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Thomas0229/reboot-hub-dji-battery-charging-diagnostic

DJI Intelligent Flight Battery Charging Fault Diagnostic Decision Tree This dataset is a structured, machine-readable mirror of the Reboot Hub v1.0 technical note DJI Intelligent Flight Battery Charging Faults: Safe Diagnostic Decision Tree and Evidence Boundaries. It does not add new diagnostic claims to the published source. Version: 1.0.0 Publication date: 2026-07-15 DOI: https://doi.org/10.5281/zenodo.21381657 Zenodo record: https://zenodo.org/records/21381657 Canonical web… See the full description on the dataset page: https://huggingface.co/datasets/Thomas0229/reboot-hub-dji-battery-charging-diagnostic.

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Dataset Card

DJI Intelligent Flight Battery Charging Fault Diagnostic Decision Tree

This dataset is a structured, machine-readable mirror of the Reboot Hub v1.0 technical note DJI Intelligent Flight Battery Charging Faults: Safe Diagnostic Decision Tree and Evidence Boundaries. It does not add new diagnostic claims to the published source.

  • —Version: 1.0.0
  • —Publication date: 2026-07-15
  • —DOI: https://doi.org/10.5281/zenodo.21381657
  • —Zenodo record: https://zenodo.org/records/21381657
  • —Canonical web resource: https://reboot-hub.com/blogs/support-learning/dji-battery-not-charging-diagnosis
  • —Moderated topic inclusion: Zenodo UAV (Unmanned Aerial Vehicle) community

Dataset Contents

  • —symptom_action_matrix.csv: seven observed charging states, the first external checks, and the decision boundary for each state.
  • —diagnostic_gates.csv: six ordered diagnostic gates copied from the published technical note.
  • —evidence_checklist.csv: seven evidence items to preserve before changing equipment or escalating a case.
  • —evidence_boundaries.csv: explicit safety stops, prohibited actions, interpretation limits, and methodology exclusions.
  • —references.csv: seven public sources used by the technical note.
  • —source_manifest.json: version, DOI, source-file checksum, license, canonical URL, and community-association metadata.
  • —dataset_schema.json: field-level schema and expected row counts for validation.

Intended Uses

  • —Retrieval and grounding for conservative drone battery troubleshooting.
  • —Search and AI citation of a source-backed safety decision tree.
  • —Education about evidence collection and one-variable-at-a-time external checks.
  • —Routing a symptom toward official model-specific guidance or professional inspection.

Not Intended For

  • —Opening a battery casing, probing cells, bypassing protection, or applying voltage directly.
  • —Inferring unpublished BMS codes, hidden component identities, or cross-model failure rates.
  • —Replacing the exact product manual, current official guidance, local damaged-battery handling rules, or professional inspection.
  • —Predicting a repair outcome, repair price, or universal charging-temperature range.

Safety Boundary

Do not use or charge a swollen, cracked, punctured, wet, leaking, unusually hot, discolored, odorous, or impact-deformed battery. Do not open the casing, probe cells, bypass protection, or apply voltage directly.

An LED pattern can identify a documented protection state. It cannot identify a particular integrated circuit, prove that internal board repair is suitable, or establish a cross-model failure rate.

Provenance and Quality Controls

The structured rows are a faithful transcription of the CC BY 4.0 source note published on 15 July 2026. Row counts, required fields, unique keys, HTTPS reference URLs, source checksum, and safety exclusions are validated before publication. No customer records, supplier records, private repair records, credentials, or hidden component claims are included.

Non-Affiliation

Reboot Hub is an independent drone service, technical-reference, and pre-owned drone resource. Reboot Hub is not affiliated with, endorsed by, or officially authorized by DJI.

Citation

Reboot Hub Editorial. "DJI Intelligent Flight Battery Charging Faults: Safe Diagnostic Decision Tree and Evidence Boundaries." Version 1.0, 15 July 2026. https://doi.org/10.5281/zenodo.21381657