Diagnostic monitoring in office procedure
Diagnostic monitoring in office procedures - biotelemetry
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery
An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.
Coffin, Thomas↗
Predictive Modeling and Diagnostic Monitoring of Extreme Science Workflows (Final Report)
This proposal addresses a critical issue of performance prediction identified in the report from the ASCR \Computational Modeling of Big Networks (COMBINE)" workshop: "end-to-end performance is not predictable due to a variety of factors. Even when some performance forecasts or predictions can be made, they often cannot explain the reasons why some predictions fail." We will develop new analytical models to predict the end-to-end performance of scientific workflows on DOE computing infrastructures, and use simulations and experimentation to validate and refine these models, as well as to pinpoint the sources of model inaccuracy. We will also use these models to help diagnose application and infrastructure problems, and to adapt the system based on this diagnosis. This section provides background in the areas relevant to the proposed work. RPI’s specific tasks within the Panorama project are as follows: (1) Develop Aspen-Simulation interface for Workflow Model Driven Simulation. (2) Validate manual performance models of two target workflow scenarios with empirical measurement and simulation. (3) Extend ROSS-Aspen API to simulate workflow descriptions when required. (4) Validate Aspen performance models of two target workflow scenarios with automatic performance model empirical measurement and simulation. (5) Design and implement final system to automatically generate Aspen performance models from workflow descriptions (including methods to compensate for limitations of Aspen analytical models). (6) Validate improved Aspen performance models with target workflow on production infrastructure. To date, all the project milestones assigned to us where reached within the best of our abilities over the course of the project performance period. Below describes the key outcome from our collaborative research in a system named, Durango .
97 MATHEMATICS AND COMPUTING↗
TOPICAL: Development of Medical Capabilities and Technologies for Health Monitoring, Diagnostics, and Treatment during Human Exploration Spaceflight
Explore the source record for details and available documents.
Shean E Phelps↗
Real-time expert system diagnostics and monitoring for the High Resolution Microwave Survey Targeted Search
An automated monitoring and diagnostics system (MDS) using virtual real-time software was developed for NASA's High Resolution Microwave Survey (HRMS) Targeted Search System (TSS). The four main tasks required of the MDS were monitoring and recording system health, alerting operators of problems, diagnosing poor system performance, and performing an emergency system shutdown. The MDS was implemented using commercial expert system software tools in addition to interface hardware and software developed on site. The expert system used objects, rules, and schematics in its TSS knowledge representation. The MDS was successfully integrated into the HRMS computer environment, and its performance met or exceeded its requirements.
Macalou, A.↗
Bladder Monitor
Diagnostic Ultrasound Corporation's Bladder Scan Monitor continuously records and monitors bladder fullness and alerts the wearer or caretaker when voiding is required. The sensor is held against the lower abdomen by a belt and connected to the monitor by a cable. The sensor obtains bladder volume data from sound waves reflecting off the bladder wall. The device was developed by Langley Research Center, the Ames Research Center and the NASA Technology Applications Team. It utilizes Langley's advanced ultrasound technology. It is licensed to the ARC for medical applications, and sublicensed to Diagnostics Ultrasound. Central monitoring systems are planned for the future.
Source record↗
Assessment of ProgPy - An Open-Source Condition Monitoring and Diagnostics Tool
Traditional maintenance programs, such as corrective and preventive strategies, may lead to high costs and operational inefficiencies. Condition Monitoring and Diagnostics (CM&D) aims to improve these maintenance strategies by enabling timely insights into equipment health and performance. However, implementation of CM&D can be challenging without a robust framework that manages data efficiently, supports interoperability and simplifies integration. To address these challenges ProgPy, an open-source Python-based prognostics tool developed by NASA Ames Research Center, offers a structured solution for broader Prognostics and Health Management (PHM) applications. Ongoing research is assessing the feasibility of implementing ProgPy as a Condition Monitoring and Diagnostics (CM&D) solution by comparing its framework to the guidelines for open CM&D systems recommended in the ISO 13374-2 standard. This evaluation aims to highlight ProgPy’s strengths and identify opportunities for improvement, thereby, contributing to its advancement as an effective tool for Prognostics and Health Management (PHM). This paper presents the results of an initial assessment of the ProgPy toolbox through a gearbox case study using open-source datasets.
