STM32粉尘监测：硬件连接与数据处理全攻略
硬件准备与连接
STM32F407VET6开发板作为主控芯片，具备丰富的外设接口和强大的处理能力。GP2Y1014AU粉尘传感器通过检测空气中的粉尘浓度输出模拟电压信号。需准备杜邦线、USB转串口模块、电源模块等基础硬件。
将GP2Y1014AU的VCC引脚连接至5V电源，GND接地，LED引脚接STM32的GPIO输出，Vo引脚接STM32的ADC输入通道。传感器内部LED需通过PWM控制以降低功耗，建议使用定时器输出PWM信号驱动LED引脚。
零知IDE环境配置
零知IDE基于Arduino框架，支持STM32系列开发。安装STM32F4支持包后，在工具菜单中选择正确板型（STM32F407VET6）和串口端口。需额外安装Adafruit PWM库用于LED控制，以及内置ADC库用于模拟信号采集。
配置项目时启用硬件定时器（如TIM1）生成1Hz PWM信号，设置ADC为12位分辨率。通过以下代码初始化外设：
void setup() {
pinMode(LED_PIN, OUTPUT);
analogReadResolution(12);
HardwareTimer *timer = new HardwareTimer(TIM1);
timer->setPWM(LED_PIN, 1000, 50); // 1kHz, 50%占空比
}
数据采集与处理
GP2Y1014AU的输出电压与粉尘浓度呈非线性关系。采集ADC值后需转换为电压值，再通过传感器特性曲线计算浓度。典型转换公式为： $$ 浓度(\mu g/m^3) = (0.17 \times 电压(V)) - 0.1 $$
实际应用中需进行多次采样取平均值以降低噪声。示例代码实现滑动窗口滤波：
#define SAMPLE_SIZE 10
int samples[SAMPLE_SIZE];
int index = 0;
float readDust() {
samples[index] = analogRead(DUST_PIN);
index = (index + 1) % SAMPLE_SIZE;
long sum = 0;
for(int i=0; i<SAMPLE_SIZE; i++) sum += samples[i];
float voltage = (sum * 3.3) / (SAMPLE_SIZE * 4095.0);
return (0.17 * voltage - 0.1) > 0 ? (0.17 * voltage - 0.1) : 0;
}
串口通信与数据可视化
通过STM32的USART接口输出数据至PC端。设置波特率为115200，发送格式建议包含时间戳和校准参数：
void sendData(float density) {
Serial.print(millis());
Serial.print(",");
Serial.println(density, 2);
}
PC端可使用Python脚本接收数据并实时绘图。Matplotlib库示例代码：
import serial
import matplotlib.pyplot as plt
ser = serial.Serial('COM3', 115200)
plt.ion()
fig, ax = plt.subplots()
x, y = [], []
while True:
data = ser.readline().decode().strip().split(',')
x.append(float(data[0])/1000)
y.append(float(data[1]))
ax.plot(x, y, 'b-')
plt.pause(0.01)
系统优化与校准
为提高测量精度，需进行两点校准：零点校准（清洁空气环境）和跨度校准（已知浓度环境）。校准参数应存储在STM32的Flash中，上电时自动加载。EEPROM库示例：
#include <EEPROM.h>
struct Calibration {
float offset;
float scale;
};
void saveCalib(Calibration calib) {
EEPROM.put(0, calib);
}
Calibration loadCalib() {
Calibration calib;
EEPROM.get(0, calib);
return calib;
}
硬件布局需避免电磁干扰，传感器进气口保持通畅。长期使用时建议增加温度补偿算法，因传感器特性会随环境温度变化。
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