| --- |
| license: mit |
| tags: |
| - telemetry |
| - time-series |
| - sls |
| - 3d-printing |
| - additive-manufacturing |
| - inova-mk1 |
| configs: |
| - config_name: ticks |
| data_files: |
| - split: train |
| path: data/ticks/*.parquet |
| default: true |
| - config_name: peregrine |
| data_files: |
| - split: train |
| path: data/peregrine/*.parquet |
| dataset_info: |
| features: |
| - name: frame_chamber |
| dtype: image |
| - name: frame_galvo |
| dtype: image |
| - name: frame_thermal |
| dtype: image |
| --- |
| |
| # Inova-Mk1-Telemetry |
|
|
| Time-aligned printer-state recordings from Inova Mk1 SLS 3D print runs. One row per 10 Hz **tick** — the recorder's `/state/snapshot` poll — with the full sensor state snapshot (~64 columns: temperatures, position, power, lights) on every row, the nearest camera frame embedded inline when one fell within the prior 100 ms window, and any 1 kHz position-stream samples from that window collected as a nested list. |
|
|
| 25 parquet files across builds spanning 2026-05 through 2026-07. Build metadata (job name, profile, start/end time) is denormalized into every row, so each file is self-sufficient for ML — no joins needed. |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("ppak10/Inova-Mk1-Telemetry", split="train") |
| row = ds[0] |
| # row["frame_chamber"] → PIL.Image.Image (or None) |
| # row["bedmatrix"] → {width, height, values (768 °C floats), path} (or None) |
| # row["powderBed.temp.current"] → float (°C) |
| # row["positions.position.z2"] → float (µm) |
| # row["position_hf_burst"] → list of {ts_offset_ms, x, y, z1, z2, r, has_homed} |
| ``` |
|
|
| Full image bytes are embedded in each row — no separate frame download. Filter to rows with a particular frame kind: |
|
|
| ```python |
| with_chamber = ds.filter(lambda r: r["frame_chamber"] is not None) |
| ``` |
|
|
| ## `peregrine` config — defect-labeled layers |
|
|
| A second, sparse config shaped like the [ORNL Peregrine dataset](https://huggingface.co/datasets/ppak10/Peregrine-Dataset-v2023-11): **one row per layer that carries a defect label**, for Peregrine-style transfer learning. Only labeled layers are recorded, so it's small and defect-focused (vs. the dense per-tick `ticks` config). |
|
|
| ```python |
| peregrine = load_dataset("ppak10/Agentic-SLS-Telemetry", "peregrine", split="train") |
| row = peregrine[0] |
| # row["image_after_powder"] → JPEG bytes, post-recoat chamber still (Peregrine after_powder) |
| # row["image_after_melt"] → JPEG bytes, post-scan chamber still (Peregrine after_melt) |
| # row["part_mask"] → PNG bytes, galvo scan mask (Peregrine part_ids) |
| # row["labels"] → list of {class, bbox [x0,y0,x1,y1] normalized, polarity} |
| # row["has_debris"], ... → bool per class (PEREGRINE_ALL_CLASSES) |
| # row["printBed_temp"], row["laser_power_w"], ... → process scalars at the layer |
| ``` |
|
|
| Images are raw encoded bytes (`binary`, like Peregrine's `image_after_*`) — decode with `PIL.Image.open(io.BytesIO(...))`. Labels are bbox-level (from the live defect detector / operator verdicts), not per-pixel masks; `polarity` is `positive` (defect present) or `negative` (operator marked the alert a false positive). One parquet per build (`data/peregrine/{build:03d}.parquet`), so a new build never rewrites existing files. |
|
|
| --- |
|
|
| ## Timelapse previews |
|
|
| Per-build layer-by-layer timelapse GIFs (one frame per detected print layer, 25 fps, ≤ 12 s). Below is the composite (chamber | thermal | galvo) for build 012, the first full Layers-phase run: |
|
|
|  |
|
|
| <sub>Galvo (scan-mirror) trace for build 012 — Hex Coasters, 221 layers. Each frame is the last captured view of one print layer just before the next powder spread. Full composite (chamber | thermal | galvo) at `previews/012/timelapse_composite.gif`.</sub> |
