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目录
一、硬件设计部分
1.1 硬件清单
1.2 接线方案
1.3 连接硬件图
1.4 接线实物图
二、软件架构部分
2.1 初始化结构
2.2 卡尔曼滤波
2.3 平均滤波及校准算法
2.4 Processing可视化代码
2.5 加速度计完整代码
三、校准过程及展示
3.1 校准过程
3.2 上位机界面展示
3.3 视频演示
四、ADXL345寄存器工作原理
4.1 DATA_FORMAT寄存器(0x31)
4.2 BW_RATE寄存器(0x2C)
4.3 POWER_CTL寄存器(0x2D)
4.4 加速度计I2C通信
五、常见问题解答
Q1: 传感器数据出现NaN值怎么办？
Q2: 如何提高角度计算精度？
Q3: 为什么三维立方体显示不全或位置不正确？
（1）项目概述
本项目基于零知增强板（主控芯片STM32F407VET6）和ADXL345三轴加速度计，开发了一套完整的实时姿态监测系统。通过先进的滤波算法和自动校准技术，实现了高精度的姿态角度解算，并通过Processing平台实现了三维可视化界面。该系统能够实时显示设备的滚转、俯仰角度，并记录历史数据变化趋势。
（2）项目亮点
>结合卡尔曼滤波和移动平均滤波，有效降低传感器噪声
>智能六点校准算法，无需手动干预
>Processing三维实时显示，支持历史数据回溯
（3）项目难点及解决方案
问题描述：传感器存在明显噪声和动态漂移
解决方案：采用双重滤波算法（卡尔曼滤波+移动平均滤波），设置合理的滤波参数，有效抑制噪声同时保持响应速度。
一、硬件设计部分
1.1 硬件清单
| 组件名称 | 规格型号 | 数量 | 备注 |
|---|---|---|---|
| 零知增强板 | STM32F407VET6主控 | 1 | 核心控制器 |
| ADXL345模块 | 三轴加速度计 | 1 | 姿态传感器 |
| 杜邦线 | 20cm | 4 | 连接线材 |
| 微型USB线 | / | 1 | 供电与编程 |
1.2 接线方案
| ADXL345引脚 | 零知增强板引脚 | 功能说明 |
|---|---|---|
| VCC | 5V | 电源正极 |
| GND | GND | 电源地 |
| SDA | 20/SDA | I2C数据线 |
| SCL | 21/SCL | I2C时钟线 |
1.3 连接硬件图
ADXL345模块通过I2C接口与零知增强板连接，使用5V供电
1.4 接线实物图
二、软件架构部分
2.1 初始化结构
#include <Wire.h>// ADXL345 I2C地址
#define ADXL345_ADDRESS 0x53// ADXL345寄存器地址
#define ADXL345_REG_DEVID 0x00
#define ADXL345_REG_POWER_CTL 0x2D
#define ADXL345_REG_DATA_FORMAT 0x31
#define ADXL345_REG_DATAX0 0x32
#define ADXL345_REG_BW_RATE 0x2C
#define ADXL345_REG_OFSX 0x1E
#define ADXL345_REG_OFSY 0x1F
#define ADXL345_REG_OFSZ 0x20// 高级滤波参数
#define MOVING_AVG_SIZE 7 // 移动平均窗口大小
#define KALMAN_Q 0.01 // 卡尔曼滤波过程噪声
#define KALMAN_R 0.1 // 卡尔曼滤波测量噪声
#define STABILITY_THRESHOLD 0.02 // 稳定性阈值(g)// 校准参数
float xOffset = 0, yOffset = 0, zOffset = 0;
bool calibrated = false;// 滤波结构体
typedef struct {float q; // 过程噪声协方差float r; // 测量噪声协方差float x; // 估计值float p; // 估计误差协方差float k; // 卡尔曼增益
} KalmanFilter;KalmanFilter kalmanX, kalmanY, kalmanZ;// ADXL345初始化函数
void initADXL345() {Wire.begin();// 检查设备IDbyte deviceID = readRegister(ADXL345_REG_DEVID);if (deviceID != 0xE5) {Serial.println("Error: ADXL345 not found");while(1);}// 设置数据速率和带宽为100HzwriteRegister(ADXL345_REG_BW_RATE, 0x0B);// 设置数据格式为±4g，全分辨率模式writeRegister(ADXL345_REG_DATA_FORMAT, 0x09);// 启用测量模式writeRegister(ADXL345_REG_POWER_CTL, 0x08);Serial.println("ADXL345 initialized successfully");
}MOVING_AVG_SIZE = 7：移动平均窗口大小，影响平滑度和响应速度
STABILITY_THRESHOLD = 0.02：稳定性判断阈值，小于此值认为设备稳定
2.2 卡尔曼滤波
// 移动平均滤波
float movingAvgBufferX[MOVING_AVG_SIZE];
float movingAvgBufferY[MOVING_AVG_SIZE];
float movingAvgBufferZ[MOVING_AVG_SIZE];
int movingAvgIndex = 0;// 稳定性检测
unsigned long lastStableTime = 0;
bool isStable = false;// 初始化卡尔曼滤波器
void initKalmanFilter(KalmanFilter *kf, float q, float r, float initialValue) {kf->q = q;kf->r = r;kf->x = initialValue;kf->p = 1.0;kf->k = 0;
}// 卡尔曼滤波更新
float updateKalmanFilter(KalmanFilter *kf, float measurement) {// 预测kf->p = kf->p + kf->q;// 更新kf->k = kf->p / (kf->p + kf->r);kf->x = kf->x + kf->k * (measurement - kf->x);kf->p = (1 - kf->k) * kf->p;return kf->x;
}// 应用卡尔曼滤波
