Prognostic Analysis of the Tactical Quiet Generator

The U.S. Army needs prognostic analysis of mission-critical equipment to enable condition-based maintenance before failure. ORNL has developed and patented prognostic technology that quantifies condition change from noisy, multi-channel, time-serial data. This report describes an initial application of ORNL's prognostic technology to the Army's Tactical Quiet Generator (TQG), which is designed to operate continuously at 10 kW. Less-than-full power operation causes unburned fuel to accumulate on internal components, thereby degrading operation and eventually leading to failure. The first objective of this work was identification of easily-acquired, process-indicative data. Two types of appropriate data were identified, namely output-electrical current and voltage, plus tri-axial acceleration (vibration). The second objective of this work was data quality analysis to avoid the garbage-in-garbage-out syndrome. Quality analysis identified more than 10% of the current data as having consecutive values that are constant, or that saturate at an extreme value. Consequently, the electrical data were not analyzed further. The third objective was condition-change analysis to indicate operational stress under non-ideal operation and machine degradation in proportion to the operational stress. Application of ORNL's novel phase-space dissimilarity measures to the vibration power quantified the rising operational stress in direct proportion to the less-than-full-load power. We conclude that ORNL's technology is an excellent candidate to meet the U.S. Army's need for equipment prognostication

Phase Space Dissimilarity Measures for Structural Health Monitoring

A novel method for structural health monitoring (SHM), known as the Phase Space Dissimilarity Measures (PSDM) approach, is proposed and developed. The patented PSDM approach has already been developed and demonstrated for a variety of equipment and biomedical applications. Here, we investigate SHM of bridges via analysis of time serial accelerometer measurements. This work has four aspects. The first is algorithm scalability, which was found to scale linearly from one processing core to four cores. Second, the same data are analyzed to determine how the use of the PSDM approach affects sensor placement. We found that a relatively low-density placement sufficiently captures the dynamics of the structure. Third, the same data are analyzed by unique combinations of accelerometer axes (vertical, longitudinal, and lateral with respect to the bridge) to determine how the choice of axes affects the analysis. The vertical axis is found to provide satisfactory SHM data. Fourth, statistical methods were investigated to validate the PSDM approach for this application, yielding statistically significant results

Error Reduction for Weigh-In-Motion

Federal and State agencies need certifiable vehicle weights for various applications, such as highway inspections, border security, check points, and port entries. ORNL weigh-in-motion (WIM) technology was previously unable to provide certifiable weights, due to natural oscillations, such as vehicle bouncing and rocking. Recent ORNL work demonstrated a novel filter to remove these oscillations. This work shows further filtering improvements to enable certifiable weight measurements (error < 0.1%) for a higher traffic volume with less effort (elimination of redundant weighing)

Prototype Weigh-In-Motion Performance

Oak Ridge National Laboratory (ORNL) has developed and patented methods to weigh slowly moving vehicles. We have used this technology to produce a portable weigh-in-motion system that is robust and accurate. This report documents the performance of the second-generation portable weigh-in-motion prototype (WIM Gen II). The results of three modes of weight determination are compared in this report: WIM Gen II dynamic mode, WIM Gen II stop-and-go mode, and static (parked) mode on in-ground, static scales. The WIM dynamic mode measures axle weights as the vehicle passes over the system at speeds of 3 to 7 miles per hour (1.3 to 3.1 meters/second). The WIM stop-and-go mode measures the weight of each axle of the vehicle as the axles are successively positioned on a side-by-side pair of WIM measurement pads. In both measurement modes the center of balance (CB) and the total weight are obtained by a straight-forward calculation from axle weights and axle spacings. The performance metric is measurement error (in percent), which is defined as 100 x (sample standard deviation)/(average); see Appendix A for details. We have insufficient data to show that this metric is predictive. This report details the results of weight measurements performed in May 2005 at two sites using different types of vehicles at each site. In addition to the weight measurements, the testing enabled refinements to the test methodology and facilitated an assessment of the influence of vehicle speed on the dynamic-mode measurements. The initial test at the National Transportation Research Center in Knoxville, TN, involved measurements of passenger and light-duty commercial vehicles. A subsequent test at the Arrival/Departure Airfield Control Group (A/DACG) facility in Ft. Bragg, NC, involved military vehicles with gross weights between 3,000 and 75,000 pounds (1,356 to 33,900 kilograms) with a 20,000-pound (9,040 kilograms) limit per axle. For each vehicle, four or more separate measurements were done using each weighing mode. WIM dynamic, WIM stop-and-go, and static-mode scale measurements were compared for total vehicle weight and the weight of the individual axles. We made WIM dynamic mode measurements with three assemblages of weight-transducer pads to assess the performance with varying numbers (2, 4, and 6) of weigh pads. Percent error in the WIM dynamic mode was 0.51%, 0.37%, and 0.37% for total vehicle weight and 0.77%, 0.50%, and 0.47% for single-axle weight for the two-, four-, and six-pad systems, respectively. Errors in the WIM stop-and-go mode were 0.55% for total vehicle weight and 0.62% for single-axle weights. In-ground scales weighed these vehicles with an error of 0.04% (within Army specifications) for total vehicle weight, and an error of 0.86% for single-axle weight. These results show that (1) the WIM error in single-axle weight was less than that obtained from in-ground static scales; (2) the WIM system eliminates time-consuming manual procedures, human errors, and safety concerns; and (3) measurement error for the WIM prototype was less than 1% (within Army requirements for this project). All the tests were performed on smooth, dry, level, concrete surfaces. Tests under non-ideal surface conditions are needed (e.g., rough but level, sun-baked asphalt, wet pavement), and future work will test WIM performance under these conditions. However, we expect the performance will be as good as, if not better than, the present WIM performance. We recommend the WIM stop-and-go mode under non-ideal surface conditions. We anticipate no performance degradation, assuming no subsurface deformation occurs

