制造业 & 控制 机器报警情报 代理

import pandas as pd
from datetime import datetime

def load_alarms(csv_file):
    df = pd.read_csv(csv_file)
    return df.sort_values('timestamp')

def correlate_alarms(df, window=5):
    df['window'] = df.groupby('machine')['timestamp'].diff().abs().le(window)
    return df[df['window']]

alarms = load_alarms('alarms.csv')
correlated = correlate_alarms(alarms)
root_causes = correlated[correlated['severity'] == 'critical']
print(json.dumps({'total':len(alarms), 'correlated':len(correlated), 'root_causes': len(root_causes)}))