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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Discrepancy Reporting Management System

Discrepancy Reporting Management System (DRMS) is a computer program designed for use in the stations of NASA's Deep Space Network (DSN) to help establish the operational history of equipment items; acquire data on the quality of service provided to DSN customers; enable measurement of service performance; provide early insight into the need to improve processes, procedures, and interfaces; and enable the tracing of a data outage to a change in software or hardware. DRMS is a Web-based software system designed to include a distributed database and replication feature to achieve location-specific autonomy while maintaining a consistent high quality of data. DRMS incorporates commercial Web and database software. DRMS collects, processes, replicates, communicates, and manages information on spacecraft data discrepancies, equipment resets, and physical equipment status, and maintains an internal station log. All discrepancy reports (DRs), Master discrepancy reports (MDRs), and Reset data are replicated to a master server at NASA's Jet Propulsion Laboratory; Master DR data are replicated to all the DSN sites; and Station Logs are internal to each of the DSN sites and are not replicated. Data are validated according to several logical mathematical criteria. Queries can be performed on any combination of data.

Cooper, Tonja M.↗
NASA NTRS2003

Enhancing DSN Operations Efficiency with the Discrepancy Reporting Management System (DRMS)

The DRMS is the Discrepancy Reporting Management System used by the Deep Space Network (DSN). It uses a web interface and is a management tool designed to track and manage: data outage incidents during spacecraft tracks against equipment and software known as DRs (discrepancy Reports), to record "out of pass" incident logs against equipment and software in a Station Log, to record instances where equipment has be restarted or reset as Reset records, and to electronically record equipment readiness status across the DSN. Tracking and managing these items increases DSN operational efficiency by providing: the ability to establish the operational history of equipment items, data on the quality of service provided to the DSN customers, the ability to measure service performance, early insight into processes, procedures and interfaces that may need updating or changing, and the capability to trace a data outage to a software or hardware change. The items listed above help the DSN to focus resources on areas of most need.

Discrepancy Reporting Management Systems (DRMS)↗
NASA NTRS1985

Determining Availability Characteristics of DSN Data Systems Using Discrepancy Report Data

A reasonably economical way was developed to determine availability characteristics of Deep Space Network (DSN) data systems, subsystems, and assemblies using the DSN discrepancy report (DR) data base and DSN operating schedule and history data bases. Operating mean time between failures (OMTBF), operating mean time to restore service (OMTTRS), and operating functional availability (OFA) can be computed by year, by system, by subsystem, by assembly, and by station. The effort required to produce the desired reports is described, specific data on the telemetry, command, and tracking systems are presented, and major contributors to system outages are identified. Future improvements in preparing and analyzing DR data are also outlined to enhance their use in correcting conditions that lead to outages.

Ruskin, A. M.↗
NASA NTRS1989

A simple model for DSS-14 outage times

A model is proposed to describe DSS-14 outage times. Discrepancy Reporting System outage data for the period from January 1986 through September 1988 are used to estimate the parameters of the model. The model provides a probability distribution for the duration of outages, which agrees well with observed data. The model depends only on a small number of parameters, and has some heuristic justification. This shows that the Discrepancy Reporting System in the Deep Space Network (DSN) can be used to estimate the probability of extended outages in spite of the discrepancy reports ending when the pass ends. The probability of an outage extending beyond the end of a pass is estimated as around 5 percent.

Rumsey, H. C.↗
NASA NTRS1978

Viking extended mission support

The status of the Viking Deep Space Network Mark 3 '77 data subsystem implementation project and related testing at DSS 42/43 from 1 September through 31 October 1977 are reported. The Viking DSN discrepancy reporting system, Viking command support, tracking support, and periodic tests conducted with the Viking spacecraft are also discussed.