Condition-Monitoring, Diagnostics, Failure, Gearbo↗
The Galileo PPS expert monitoring and diagnostic prototype
The Galileo PPS Expert Monitoring Module (EMM) is a prototype system implemented on the SUN workstation that will demonstrate a knowledge-based approach to monitoring and diagnosis for the Galileo spacecraft Power/Pyro subsystems. The prototype will simulate an analysis module functioning within the SFOC Engineering Analysis Subsystem Environment (EASE). This document describes the implementation of a prototype EMM for the Galileo spacecraft Power Pyro Subsystem. Section 2 of this document provides an overview of the issues in monitoring and diagnosis and comparison between traditional and knowledge-based solutions to this problem. Section 3 describes various tradeoffs which must be considered when designing a knowledge-based approach to monitoring and diagnosis, and section 4 discusses how these issues were resolved in constructing the prototype. Section 5 presents conclusions and recommendations for constructing a full-scale demonstration of the EMM. A Glossary provides definitions of terms used in this text.
Bahrami, Khosrow↗
Flight Test of Propulsion Monitoring and Diagnostic System
The objective of this program was to perform flight tests of the propulsion monitoring and diagnostic system (PMDS) technology concept developed by Honeywell under the NASA Advanced General Aviation Transport Experiment (AGATE) program. The PMDS concept is intended to independently monitor the performance of the engine, providing continuous status to the pilot along with warnings if necessary as well as making the data available to ground maintenance personnel via a special interface. These flight tests were intended to demonstrate the ability of the PMDS concept to detect a class of selected sensor hardware failures, and the ability to successfully model the engine for the purpose of engine diagnosis.
Gabel, Steve↗
A Model-based Health Monitoring and Diagnostic System for the UH-60 Helicopter
Model-based reasoning techniques hold much promise in providing comprehensive monitoring and diagnostics capabilities for complex systems. We are exploring the use of one of these techniques, which utilizes multi-signal modeling and the TEAMS-RT real-time diagnostic engine, on the UH-60 Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) flight research aircraft. We focus on the engine and transmission systems, and acquire sensor data across the 1553 bus as well as by direct analog-to-digital conversion from sensors to the QHuMS (Qualtech health and usage monitoring system) computer. The QHuMS computer uses commercially available components and is rack-mounted in the RASCAL facility. A multi-signal model of the transmission and engine subsystems enables studies of system testability and analysis of the degree of fault isolation available with various instrumentation suites. The model and examples of these analyses will be described and the data architectures enumerated. Flight tests of this system will validate the data architecture and provide real-time flight profiles to be further analyzed in the laboratory.
Patterson-Hine, Ann↗
Smart Monitoring and Diagnostic System (SMDS) for Packaged Air Conditioners and Heat Pumps for Small/Medium Commercial Buildings: Preparation for Commercialization: CRADA 478 [Abstract only]
This project will enable Pacific Northwest National Laboratory (PNNL) and industry partner, mCloud Technologies, to work collaboratively to ready the Smart Monitoring and Diagnostic System (SMDS) for commercial deployment and validate its performance under real-world conditions at field sites. This project will specifically focus on 1) implementing the SMDS algorithms in a scalable cloud-based software architecture, 2) designing new, innovative, complimentary commercial services based on the SMDS, 3) enhancing the SMDS energy and cost impact algorithms to reduce uncertainty in estimates, 4) determining the lower limits on SMDS performance degradation detection, 5) validating algorithm performance and default values of adjustable thresholds with existing data from controlled physical testing and from customer packaged air conditioners and heat pumps (commonly referred to as rooftop units or RTUs), 6) field testing to validate the system on multiple customer buildings in diverse environments, and 7) expanding field deployment to a larger set of mCloud’s customer buildings. Project results by validating, enhancing, and quantifying the performance of the SMDS will position mCloud, and potential future licensees, to implement the SMDS in commercial offerings that encourage and enable use of condition-based and predictive maintenance, leading to significant reductions in energy use and greenhouse gas emissions associated with space conditioning by RTUs. Furthermore, these enhancements will increase the value of the SMDS for users and increase the potential market for its use and impacts.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Towards a machine learning framework for acquiring and exploiting monitoring and diagnostic knowledge
In this paper we address the problem of detecting and diagnosing faults in physical systems, for which neither prior expertise for the task nor suitable system models are available. We propose an architecture that integrates the on-line acquisition and exploitation of monitoring and diagnostic knowledge. The focus of the paper is on the component of the architecture that discovers classes of behaviors with similar characteristics by observing a system in operation. We investigate a characterization of behaviors based on best fitting approximation models. An experimental prototype has been implemented to test it. We present preliminary results in diagnosing faults of the Reaction Control System of the Space Shuttle. The merits and limitations of the approach are identified and directions for future work are set.
