自动化诊断最终版本

api_diag.py

@@ -11,200 +11,9 @@ from fastapi.responses import JSONResponse
 from pydantic import BaseModel, Field, model_validator
 from typing import List, Optional, Union
 from autodiag_class import Auto_diag
-from Temp_Diag import MSET_Temp
 
-app = FastAPI(root_path="/api/diag",title=" Diagnosis API")
-
-# 全局：{ windCode: { turbine: { channel: model, … }, … }, … }
-MODEL_STORE: dict[str, dict[str, dict[str, MSET_Temp]]] = {}
-
-# 英文→中文映射
-cn_map = {
-    'main_bearing_temperature': '主轴承温度',
-    'gearbox_oil_temperature': '齿轮箱油温',
-    'generatordrive_end_bearing_temperature': '发电机驱动端轴承温度',
-    'generatornon_drive_end_bearing_temperature': '发电机非驱动端轴承温度'
-}
-
-class TemperatureInput(BaseModel):
-    windCode: str
-    windTurbineNumberList: List[str]
-    startTime: str
-    endTime: str
-
-    @model_validator(mode='before')
-    def ensure_list(cls, v):
-        raw = v.get('windTurbineNumberList')
-        if isinstance(raw, str):
-            v['windTurbineNumberList'] = [raw]
-        return v
-
-class TemperatureThresholdInput(TemperatureInput):
-    pageNo:   int
-    pageSize: int
-
-@app.on_event("startup")
-def load_all_models():
-    for f in glob.glob("models/*/*/*.pkl"):
-        _, wc, turbine, fname = f.split(os.sep)
-        ch = os.path.splitext(fname)[0]
-        MODEL_STORE.setdefault(wc, {}).setdefault(turbine, {})[ch] = MSET_Temp.load_model(f)
-    print("模型加载完成:", {k: list(v.keys()) for k,v in MODEL_STORE.items()})
-
-@app.post("/temperature/threshold")
-async def route_threshold(inp: TemperatureThresholdInput):
-    """
-    输入：
-    {
-      "windCode": "WOF091200030",
-      "windTurbineNumberList": ["WOG01355"],
-      "startTime": "2024-06-01 00:00",
-      "endTime":   "2024-06-05 01:00",
-      "pageNo":    1,
-      "pageSize":  10
-    }
-    输出：
-    {
-      "data": {
-        "type": "temperature_threshold",
-        "records": [
-          {
-            "wind_turbine_number": "WOG01355",
-            "time_stamp": "2025-06-01 00:05:00",
-            "temp_channel": "主轴承温度",
-            "SPRT_score": 0.12,
-            "status": "正常"
-          },
-          ...
-        ],
-        "totalSize": 42
-      },
-      "code": 200,
-      "message": "success"
-    }
-    """
-    # 1) 校验模型是否存在
-    if inp.windCode not in MODEL_STORE:
-        raise HTTPException(404, f"无模型：{inp.windCode}")
-    # 2) 为每台待分析风机，拉数据并推理
-    records = []
-    for turbine in inp.windTurbineNumberList:
-        if turbine not in MODEL_STORE[inp.windCode]:
-            continue
-        analyzer = MSET_Temp(inp.windCode, [turbine], inp.startTime, inp.endTime)
-        df = analyzer._get_data_by_filter()
-        if df.empty:
-            continue
-        df['time_stamp'] = pd.to_datetime(df['time_stamp'])
-
-        for eng, cn in cn_map.items():
-            if eng not in df.columns:
-                continue
-            sub = df[['time_stamp', eng]].dropna()
-            arr = sub[eng].values.reshape(-1,1)
-            ts  = sub['time_stamp'].dt.strftime("%Y-%m-%d %H:%M:%S").tolist()
-
-            model = MODEL_STORE[inp.windCode][turbine].get(eng)
-            if not model:
-                continue
-            flags = model.predict_SPRT(arr, decisionGroup=1)
-
-            for i, sc in enumerate(flags):
-                records.append({
-                    "wind_turbine_number": turbine,
-                    "time_stamp": ts[i],
-                    "temp_channel": cn,
-                    "SPRT_score": sc,
-                    "status": "危险" if sc>0.99 else "正常"
-                })
-
-    # 分页返回
-    total = len(records)
-    start = (inp.pageNo-1)*inp.pageSize
-    end   = start+inp.pageSize
-    return {
-        "data": {
-            "type": "temperature_threshold",
-            "records": records[start:end],
-            "totalSize": total
-        },
-        "code": 200,
-        "message": "success"
-    }
-
-@app.post("/SPRT/trend")
-async def route_trend(inp: TemperatureInput):
-    """
-    输入：
-    {
-      "windCode": "WOF091200030",
-      "windTurbineNumberList": ["WOG01355"],
-      "startTime": "2024-06-01 00:00",
-      "endTime":   "2024-06-05 01:00"
-    }
-    输出：
-    {
-      "data": {
-        "type": "SPRT_trend",
-        "main_bearing": {"timestamps": [...], "values": [...]},
-        "gearbox_oil": {"timestamps": [...], "values": [...]},
-        "generator_drive_end": {"timestamps": [...], "values": [...]},
-        "generator_nondrive_end": {"timestamps": [...], "values": [...]}
-      },
-      "code": 200,
-      "message": "success"
-    }
-
-    """
-    if inp.windCode not in MODEL_STORE:
-        raise HTTPException(404, f"无模型：{inp.windCode}")
-
-    turbines_out = []
-    for turbine in inp.windTurbineNumberList:
-        if turbine not in MODEL_STORE[inp.windCode]:
-            continue
-        analyzer = MSET_Temp(inp.windCode, [turbine], inp.startTime, inp.endTime)
-        df = analyzer._get_data_by_filter()
-        if df.empty:
-            continue
-        df['time_stamp'] = pd.to_datetime(df['time_stamp'])
-
-        ch_data = {}
-        for eng, key in {
-            'main_bearing_temperature':'main_bearing',
-            'gearbox_oil_temperature':'gearbox_oil',
-            'generatordrive_end_bearing_temperature':'generator_drive_end',
-            'generatornon_drive_end_bearing_temperature':'generator_nondrive_end'
-        }.items():
-            if eng not in df.columns:
-                ch_data[key] = {"timestamps": [], "values": []}
-                continue
-            sub = df[['time_stamp', eng]].dropna()
-            ts  = sub['time_stamp'].dt.strftime("%Y-%m-%d %H:%M:%S").tolist()
-            arr = sub[eng].values.reshape(-1,1)
-
-            model = MODEL_STORE[inp.windCode][turbine].get(eng)
-            vals = model.predict_SPRT(arr, decisionGroup=1) if model else []
-            ch_data[key] = {"timestamps": ts, "values": vals}
-
-        # turbines_out.append({
-        #   "wind_turbine_number": turbine,
-        #     **ch_data
-        # })
-
-    return {
-        "data": {
-            "type": "SPRT_trend",
-            **ch_data
-        },
-        "code": 200,
-        "message": "success"
-    }
-
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True)
 
+app = FastAPI(root_path="/api/diag",title=" Diagnosis API")
 
 
 # 请求模型定义