智能室内空气质量监控与净化系统
一、实际应用场景描述
场景背景
在现代煤矿智能化开采的办公环境中，由于煤矿设备维护区域、实验室、会议室等封闭空间可能存在甲醛（来自新设备、装修材料）和PM2.5（来自外部空气、设备运行）污染。长期暴露在这样的环境中会影响员工健康和工作效率。
痛点分析
- 健康风险：甲醛是致癌物，PM2.5可引发呼吸道疾病
- 被动响应：传统方式依赖人工发现污染并手动开启净化设备
- 能源浪费：净化器常开造成电力浪费，设备损耗
- 监管困难：缺乏实时数据记录和分析，难以优化空气质量
二、核心逻辑讲解
系统架构
传感器数据采集 → 数据处理分析 → 阈值判断 → 设备控制 → 状态反馈
控制逻辑
- 实时监测甲醛和PM2.5浓度
- 当任一指标超标时，自动启动净化器
- 持续监测直至两项指标均达标
- 达标后延迟关闭，防止频繁启停
- 记录所有数据用于分析和优化
三、代码实现
项目结构
air_quality_system/ ├── main.py # 主程序 ├── sensors/ │ ├── init.py │ ├── air_quality_sensor.py # 传感器模拟/接口 │ └── sensor_interface.py # 传感器抽象接口 ├── controllers/ │ ├── init.py │ └── purifier_controller.py # 净化器控制器 ├── config/ │ ├── init.py │ └── settings.py # 配置文件 ├── utils/ │ ├── init.py │ ├── logger.py # 日志模块 │ └── data_handler.py # 数据处理 ├── requirements.txt # 依赖包 └── README.md # 说明文档
- 配置文件 (config/settings.py)
""" 系统配置文件 定义空气质量标准和系统参数 """
class AirQualityStandard: """空气质量标准类 (基于GB/T 18883-2022室内空气质量标准)"""
# 甲醛浓度标准 (mg/m³)
FORMALDEHYDE = {
'excellent': 0.03, # 优级
'good': 0.05, # 良好
'limit': 0.08, # 国家标准限值
'warning': 0.10, # 警告阈值
'danger': 0.20 # 危险阈值
}
# PM2.5浓度标准 (μg/m³)
PM25 = {
'excellent': 15, # 优级
'good': 35, # 良好
'limit': 50, # 国家标准限值
'warning': 75, # 警告阈值
'danger': 150 # 危险阈值
}
class SystemConfig: """系统运行参数配置"""
# 监测间隔（秒）
MONITOR_INTERVAL = 5
# 净化器控制参数
PURIFIER_DELAY_OFF = 60 # 达标后延迟关闭时间（秒）
PURIFIER_MIN_RUN_TIME = 300 # 净化器最小运行时间（秒）
# 报警参数
ENABLE_ALERT = True
ALERT_INTERVAL = 300 # 报警间隔（秒）
# 数据记录
LOG_ENABLED = True
DATA_SAVE_INTERVAL = 60 # 数据保存间隔（秒）
2. 传感器接口模块 (sensors/sensor_interface.py)
""" 传感器抽象接口模块 定义统一的传感器接口规范 """ from abc import ABC, abstractmethod import time from datetime import datetime
class AirQualitySensor(ABC): """空气质量传感器抽象基类"""
def __init__(self, sensor_id: str, location: str = "unknown"):
"""
初始化传感器
参数:
sensor_id: 传感器唯一标识
location: 传感器位置描述
"""
self.sensor_id = sensor_id
self.location = location
self.status = "disconnected"
self.last_update = None
@abstractmethod
def connect(self) -> bool:
"""连接传感器设备"""
pass
@abstractmethod
def disconnect(self) -> bool:
"""断开传感器连接"""
pass
@abstractmethod
def read_data(self) -> dict:
"""
读取传感器数据
返回:
包含空气质量数据的字典
"""
pass
def get_status(self) -> dict:
"""获取传感器状态"""
return {
"sensor_id": self.sensor_id,
"location": self.location,
"status": self.status,
"last_update": self.last_update
}
class SensorData: """传感器数据封装类"""
def __init__(self, formaldehyde: float, pm25: float, temperature: float = None,
humidity: float = None, co2: float = None):
"""
初始化传感器数据
参数:
formaldehyde: 甲醛浓度 (mg/m³)
pm25: PM2.5浓度 (μg/m³)
temperature: 温度 (°C)
humidity: 湿度 (%)
co2: 二氧化碳浓度 (ppm)
"""
self.formaldehyde = formaldehyde
self.pm25 = pm25
self.temperature = temperature
self.humidity = humidity
self.co2 = co2
self.timestamp = datetime.now()
def to_dict(self) -> dict:
"""转换为字典格式"""
return {
"timestamp": self.timestamp.isoformat(),
"formaldehyde": self.formaldehyde,
