Sample data, including nominal and faulty scenarios, for Diagnostic Problems I and II of the Second International Diagnostic Competition. Three file formats are provided, tab-delimited .txt files, Matlab .mat files, and tab-delimited .scn files. The scenario (.scn) files are read by the DXC framework. See the Second International Diagnostic Competition project page for more information.

Competition data, including nominal and faulty scenarios, for Industrial Track Tier 1 and Tier 2 of the First International Diagnostic Competition. Three file formats are provided, tab-delimited .txt files, Matlab .mat files, and tab-delimited .scn files. The scenario (.scn) files are read by the DXC framework. See the DXC'09 Industrial Track Sample Data resource page for additional documentation, including system catalogs and schematics. Note that a "rematch" took place after the competition at the DX-09 Workshop. The rematch data consisted of the data for the original competition plus new data sets taken specifically for the rematch.

Competition data, including nominal and faulty scenarios, for Diagnostic Problems I and II of the Second International Diagnostic Competition. Three file formats are provided, tab-delimited .txt files, Matlab .mat files, and tab-delimited .scn files. The scenario (.scn) files are read by the DXC framework. See the DXC'10 Industrial Track Sample Data resource page for additional documentation, including system catalogs and schematics.

Competition data, including nominal and faulty scenarios, for Diagnostic Problem I of the Third International Diagnostic Competition. Three file formats are provided, tab-delimited .txt files, Matlab .mat files, and tab-delimited .scn files. The scenario (.scn) files are read by the DXC framework. See the DXC'11 Industrial Track Sample Data resource page for additional documentation, including system catalogs and schematics. There were no DA entries for Diagnostic Problem II so we are withholding the data for use in a future Diagnostic Competition.

The sample scenarios provided here are competition scenarios from previous DXC competitions. They are identical to the competition data associated with previous years' projects, but also listed here for convenience. The zip files have a spreadsheet that lists the scenarios and relevant fault information. Each scenario is provided in three formats: tab-delimited .txt file, Matlab .mat file, and tab-delimited .scn file. The different formats are provided for your convenience; they have the same data. The scenario (.scn) files are the format read by the DXC framework. See the system catalogs and schematics for additional information.

We present the third implementation of a framework created jointly by NASA Ames Research Center, Palo Alto Research Center, and Delft University of Technology to com- pare and evaluate diagnosis algorithms (DAs). This year‟s competition, DXC‟11, introduces a software track in addition to the industrial and synthetic tracks of previous competitions. A total of eleven DAs competed in the three tracks. The paper describes the systems, diag- nostic problems of the tracks, fault scenarios, evaluation metrics, participating DAs, results and analysis.

Sample data for the DXC'09 Synthetic Track.

Results for the DXC'11 Industrial Track, Diagnostic Problem I (no entries for DP II).

A framework to compare and evaluate diagnosis algorithms (DAs) has been created jointly by NASA Ames Research Center and PARC. In this paper, we present the first concrete implementation of this framework as a competition called DXC’09. The goal of this competition was to evaluate and compare DAs in a common platform and to determine a winner based on diagnosis results. 12 DAs (model-based and otherwise) competed in this first year of the competition in 3 tracks that included industrial and synthetic systems. Specifically, the participants provided algorithms that communicated with the run-time architecture to receive scenario data and return diagnostic results. These algorithms were run on extended scenario data sets (different from sample set) to compute a set of pre-defined metrics. A ranking scheme based on weighted metrics was used to declare winners. This paper presents the systems used in DXC’09, description of faults and data sets, a listing of participating DAs, the metrics and results computed from running the DAs, and a superficial analysis of the results.

A framework to compare and evaluate diagnosis algorithms (DAs) has been created jointly by NASA Ames Research Center, Palo Alto Research Center, and Delft University of Technology. In this paper, we present the second implementation of this framework in a competition called DXC’10. The overall goal of this competition is to evaluate the performance of different diagnostic methods. In order to accurately mimic diagnostic technology use in a real-world context, we have defined diagnostic problems driven by use cases representing different roles of diagnosis results. In the end, the competition pitted seven DAs competing in two diagnostic problems. The paper presents the systems used in DXC’10, a description of faults and data sets used for each diagnostic problem, a listing of participating DAs, the performance metrics and results computed from running the DAs with the framework, and an analysis of the results.