diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py
index fce11d3e..764fa7c8 100644
--- a/freqtrade/templates/freqaiprimer.py
+++ b/freqtrade/templates/freqaiprimer.py
@@ -184,6 +184,9 @@ class FreqaiPrimer(IStrategy):
         df_1h['macd_signal_1h'] = macd_1h['MACDs_12_26_9']
         df_1h['macd_hist_1h'] = macd_1h['MACDh_12_26_9']
 
+        # 验证 MACD 列是否正确生成
+        logger.info(f"[{metadata['pair']}] 1小时 MACD 列: {list(macd_1h.columns)}")
+
         # 新增 StochRSI 指标
         stochrsi_1h = ta.stochrsi(df_1h['close'], length=14, rsi_length=14)
         df_1h['stochrsi_k_1h'] = stochrsi_1h['STOCHRSIk_14_14_3_3']
@@ -195,12 +198,23 @@ class FreqaiPrimer(IStrategy):
         df_1h = df_1h[['date', 'rsi_1h', 'trend_1h', 'ema_50_1h', 'ema_200_1h', 'bb_lower_1h', 'bb_upper_1h', 'stochrsi_k_1h', 'stochrsi_d_1h']].fillna(method='ffill')
         
         # 确保所有需要的列都被合并
-        df_1h = df_1h[['date', 'rsi_1h', 'trend_1h', 'ema_50_1h', 'ema_200_1h', 
-                       'bb_lower_1h', 'bb_upper_1h', 'stochrsi_k_1h', 'stochrsi_d_1h',
-                       'macd_1h', 'macd_signal_1h']]  # 确保包含 macd_1h 和 macd_signal_1h
+        required_columns = ['date', 'rsi_1h', 'trend_1h', 'ema_50_1h', 'ema_200_1h', 
+                            'bb_lower_1h', 'bb_upper_1h', 'stochrsi_k_1h', 'stochrsi_d_1h',
+                            'macd_1h', 'macd_signal_1h']
+        
+        # 验证所需列是否存在
+        missing_columns = [col for col in required_columns if col not in df_1h.columns]
+        if missing_columns:
+            logger.error(f"[{metadata['pair']}] 缺少以下列: {missing_columns}")
+            raise KeyError(f"缺少以下列: {missing_columns}")
+        
+        df_1h = df_1h[required_columns]  # 确保包含 macd_1h 和 macd_signal_1h
         
         # 合并 1h 数据
         dataframe = dataframe.merge(df_1h, how='left', on='date').fillna(method='ffill')
+        
+        # 验证合并后的列
+        logger.info(f"[{metadata['pair']}] 合并后的数据框列名: {list(dataframe.columns)}")
 
         # K线形态：看涨吞没
         dataframe['bullish_engulfing'] = (