"pm25": self.pm25,
"temperature": self.temperature,
"humidity": self.humidity,
"co2": self.co2
}
def __str__(self) -> str:
"""字符串表示"""
return (f"时间: {self.timestamp.strftime('%Y-%m-%d %H:%M:%S')}, "
f"甲醛: {self.formaldehyde:.3f} mg/m³, "
f"PM2.5: {self.pm25:.1f} μg/m³")
3. 传感器模拟实现 (sensors/air_quality_sensor.py)
""" 空气质量传感器实现模块 包含真实传感器接口和模拟传感器 """ import random import time from typing import Optional from .sensor_interface import AirQualitySensor, SensorData
class SimulatedAirQualitySensor(AirQualitySensor): """模拟空气质量传感器（用于开发和测试）"""
def __init__(self, sensor_id: str, location: str = "模拟传感器",
base_levels: Optional[dict] = None):
"""
初始化模拟传感器
参数:
sensor_id: 传感器ID
location: 传感器位置
base_levels: 基础污染物水平
"""
super().__init__(sensor_id, location)
# 基础污染物水平
self.base_levels = base_levels or {
"formaldehyde": 0.02, # 基础甲醛水平
"pm25": 20, # 基础PM2.5水平
}
# 污染事件参数
self.pollution_event = False
self.event_start_time = None
self.event_duration = 0
def connect(self) -> bool:
"""连接模拟传感器"""
print(f"[INFO] 连接模拟传感器 {self.sensor_id} 在 {self.location}")
self.status = "connected"
return True
def disconnect(self) -> bool:
"""断开模拟传感器"""
print(f"[INFO] 断开模拟传感器 {self.sensor_id}")
self.status = "disconnected"
return True
def _simulate_pollution_event(self) -> tuple:
"""模拟污染事件"""
current_time = time.time()
# 随机触发污染事件
if not self.pollution_event and random.random() < 0.05: # 5%概率触发
self.pollution_event = True
self.event_start_time = current_time
self.event_duration = random.randint(300, 1800) # 5-30分钟
# 处理污染事件
if self.pollution_event:
event_progress = (current_time - self.event_start_time) / self.event_duration
if event_progress >= 1: # 事件结束
self.pollution_event = False
return 0, 0
else:
# 污染峰值在事件中期
pollution_factor = 4 * event_progress * (1 - event_progress)
return pollution_factor * 0.3, pollution_factor * 200 # 甲醛和PM2.5增量
return 0, 0
def read_data(self) -> dict:
"""
读取模拟传感器数据
返回:
传感器数据字典
"""
if self.status != "connected":
raise ConnectionError("传感器未连接")
# 获取基础水平
formaldehyde_base = self.base_levels["formaldehyde"]
pm25_base = self.base_levels["pm25"]
# 模拟日常波动
hour = time.localtime().tm_hour
time_factor = 0.5 + 0.5 * abs(12 - hour) / 12 # 中午最高
# 模拟随机波动
formaldehyde_variation = random.uniform(-0.01, 0.01) * time_factor
pm25_variation = random.uniform(-5, 5) * time_factor
# 模拟污染事件
formaldehyde_event, pm25_event = self._simulate_pollution_event()
# 计算最终值
formaldehyde = max(0.01, formaldehyde_base + formaldehyde_variation + formaldehyde_event)
pm25 = max(5, pm25_base + pm25_variation + pm25_event)
# 添加温湿度模拟
temperature = 20 + random.uniform(-2, 2) + (hour - 12) * 0.5
humidity = 50 + random.uniform(-10, 10)
# 创建数据对象
sensor_data = SensorData(
formaldehyde=formaldehyde,
pm25=pm25,
temperature=round(temperature, 1),
humidity=round(humidity, 1)
)
self.last_update = time.time()
return sensor_data.to_dict()