Howe, T. W.↗
NASA NTRS2002

Deep Space Network equipment performance, reliability, and operations management information system

The Deep Space Mission System (DSMS) Operations Program Office and the DeepSpace Network (DSN) facilities utilize the Discrepancy Reporting Management System (DRMS) to collect, process, communicate and manage data discrepancies, equipment resets, physical equipment status, and to maintain an internal Station Log. A collaborative effort development between JPL and the Canberra Deep Space Communication Complex delivered a system to support DSN Operations.

discrepancy reporting DSN operations web-based too↗
NASA NTRS1977

Viking extended mission support

The period from 1 July through 31 August 1977 is covered and included is the remainder of post DSN Mark 3 Data Subsystem Implementation Project Viking-related testing at DSS14. Also included are reports on the Viking DSN Discrepancy Reporting System, Viking command support, tracking support, and periodic tests conducted with the Viking spacecraft.

Howe, T. W.↗
NASA NTRS2001

Integrating Safety in the Aviation System: Interdepartmental Training for Pilots and Maintenance Technicians

The study of human factors has had a decisive impact on the aviation industry. However, the entire aviation system often is not considered in researching, training, and evaluating human factors issues especially with regard to safety. In both conceptual and practical terms, we argue for the proactive management of human error from both an individual and organizational systems perspective. The results of a multidisciplinary research project incorporating survey data from professional pilots and maintenance technicians and an exploratory study integrating students from relevant disciplines are reported. Survey findings suggest that latent safety errors may occur during the maintenance discrepancy reporting process because pilots and maintenance technicians do not effectively interact with one another. The importance of interdepartmental or cross-disciplinary training for decreasing these errors and increasing safety is discussed as a primary implication.

Mattson, Marifran↗
NASA NTRS1976

Viking mission support

The most significant Viking Mission events supported by the DSN during August and September 1976 are reported. Intermediate Data production and DSS support are also summarized for this period. Viking DSN Discrepancy Report activity for the period January 1975 through September 1976 is also included.

Johnston, D. W. H.↗
NASA NTRS2005

Discovering Recurring Anomalies in Text Reports Regarding Complex Space Systems

Many existing complex space systems have a significant amount of historical maintenance and problem data bases that are stored in unstructured text forms. For some platforms, these reports may be encoded as scanned images rather than even searchable text. The problem that we address in this paper is the discovery of recurring anomalies and relationships between different problem reports that may indicate larger systemic problems. We will illustrate our techniques on data from discrepancy reports regarding software anomalies in the Space Shuttle. These free text reports are written by a number of different penp!e, thus the emphasis and wording varies considerably.

Zane-Ulman, Brett↗
NASA NTRS1977

Viking extended mission support

The period 1 March 1977 through 30 April 1977 is reported and includes Deep Space Network (DSN) Mark III data system testing. Status of the Viking DSN discrepancy reporting system as well as the status of Viking related tracking and command support were also considered. Operations support of Viking events and radio science activities were examined. Current progress on the major reconfiguration of the Network is presented in the context of support for the Viking extended mission.

Howe, T. W.↗
NASA NTRS2006

Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)

This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search

McIntosh, Dawn↗
NASA NTRS1997

Report on the Radar/PIREP Cloud Top Discrepancy Study

This report documents the results of the Applied Meteorology Unit's (AMU) investigation of inconsistencies between pilot reported cloud top heights and weather radar indicated echo top heights (assumed to be cloud tops) as identified by the 45 Weather Squadron (45WS). The objective for this study is to document and understand the differences in echo top characteristics as displayed on both the WSR-88D and WSR-74C radars and cloud top heights reported by the contract weather aircraft in support of space launch operations at Cape Canaveral Air Station (CCAS), Florida. These inconsistencies are of operational concern since various Launch Commit Criteria (LCC) and Flight Rules (FR) in part describe safe and unsafe conditions as a function of cloud thickness. Some background radar information was presented. Scan strategies for the WSR-74C and WSR-88D were reviewed along with a description of normal radar beam propagation influenced by the Effective Earth Radius Model. Atmospheric conditions prior to and leading up to both launch operations were detailed. Through the analysis of rawinsonde and radar data, atmospheric refraction or bending of the radar beam was identified as the cause of the discrepancies between reported cloud top heights by the contract weather aircraft and those as identified by both radars. The atmospheric refraction caused the radar beam to be further bent toward the Earth than normal. This radar beam bending causes the radar target to be displayed erroneously, with higher cloud top heights and a very blocky or skewed appearance.

