Spacecraft Anomaly Analysis and Prediction System SAAPS Peter - PowerPoint PPT Presentation

Mar 20, 2023 •362 likes •576 views

Spacecraft Anomaly Analysis and Prediction System SAAPS Peter Wintoft 1) , Henrik Lundstedt 1) , Lars Eliasson 2) , Leif Kalla 2) , and Alain Hilgers 3) 1) Swedish Institute of Space Physics Lund 2) Swedish Institute of Space Physics

Spacecraft Anomaly Analysis and Prediction System – SAAPS Peter Wintoft 1) , Henrik Lundstedt 1) , Lars Eliasson 2) , Leif Kalla 2) , and Alain Hilgers 3) 1) Swedish Institute of Space Physics – Lund 2) Swedish Institute of Space Physics – Kiruna 3) ESA/ESTEC
SAAPS Spacecraft Anomaly Analysis and Prediction System • ESA Contract 11974/96/NL/JG(SC): – Development of AI Methods in Spacecraft Anomaly Predictions • Extension of the SPEE study • Two year project (April 1999 - June 2001) • Database and software
Purpose Develop tools for the analysis and prediction of spacecraft anomalies.
Approach • Statistical methods for the analysis. • Artificial intelligence (AI) based models, such as neural networks, for predictions. • Real time operation. • Database of space weather data and spacecraft anomalies.
The model SAAPS Database External FTP / J ava HTTP / Ja va DBT User databas e SAAM SAPM User User
SAAPS Data Sources GOES ACE Kp SEC keV el. Dst, pred LANL Kp, pred IRF-Lun SAAPS AE, pred S/C op. NSSD C ESA Anomaly OMNI Anomaly
SAAM Spacecraft Anomaly Analysis Module • Plotting tools • Statistics – Superposed epoch analysis – Correlations (linear and entropy based) – Cluster analysis – Pattern definition and search • Guidelines • Estimate best prediction model
SAPM Spacecraft Anomaly Prediction Module • Neural network based prediction models • Real time forecast • Connects to SAAM for analysis • Anomaly index (?) and/or • Spacecraft dependent anomaly predictions
Anomaly index? S1 S2 S3 NSSDC S1 1.00 0.02 0.03 0.03 S2 0.02 1.00 0.04 0.04 S3 0.02 0.02 1.00 0.11 NSSDC 0.02 0.02 0.10 1.00
Σ Kp based predictions Kp(t-8*24h) Σ Kp(t-8d) A(t+1d) Σ Kp(t) Kp(t) • Satellite specific model (geostationary) • Fraction of correct classifications is 0.65 on balanced test set
Mutual information between average Σ Kp and ESD anomaly data
Mutual information between Σ Kp and ESD anomaly data
Anom
SAAPS part of RWC-Sweden
Issues • SAAPS Applets – communicate over port 2001 => Firewall problems. – use of RMI for data access => RMI might be a problem on specific OS. • SAAPS uses non-standard database engine.
Future • SAAPS database and models will be merged with the IRF-GIC Pilot Project. • A standard database engine will be used (MySQL). • More development on the anomaly prediction models are necessary.
IRF SAAPS Server http://www.lund.irf.se/saaps/ ESTEC SAAPS Server http://em450.wm.estec.esa.nl:6668/saaps/
New ACE data set • A new ACE data set will soon be released – Merged MAG and SWEPAM data – 64 second resolution • http://www.srl.caltech.edu/ACE/ASC/level2/index.html
Lund Dst model www.lund.irf.se/rwc/dst/models/ - Matlab - Java

Recommend

State-of-the-Art Thermal Analysis Methods and Validation for Small Spacecraft Kristina Hogstrom

State-of-the-Art Thermal Analysis Methods and Validation for Small Spacecraft Kristina Hogstrom March 4 th , 2013 Introduction Thermal analysis is integral part of development cycle Inadequate thermal system decreased performance

512 views • 18 slides

Outlook of Summer Rainfall Anomaly in Asia with Outlook of Summer Rainfall Anomaly in Asia with