void applyKalmanFilter(float &x, float &y, float &z) {x = updateKalmanFilter(&kalmanX, x);y = updateKalmanFilter(&kalmanY, y);z = updateKalmanFilter(&kalmanZ, z);
}
2.3 平均滤波及校准算法
// 应用移动平均滤波
void applyMovingAverageFilter(float &x, float &y, float &z) {// 更新缓冲区movingAvgBufferX[movingAvgIndex] = x;movingAvgBufferY[movingAvgIndex] = y;movingAvgBufferZ[movingAvgIndex] = z;movingAvgIndex = (movingAvgIndex + 1) % MOVING_AVG_SIZE;// 计算平均值float xSum = 0, ySum = 0, zSum = 0;for (int i = 0; i < MOVING_AVG_SIZE; i++) {xSum += movingAvgBufferX[i];ySum += movingAvgBufferY[i];zSum += movingAvgBufferZ[i];}x = xSum / MOVING_AVG_SIZE;y = ySum / MOVING_AVG_SIZE;z = zSum / MOVING_AVG_SIZE;
}// 自动校准函数
void autoCalibrate() {Serial.println("Start automatic calibration...");Serial.println("Please ensure that the sensor is placed horizontally and stationary");// 等待2秒让用户放置传感器delay(2000);float xSum = 0, ySum = 0, zSum = 0;const int samples = 200;int validSamples = 0;// 采集多个样本求平均值for (int i = 0; i < samples; i++) {float x, y, z;readAcceleration(x, y, z);// 检查数据有效性if (!isnan(x) && !isnan(y) && !isnan(z)) {xSum += x;ySum += y;zSum += z;validSamples++;}delay(10); // 每10ms采集一次}if (validSamples > 0) {// 计算偏移量xOffset = xSum / validSamples;yOffset = ySum / validSamples;zOffset = zSum / validSamples - 1.0; // 减去重力加速度// 设置硬件偏移寄存器writeRegister(ADXL345_REG_OFSX, (byte)(xOffset / 0.0156));writeRegister(ADXL345_REG_OFSY, (byte)(yOffset / 0.0156));writeRegister(ADXL345_REG_OFSZ, (byte)(zOffset / 0.0156));calibrated = true;Serial.println("Automatic calibration completed!");Serial.print("XOffset: "); Serial.print(xOffset, 6);Serial.print(" g, YOffset: "); Serial.print(yOffset, 6);Serial.print(" g, ZOffset: "); Serial.print(zOffset, 6);Serial.println(" g");} else {Serial.println("Calibration failure: No valid data can be obtained");}
}// 处理串口命令
void processSerialCommands() {if (Serial.available()) {char command = Serial.read();if (command == 'c' || command == 'C') {autoCalibrate();} else if (command == 'r' || command == 'R') {// 重置校准数据calibrated = false;xOffset = 0;yOffset = 0;zOffset = 0;writeRegister(ADXL345_REG_OFSX, 0);writeRegister(ADXL345_REG_OFSY, 0);writeRegister(ADXL345_REG_OFSZ, 0);Serial.println("The calibration data has been reset");} else if (command == 's' || command == 'S') {// 显示状态Serial.print("校准状态 : ");Serial.println(calibrated ? "Calibrated Resistance" : "Uncalibrated");Serial.print("XOffset: "); Serial.println(xOffset, 6);Serial.print("YOffset: "); Serial.println(yOffset, 6);Serial.print("ZOffset: "); Serial.println(zOffset, 6);}}
}
2.4 Processing可视化代码
import processing.serial.*;// 传感器数据
float roll, pitch, yaw;
PVector accelerometer = new PVector();
PVector gyroscope = new PVector(0, 0, 0);
PVector magneticField = new PVector(0, 0, 0);// 3D模型
PShape model;
PImage bgImage;// 串口配置
Serial port;
String[] serialPorts;
int selectedPort = 0;
boolean printSerial = true;
boolean connected = false;// 历史数据
float[] rollHistory = new float[200];
float[] pitchHistory = new float[200];
int historyIndex = 0;// UI颜色主题
