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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Inductive monitoring system constructed from nominal system data and its use in real-time system monitoring

The present invention relates to an Inductive Monitoring System (IMS), its software implementations, hardware embodiments and applications. Training data is received, typically nominal system data acquired from sensors in normally operating systems or from detailed system simulations. The training data is formed into vectors that are used to generate a knowledge database having clusters of nominal operating regions therein. IMS monitors a system's performance or health by comparing cluster parameters in the knowledge database with incoming sensor data from a monitored-system formed into vectors. Nominal performance is concluded when a monitored-system vector is determined to lie within a nominal operating region cluster or lies sufficiently close to a such a cluster as determined by a threshold value and a distance metric. Some embodiments of IMS include cluster indexing and retrieval methods that increase the execution speed of IMS.

Iverson, David L.↗
NASA NTRS2000

Autonomous Performance Monitoring System: Monitoring and Self-Tuning (MAST)

Maintaining the long-term performance of software onboard a spacecraft can be a major factor in the cost of operations. In particular, the task of controlling and maintaining a future mission of distributed spacecraft will undoubtedly pose a great challenge, since the complexity of multiple spacecraft flying in formation grows rapidly as the number of spacecraft in the formation increases. Eventually, new approaches will be required in developing viable control systems that can handle the complexity of the data and that are flexible, reliable and efficient. In this paper we propose a methodology that aims to maintain the accuracy of flight software, while reducing the computational complexity of software tuning tasks. The proposed Monitoring and Self-Tuning (MAST) method consists of two parts: a flight software monitoring algorithm and a tuning algorithm. The dependency on the software being monitored is mostly contained in the monitoring process, while the tuning process is a generic algorithm independent of the detailed knowledge on the software. This architecture will enable MAST to be applicable to different onboard software controlling various dynamics of the spacecraft, such as attitude self-calibration, and formation control. An advantage of MAST over conventional techniques such as filter or batch least square is that the tuning algorithm uses machine learning approach to handle uncertainty in the problem domain, resulting in reducing over all computational complexity. The underlying concept of this technique is a reinforcement learning scheme based on cumulative probability generated by the historical performance of the system. The success of MAST will depend heavily on the reinforcement scheme used in the tuning algorithm, which guarantees the tuning solutions exist.

Peterson, Chariya↗
NASA NTRS2003

Aircraft signal definition for flight safety system monitoring system

A system and method compares combinations of vehicle variable values against known combinations of potentially dangerous vehicle input signal values. Alarms and error messages are selectively generated based on such comparisons. An aircraft signal definition is provided to enable definition and monitoring of sets of aircraft input signals to customize such signals for different aircraft. The input signals are compared against known combinations of potentially dangerous values by operational software and hardware of a monitoring function. The aircraft signal definition is created using a text editor or custom application. A compiler receives the aircraft signal definition to generate a binary file that comprises the definition of all the input signals used by the monitoring function. The binary file also contains logic that specifies how the inputs are to be interpreted. The file is then loaded into the monitor function, where it is validated and used to continuously monitor the condition of the aircraft.

Gibbs, Michael↗
NASA NTRS1979

Automated biowaste sampling system feces monitoring system

The Feces Monitoring System (FMS) Program designed, fabricated, assembled and tested an engineering model waste collector system (WCS) to be used in support of life science and medical experiments related to Shuttle missions. The FMS design was patterned closely after the Shuttle WCS, including: interface provisions; mounting; configuration; and operating procedures. These similarities make it possible to eventually substitute an FMS for the Shuttle WCS of Orbiter. In addition, several advanced waste collection features, including the capability of real-time inertial fecal separation and fecal mass measurement and sampling were incorporated into the FMS design.

