. The healthy gearbox was only tested in the dynamometer. The damaged gearbox was first tested in the dynamometer and later sent to a wind farm close to NREL for field testing. In the field test, it experienced two loss-of-oil events that damaged its internal bearings and gear elements. The gearbox was brought back to NREL and it was retested in the dynamometer with CM systems deployed under controlled loading conditions that would not cause catastrophic failure of the gearbox. The objective of releasing these datasets to the public along with information about the real damage that occurred to the damaged gearbox is to provide the wind industry with some benchmarking datasets. These datasets will benefit research, development, validation, verification, and advancement of vibration-based wind condition-monitoring techniques. By accessing this data you acknowledge the terms outlined in the "License Information" document. Please contract Shawn Sheng (NREL) if you have any questions on the data or would like to collaborate on publications based on the datasets.