Sixteenth Session of the Forum on Regional Climate Monitoring, Assessment and Prediction for Asia (FOCRAII), May 7, 2020 ( ), y , Outlook of Summer Rainfall Anomaly in Asia with Outlook of Summer Rainfall Anomaly in Asia with SMART-based

457 views • 16 slides

Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection

Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection Presented By: Akash Kulkarni System Log Analysis is complicated 1. Log sources generate TBs of data per day 2. Lack of labelled data (scarce or

719 views • 15 slides

A Domain Specific Design Tool for Spacecraft System Behavior Sravanthi Venigalla, Brandon Eames

A Domain Specific Design Tool for Spacecraft System Behavior Sravanthi Venigalla, Brandon Eames Utah State University, USA Allan McInnes University of Canterbury, New Zealand Domain Specific Modeling Workshop 2008 (DSM08) Spacecraft Design Not an

574 views • 29 slides

Chapter 7 Our Planetary System Earth, as viewed by the Voyager spacecraft 7.1 Studying the Solar

Chapter 7 Our Planetary System Earth, as viewed by the Voyager spacecraft 7.1 Studying the Solar System Our goals for learning What does the solar system look like? What can we learn by comparing the planets to one another?

696 views • 44 slides

Anomaly Detection Jia-Bin Huang Virginia Tech Spring 2019 ECE-5424G / CS-5824 Administrative

Anomaly Detection Jia-Bin Huang Virginia Tech Spring 2019 ECE-5424G / CS-5824 Administrative Anomaly Detection Motivation Developing an anomaly detection system Anomaly detection vs. supervised learning Choosing what features

514 views • 34 slides

What is an anomaly? Alastair Rushworth Data Scientist DataCamp Anomaly Detection in R Defining

DataCamp Anomaly Detection in R ANOMALY DETECTION IN R What is an anomaly? Alastair Rushworth Data Scientist DataCamp Anomaly Detection in R Defining the term anomaly Anomaly: a data point or collection of data points that do not follow the

870 views • 21 slides

Anomaly Detection of Trajectories Junier B. Oliva Anomaly Detection An anomaly (or outlier)

Anomaly Detection of Trajectories Junier B. Oliva Anomaly Detection An anomaly (or outlier) in a dataset is an instance that is abnormal or unlikely based on the rest of the dataset If the instances in the dataset are labeled as

760 views • 19 slides

Comparison of Comparison of Several Anomaly Detection Methods on Several Anomaly Detection

The Fifth Japan-Taiwan International Workshop The Fifth Japan-Taiwan International Workshop on Hydrological and Geochemical Research for Earthquake Prediction on Hydrological and Geochemical Research for Earthquake Prediction Comparison of

775 views • 38 slides

HIGH-PRECISION METALWORKING WWW.GHALAM.KZ Main activities Production of spacecraft for

HIGH-PRECISION METALWORKING WWW.GHALAM.KZ Main activities Production of spacecraft for scientific and technological purposes, earth remote sensing and communication General information Assembly and testing of spacecraft weighing up to 6

433 views • 12 slides

Anomaly Detection Algorithms for Malware Traffic Analysis using Tamper Resistant Features Dr.

Anomaly Detection Algorithms for Malware Traffic Analysis using Tamper Resistant Features Dr. Patrick McDaniel Berkay Celik Fall 2015 Introduction Motivation Related Work Data Approach Experimental Results Comparison

391 views • 25 slides

Testing General Relativity with Interplanetary Spacecraft Luciano Iess Dipartimento di

Testing General Relativity with Interplanetary Spacecraft Luciano Iess Dipartimento di Ingegneria Aerospaziale ed Astronautica Universit La Sapienza Rome, Italy Testing gravitational theories in the solar system Deflection of light M R

558 views • 33 slides

The Six-Day Spacecraft: Creating a Plug-and-play approach for aerospace systems y James Lyke

The Six-Day Spacecraft: Creating a Plug-and-play approach for aerospace systems y James Lyke Air Force Research Laboratory 23 September 2008 From National Defense Magazine , July 2007 Create a spacecraft in less than one week Problem

729 views • 53 slides

A New SU(2) Anomaly Edward Witten PCTS, October 3, 2018 A familiar anomaly says that in four

