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---
pretty_name: "SafeLeak-RCD: Residential Residual Current Decomposition Benchmark"
license: "cc-by-nc-4.0"
tags:
- tabular
- timeseries
- electrical-safety
- nilm
- physics-informed-learning
- datasets
configs:
- config_name: benchmark_split
default: true
data_files:
- split: train
path: "benchmark/train.csv"
- split: validation
path: "benchmark/validation.csv"
- split: test
path: "benchmark/test.csv"
---
# SafeLeak-RCD: Residential Residual Current Decomposition Benchmark
This repository contains `SafeLeak-RCD`, the public benchmark bundle prepared for the manuscript:
`Physics-Regularized Conditional Flow Matching for Branch-Conditioned Residual Current Decomposition in Electrical Safety Monitoring`
## Release Contents
- `benchmark/`
The exact train/validation/test split used in the manuscript revision.
- `processed_entities/`
The processed per-entity bundle used to construct the benchmark and inspect the augmentation pipeline.
## Task
Given:
- aggregate residual current
- aggregate active power
- a target-branch power cue
predict the residual current of the selected branch.
## Benchmark Summary
- single-phase residential electrical safety monitoring
- `12` branches
- `1`-minute target interval
- `7` entity-level panels in total
- entity-disjoint `train/validation/test = 5/1/1`
- train split: `104,835` rows total with synthetic variants restricted to training only
- validation split: `7,091` real rows
- test split: `11,991` real rows
## Split Files
- `benchmark/train.csv`
- `benchmark/validation.csv`
- `benchmark/test.csv`
- `benchmark/split_config.json`
## Example Row
Each CSV row is one timestamped panel snapshot. The benchmark stores the aggregate channels and all branch channels in the same row. A selected real example from `benchmark/train.csv` looks like this:
```json
{
"timestamp": "2024-08-01 00:10:00",
"total_residual_current": "13.32345",
"total_power": "20632.769769",
"branch_1_power": "2210.233346",
"branch_1_current": "0.0036",
"branch_2_power": "190.9009",
"branch_2_current": "0.1582",
"branch_3_power": "0.0",
"branch_3_current": "0.0003",
"branch_12_power": "3974.763915",
"branch_12_current": "2.774",
"synthetic_variant": 0,
"segment_id": "shanse001_aug_chunk_01_1min_base",
"entity_id": "shanse001_aug_chunk_01_1min"
}
```
Branches `4` to `11` are omitted above for brevity. For branch-conditioned learning, pick one branch index `k` and map:
```text
target branch: 12
inputs = (total_residual_current=13.32345, total_power=20632.769769, branch_12_power=3974.763915)
target = branch_12_current=2.774
```
## Processed-Entity Bundle
- `processed_entities/manifest.json` lists every released entity bundle.
- Each entity directory contains:
- `*.base.csv` for the real observed base panel
- `*.variant_*.csv` for synthetic augmentation variants
- `*.csv` for the combined training-time view used by the benchmark builders
- `*.metadata.json` for dataset-level statistics and notes
- All paths stored in `manifest.json` and `*.metadata.json` are repo-relative paths inside this dataset repository.
## Loading Example
```python
from datasets import load_dataset
dataset = load_dataset("haayan/safeleak-rcd", "benchmark_split")
print(dataset["train"])
```
## Access and Use
This release is intended to support research reproducibility for the associated manuscript. Check the license field and any additional usage notice configured on the Hugging Face repository before downstream redistribution or commercial use.
## License
This dataset is released under `CC-BY-NC-4.0`. This means downstream users may:
- download and reuse the data
- redistribute derived copies
- adapt the benchmark for follow-up work
- use it for non-commercial research and educational purposes with attribution
Commercial use is not permitted without separate permission from the dataset authors.
## Citation
If you use this dataset, cite both:
- the manuscript `Physics-Regularized Conditional Flow Matching for Branch-Conditioned Residual Current Decomposition in Electrical Safety Monitoring`
- the dataset repository `https://huggingface.co/datasets/haayan/safeleak-rcd`