color backgroundColor = color(30, 30, 40);
color panelColor = color(40, 40, 50, 200);
color textColor = color(220, 220, 220);
color accentColor = color(65, 105, 225); // 皇家蓝
color rollColor = color(220, 80, 80); // 红色
color pitchColor = color(80, 220, 80); // 绿色
color yawColor = color(80, 80, 220); // 蓝色// 字体
PFont dataFont, titleFont;void setup() {size(1400, 900, P3D);frameRate(60);// 创建字体dataFont = createFont("Arial", 16);titleFont = createFont("Arial Bold", 20);// 创建默认背景bgImage = createGradientBackground();// 创建默认模型 - 更大的立方体model = createEnhancedCube();// 初始化串口serialPorts = Serial.list();if (serialPorts.length > 0) {connectSerial(serialPorts[0]);}// 初始化历史数据for (int i = 0; i < rollHistory.length; i++) {rollHistory[i] = 0;pitchHistory[i] = 0;}println("等待数据...");
}PImage createGradientBackground() {PGraphics pg = createGraphics(width, height);pg.beginDraw();pg.background(backgroundColor);// 添加渐变效果for (int i = 0; i < height; i++) {float inter = map(i, 0, height, 0, 1);color c = lerpColor(color(20, 20, 30), color(40, 40, 60), inter);pg.stroke(c);pg.line(0, i, width, i);}// 添加网格线pg.stroke(50, 100);for (int x = 0; x < width; x += 50) {pg.line(x, 0, x, height);}for (int y = 0; y < height; y += 50) {pg.line(0, y, width, y);}pg.endDraw();return pg.get();
}PShape createEnhancedCube() {// 创建一个更详细、更大的立方体模型PShape cube = createShape(GROUP);// 立方体主体 (100x100x100)PShape mainBody = createShape(BOX, 150, 150, 150);mainBody.setFill(color(180, 100, 100, 200));mainBody.setStroke(false);cube.addChild(mainBody);// 添加边缘高光PShape edges = createShape();edges.beginShape(LINES);edges.stroke(255, 150);edges.strokeWeight(2);// 立方体边缘float s = 75; // 半边长edges.vertex(-s, -s, -s); edges.vertex(s, -s, -s);edges.vertex(-s, -s, -s); edges.vertex(-s, s, -s);edges.vertex(-s, -s, -s); edges.vertex(-s, -s, s);edges.vertex(s, s, s); edges.vertex(-s, s, s);edges.vertex(s, s, s); edges.vertex(s, -s, s);edges.vertex(s, s, s); edges.vertex(s, s, -s);edges.vertex(-s, s, -s); edges.vertex(s, s, -s);edges.vertex(-s, s, -s); edges.vertex(-s, s, s);edges.vertex(s, -s, -s); edges.vertex(s, s, -s);edges.vertex(s, -s, -s); edges.vertex(s, -s, s);edges.vertex(-s, -s, s); edges.vertex(s, -s, s);edges.vertex(-s, -s, s); edges.vertex(-s, s, s);edges.endShape();cube.addChild(edges);// 添加方向指示器PShape xIndicator = createShape(SPHERE, 10);xIndicator.setFill(rollColor);xIndicator.setStroke(false);xIndicator.translate(85, 0, 0);cube.addChild(xIndicator);PShape yIndicator = createShape(SPHERE, 10);yIndicator.setFill(pitchColor);yIndicator.setStroke(false);yIndicator.translate(0, 85, 0);cube.addChild(yIndicator);PShape zIndicator = createShape(SPHERE, 10);zIndicator.setFill(yawColor);zIndicator.setStroke(false);zIndicator.translate(0, 0, 85);cube.addChild(zIndicator);return cube;
}void draw() {// 绘制背景image(bgImage, 0, 0);// 绘制3D场景 (占据左侧大部分区域)draw3DScene();// 绘制数据面板 (右侧)drawDataPanel();// 绘制波形图 (右下角)drawWaveformGraph();// 绘制连接状态drawConnectionStatus();
