Update 7 files

- /liuice_index.md
- /lumen_index.md
- /slide_index.md
- /liuice/liuice_index.md
- /lumen/lumen_index.md
- /slide/slide_index.md
- /index.md

index.md

@@ -33,7 +33,7 @@ At each time instance, a new sample is provided to the diagnosis system and a di
 The LiU-ICE benchmark covers some challenging problems of fault diagnosis of technical systems. The diagnosis system needs to identify the faulty component as fast and accurately as possible while avoiding misclassifications and falsely rejecting the true diagnosis. The objective of the competition is to address these challenges by designing a diagnosis system for the air path of an internal combustion engine. It is a challenging system because of its dynamic non-linear behavior and wide operating range. A state-of-the-art structural model of the system is provided together with training data from different fault scenarios. The set of available actuator and sensor signals corresponds to the standard signals that are available in a commercial vehicle. 
 
 More information and downloadable resources can be found here: 
-* [LiU-ICE benchmark](liuice_index.md)
+* [LiU-ICE benchmark](liuice_index)
 
 Contact: Daniel Jung 
 
@@ -43,7 +43,7 @@ Contact: Daniel Jung
 SLIDe (Steam Line Intrusion Detection Benchmark) benchmark is devoted to the analysis of diagnostic algorithms for the detection and isolation of process faults and the detection of cyberattacks for a simulated fragment of the steam line of a fluidized bed boiler including the third and fourth stage of superheaters. It includes challenging scenarios including sensor, actuator, and technological components faults as well as cyber-attacks. To reflect the industrial nature of the benchmark, participants will only have a qualitative description of the process with a list of measurements and a few archival datasets representing different operating conditions, but only for fault-free and attack-free states.
 
 More information and downloadable resources can be found here: 
-* [SLIDe benchmark](slide_index.md)
+* [SLIDe benchmark](slide_index)
 
 Contact: Anna Sztyber-Betley
 
@@ -53,6 +53,6 @@ Contact: Anna Sztyber-Betley
 LUMEN (Liquid Upper stage demonstrator Engine) is a modular pump-fed liquid oxygen (LOX) and liquid methane (LNG) rocket engine developed by the Institute of Space Propulsion of the German Aerospace Center (DLR). This benchmark focuses on the fuel turbopump subsystem of the rocket engine and addresses key challenges encountered in safety-critical systems, such as the lack of experimental data from faulty operation. The goal of this benchmark is to utilize information from a simulation model with uncertain parameter and limited experimental data from nominal operation to enable the diagnosis system to perform effectively under realistic operating conditions.  
 
 More information and downloadable resources can be found here: 
-* [LUMEN benchmark](lumen_index.md)
+* [LUMEN benchmark](lumen_index)
 
 Contact: Eldin Kurudzija
\ No newline at end of file

liuice_index.md → liuice/liuice_index.md

@@ -39,8 +39,8 @@ The objective of the competition is to address these challenges by designing a d
 
 <i>The LiU-ICE benchmark has previously been used in the <a href="https://vehsys.gitlab-pages.liu.se/diagnostic_competition/">IFAC Safeprocess 2024 competition</a>. The main updates in this competition, with respect to the IFAC Safeprocess 2024 competition, is that the training data set is extended, test data will consist of new fault scenarios from different driving cycles, and an updated set of performance matrics.<\i> 
 
-![A picture of the experimental test bench](liuice/images/engine_test_bench.jpg){: width="40%"}
-![A schematic of the air path of the internal combustion engine](liuice/images/schematics.jpg){: width="40%"}
+![A picture of the experimental test bench](images/engine_test_bench.jpg){: width="40%"}
+![A schematic of the air path of the internal combustion engine](images/schematics.jpg){: width="40%"}
 
 ## Data
 <a name="data"></a>
@@ -60,7 +60,7 @@ Available actuator signals:
 * Requested injected fuel mass - umf
 * Requested wastegate actuator position - uwg
 
-![An example of measurement data](liuice/images/engine_signals.jpg){: width="80%"}
+![An example of measurement data](images/engine_signals.jpg){: width="80%"}
 
 The ambient pressure and temperature signals vary between different datasets mainly due to the ambient conditions in the lab and not due to faults.
 