Wheeler, Mark M.↗
NASA NTRS1992

Study report recommendations for the next generation Range Safety System (RSS) Integrated Receiver/Decoder (IRD)

The Integrated Receiver/Decoder (IRD) currently used on the Space Shuttle was designed in the 1980 and prior time frame. Over the past 12 years, several parts have become obsolete or difficult to obtain. As directed by the Marshall Space Flight Center, a primary objective is to investigate updating the IRD design using the latest technology subsystems. To take advantage of experience with the current designs, an analysis of failures and a review of discrepancy reports, material review board actions, scrap, etc. are given. A recommended new design designated as the Advanced Receiver/Decoder (ARD) is presented. This design uses the latest technology components to simplify circuits, improve performance, reduce size and cost, and improve reliability. A self-test command is recommended that can improve and simplify operational procedures. Here, the new design is contrasted with the old. Possible simplification of the total Range Safety System is discussed, as is a single-step crypto technique that can improve and simplify operational procedures.

Crosby, Robert H.↗
NASA NTRS1982

LANDSAT-4 post launch report 1

LANDSAT-4 (formerly LANDSAT-D) was launched successfully at 1:59 p.m. EDT on July 16, 1982, from Vandenberg Air Force Base. The Delta 3920 launch vehicle performed flawlessly and placed the satellite into the planned three sigma low orbit of 694 km. The lower orbit was selected to eliminate a retrograde maneuver for the orbit adjust burns necessary to place the satellite into its planned operational 16-day repeat track at 705 km. Spacecraft separation and the initiation of solar array depolyment occurred, over the Indian Ocean tracking station. Spacecraft attitude rates at separation were low, allowing the Earth sensor to immediately acquire the Earth with the momentum wheels and without use of the propulsion system. All systems activated as of noon on July 18, 1982, are performing well with no significant discrepancies reported.

Source record↗
NASA NTRS2021

Time series comparisons in Deep Space Network

The Deep Space Network (DSN) is NASA’s international array of antennas that support interplanetary spacecraft missions. DSN provides radar and radio astronomy observations that enhance our understanding of the solar system and the larger universe. A track is a block of continuous multi-dimensional time series from the beginning to end of DSN communication with the target spacecraft, containing 129 monitor data items lasting several hours at a frequency of 0.2-1Hz. Monitor data on each track reports on the performance of specific spacecraft operations and the DSN itself. DSN is receiving signals from 32 spacecraft across the solar system. DSN has pressure to reduce costs while maintaining the quality of support for DSN mission users. DSN operators need to simultaneously monitor multiple tracks and identify anomalies in real time. DSN has seen that as the number of missions increases, the data that needs to be processed increases over time. In this project, we look at the last 8 years of data for analysis. Any anomaly in the track indicates a problem with either the spacecraft, DSN equipment, or weather conditions. DSN operators typically write “discrepancy reports” for further analysis. It is recognized that it would be quite helpful to identify 10 similar historical tracks out of the huge database to quickly find/match anomalies. This tool has three functions: (1) identification of the top 10 similar historical tracks, (2) detection of anomalies compared to the reference normal track, and (3) comparison of statistical differences between two given tracks. The requirements for these features were confirmed by survey responses from 21 DSN operators and engineers. The preliminary machine learning model has shown promising performance (AUC=0.92). We plan to increase the number of data sets and perform additional testing to improve performance further before its planned integration into the Track Visualizer to assist DSN field operators and engineers.

Rebbapragada, Umaa↗
NASA NTRS1972

The effect of an isotopic non-equilibrium plasma on electron temperature measurements

Electron temperatures determined by electrostatic probe, diffuse resonance, and radar backscatter techniques in an isotropic two temperature plasma are presented. Plasma models corresponding to the addition of a minor component of energetic electrons, and models corresponding to a process that cools a fraction of the ionospheric electrons are considered. The diffuse resonance temperature is found to lie between the probe and radar backscatter temperatures. The isotropic models corresponding to the addition of energetic electrons cannot support the reported discrepancies between radio wave and probe electron temperature measurements. Temperature differences similar to the observed differences can be produced by models with a fraction of the electrons at a temperature cooler than that of the main component of electrons.

Benson, R. F.↗