n8n_8_Revit_IFC_DWG_Konvertierung_Extractionphase_XLSX_Parsen
中級
これはEngineering, Multimodal AI分野の自動化ワークフローで、13個のノードを含みます。主にIf, Set, ManualTrigger, ExecuteCommand, ReadBinaryFileなどのノードを使用。 Revit モデルデータを抽出し、構造化された Excel 形式に解析
前提条件
- •特別な前提条件なし、インポートしてすぐに使用可能
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
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"tags": [],
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"value": "C:\\Users\\Artem Boiko\\Desktop\\n8n\\cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto-main\\cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto-main\\DDC_Converter_Revit\\RvtExporter.exe"
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"parameters": {
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"continueOnFail": true
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{
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"name": "xlsx_filename",
"type": "string",
"value": "={{ $node[\"Setup - Define file paths\"].json[\"revit_file\"].slice(0, -4) + \"_rvt.xlsx\" }}"
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"type": "string",
"value": "=Extraction failed: {{ $node[\"Extract - Run Revit converter\"].json.error || \"Unknown error\" }}"
},
{
"id": "error-code-id",
"name": "error_code",
"type": "number",
"value": "={{ $node[\"Extract - Run Revit converter\"].json.code || -1 }}"
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{
"id": "6010e598-b0de-415b-b812-3dcbf656dd65",
"name": "抽出 - ディスクからExcelファイルを読み込み",
"type": "n8n-nodes-base.readBinaryFile",
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"parameters": {
"filePath": "={{ $json[\"xlsx_filename\"] }}"
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"name": "抽出 - Excelをデータに解析",
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"content": "## 🔷 EXTRACT Phase\n\n**E**xtract data from Revit file:\n1. Setup file paths\n2. Run Revit converter (RVT → Excel)\n3. Check if conversion succeeded\n4. Read Excel file from disk\n5. Parse Excel into structured data"
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"content": "# ETL with CAD (BIM) \n**Extract. Transform. Load — the future of data processing in construction**\n\nETL (Extract, Transform, Load) is a time-tested and universal approach at the heart of every mature digital infrastructure. When applied to CAD and BIM data, it becomes not just relevant — but essential.\nETL is more than just a technical process. It’s a mindset shift — one that takes BIM out of the siloed world of 3D modeling and into the open world of transparent, interoperable, and machine-readable data. It is this paradigm that powers platforms like [DataDrivenConstruction.io](https://datadrivenconstruction.io) and drives the future of digital transformation in the built environment.\n"
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"content": "⭐ **If you find our tools helpful**, please **consider starring** our repository on [GitHub](https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto). \n\nYour support helps us improve and continue developing open solutions for the community!\n"
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"content": "## ⬇️ Only modify the variables here \neverything else works automatically"
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}よくある質問
このワークフローの使い方は?
上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。
このワークフローはどんな場面に適していますか?
中級 - エンジニアリング, マルチモーダルAI
有料ですか?
このワークフローは完全無料です。ただし、ワークフローで使用するサードパーティサービス(OpenAI APIなど)は別途料金が発生する場合があります。
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ワークフロー情報
難易度
中級
ノード数13
カテゴリー2
ノードタイプ7
作成者
Artem Boiko
@datadrivenconstructionFounder DataDrivenConstruction.io | AEC Tech Consultant & Automation Expert | Bridging Software and Construction
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