Hunt, S. R.↗
DOE OSTI2025

Application of Ocean Thermal Energy Conversion (OTEC) Systems for Powering Safety Monitoring Systems of Offshore Oil and Gas Operations. OESI 2.0 M-1 T-1-P1.1 – Objective 1 Interim Report: Summary of Offshore Oil and Gas Well Monitoring Systems and Process Power Requirements

This report is part of a comprehensive research initiative aimed at evaluating the technoeconomic feasibility of deploying greenhouse gas (GHG) emissions monitoring systems powered by small-scale renewable energy sources on the U.S. Outer Continental Shelf (OCS). The study has three primary objectives: summarizing available GHG monitoring systems for the OCS, modeling a renewable marine energy source (specifically ocean thermal energy conversion, or OTEC), and modeling the collocation of OTEC power sources with offshore oil and gas activities to offset power demand.

02 PETROLEUM↗
NASA NTRS2008

Inductive System Monitors Tasks

The Inductive Monitoring System (IMS) software developed at Ames Research Center uses artificial intelligence and data mining techniques to build system-monitoring knowledge bases from archived or simulated sensor data. This information is then used to detect unusual or anomalous behavior that may indicate an impending system failure. Currently helping analyze data from systems that help fly and maintain the space shuttle and the International Space Station (ISS), the IMS has also been employed by data classes are then used to build a monitoring knowledge base. In real time, IMS performs monitoring functions: determining and displaying the degree of deviation from nominal performance. IMS trend analyses can detect conditions that may indicate a failure or required system maintenance. The development of IMS was motivated by the difficulty of producing detailed diagnostic models of some system components due to complexity or unavailability of design information. Successful applications have ranged from real-time monitoring of aircraft engine and control systems to anomaly detection in space shuttle and ISS data. IMS was used on shuttle missions STS-121, STS-115, and STS-116 to search the Wing Leading Edge Impact Detection System (WLEIDS) data for signs of possible damaging impacts during launch. It independently verified findings of the WLEIDS Mission Evaluation Room (MER) analysts and indicated additional points of interest that were subsequently investigated by the MER team. In support of the Exploration Systems Mission Directorate, IMS is being deployed as an anomaly detection tool on ISS mission control consoles in the Johnson Space Center Mission Operations Directorate. IMS has been trained to detect faults in the ISS Control Moment Gyroscope (CMG) systems. In laboratory tests, it has already detected several minor anomalies in real-time CMG data. When tested on archived data, IMS was able to detect precursors of the CMG1 failure nearly 15 hours in advance of the actual failure event. In the Aeronautics Research Mission Directorate, IMS successfully performed real-time engine health analysis. IMS was able to detect simulated failures and actual engine anomalies in an F/A-18 aircraft during the course of 25 test flights. IMS is also being used in colla

Source record↗
NASA NTRS2010

Monitoring system and methods for a distributed and recoverable digital control system

A monitoring system and methods are provided for a distributed and recoverable digital control system. The monitoring system generally comprises two independent monitoring planes within the control system. The first monitoring plane is internal to the computing units in the control system, and the second monitoring plane is external to the computing units. The internal first monitoring plane includes two in-line monitors. The first internal monitor is a self-checking, lock-step-processing monitor with integrated rapid recovery capability. The second internal monitor includes one or more reasonableness monitors, which compare actual effector position with commanded effector position. The external second monitor plane includes two monitors. The first external monitor includes a pre-recovery computing monitor, and the second external monitor includes a post recovery computing monitor. Various methods for implementing the monitoring functions are also disclosed.

Stange, Kent↗
DOE OSTI2025

Application of Ocean Thermal Energy Conversion (OTEC) Systems for Powering Safety Monitoring Systems of Offshore Oil and Gas Operations, OESI 2.0 M-1 T-1-P1.1 – Objective 3 Report: Collocation of OTEC with Offshore Oil and Gas Activities

This report is a component of a comprehensive research initiative aimed at evaluating the technoeconomic feasibility of deploying Ocean Thermal Energy Conversion (OTEC) systems to power safety monitoring systems for offshore oil and gas operations in the Gulf of America (GOA). The overarching study has three primary objectives: summarizing existing oil and gas equipment monitoring systems, modeling OTEC as a renewable marine energy source, and exploring the collocation of OTEC power sources with offshore oil and gas activities to offset power demand. This report specifically addresses Objective 3, focusing on the integration of OTEC systems with floating oil and gas facilities.