}void draw3DScene() {pushMatrix();// 将3D场景移到左侧中心，占据更大空间translate(width/3, height/2, 0);// 设置灯光 - 增强照明lights();directionalLight(150, 150, 150, 0, 0, -1);directionalLight(100, 100, 100, 0, 1, 0);directionalLight(80, 80, 80, 1, 0, 0);lightSpecular(255, 255, 255);shininess(20.0);// 应用旋转 - 调整Z轴方向// 注意: Processing默认Y向上，我们需要调整使Z向上rotateX(radians(0)); // 先旋转使Z轴向上rotateZ(radians(-roll));rotateX(radians(-pitch));rotateY(radians(-yaw)); // 调整yaw旋转方向// 绘制参考坐标系 (更大)drawCoordinateSystem();// 绘制模型shape(model);popMatrix();
}void drawCoordinateSystem() {float axisLength = 120;// 绘制X轴 (红色)strokeWeight(3);stroke(rollColor);line(0, 0, 0, axisLength, 0, 0);pushMatrix();translate(axisLength + 15, 0, 0);fill(rollColor);textFont(titleFont);text("Y", 0, 0);popMatrix();// 绘制Y轴 (绿色)stroke(pitchColor);line(0, 0, 0, 0, axisLength, 0);pushMatrix();translate(0, axisLength + 15, 0);fill(pitchColor);text("Z", 0, 0);popMatrix();// 绘制Z轴 (蓝色) - 现在向上stroke(yawColor);line(0, 0, 0, 0, 0, axisLength);pushMatrix();translate(0, 0, axisLength + 15);fill(yawColor);text("X", 0, 0);popMatrix();strokeWeight(1);
}void drawDataPanel() {// 绘制数据面板背景 (右侧)float panelWidth = 400;float panelX = width - panelWidth - 20;fill(panelColor);noStroke();rect(panelX, 20, panelWidth, 280, 10);// 面板标题fill(accentColor);textFont(titleFont);textAlign(LEFT, TOP);text("Sensor Data Panel", panelX + 15, 30);// 显示传感器数据textFont(dataFont);fill(textColor);String accelX = Float.isNaN(accelerometer.x) ? "N/A" : nfp(accelerometer.x, 1, 3);String accelY = Float.isNaN(accelerometer.y) ? "N/A" : nfp(accelerometer.y, 1, 3);String accelZ = Float.isNaN(accelerometer.z) ? "N/A" : nfp(accelerometer.z, 1, 3);String yawStr = Float.isNaN(yaw) ? "N/A" : nfp(yaw, 1, 1);String pitchStr = Float.isNaN(pitch) ? "N/A" : nfp(pitch, 1, 1);String rollStr = Float.isNaN(roll) ? "N/A" : nfp(roll, 1, 1);// 使用表格形式显示数据float startY = 70;float rowHeight = 30;// 表头fill(accentColor);text("parameter:", panelX + 20, startY);text("value:", panelX + 200, startY);// 加速度数据drawDataRow("accelerate X:", accelX + " g", startY + rowHeight, rollColor);drawDataRow("accelerate Y:", accelY + " g", startY + rowHeight * 2, pitchColor);drawDataRow("accelerate Z:", accelZ + " g", startY + rowHeight * 3, yawColor);// 姿态数据drawDataRow("Roll:", rollStr + "°", startY + rowHeight * 5, rollColor);drawDataRow("Pitch:", pitchStr + "°", startY + rowHeight * 6, pitchColor);drawDataRow("Yaw:", yawStr + "°", startY + rowHeight * 7, yawColor);
}void drawDataRow(String label, String value, float y, color c) {float panelX = width - 400 - 20;fill(textColor);text(label, panelX + 20, y);fill(c);text(value, panelX + 200, y);
}void drawWaveformGraph() {float graphX = width - 420;float graphY = 320;float graphWidth = 400;float graphHeight = 250;// 绘制波形图背景fill(panelColor);noStroke();rect(graphX, graphY, graphWidth, graphHeight, 10);// 标题fill(accentColor);textFont(titleFont);text("Angle Waveform Diagram", graphX + 15, graphY + 15);// 绘制网格drawWaveformGrid(graphX, graphY, graphWidth, graphHeight);// 绘制零线stroke(150, 150);float zeroY = graphY + graphHeight / 2;line(graphX, zeroY, graphX + graphWidth, zeroY);// 