Manganaris, Stefanos↗
Cooperating Expert Systems For Automated Monitoring And Diagnostics
Human operators freer to perform nonrepetitive tasks. Expert software system for monitoring multiple streams of sensory data from interacting equipment subsystems undergoing development. Organized hierarchically to monitor multiple equipment subsystems simultaneously. Each expert software subsystem responsible for one of equipment subsystems. Intended to assist human analysts in interpretation of telemetry data indicating operating statuses of subsystems of spacecraft, enables analysts to maintain desired mode(s) of operation, and helps to correct anomalies in subsystems or in overall spacecraft system. Other versions devised for industrial monitoring and analysis tasks similarly complicated.
Schwuttke, Ursula M.↗
Feasibility Investigation on the Development of a Structural Damage Diagnostic and Monitoring System for Rocket Engines
The research activity for this project is mainly to investigate the necessity and feasibility to develop a structural health monitoring system for rocket engines, and to carry out a research plan for further development of the system. More than one hundred technical papers have been searched and reviewed during the period. We concluded after this investigation that adding a new module in NASA's existing automated diagnostic system to monitor the healthy condition of rocket engine structures is a crucial task, and it's possible to develop such a system based upon the vibrational-based nondestructive damage assessment techniques. A number of such techniques have been introduced. Their advantages and disadvantages are also discussed. A global research plan has been figured out. As the first step of the overall research plan, a proposal for the next fiscal year has been submitted.
Shen, Ji Y.↗
Remote Monitoring and Diagnostics of Pitch-Bearing Defects in an MW-Scale Wind Turbine Using Pitch Symmetrical-Component Analysis
Recently, multiple wind turbine failure databases have reviewed that the pitch system is one of the subassemblies with the highest failure rates and largest contributors to the overall downtime. Therefore, there has been an increasing interest to provide remote health monitoring for wind turbine pitch system. While most of the research articles are discussing pitch actuation system (hydraulic or electric actuator) faults only, there is very limited research on pitch-bearing-defect detection. This article provides a remote and hardware-free solution to monitor multiaxis pitch-bearing health condition called pitch symmetrical-component analysis. It leverages readily available low-resolution (100 Hz) electrical measurements, mechanical measurements, and control signals from the existing pitch control platform, and innovatively applies symmetrical-component analysis in multiphase ac system to multiaxis pitch control system and introduces multiaxis pitch-bearing degradation trending curves. This hardware-free solution can be directly applied to the existing wind turbines and successfully give the wind farm operator an early warning before multiaxis pitch bearing fails. It has been proved to be accurate, low cost, and has minimum impacts on turbine normal operation, and has been validated by field data from several North America MW-scale wind farms. This approach turns out to be the first hardware-free (no additional hardware needed) method to remotely monitor and diagnose multiaxis wind turbine pitch-bearing condition.