class RealAirQualitySensor(AirQualitySensor): """真实空气质量传感器接口（示例，需根据实际硬件实现）"""
def __init__(self, sensor_id: str, location: str, port: str, baudrate: int = 9600):
"""
初始化真实传感器
参数:
sensor_id: 传感器ID
location: 传感器位置
port: 串口端口
baudrate: 波特率
"""
super().__init__(sensor_id, location)
self.port = port
self.baudrate = baudrate
self.serial_conn = None
def connect(self) -> bool:
"""连接真实传感器"""
try:
import serial
self.serial_conn = serial.Serial(
port=self.port,
baudrate=self.baudrate,
timeout=2
)
self.status = "connected"
print(f"[INFO] 成功连接传感器 {self.sensor_id} 在端口 {self.port}")
return True
except Exception as e:
print(f"[ERROR] 连接传感器失败: {e}")
self.status = "disconnected"
return False
def disconnect(self) -> bool:
"""断开传感器连接"""
if self.serial_conn and self.serial_conn.is_open:
self.serial_conn.close()
self.status = "disconnected"
return True
def _parse_sensor_data(self, raw_data: bytes) -> Optional[dict]:
"""
解析传感器原始数据
注意：此函数需要根据实际传感器协议实现
"""
# 示例解析逻辑（需根据实际传感器调整）
try:
# 假设传感器数据格式: "HCHO:0.05,PM2.5:35,TEMP:25.0,HUM:50"
data_str = raw_data.decode('utf-8').strip()
data_dict = {}
for item in data_str.split(','):
if ':' in item:
key, value = item.split(':')
data_dict[key.strip()] = float(value)
# 映射到标准字段
formaldehyde = data_dict.get('HCHO', 0.0)
pm25 = data_dict.get('PM2.5', 0.0)
temperature = data_dict.get('TEMP', None)
humidity = data_dict.get('HUM', None)
sensor_data = SensorData(
formaldehyde=formaldehyde,
pm25=pm25,
temperature=temperature,
humidity=humidity
)
return sensor_data.to_dict()
except Exception as e:
print(f"[ERROR] 解析传感器数据失败: {e}")
return None
def read_data(self) -> dict:
"""从真实传感器读取数据"""
if not self.serial_conn or not self.serial_conn.is_open:
raise ConnectionError("传感器未连接")
try:
# 发送读取命令（根据实际传感器协议）
self.serial_conn.write(b'READ\r\n')
time.sleep(0.1)
# 读取返回数据
raw_data = self.serial_conn.readline()
# 解析数据
data = self._parse_sensor_data(raw_data)
if data:
self.last_update = time.time()
return data
else:
raise ValueError("无效的传感器数据")
except Exception as e:
print(f"[ERROR] 读取传感器数据失败: {e}")
raise
4. 净化器控制器 (controllers/purifier_controller.py)
""" 空气净化器控制器模块 控制净化器的开启和关闭 """ import time from abc import ABC, abstractmethod from datetime import datetime, timedelta
class AirPurifierController(ABC): """空气净化器控制器抽象基类"""
def __init__(self, device_id: str, location: str = "unknown"):
"""
初始化净化器控制器
参数:
device_id: 设备ID
location: 设备位置
"""
self.device_id = device_id
self.location = location
self.status = "off" # "off", "on", "error"
self.start_time = None
self.total_runtime = timedelta(0)
self.energy_consumption = 0 # 千瓦时
@abstractmethod
def turn_on(self) -> bool:
"""开启净化器"""
pass
@abstractmethod
def turn_off(self) -> bool:
"""关闭净化器"""
pass
@abstractmethod
def get_status(self) -> dict:
"""获取净化器状态"""
pass
def update_runtime(self):
"""更新运行时间统计"""
if self.status == "on" and self.start_time:
runtime = datetime.now() - self.start_time