@@ -102,10 +102,10 @@ L Eriksson <br>
 Oil & Gas Science and Technology-Revue de l'IFP 62 (4), 523-538</i>
 
 The provided model is implemented in <a href="https://faultdiagnosistoolbox.github.io">Fault Diagnosis Toolbox</a> which is available in Python. The model can be downloaded here:
-* python ([engine_model.py](liuice/competition/model/engine_model.py), [main.py](liuice/competition/model/main.py))
+* python ([engine_model.py]competition/model/engine_model.py), [main.py](competition/model/main.py))
 
 The figure below is generated using the Fault Diagnosis Toolbox shows a structural representation of the mathematical model. Each row represents an equation and each column a model variable where blue are unknown variables, red are fault signals, and black are known signals.
-![A structural representation of the model generated using the Fault Diagnosis Toolbox](liuice/images/structural_model.jpg){: width="40%"}
+![A structural representation of the model generated using the Fault Diagnosis Toolbox](images/structural_model.jpg){: width="40%"}
 
 ### Description of the diagnosis system interface and evaluation script
 

slide_index.md → slide/slide_index.md

@@ -55,7 +55,7 @@ The 2-stages steam line superheaters simulator models the processes within the b
 
 The schematic diagram of the process is shown below:
 
-![Process block diagram](slide/images/process_block_diagram.png)
+![Process block diagram](images/process_block_diagram.png)
 
 ### Control loops
 
@@ -78,7 +78,7 @@ The parameters of the particular control loops are given in the table below:
 | CV range  | %     |   <0, 100>    | <0, 100>      | <0, 100>      | <0, 100>      | -->
 
 Assignment of components and process variables to individual control loops (please take this asignment into account when isolating attacked control loops):
-![Control loop assignment](slide/images/control_loop_assignment.png)
+![Control loop assignment](images/control_loop_assignment.png)
 
 
 
@@ -116,15 +116,15 @@ Key process variables are described in the table below:
 | 4.2                     | $CV_{4.2}$     | Control signal of temperature controller at the outlet of the superheater 4 | %     | 0-100   | 52.69         |
 
 Control loops and process variables are in the plots below:
-![Control loops - plots](slide/images/dxc_loops.png)
-![Variables - plots](slide/images/dxc_variables.png)
+![Control loops - plots](images/dxc_loops.png)
+![Variables - plots](images/dxc_variables.png)
 
 ### Fault scenarios
 
 The symbolic locations where process faults can be introduced are shown in the figure below:
 
-![Process faults entry points](slide/images/fault_scenarios.png)
-![Symbolic designation of types and places of introduction of process faults](slide/images/faults.png)
+![Process faults entry points](images/fault_scenarios.png)
+![Symbolic designation of types and places of introduction of process faults](images/faults.png)
 
 #### Fault Types
 
@@ -165,8 +165,8 @@ Each cybernetic attack is carried out according to a designed scenario - a speci
 
 The symbolic place of introduction of the cybernetic faults in the simulator is shown in the figure below:
 
-![Cyber faults entry points](slide/images/cyber_faults.png)
-![Symbolic designation of types and places of introduction of cybernetic faults](slide/images/cyber_faults_symbolic.png)
+![Cyber faults entry points](images/cyber_faults.png)
+![Symbolic designation of types and places of introduction of cybernetic faults](images/cyber_faults_symbolic.png)
 
 We consider the following types of cybernetic attacks:
 * CON - attack on the controller (change of operating mode, change of parameters),
@@ -181,9 +181,9 @@ Cyber faults should be isolated to the specific control loop, i.e. the competito
 <a name="resources"></a>
 
 We provide you with three data files with data from normal operation:
-* [nf11](slide/competition/trainingdata/nf11.csv) - 96 hours, variable set points
-* [nf12](slide/competition/trainingdata/nf12.csv) - 96 hours, variable set points
-* [nf13](slide/competition/trainingdata/nf13.csv) - 24 hours, constant set points
+* [nf11](competition/trainingdata/nf11.csv) - 96 hours, variable set points
+* [nf12](competition/trainingdata/nf12.csv) - 96 hours, variable set points
+* [nf13](competition/trainingdata/nf13.csv) - 24 hours, constant set points
 
 Code for the submission and usage instructions can be found in the [github repository](https://github.com/asztyber/DXC25_SLIDe).