|
|
| Individual-kind GIFs (`timelapse_chamber.gif`, `timelapse_thermal.gif`) and full-speed MP4 previews are also available under `previews/{build_id:03d}/`. See the **Previews** section below. |
|
|
| --- |
|
|
| ## Row shape |
|
|
| Each row is one moment in time (a single 10 Hz tick). ~80 columns: |
|
|
| | Group | Columns | Notes | |
| |---|---|---| |
| | **Build context** | `build_id`, `job_name`, `started_at`, `ended_at`, `phase`, `print_profile_name`, `inova_session_id` | Denormalized — same value on every row in a given file. `inova_session_id` is null until the upstream sidecar CSV is curated by hand. | |
| | **Timestamp** | `ts` (`timestamp[us, UTC]`) | `respondedAt` from `/state/snapshot`. | |
| | **Position (10 Hz)** | `positions.position.{x,y,z1,z2,r}` | Stage position in **microns** (firmware native; divide by 1000 for mm). Always present. `z2` advances with each deposited layer and is used for layer detection in the timelapse scripts. | |
| | **Lights** | `lights.lights.{enabled,count}` | | |
| | **Power (W)** | `{laser,fanGalvo,buzzer,laserSafety,io-en,wd-en,wd-in}.power`, `powerman.power.{current,required,max}` | Per-component draw and manager state. | |
| | **Temperature (°C)** | `{powderBed,printBed}.temp.{current,average,target}`, `{powderChamber1..4,printChamber1..4}.temp.{current,average,target}`, `{quadrant1..4,surface,surfaceAvg,surfaceMin,surfaceMax,testTemp1}.temp.{current,average}` | ~51 columns. | |
| | **Frame images** | `frame_chamber`, `frame_galvo`, `frame_thermal` | HF `Image` feature (struct of `{bytes, path}`). Null when no frame of that kind was captured in the 100 ms window. Loads as `PIL.Image` via `datasets`. `path` preserves the original filename for traceability. **`frame_thermal` is a legacy pre-rendered IR heatmap GIF and is null for builds recorded after 2026-07-12 — use `bedmatrix` for thermal from there on** (see below). | |
| | **Bed temperature matrix** | `bedmatrix` | Struct `{width: int32, height: int32, values: list<float32>, path: string}`. The raw IR bed-surface temperature grid (32×24 = 768 cells, row-major, °C) attached nearest-before-tick in the same 100 ms window; null when none landed. Reshape `values` to `height × width` and colormap to render a heatmap. This supersedes `frame_thermal` and is available on all builds (the stream has run since build 013). | |
| | **Position burst** | `position_hf_burst` | `list<struct<ts_offset_ms, x, y, z1, z2, r, has_homed>>`. 1 kHz position events that fell in `(tick_ts − 100 ms, tick_ts]`. Empty list during heating/idle. | |
|
|
| ### Null frames |
|
|
| `frame_*` columns are null when no frame of that kind was captured within the 100 ms tick window — this preserves the "is this image fresh?" signal. Forward-fill for display or training: |
|
|
| ```python |
| import polars as pl |
| df = pl.read_parquet("data/ticks/026.parquet") |
| df = df.with_columns( |
| pl.col("frame_chamber").forward_fill(), |
| pl.col("frame_thermal").forward_fill(), |
| pl.col("frame_galvo").forward_fill(), |
| ) |
| ``` |
|
|
| --- |
|
|
| ## Build inventory |
|
|
| 25 builds total. Very short failed-heating runs (2–24 ticks) produce a parquet but represent only seconds of recording. The **timelapse** column shows the layer-by-layer composite GIF (chamber | thermal | galvo) for builds where the printer reached the sintering phase (z2 > 0). |
|
|
| | build_id | timelapse | job_name | ticks | date | |
| |---:|:---:|---|---:|---| |
| | 001 | <img src="previews/001/timelapse_composite.gif" width="280"> | Hex Coasters 2026_05_31 | 102,805 | 2026-05-31 | |
| | 002 | <img src="previews/002/timelapse_composite.gif" width="280"> | Hex Coasters 2026_05_31 | 68 | 2026-05-31 | |