A New SU(2) Anomaly Edward Witten PCTS, October 3, 2018 A familiar anomaly says that in four spacetime dimensions, an SU(2) gauge theory with a single multiplet of fermions that transform under SU(2) in the spin 1/2 representation is

820 views • 43 slides

The Canadian Urban km and sub km- scale Weather Prediction System Stephane Belair, s Sylvie

The Canadian Urban km and sub km- scale Weather Prediction System Stephane Belair, s Sylvie Leroyer, Lubos Spacek Environment and Climate Change Canada Montreal, Canada WSN16, Hong Kong, 28 July 2016 The NUMERICAL PREDICTION SYSTEM

469 views • 16 slides

ADNA: online, context-aware, intelligent framework for Anomaly Detection aNd Analysis in SCADA

ADNA: online, context-aware, intelligent framework for Anomaly Detection aNd Analysis in SCADA networks Researchers: Wenyu Ren , Klara Nahrstedt, Tim Yardley Motivation Supervisory Control And Data Acquisition (SCADA) Problem with

1.12k views • 22 slides

Anomaly Detection Through Blind Flow Analysis Inside a Local Network Ron McLeod, BCSc, MCSc.

Anomaly Detection Through Blind Flow Analysis Inside a Local Network Ron McLeod, BCSc, MCSc. Director - Corporate Development Telecom Applications Research Alliance Doctoral Student, Faculty of Computer Science, Dalhousie University

663 views • 32 slides

Online, Context-aware, Intelligent Anomaly Detection, Causality and Consequence Analysis, and

Online, Context-aware, Intelligent Anomaly Detection, Causality and Consequence Analysis, and Response Suggestion for SCADA Systems Wenyu Ren, Tim Yardley , Klara Nahrstedt University of Illinois Urbana-Champaign, Urbana, Illinois, USA

156 views • 5 slides

Signal Processing Methods for Network Single Time Series Methods Anomaly Detection

Outline Introduction and Background Signal Processing Methods for Network Single Time Series Methods Anomaly Detection Spectral Analysis Lingsong Zhang Wavelet Analysis Department of Statistics and Operations

424 views • 18 slides

SMALL SPACECRAFT SYSTEMS VIRTUAL INSTITUTE OVERVIEW August 2017 www.nasa.gov S 3 VI Charter

National Aeronautics and Space Administration SMALL SPACECRAFT SYSTEMS VIRTUAL INSTITUTE OVERVIEW August 2017 www.nasa.gov S 3 VI Charter Advance clear communications, coordination, and consistent guidance regarding small spacecraft

410 views • 9 slides

The Impact of Observational data p on Numerical Weather Prediction Hirokatsu Onoda Numerical

The Impact of Observational data p on Numerical Weather Prediction Hirokatsu Onoda Numerical Prediction Division, JMA Outline Data Analysis system of JMA in Global Spectral Model (GSM) and Meso-Scale Model (MSM) p ( ) ( )

567 views • 38 slides

Spacecraft Navigation Kipp Cannon Ryerson University, March 14th 2015 slides.tex Challenges

Spacecraft Navigation Kipp Cannon Ryerson University, March 14th 2015 slides.tex Challenges Distance: light travel time forces spacecraft to be autonomous, repair is not possible so robustness and exhaustive pre-flight testing is

274 views • 10 slides

BT-IDS: An anomaly-based Intrusion Detection System for Bluetooth Devices Shalaka Satam, Pratik

BT-IDS: An anomaly-based Intrusion Detection System for Bluetooth Devices Shalaka Satam, Pratik Satam and Salim Hariri Cloud and Autonomic Computing Center Semi Annual IAB Meeting Tucson, Arizona Project Team Members n UA Faculty p Salim

269 views • 11 slides

Control AIRS clear-sky radiances AIRS cloudy retrievals Anomaly Correlations computed from 90S

Control AIRS clear-sky radiances AIRS cloudy retrievals Anomaly Correlations computed from 90S to 90N Anomaly Correlations computed from 90S to 90N Anomaly Correlations computed from 90S to 90N Slp RAD analysis (contour) RAD slp impact

409 views • 28 slides