self.total_runtime += runtime
# 假设功率为50W
self.energy_consumption += 0.05 * runtime.total_seconds() / 3600
self.start_time = datetime.now()
class SimulatedPurifierController(AirPurifierController): """模拟空气净化器控制器（用于开发和测试）"""
def __init__(self, device_id: str, location: str = "模拟净化器"):
"""初始化模拟净化器控制器"""
super().__init__(device_id, location)
self.power_consumption = 0.05 # 千瓦
self.filter_life = 100 # 过滤器寿命百分比
self.air_flow_level = 2 # 1-3档
def turn_on(self) -> bool:
"""开启模拟净化器"""
if self.status != "on":
print(f"[INFO] 开启净化器 {self.device_id} 在 {self.location}")
self.status = "on"
self.start_time = datetime.now()
# 模拟过滤器损耗
if self.filter_life > 0:
self.filter_life -= 0.01
return True
def turn_off(self) -> bool:
"""关闭模拟净化器"""
if self.status == "on":
print(f"[INFO] 关闭净化器 {self.device_id}")
self.update_runtime()
self.status = "off"
self.start_time = None
return True
def get_status(self) -> dict:
"""获取净化器状态"""
self.update_runtime()
return {
"device_id": self.device_id,
"location": self.location,
"status": self.status,
"total_runtime_hours": round(self.total_runtime.total_seconds() / 3600, 2),
"energy_consumption_kwh": round(self.energy_consumption, 2),
"filter_life_percent": round(self.filter_life, 1),
"air_flow_level": self.air_flow_level
}
class SmartPurifierController(AirPurifierController): """智能净化器控制器（支持多档位和模式）"""
def __init__(self, device_id: str, location: str, power: float = 0.05):
"""
初始化智能净化器
参数:
device_id: 设备ID
location: 设备位置
power: 额定功率（千瓦）
"""
super().__init__(device_id, location)
self.power = power
self.mode = "auto" # auto, manual, sleep
self.fan_speed = 0 # 0-3
self.air_quality_history = []
self.max_history_size = 100
def turn_on(self, speed: int = 2) -> bool:
"""
开启净化器
参数:
speed: 风扇速度 (1-3)
返回:
操作是否成功
"""
if self.status != "on":
print(f"[INFO] 开启智能净化器 {self.device_id}，风速{speed}档")
self.status = "on"
self.fan_speed = max(1, min(3, speed))
self.start_time = datetime.now()
return True
def turn_off(self) -> bool:
"""关闭净化器"""
if self.status == "on":
print(f"[INFO] 关闭智能净化器 {self.device_id}")
self.update_runtime()
self.status = "off"
self.fan_speed = 0
self.start_time = None
return True
def set_mode(self, mode: str) -> bool:
"""
设置净化器模式
参数:
mode: 模式 (auto, manual, sleep)
返回:
操作是否成功
"""
valid_modes = ["auto", "manual", "sleep"]
if mode in valid_modes:
self.mode = mode
print(f"[INFO] 设置净化器 {self.device_id} 为 {mode} 模式")
if mode == "sleep":
self.fan_speed = 1
elif mode == "auto" and self.status == "on":
# 根据历史数据调整风速
self._adjust_speed_auto()
return True
return False
def _adjust_speed_auto(self):
"""根据空气质量自动调整风速"""
if not self.air_quality_history:
return
# 获取最近的平均空气质量
recent_data = self.air_quality_history[-10:] # 最近10个数据点
avg_formaldehyde = sum(d["formaldehyde"] for d in recent_data) / len(recent_data)
avg_pm25 = sum(d["pm25"] for d in recent_data) / len(recent_data)
# 根据污染物水平调整风速
if avg_formaldehyde > 0.15 or avg_pm25 > 150:
