narteybrown/twinnable-agent-data

TwinnableAgent C-MAPSS Processed Parquet Data

This dataset hosts the processed NASA C-MAPSS turbofan degradation files used by TwinnableAgent. It includes FD001 through FD004 as parquet files plus the conversion script used to derive them from the NASA raw training text files.

Raw NASA zip and text dumps are intentionally not mirrored here. The raw source of record is the NASA Prognostics Center of Excellence C-MAPSS Turbofan Engine Degradation dataset, currently distributed through NASA Open Data as CMAPSSData.zip.

Files

File	Rows	Units	Operating conditions	Fault modes
FD001_processed.parquet	20,631	100	1	1
FD002_processed.parquet	53,759	260	6	1
FD003_processed.parquet	24,720	100	1	2
FD004_processed.parquet	61,249	249	6	2
scripts/convert_cmapss_to_parquet.py	-	-	-	-

Conversion

Each processed parquet is derived from the matching NASA training file:

train_FD001.txt -> FD001_processed.parquet
train_FD002.txt -> FD002_processed.parquet
train_FD003.txt -> FD003_processed.parquet
train_FD004.txt -> FD004_processed.parquet

The conversion keeps the NASA column order, assigns explicit column names, and adds a per-row remaining-useful-life label:

rul = max(cycle for unit) - cycle

The conversion command used by TwinnableAgent is:

python scripts/convert_cmapss_to_parquet.py --datasets FD001 FD002 FD003 FD004

Schema

All four parquet files use the same schema:

Column	Type	Meaning
unit	integer	Engine trajectory identifier.
cycle	integer	Time-cycle index within the trajectory.
op1, op2, op3	float	NASA operating setting columns.
s1 through s21	float	NASA sensor channels. Sensor units are anonymized by C-MAPSS.
rul	integer	Remaining useful life in cycles, derived during conversion.

Operating-condition clusters

TwinnableAgent PAL resolves FD002 and FD004 into six operating-condition groups by rounding the three operating settings to the nearest integer and assigning a stable label by sorted tuple order.

FD002 mapping:

Cluster	Rounded (op1, op2, op3)	Rows	Units represented
op_cluster_0	(0, 0, 100)	8,044	260
op_cluster_1	(10, 0, 100)	8,096	260
op_cluster_2	(20, 1, 100)	8,122	260
op_cluster_3	(25, 1, 60)	8,002	260
op_cluster_4	(35, 1, 100)	8,037	260
op_cluster_5	(42, 1, 100)	13,458	260

FD004 mapping:

Cluster	Rounded (op1, op2, op3)	Rows	Units represented
op_cluster_0	(0, 0, 100)	9,238	249
op_cluster_1	(10, 0, 100)	9,224	249
op_cluster_2	(20, 1, 100)	9,091	249
op_cluster_3	(25, 1, 60)	9,139	249
op_cluster_4	(35, 1, 100)	9,162	249
op_cluster_5	(42, 1, 100)	15,395	249

Provenance note: FD004 unit count

The NASA readme describes FD004 training data as 248 trajectories, but the raw train_FD004.txt file contains 249 distinct unit identifiers. This repository preserves the raw file as authoritative and reports FD004 as 249 units.

Intended use

These files support TwinnableAgent reproducibility, PAL adapter validation, cross-dataset predictive-maintenance experiments, and C-MAPSS RUL benchmark work. They are processed training trajectories, not raw NASA archives.