02 PETROLEUM↗
NASA NTRS1971

DSN monitor system

DSN monitor system changes after using IBM 360/75 computers

Maclay, J. E.↗
NASA NTRS2005

Tributary Analysis Monitoring System

A monitoring system for a fleet of vehicles includes at least one data acquisition and analysis module (DAAM) mounted on each vehicle in the fleet, a control module on each vehicle in communication with each DAAM, and terminal module located remotely with respect to the vehicles in the fleet. Each DAAM collects/analyzes sensor data to generate analysis results that identify the state of a plurality of systems of the vehicle. Each vehicle's control module collects/analyzes the analysis results from each onboard DAAM to generate vehicle status results that identify potential sources of vehicle anomalies. The terminal module collects/analyzes the analysis results and vehicle status results transmitted from each control module from the fleet of vehicles to identify multiple occurrences of vehicle anomalies and multiple occurrences of those vehicle systems operating at a performance level that is unacceptable. Results of the terminal module's analysis are provided to organizations responsible for the operation, maintenance and manufacturing of the vehicles in the fleet as well as the plurality of systems used in the fleet.

Stanley E Woodard↗
NASA NTRS1992

Power system monitoring and source control of the Space Station Freedom DC power system testbed

Unlike a terrestrial electric utility which can purchase power from a neighboring utility, the Space Station Freedom (SSF) has strictly limited energy resources; as a result, source control, system monitoring, system protection, and load management are essential to the safe and efficient operation of the SSF Electric Power System (EPS). These functions are being evaluated in the DC Power Management and Distribution (PMAD) Testbed which NASA LeRC has developed at the Power System Facility (PSF) located in Cleveland, Ohio. The testbed is an ideal platform to develop, integrate, and verify power system monitoring and control algorithms. State Estimation (SE) is a monitoring tool used extensively in terrestrial electric utilities to ensure safe power system operation. It uses redundant system information to calculate the actual state of the EPS, to isolate faulty sensors, to determine source operating points, to verify faults detected by subsidiary controllers, and to identify high impedance faults. Source control and monitoring safeguard the power generation and storage subsystems and ensure that the power system operates within safe limits while satisfying user demands with minimal interruptions. System monitoring functions, in coordination with hardware implemented schemes, provide for a complete fault protection system. The objective of this paper is to overview the development and integration of the state estimator and the source control algorithms.

Kimnach, Greg L.↗
NASA NTRS1994

Alarm- And Power-Monitoring System

Electronic central monitoring system, called Remote Monitor Alarm System, RMAS, used to monitor malfunction alarms and power supplies of remotely located equipment modules of transmitting and receiving equipment in fiber-optic communication network at Kennedy Space Center. Includes central monitoring unit at location convenient for technicians, plus remote terminal unit at each remote site containing equipment to be monitored.

Stute, Rob↗
NASA NTRS1992

Power system monitoring and source control of the Space Station Freedom dc-power system testbed

Unlike a terrestrial electric utility which can purchase power from a neighboring utility, the Space Station Freedom (SSF) has strictly limited energy resources; as a result, source control, system monitoring, system protection, and load management are essential to the safe and efficient operation of the SSF Electric Power System (EPS). These functions are being evaluated in the dc Power Management and Distribution (PMAD) Testbed which NASA LeRC has developed at the Power System Facility (PSF) located in Cleveland, Ohio. The testbed is an ideal platform to develop, integrate, and verify power system monitoring and control algorithms. State Estimation (SE) is a monitoring tool used extensively in terrestrial electric utilities to ensure safe power system operation. It uses redundant system information to calculate the actual state of the EPS, to isolate faulty sensors, to determine source operating points, to verify faults detected by subsidiary controllers, and to identify high impedance faults. Source control and monitoring safeguard the power generation and storage subsystems and ensure that the power system operates within safe limits while satisfying user demands with minimal interruptions. System monitoring functions, in coordination with hardware implemented schemes, provide for a complete fault protection system. The objective of this paper is to overview the development and integration of the state estimator and the source control algorithms.