self.fan_speed = 3
elif avg_formaldehyde > 0.08 or avg_pm25 > 75:
self.fan_speed = 2
else:
self.fan_speed = 1
def update_air_quality(self, formaldehyde: float, pm25: float):
"""
更新空气质量数据（用于自动模式）
参数:
formaldehyde: 甲醛浓度
pm25: PM2.5浓度
"""
data_point = {
"timestamp": datetime.now(),
"formaldehyde": formaldehyde,
"pm25": pm25
}
self.air_quality_history.append(data_point)
# 保持历史数据大小
if len(self.air_quality_history) > self.max_history_size:
self.air_quality_history.pop(0)
# 自动模式下调整风速
if self.mode == "auto" and self.status == "on":
self._adjust_speed_auto()
def get_status(self) -> dict:
"""获取净化器详细状态"""
self.update_runtime()
status = {
"device_id": self.device_id,
"location": self.location,
"status": self.status,
"mode": self.mode,
"fan_speed": self.fan_speed,
"total_runtime_hours": round(self.total_runtime.total_seconds() / 3600, 2),
"energy_consumption_kwh": round(self.energy_consumption, 2),
"power_kw": self.power
}
if self.air_quality_history:
latest = self.air_quality_history[-1]
status["latest_formaldehyde"] = latest["formaldehyde"]
status["latest_pm25"] = latest["pm25"]
return status
5. 数据处理器 (utils/data_handler.py)
""" 数据处理模块 处理、分析和保存空气质量数据 """ import json import csv from datetime import datetime, timedelta from typing import List, Dict, Optional import statistics
class AirQualityDataHandler: """空气质量数据处理类"""
def __init__(self, data_file: str = "air_quality_data.json"):
"""
初始化数据处理器
参数:
data_file: 数据存储文件路径
"""
self.data_file = data_file
self.history_data = []
self._load_data()
def _load_data(self):
"""从文件加载历史数据"""
try:
with open(self.data_file, 'r', encoding='utf-8') as f:
self.history_data = json.load(f)
print(f"[INFO] 从 {self.data_file} 加载了 {len(self.history_data)} 条历史数据")
except (FileNotFoundError, json.JSONDecodeError):
self.history_data = []
print(f"[INFO] 未找到历史数据文件，创建新的数据存储")
def save_data(self, data: dict):
"""
保存单条数据
参数:
data: 空气质量数据字典
"""
# 添加时间戳
if "timestamp" not in data:
data["timestamp"] = datetime.now().isoformat()
self.history_data.append(data)
# 定期保存到文件
if len(self.history_data) % 10 == 0:
self._save_to_file()
def _save_to_file(self):
"""保存数据到文件"""
try:
with open(self.data_file, 'w', encoding='utf-8') as f:
json.dump(self.history_data, f, ensure_ascii=False, indent=2)
except Exception as e:
print(f"[ERROR] 保存数据失败: {e}")
def get_recent_data(self, hours: int = 24) -> List[dict]:
"""
获取最近指定小时的数据
参数:
hours: 小时数
返回:
最近的数据列表
"""
cutoff_time = datetime.now() - timedelta(hours=hours)
recent_data = []
for data_point in self.history_data:
try:
data_time = datetime.fromisoformat(data_point["timestamp"])
if data_time >= cutoff_time:
recent_data.append(data_point)
except (KeyError, ValueError):
continue
return recent_data
def analyze_air_quality(self, hours: int = 24) -> dict:
"""
分析空气质量数据
参数:
hours: 分析的时间范围（小时）
返回:
分析结果字典
"""
recent_data = s
如果你觉得这个工具好用，欢迎关注我！