| | 012 | <img src="previews/012/timelapse_composite.gif" width="280"> | Hex Coasters 2026_05_31 | 201,660 | 2026-05-31 | |
| | 013 | <img src="previews/013/timelapse_composite.gif" width="280"> | D790 and D638 and Benchy 2026_06_02 | 13,811 | 2026-06-02 | |
| | 014 | | D790 and D638 and Benchy 2026_06_02 | 2 | 2026-06-02 | |
| | 016 | | D790 and D638 and Benchy 2026_06_02 | 14 | 2026-06-02 | |
| | 017 | | D790 and D638 and Benchy 2026_06_02 | 2 | 2026-06-02 | |
| | 025 | | D790 and D638 and Benchy 2026_06_02 | 24 | 2026-06-02 | |
| | 026 | <img src="previews/026/timelapse_composite.gif" width="280"> | D790 and D638 and Benchy 2026_06_02 | 355,580 | 2026-06-02 | |
| | 028 | <img src="previews/028/timelapse_composite.gif" width="280"> | D790 and D638 2026_06_07 | 340,162 | 2026-06-07 | |
| | 029 | <img src="previews/029/timelapse_composite.gif" width="280"> | D790 and D638 and Cards 2026_06_09 | 285,092 | 2026-06-09 | |
| | 030 | <img src="previews/030/timelapse_composite.gif" width="280"> | D790 and D638 Recycled Powder 2026_06_24 | 228,723 | 2026-06-24 | |
| | 031 | <img src="previews/031/timelapse_composite.gif" width="280"> | D790 and D638 Recycled Powder 2026_06_25 | 161,379 | 2026-06-25 | |
| | 032 | <img src="previews/032/timelapse_composite.gif" width="280"> | Hex Coasters and Nameplates and Benchies | 19,954 | 2026-06-27 | |
| | 033 | <img src="previews/033/timelapse_composite.gif" width="280"> | Hex Coasters and Nameplates and Benchies | 1,559 | 2026-06-27 | |
| | 034 | <img src="previews/034/timelapse_composite.gif" width="280"> | Hex Coasters and Nameplates and Benchies | 18,251 | 2026-06-27 | |
| | 035 | <img src="previews/035/timelapse_composite.gif" width="280"> | D790 and D638 and other objects 2026_06_27 | 430,997 | 2026-06-27 | |
| | 036 | <img src="previews/036/timelapse_composite.gif" width="280"> | Hex Coasters and Nameplates and Benchies | 734,064 | 2026-06-28 | |
| | 037 | <img src="previews/037/timelapse_composite.gif" width="280"> | D790 and D638 Debug Run 2026_06_29 | 776 | 2026-06-29 | |
| | 038 | <img src="previews/038/timelapse_composite.gif" width="280"> | D790 and D638 Debug Run 2026_06_29 | 8,294 | 2026-06-29 | |
| | 039 | <img src="previews/039/timelapse_composite.gif" width="280"> | D790 and D638 and Nameplate 2026_06_29 | 334,454 | 2026-06-29 | |
| | 040 | <img src="previews/040/timelapse_composite.gif" width="280"> | D790 and D638 and D256 and Benchy 2026_07_01 | 446,764 | 2026-07-01 | |
| | 041 | <img src="previews/041/timelapse_composite.gif" width="280"> | Unknown 2026_07_09 ¹ | 134,790 | 2026-07-09 | |
| | 042 | <img src="previews/042/timelapse_composite.gif" width="280"> | Nameplates 2026_07_09 | 203,425 | 2026-07-10 | |
| | 043 | <img src="previews/043/timelapse_composite.gif" width="280"> | D790 and D638 and Nameplate 2026_07_10 | 373,863 | 2026-07-10 | |
| | **total** | | | **4,900,289** | | |
|
|
| ¹ Build 041 was recovered from the NVMe spool after the recorder's Postgres database was reset; `job_name` is a placeholder. |
|
|
| --- |
|
|
| ## Files |
|
|
| ``` |
| data/ticks/{build_id:03d}.parquet # one file per build, zero-padded (001–043) |
| |
| previews/{build_id:03d}/ |
| chamber.mp4 # optical — real-time 10 fps, forward-filled |
| thermal.mp4 # IR bed heatmap (from bedmatrix; inferno, fixed 20–200 °C) |
| galvo.mp4 # scan-mirror trace |
| composite.mp4 # 1×3 panel: chamber | thermal | galvo |
| timelapse_chamber.gif # layer-by-layer, 25 fps, ≤ 12 s |
| timelapse_thermal.gif |
| timelapse_galvo.gif |
| timelapse_composite.gif # 1×3 panel GIF |
| ``` |
|
|
| The HF glob `data/ticks/*.parquet` loads the full dataset across all builds. Builds that never started printing (z2 = 0 throughout) produce a timelapse GIF with zero or one frame. |
|
|
| --- |
|
|
| ## Previews |
|
|
