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Comparative Analysis of Data-Driven Anomaly Detection Methods
This paper provides a review of three different advanced machine learning algorithms for anomaly detection in continuous data streams from a ground-test firing of a subscale... -
Towards Prognostics of Power MOSFETs: Accelerated Aging and Precursors of Failure
This paper presents research results dealing with power MOSFETs (metal oxide semiconductor field effect tran- sistor) within the prognostics and health management of... -
Estimation of Faults in DC Electrical Power System
This paper demonstrates a novel optimizationbased approach to estimating fault states in a DC power system. The model includes faults changing the circuit topology along with... -
Space Shuttle Main Propulsion System Anomaly Detection: A Case Study
The space shuttle main engine (SSME) is part of the Main Propnlsion System (MPS) which is an extremely complex system containing several sub-systems and components, each of... -
Machine Learning for Earth Observation Flight Planning Optimization
This paper is a progress report of an effort whose goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science... -
An Energy-Based Prognostic Framework to Predict Fatigue Damage Evolution in Composites
In this work, a prognostics framework to predict the evolution of damage in fiber-reinforced composites materials under fatigue loads is proposed. The assessment of internal... -
Disk Defect Data
How Data Was Acquired: The data presented is from a physical simulator that simulated engine disks. Sample Rates and Parameter Description: All parameters are sampled once per... -
HIRENASD Experimental Data - matlab format
This resource contains the experimental data that was included in tecplot input files but in matlab files. dba1_cp has all the results is dimensioned (7,2) first dimension is... -
MKAD (Open Sourced Code)
The Multiple Kernel Anomaly Detection (MKAD) algorithm is designed for anomaly detection over a set of files. It combines multiple kernels into a single optimization function... -
A knowledge-based system approach for sensor fault modeling, detection and mitigation
Sensors are vital components for control and advanced health management techniques. However, sensors continue to be considered the weak link in many engineering applications... -
Probabilistic Delamination Diagnosis of Composite Materials Using a Novel Bayesian Imaging Method
In this paper, a probabilistic delamination location and size detection framework is proposed. The delamination probability image using Lamb wave-based damage detection is... -
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression... -
HIRENASD FEM wing only HEX20
The finite element model being used by the AePW is based on the model provided at HIRENASD website The NASTRAN FEM's using HEXA solid elements and identified as... -
Modeling Li-ion Battery Capacity Depletion in a Particle Filtering Framework
This paper presents an empirical model to describe battery behavior during individual discharge cycles as well as over its cycle life. The basis for the form of the model has... -
Single reusable spacecraft
Design of a my single person reusable spacecraft. It can carry one person and it has to be dropped from an aircraft at an altitude of 40,000 - 45,000 feet. Can be the future... -
A Survey of Artificial Intelligence for Prognostics
Integrated Systems Health Management includes as key elements fault detection, fault diagnostics, and failure prognostics. Whereas fault detection and diagnostics have been the... -
Accelerated Aging with Electrical Overstress and Prognostics for Power MOSFETs
Power electronics play an increasingly important role in energy applications as part of their power converter circuits. Understanding the behavior of these devices, especially... -
Sparse Inverse Gaussian Process Regression with Application to Climate Network Discovery
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. Gaussian Process regression...
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