GearXAI
Industrial gearbox with sensor traces and explainability heatmaps
IJCAI-ECAI 2026 Dataset and devkit available

Accepted to the IJCAI-ECAI 2026 Competitions and Challenges Track

GearXAI

An Explainable Neuro-Symbolic Gearbox Fault Diagnosis Challenge

Bremen, Germany · August 15-21, 2026 · Online competition in advance

Read the abstract View timeline
Task
9-class fault diagnosis
Input
8-channel vibration windows
Artifact
ONNX, CPU-only
Ranking
Explainability first

Competition abstract

Transparent diagnostics for rotating machinery

Title
GearXAI: An Explainable Neuro-Symbolic Gearbox Fault Diagnosis Challenge

GearXAI is a single-track IJCAI-ECAI 2026 competition focused on explainable and neuro-symbolic approaches for multiclass gearbox fault diagnosis from vibration time series. Participants submit ONNX models that are evaluated in CPU-only, containerized runs for reproducible inference. Submissions must meet a minimum predictive-performance requirement, after which ranking is determined by an automated explainability score that quantifies faithfulness under controlled perturbations and stability under small input changes. The challenge releases a realistic drivetrain dataset and a unified devkit with ready ONNX baselines, validation, leaderboard metric reporting, and submission packaging to enable transparent comparison and follow-up research.

Competition task

Predict the fault. Explain the evidence.

01

Drivetrain data

Participants work with synchronized multichannel signals from the Drivetrain Dynamics Simulator testbed, sampled at 5120 Hz across multiple speed-load regimes and fault states.

02

Shared label space

Each window is classified into one of nine classes: healthy operation plus eight fault types, aggregated across planetary gearbox operating regimes.

03

Standardized tensors

The official loader outputs windows shaped [N, 8, 100]. Models return class probabilities [N, 9] and relevance maps [N, 8, 100] for XAI scoring.

Evaluation

Accuracy is reported. Explanations decide the rank.

XAI

Explainability Score

Faithfulness
40%
Mechanistic relevance
40%
Simplicity
20%

Every valid submission is ranked by an automated Explainability Score combining deletion/insertion faithfulness, physically plausible relevance, stability under small perturbations, and compactness. The leaderboard also reports whether each model reaches 80% macro-F1 on the hidden test set.

  • Final submissions are single ONNX models evaluated with ONNX Runtime.
  • Organizer evaluation runs offline in a sealed, CPU-only container with no internet access.
  • Determinism, runtime, memory, and explanation sanity checks are part of the evaluation process.
  • Teams may include up to five members; each participant may join only one team.

Official standings

GearXAI leaderboard

Submissions
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Eligible
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Next update
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Loading official standings...

Mechanical scoring was upgraded on June 9, 2026 to improve frequency resolution and perturbation-stability measurement. The new formula checks whether explanations emphasize mechanically meaningful signal regions. All submissions were re-evaluated identically.

Only each team's best submission is considered for ranking. Earlier submissions may be shown for progress reference to support development; this is subject to change if evaluator load becomes too high.

Rank Team submission Final score Macro-F1 Faithfulness Mechanical Simplicity Status
Loading official standings...

Last published:

Submission

From dataset to final ZIP.

Participants train their own model, export it as ONNX, then run the devkit on that model to produce the final submission.zip for manual upload.

  1. 01 Start with the dataset

    Use the released DDS-SEU PGB windows and prepare the public validation split once with the devkit.

    gearxai prepare-data --windows-dir data/windows_100 --out prepared Open dataset
  2. 02 Download the devkit

    Install the submission packager, metric report writer, and ready ONNX baselines for a first test.

    Download devkit
  3. 03 Train and export your model

    Your model must accept [N, 8, 100] windows and return probabilities plus relevance maps.

    model.onnx
  4. 04 Run the devkit on your ONNX

    The command validates the model, computes public validation metrics, and creates the artifact.

    Creates submission.zip
  5. 05 Manually upload the ZIP

    Upload submission.zip through the participant form.

    Open upload form
Core command gearxai package --model model.onnx --data-dir prepared --split validation --out submission.zip

Awards and recognition

Recognition for top GearXAI teams

Top-ranked teams will receive official competition certificates, be listed on the GearXAI website, and be invited to present their methods during the GearXAI session at IJCAI-ECAI 2026 in Bremen. Subject to conference space, selected teams may also be invited to present posters.

🥇 1st Place

GearXAI Winner

Winner Certificate, featured method presentation at IJCAI-ECAI 2026, featured speaker invitation to the Neuro-Symbolic Artificial Intelligence special session at IEEE SYNASC 2026 in Timișoara, and first priority for any confirmed compute award.

🥈 2nd Place

GearXAI Runner-Up

Runner-Up Certificate, method presentation at IJCAI-ECAI 2026, website recognition, and access to any confirmed compute award subject to availability.

🥉 3rd Place

GearXAI Third Place

Third-Place Certificate, method presentation at IJCAI-ECAI 2026, website recognition, and access to any confirmed compute award subject to availability.

Mentions

Honorable Mentions

Website recognition and optional short presentation or poster invitation, depending on submission quality and available session space.

Remote presentations will be accommodated where possible for winning teams that cannot attend in person because of logistical, financial, visa, or other constraints.

The organizers are working to provide a compute award of up to 100 GPU hours on the GPU@Timișoara high-performance computing infrastructure at West University of Timișoara, including H200 GPU resources. The final allocation will follow the progress and availability of the university infrastructure and will be confirmed before the final evaluation phase.

Timeline

Competition milestones

  1. Official competition announcement submitted to IJCAI-ECAI
  2. Call for Participation, dataset details, and unified devkit release
  3. Development submission window and organizer validation feedback
  4. Final ONNX submission deadline, 23:59 AoE
  5. Winner notifications
  6. Competition session at IJCAI-ECAI 2026 in Bremen

Resources

Competition resources

Dataset

Public DDS-SEU PGB windows, metadata, and evaluator-ready preparation workflow.

Open on Hugging Face

Devkit

Strict participant package with the ONNX validator, metrics report, submission ZIP builder, and ready baseline ONNX files.

Download devkit (.zip)

Upload

Manual upload page for the final submission.zip generated by gearxai package.

Open upload page

Organizers

Organizing team

GearXAI is organized by researchers affiliated with UVT, HRIA, and Xi'an Jiaotong University.

West University of Timișoara Timișoara, Romania HRIA Romanian Hub for Artificial Intelligence Xi'an Jiaotong University Xi'an, China

Cite us

Referencing the GearXAI challenge

If GearXAI is useful for your work, please cite the challenge website until the official competition proceedings or archival report is available. 

@misc{hogea2026gearxai,
  title = {GearXAI: An Explainable Neuro-Symbolic Gearbox Fault Diagnosis Challenge},
  author = {Hogea, E. and Onchis, D. M. and Ivascu, T. and Yan, R.},
  year = {2026},
  note = {IJCAI-ECAI 2026 Competitions and Challenges Track},
  url = {https://gearxai-ijcai-ecai2026.pages.dev/}
}