| ### Real-time MP4s |
|
|
| Four MP4s per build under `previews/{build_id:03d}/`: `chamber.mp4`, `thermal.mp4`, `galvo.mp4`, and `composite.mp4`. Playback at 10 fps (the tick rate), so video duration equals build wall-clock time — build 026 → ~9h54m of video. Null frames are forward-filled for viewing continuity. |
|
|
| ### Timelapse GIFs |
|
|
| Four animated GIFs per build sampled one frame per detected print layer: |
|
|
| - **Layer detection**: `positions.position.z2` quantized in 100 µm buckets. Only z2 > 0 rows are used, so pre-print heating is automatically excluded. |
| - **Representative frame**: the *last* non-null frame within each z2 bucket — the most-recent view of the layer just before recoating begins. |
| - **Playback**: 25 fps, capped at 300 frames (12 s max). Null-frame levels are forward-filled within the GIF. |
| - **Canvas**: 240 px height (half the MP4 canvas) for web-friendly file sizes. |
|
|
| Both previews are sourced from this dataset's own parquet (not the recorder's raw frame files), so they see only the per-tick-attached frame subset (~36% chamber, ~37% galvo attachment rate). The **thermal** panel is rendered from the numeric `bedmatrix` IR grid — inferno colormap over a fixed 20–200 °C range, so the same color means the same temperature across every build — rather than the legacy `frame_thermal` GIF. Builds 001/002/012 predate the bedmatrix stream and fall back to the old GIF. |
|
|
| --- |
|
|
| ## What's lost vs the raw exporter format |
|
|
| This dataset is **tick-anchored**, not a strict outer join. Three things are reduced compared to the upstream flat exports: |
|
|
| - **Between-tick position resolution**: the 1 kHz `position_hf` stream is preserved *during* motion via `position_hf_burst`, but not as standalone rows between ticks. For the raw 1 kHz timeline fall back to the upstream `position_hf/{build_id}.parquet`. |
| - **Sparse events without telemetry**: no row exists for a camera frame or `events` record that doesn't land near a 10 Hz tick. This dataset represents "state at each tick", not "every recorded event". |
| - **`plotter_commands`**: not surfaced — historical builds predate this recorder feature and the table is empty. |
| |
| --- |
| |
| ## Joining back to Inova-Mk1-Database |
| |
| Each row carries `print_profile_name` — the string the printer was running when the build started, taken from the `build_start` event payload. To recover the matching `PrintProfile.Id` UUID, join against [`ppak10/Inova-Mk1-Database`](https://huggingface.co/datasets/ppak10/Inova-Mk1-Database): |
| |
| ```python |
| import json |
| from pathlib import Path |
| |
| profiles_dir = Path("Inova-Mk1-Database/source/PrintProfiles") |
| name_to_id = { |
| json.load(p.open())["Name"]: json.load(p.open())["Id"] |
| for p in profiles_dir.glob("*.json") |
| } |
| ds = ds.map(lambda r: {**r, "print_profile_id": name_to_id.get(r["print_profile_name"])}) |
| ``` |
| |
| --- |
| |
| ## Upstream |
| |
| Raw data lives in [`Agentic-Additive-Manufacturing-Process-Optimization`](https://github.com/ppak10/Agentic-Additive-Manufacturing-Process-Optimization). Its `scripts/export.py` produces flat JSONL/parquet files under `data/exports/`. This dataset reads from those directly — no live database connection required. |
| |
| --- |
| |
| ## Regenerate |
| |
| ```sh |
| # Full ETL (all builds) |
| uv run scripts/ticks/01_extract.py |
| |
| # Specific builds only |
| uv run scripts/ticks/01_extract.py 26 28 |
| |
| # MP4 previews |
| uv run scripts/previews/01_render.py # all builds |
| uv run scripts/previews/01_render.py 26 28 # specific builds |
| |
| # Timelapse GIFs |
| uv run scripts/previews/02_timelapse.py # all builds |
| uv run scripts/previews/02_timelapse.py 26 28 # specific builds |
| ``` |
| |