Kimnach, Greg L.↗
DOE OSTI2020

Remote monitoring system

A remote monitoring system for monitoring parameters of an underground asset, such as an electric cable system, a pipeline serving as a conduit for water, gas, oil, sewage, or the like. Parameter detectors, such as sensors that measure temperature, voltage, current, moisture, etc., are distributed along the asset to provide electrical signals that represent respective monitored parameters of the asset. An underground hub disposed in an underground vault, or manhole, through which the asset passes is coupled to the parameter detectors to acquire the signals provided by the parameter detectors. The hub includes a controller to provide data derived from the acquired signals, the data being transmitted to a remote central location by a transceiver, or modem, via LP-WAN communication. Signals from the transceiver are transmitted directly from underground.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Projected network performance for next generation aerosol monitoring systems

Aerosol monitoring for radioactivity is a mature and proven technology. However, by improving key specifications of aerosol monitoring equipment, more samples per day can be collected and analyzed with the same minimum detectable concentrations as current systems. This work models hypothetical releases of 140 Ba and 131 I over a range of magnitudes corresponding to the inventory produced from the fission of about 100 g to 1 kiloton TNT-equivalent of 235 U. The releases occur over an entire year to incorporate the natural variability in atmospheric transport. Sampling equipment located at the 79 locations for radionuclide stations identified in the Comprehensive Nuclear-Test-Ban Treaty (CTBT) for the International Monitoring System are used to determine the detections of the individual releases. Alternative collection schemes in next generation equipment that collect 2, 3, or 4 samples per day, rather than the current 1 sample per day, would result in detections in many more samples at more stations with detections for a given release level. The authors posit that next generation equipment will result in increased network resilience to outages and improved source-location capability for lower yield source releases. The application of dual-detector and coincidence measurements to these systems would significantly boost sensitivity for some isotopes and would further enhance the monitoring capability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2009

Urine Monitoring System

The Urine Monitoring System (UMS) is a system designed to collect an individual crewmember's void, gently separate urine from air, accurately measure void volume, allow for void sample acquisition, and discharge remaining urine into the Waste Collector Subsystem (WCS) onboard the International Space Station. The Urine Monitoring System (UMS) is a successor design to the existing Space Shuttle system and will resolve anomalies such as: liquid carry-over, inaccurate void volume measurements, and cross contamination in void samples. The crew will perform an evaluation of airflow at the ISS UMS urinal hose interface, a calibration evaluation, and a full user interface evaluation. o The UMS can be used to facilitate non-invasive methods for monitoring crew health, evaluation of countermeasures, and implementation of a variety of biomedical research protocols on future exploration missions.

Feedback, Daniel L.↗
NASA NTRS2010

Distributed Impact Detector System (DIDS) Health Monitoring System Evaluation

Damage due to impacts from micrometeoroids and orbital debris is one of the most significant on-orbit hazards for spacecraft. Impacts to thermal protection systems must be detected and the damage evaluated to determine if repairs are needed to allow safe re-entry. To address this issue for the International Space Station Program, Langley Research Center and Johnson Space Center technologists have been working to develop and implement advanced methods for detecting impacts and resultant leaks. LaRC funded a Small Business Innovative Research contract to Invocon, Inc. to develop special wireless sensor systems that are compact, light weight, and have long battery lifetimes to enable applications to long duration space structures. These sensor systems are known as distributed impact detection systems (DIDS). In an assessment, the NASA Engineering and Safety Center procured two prototype DIDS sensor units to evaluate their capabilities in laboratory testing and field testing in an ISS Node 1 structural test article. This document contains the findings of the assessment.

Prosser, William H.↗