diff --git a/influxdb_api.py b/influxdb_api.py
index 6d1c386..64c736f 100644
--- a/influxdb_api.py
+++ b/influxdb_api.py
@@ -4602,7 +4602,7 @@ def import_multicolumn_data_from_file(
         )
 
     def convert_to_iso(timestr):
-        # 假设原格式为 '2025/8/3 0:00'
+        # 假设原格式为 '2025-08-03 00:00:00'
         dt = datetime.strptime(timestr, "%Y-%m-%d %H:%M:%S")
         return dt.isoformat()
 
@@ -4627,8 +4627,8 @@ def import_multicolumn_data_from_file(
                         .tag("description", None)
                         .tag("device_ID", scada_id)
                         .field("monitored_value", raw_value)
-                        .field("datacleaning_value", 0.0)
-                        .field("simulation_value", 0.0)
+                        # .field("datacleaning_value", 0.0)
+                        # .field("simulation_value", 0.0)
                         .time(iso_time, WritePrecision.S)
                     )
                     points_to_write.append(point)
@@ -4649,9 +4649,9 @@ def import_multicolumn_data_from_file(
                         .tag("date", iso_time.split("T")[0])
                         .tag("description", "None")
                         .tag("device_ID", scada_id)
-                        .field("monitored_value", 0.0)
+                        # .field("monitored_value", 0.0)
                         .field("datacleaning_value", datacleaning_value)
-                        .field("simulation_value", 0.0)
+                        # .field("simulation_value", 0.0)
                         .time(iso_time, WritePrecision.S)
                     )
                     points_to_write.append(point)
@@ -4708,24 +4708,24 @@ def import_multicolumn_data_from_dict(
                 # 如果是原始数据,写入monitored_value
                 point = (
                     Point("SCADA")
-                    .tag("date", time_str.split("T")[0])
+                    .tag("date", datetime.fromisoformat(time_str).date().isoformat())
                     .tag("description", None)
                     .tag("device_ID", device_id)
                     .field("monitored_value", float_value)
-                    .field("datacleaning_value", 0.0)
-                    .field("simulation_value", 0.0)
+                    # .field("datacleaning_value", 0.0)
+                    # .field("simulation_value", 0.0)
                     .time(time_str, WritePrecision.S)
                 )
             else:
                 # 如果是清洗数据,写入datacleaning_value
                 point = (
                     Point("SCADA")
-                    .tag("date", time_str.split("T")[0])
+                    .tag("date", datetime.fromisoformat(time_str).date().isoformat())
                     .tag("description", "None")
                     .tag("device_ID", device_id)
-                    .field("monitored_value", 0.0)
+                    # .field("monitored_value", 0.0)
                     .field("datacleaning_value", float_value)
-                    .field("simulation_value", 0.0)
+                    # .field("simulation_value", 0.0)
                     .time(time_str, WritePrecision.S)
                 )
             points_to_write.append(point)
diff --git a/main.py b/main.py
index 2e4d098..62c298e 100644
--- a/main.py
+++ b/main.py
@@ -4154,7 +4154,7 @@ async def fastapi_scada_device_data_cleaning(
         elif device_type == "pipe_flow":
             cleaned_value_df = api_ex.Fdataclean.clean_flow_data_dict(value_df)
 
-            # 添加 time 列到首列
+        # 添加 time 列到首列
         cleaned_value_df = pd.DataFrame(cleaned_value_df)
         # 只选择以 '_cleaned' 结尾的清洗数据列
         cleaned_columns = [