17 WIND ENERGY↗
Cost Benefit Analyses through Integrated Online Monitoring and Diagnostics (Final Report)
The objective of this research is to improve the economic competitiveness of advanced reactors through the optimization of cost and plant performance, which can be achieved by coupling intelligent online monitoring with asset management decision-making. As advanced reactors are early in the development life-cycle, online monitoring systems and associated sensor networks can be incorporated directly into the design without constraints related to retrofitting and system upgrades
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Return on Investment and Sustainability of HVDC Links: Role of Diagnostics, Condition Monitoring, and Material Innovations
HVDC cable systems are becoming an upscaled technical option, compared to AC, because of various factors, including easier interconnections, lower losses, and longer transmission distances. In addition, renewables providing direct DC energy, electrified transportation, and aerospace where DC can be favored because of higher carried specific power all point in the direction of broad future usage of HV and MV DC links. However, contrary to AC, there is little return from on-field installation as regards long-term cable reliability and aging processes. This gap must be covered by intensive research, and contributing to this research is the purpose of this paper. The focus is on key points for HVDC (and MVDC) cable reliability and sustainability, from design modeling able to account for voltage transients and extrinsic aging (such as that caused by partial discharges) to the impact of aging on insulation conductivity (which rules the electric field distribution, thus aging rate). Also, recyclable and nanostructured materials, as well as health conditions, are considered. It is shown how cable design can account for accelerated aging due to voltage transients, as well as for aging-time dependence of conductivity, and how design can be free of extrinsic aging caused by PDs. Algorithms for health condition evaluations, which have additional value in a relatively new technology such as HVDC polymeric cables, are applied to insulation system aging under partial discharges, showing how they can provide an indication of insulation degradation globally or locally (weak spots) and of possible maintenance times. All of this can effectively contribute to reducing the risk of major cable breakdown and damage under operation, which would significantly affect the return on investment (ROI).
Montanari, Gian Carlo (ORCID:0000000320258693)↗
Partitioning of ocean and land uptake of CO2 as inferred by delta C-13 measurements from the NOAA Climate Monitoring and Diagnostics Laboratory Global Air Sampling Network
Using delta C-13 measurements in atmospheric CO2 from a cooperative global air sampling network, we determined the partitioning of the net uptake of CO2 between ocean and land as a function of latitude and time. The majority of delta C-13 measurements were made at the Institute of Arctic and Alpine Research (INSTAAR) of the University of Colorado. We perform an inverse deconvolution of both CO2 and delta C-13 observations, using a two-dimensional model of atmospheric transport. Also, the discrimination against C-13 by plant photosynthesis, as a function of latitude and time, is calculated from global runs of the simple biosphere (SiB) model. Uncertainty due to the longitudinal structure of the data, which is not represented by the model, is studied through a bootstrap analysis by adding and omitting measurement sites. The resulting error estimates for our inferred sources and sinks are of the order of 1 GTC (1 GTC = 10(exp 15) gC). Such error bars do not reflect potential systematic errors arising from our estimates of the isotopic disequilibria between the atmosphere and the oceans and biosphere, which are estimated in a separate sensitivity analysis. With respect to global totals for 1992 we found that 3.2 GTC of carbon dissolved into the ocean and that 1.5 GTC were sequestered by land ecosystems. Northern hemisphere ocean gyres north of 15 deg N absorbed 2.7 GTC. The equatorial oceans between 10 deg S and 10 deg N were a net source to the atmosphere of 0.9 GTC. We obtained a sink of 1.6 GTC in southern ocean gyres south of 20 deg S, although the deconvolution is poorly constrained by sparse data coverage at high southern latitudes. The seasonal uptake of CO2 in the northern gyres appears to be correlated with a bloom of phytoplankton in surface waters. On land, northern temperate and boreal ecosystems between 35 deg N and 65 deg N were found to be a major sink of CO2 in 1992, as large as 3.5 GTC. Northern tropical ecosystems (equator-30 deg N) appear to be a net source to the source to the atmosphere of 2 GTC which could reflect biomass burning. A small sink, 0.3 GTC, was inferred for southern tropical ecosystems (30 deg S-equator).
Ciais, Philippe↗