Requirements Definition for ORNL Trusted Corridors Project

The ORNL Trusted Corridors Project has several other names: SensorNet Transportation Pilot; Identification and Monitoring of Radiation (in commerce) Shipments (IMR(ic)S); and Southeastern Transportation Corridor Pilot (SETCP). The project involves acquisition and analysis of transportation data at two mobile and three fixed inspection stations in five states (Kentucky, Mississippi, South Carolina, Tennessee, and Washington DC). Collaborators include the State Police organizations that are responsible for highway safety, law enforcement, and incident response. The three states with fixed weigh-station deployments (KY, SC, TN) are interested in coordination of this effort for highway safety, law enforcement, and sorting/targeting/interdiction of potentially non-compliant vehicles/persons/cargo. The Domestic Nuclear Detection Office (DNDO) in the U.S. Department of Homeland Security (DHS) is interested in these deployments, as a Pilot test (SETCP) to identify Improvised Nuclear Devices (INDs) in highway transport. However, the level of DNDO integration among these state deployments is presently uncertain. Moreover, DHS issues are considered secondary by the states, which perceive this work as an opportunity to leverage these (new) dual-use technologies for state needs. In addition, present experience shows that radiation detectors alone cannot detect DHS-identified IND threats. Continued SETCP success depends on the level of integration of current state/local police operations with the new DHS task of detecting IND threats, in addition to emergency preparedness and homeland security. This document describes the enabling components for continued SETCP development and success, including: sensors and their use at existing deployments (Section 1); personnel training (Section 2); concept of operations (Section 3); knowledge discovery from the copious data (Section 4); smart data collection, integration and database development, advanced algorithms for multiple sensors, and network communications (Section 5); and harmonization of local, state, and Federal procedures and protocols (Section 6)

FED-A, an advanced performance FED based on low safety factor and current drive

This document is one of four describing studies performed in FY 1982 within the context of the Fusion Engineering Device (FED) Program for the Office of Fusion Energy, U.S. Department of Energy. The documents are: 1. FED Baseline Engineering Studies (ORNL/FEDC-82/2), 2. FED-A, An Advanced Performance FED Based on Low Safety Factor and Current Drive (this document), 3. FED-R, A Fusion Device Utilizing Resistive Magnets (ORNL/FEDC-82/1), and 4. Technology Demonstration Facility TDF. These studies extend the FED Baseline concept of FY 1981 and develop innovative and alternative concepts for the FED. The FED-A study project was carried out as part of the Innovative and Alternative Tokamak FED studies, under the direction of P. H. Rutherford, which were part of the national FED program during FY 1982. The studies were performed jointly by senior scientists in the magnetic fusion community and the staff of the Fusion Engineering Design Center (FEDC). Y-K. M. Peng of the FEDC, on assignment from Oak Ridge National Laboratory, served as the design manager

U.S. Patent 8,410,952, Method for Forewarning of Critical Condition Changes in Monitoring Civil Structures

Sensor modules including accelerometers are placed on a physical structure and tri-axial accelerometer data is converted to mechanical power (P) data which then processed to provide a forewarning of a critical event concerning the physical structure. The forewarning is based on a number of occurrences of a composite measure of dissimilarity (Ci) exceeding a forewarning threshold over a defined sampling time; and a forewarning signal is provided to a human observer through a visual, audible or tangible s1gnal. A forewarning of a structural failure can also be provided based on a number of occurrences of (Ci) above a failure value threshold