| Name | phm-algo-ias JSON |
| Version |
1.3.2
JSON |
| download |
| home_page | None |
| Summary | Example algo package with Cython-compiled submodules |
| upload_time | 2025-11-13 09:52:28 |
| maintainer | None |
| docs_url | None |
| author | Your Name |
| requires_python | >=3.11 |
| license | None |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# 參數列表
| | 演算法功能 | 建模參數 |
|-----|-----------------------------------|---------------------------|
| 0 | DEMO | "0, 1, 1, 1, 1, 1, 1, 1" |
| 1-1 | 一般建模(TSMC) | "1, 0, 1, 3, 3, 1, 1, 1" |
| 1-2 | 一般建模(SDP、雲界) | "1, 0, 1, 1, 2, 1, 1, 1" |
| 2-1 | 快速建模-暫態(TSMC) | "1, 0, 1, 3, 3, 1, 1, 2" |
| 2-2 | 快速建模-穩態(TSMC) | "1, 0, 1, 3, 3, 1, 1, 3" |
# 參數意義
| | 0 | 1 | 2 | 3 | 4 |
|---|---|---|---|---|---|
| 1. 時間長度設定 | min | hour | | | |
| 2. 測試資料群值處理 | close | open | | | |
| 3. 低解析度特徵篩選 | close | open | | | |
| 4. 特徵選擇 | | Time, Frequency, fail mode | Time, Frequency | Frequency | |
| 5. Scale | | df_scaled = df | Standardize() | minmax() | |
| 6. 模型 | | PCA + T² | | | |
| 7. rul_deadline | | T² + 12 * σ(T²) → Score | Warning: T² + 24 * σ(T²) → Score<br>rul_deadline = 0 | | |
| 8. feature_extraction_setting | | 每小時取特徵<br>小時不足1800筆則刪除 | 依資料進行rolling計算<br>Window = 120s<br>Step = 60s (暫態) | Rolling計算<br>Window = 3600s<br>Step = 1800s (穩態) | |
# error_stage列表
|Training | error_stage | 程式步驟 |
|-----|-----------------------------------|---------------------------|
| | Error_01 | df 轉換成每秒一筆資料 |
| | Error_02 | 出廠設定參數 |
| | Error_03 | 前處理 |
| | Error_04 | 特徵分類/挑選 |
| | Error_05 | 低解析度特徵篩選 |
| | Error_06 | 特徵萃取 |
| | Error_07 | 資料正規化 |
| | Error_08 | 建模 |
| | Error_09 | RUL 計算 |
|Inference | error_stage | 程式步驟 |
|-----|-----------------------------------|---------------------------|
| | Error_01 | df 轉換成每秒一筆資料 |
| | Error_02 | 檢查資料筆數 (是否<301) |
| | Error_03 | 出廠設定參數 |
| | Error_04 | 前處理 |
| | Error_05 | 特徵萃取 |
| | Error_06 | 資料正規化 |
| | Error_07 | 計算 HI & T2 & 嫌疑度變量 |
Raw data
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