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.

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["frame_thermal"]            → PIL.Image.Image (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:

with_chamber = ds.filter(lambda r: r["frame_chamber"] is not None)

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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:

_{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.}

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.

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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.
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:

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		Hex Coasters 2026_05_31	102,805	2026-05-31
002		Hex Coasters 2026_05_31	68	2026-05-31
012		Hex Coasters 2026_05_31	201,660	2026-05-31
013		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		D790 and D638 and Benchy 2026_06_02	355,580	2026-06-02
028		D790 and D638 2026_06_07	340,162	2026-06-07
029		D790 and D638 and Cards 2026_06_09	285,092	2026-06-09
030		D790 and D638 Recycled Powder 2026_06_24	228,723	2026-06-24
031		D790 and D638 Recycled Powder 2026_06_25	161,379	2026-06-25
032		Hex Coasters and Nameplates and Benchies	19,954	2026-06-27
033		Hex Coasters and Nameplates and Benchies	1,559	2026-06-27
034		Hex Coasters and Nameplates and Benchies	18,251	2026-06-27
035		D790 and D638 and other objects 2026_06_27	430,997	2026-06-27
036		Hex Coasters and Nameplates and Benchies	734,064	2026-06-28
037		D790 and D638 Debug Run 2026_06_29	776	2026-06-29
038		D790 and D638 Debug Run 2026_06_29	8,294	2026-06-29
039		D790 and D638 and Nameplate 2026_06_29	334,454	2026-06-29
040		D790 and D638 and D256 and Benchy 2026_07_01	446,764	2026-07-01
041		Unknown 2026_07_09 ¹	134,790	2026-07-09
042		Nameplates 2026_07_09	203,425	2026-07-10
043		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.

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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 matrix
  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.

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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, ~16% thermal attachment rate).

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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.

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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:

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"])})

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Upstream

Raw data lives in 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.

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Regenerate

# 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