diff --git a/config.py b/config.py
index 4cf6311..58ef29b 100644
--- a/config.py
+++ b/config.py
@@ -76,6 +76,7 @@ WINDOW_SIZE = {"window_sizes":[50, 80, 100, 120]}
 BAR_THRESHOLD = {
     "5m": 1000 * 60 * 5,
     "15m": 1000 * 60 * 15,
+    "30m": 1000 * 60 * 30,
     "1H": 1000 * 60 * 60,
     "4H": 1000 * 60 * 60 * 4,
     "1D": 1000 * 60 * 60 * 24
diff --git a/core/biz/__pycache__/market_monitor.cpython-312.pyc b/core/biz/__pycache__/market_monitor.cpython-312.pyc
index ec5390a..93d3cf5 100644
Binary files a/core/biz/__pycache__/market_monitor.cpython-312.pyc and b/core/biz/__pycache__/market_monitor.cpython-312.pyc differ
diff --git a/core/biz/market_monitor.py b/core/biz/market_monitor.py
index 84fdeb5..cbc5942 100644
--- a/core/biz/market_monitor.py
+++ b/core/biz/market_monitor.py
@@ -1,6 +1,7 @@
 import pandas as pd
 import numpy as np
 from metrics_config import METRICS_CONFIG
+from config import BAR_THRESHOLD
 from time import time
 
 import logging
@@ -12,6 +13,7 @@ def create_metrics_report(
     row: pd.Series, 
     next_bar_row: pd.Series, 
     btc_bar_row: pd.Series,
+    all_data: pd.DataFrame,
     only_output_huge_volume: bool = False,
     only_output_rise: bool = False,
     now_datetime_str: str = None,
@@ -64,7 +66,7 @@ def create_metrics_report(
     k_shape = str(row["k_shape"])
     contents.append(f"### 价格信息")
     contents.append(f"当前价格: {close}, 开盘价: {open}, 最高价: {high}, 最低价: {low}")
-    contents.append(f"涨跌幅: {pct_chg}")
+    contents.append(f"涨跌幅: {pct_chg}%")
     contents.append(f"当前K线形态: {k_shape}")
 
     volume = round(float(row["volume"]), 4)
@@ -95,6 +97,10 @@ def create_metrics_report(
     elif close_10_low:
         contents.append(f"当前价格处于滑动窗口期10%分位数低点")
 
+    timestamp = int(row["timestamp"])
+    last_huge_volume_info = get_last_huge_volume_record(all_data, bar, timestamp)
+    contents.extend(last_huge_volume_info)
+
     long_short_info = {"多": [], "空": []}
     ma_long_short = str(row["ma_long_short"])
     ma_long_short_value = METRICS_CONFIG.get("ma_long_short", {}).get(ma_long_short, 1)
@@ -300,6 +306,57 @@ def create_metrics_report(
     return mark_down_text
 
 
+def get_last_huge_volume_record(all_data: pd.DataFrame, bar: str, timestamp: int):
+    """
+    1. 获取最近一次巨量记录
+        a. 获取最近一次巨量记录的日期时间
+        b. 获取最近一次巨量记录的日期时间距今多少个K线
+        c. 获取最近一次巨量记录的涨跌幅
+        d. 获取最近一次巨量记录的成交量比率
+    2. 获得最近十个周期内，出现巨量的次数
+    """
+    last_record_title = f"#### 最近一次{bar}周期巨量记录信息"
+    results = []
+    results.append(last_record_title)
+    try:
+        # 根据timestamp降序排序
+        all_data = all_data.sort_values(by="timestamp", ascending=False)
+        # 获取timestamp小于等于timestamp的行
+        earlier_huge_volume_data = all_data[(all_data["timestamp"] < timestamp) & (all_data["huge_volume"] == 1)]
+        
+        if earlier_huge_volume_data.empty:
+            results.append(f"窗口周期内无其他巨量记录，当前为首次出现巨量")
+            return results
+        else:
+            #a. 获取最近一次巨量记录的日期时间
+            #b. 获取最近一次巨量记录的日期时间距今多少个K线
+            #c. 获取最近一次巨量记录的涨跌幅
+            #d. 获取最近一次巨量记录的成交量比率
+            last_record = earlier_huge_volume_data.iloc[0]
+            last_record_date_time = last_record["date_time"]
+            last_record_timestamp = last_record["timestamp"]
+            last_record_pct_chg = float(round(last_record["pct_chg"], 4))
+            last_record_volume_ratio = float(round(last_record["volume_ratio"], 4))
+            
+            bar_threshold = BAR_THRESHOLD.get(bar, 1000 * 60 * 60 * 24)
+            period_diff = int((timestamp - last_record_timestamp) / bar_threshold)
+            last_record_text = f"日期时间: {last_record_date_time}"
+            last_record_text += f"，距今{period_diff}个K线"
+            last_record_text += f"，涨跌幅: {last_record_pct_chg}%"
+            last_record_text += f"，成交量比率: {last_record_volume_ratio}"
+            results.append(last_record_text)
+            # 2. 获得最近十个周期内，出现巨量的次数
+            # 从第2行开始取，取10行
+            ten_period_data = all_data.iloc[1:11]
+            huge_volume_in_ten_period_count= int(ten_period_data["huge_volume"].sum())
+            results.append(f"最近十个周期内，出现巨量的次数: {huge_volume_in_ten_period_count}")
+            return results
+    except Exception as e:
+        logging.error(f"获取最近一次巨量记录信息失败: {e}")
+        results.append(f"获取最近一次巨量记录信息失败: {e}")
+        return results
+
+
 def get_long_short_over_buy_sell(
     row: pd.Series,
     now_datetime_str: str = None,
diff --git a/market_monitor_main.py b/market_monitor_main.py
index 59b955f..4ba0f20 100644
--- a/market_monitor_main.py
+++ b/market_monitor_main.py
@@ -161,6 +161,7 @@ class MarketMonitorMain:
             realtime_row,
             next_bar_row,
             btc_bar_row,
+            real_time_data,
             only_output_huge_volume,
             only_output_rise,
             now_datetime_str,
@@ -258,6 +259,6 @@ if __name__ == "__main__":
     market_monitor_main.monitor_realtime_market(
         symbol="PUMP-USDT",
         bar="15m",
-        only_output_huge_volume=True,
-        only_output_rise=True,
+        only_output_huge_volume=False,
+        only_output_rise=False,
     )