绘制Roll历史stroke(rollColor);drawWaveformLine(graphX, graphY, graphWidth, graphHeight, rollHistory, -90, 90);// 绘制Pitch历史stroke(pitchColor);drawWaveformLine(graphX, graphY, graphWidth, graphHeight, pitchHistory, -90, 90);// 绘制标签fill(textColor);textFont(dataFont);textAlign(LEFT);text("Roll", graphX, graphY + graphHeight + 40);fill(rollColor);rect(graphX + 40, graphY + graphHeight + 30, 15, 5);fill(textColor);text("Pitch", graphX, graphY + graphHeight + 70);fill(pitchColor);rect(graphX + 40, graphY + graphHeight + 62, 15, 5);// 绘制刻度fill(150);textAlign(CENTER);text("-90°", graphX, graphY + graphHeight + 20);text("0°", graphX + graphWidth / 2, graphY + graphHeight + 20);text("90°", graphX + graphWidth, graphY + graphHeight + 20);
}void drawWaveformGrid(float x, float y, float w, float h) {stroke(80, 100);// 水平网格线for (int i = 1; i < 4; i++) {float lineY = y + h * i / 4;line(x, lineY, x + w, lineY);}// 垂直网格线for (int i = 1; i < 5; i++) {float lineX = x + w * i / 5;line(lineX, y, lineX, y + h);}
}void drawWaveformLine(float x, float y, float w, float h, float[] history, float minVal, float maxVal) {noFill();beginShape();for (int i = 0; i < history.length; i++) {float xPos = x + map(i, 0, history.length - 1, 0, w);float yPos = y + h/2 - map(history[i], minVal, maxVal, -h/2, h/2);vertex(xPos, yPos);}endShape();
}void drawConnectionStatus() {float statusX = 20;float statusY = height - 80;// 连接状态背景fill(panelColor);noStroke();rect(statusX, statusY, 300, 60, 8);// 连接状态指示器fill(connected ? color(0, 200, 0) : color(200, 0, 0));ellipse(statusX + 20, statusY + 20, 15, 15);fill(textColor);textFont(dataFont);textAlign(LEFT, CENTER);text("UART: " + (connected ? serialPorts[selectedPort] : "No connection"), statusX + 45, statusY + 20);text("Data receiving: " + (millis() - lastDataTime < 1000 ? "Normal" : "No found"), statusX + 45, statusY + 40);// 指令提示text("Press the space bar to switch the serial port | C:Calibration | R:Reset", statusX, statusY + 70);
}void checkDataReceiving() {// 检查数据接收状态if (millis() - lastDataTime > 1000) {dataReceived = 0;}
}void serialEvent(Serial p) {try {String rawData = p.readStringUntil('\n');if (rawData == null) return;rawData = rawData.trim();if (printSerial) println("Raw: " + rawData);String[] parts = split(rawData, ' ');if (parts.length >= 4) {if (parts[0].equals("Or:")) {// 解析姿态数据: Or: yaw pitch rolltry {yaw = float(parts[1]);pitch = float(parts[2]);roll = float(parts[3]);// 检查NaN值if (Float.isNaN(yaw)) yaw = 0;if (Float.isNaN(pitch)) pitch = 0;if (Float.isNaN(roll)) roll = 0;// 更新历史数据rollHistory[historyIndex] = roll;pitchHistory[historyIndex] = pitch;historyIndex = (historyIndex + 1) % rollHistory.length;dataReceived |= 1;lastDataTime = millis();} catch (Exception e) {println("Error parsing orientation data: " + e.getMessage());}} else if (parts[0].equals("Accel:")) {// 解析加速度数据: Accel: x y ztry {float accelX = float(parts[1]);float accelY = float(parts[2]);float accelZ = float(parts[3]);// 检查NaN值if (Float.isNaN(accelX)) accelX = 0;if (Float.isNaN(accelY)) accelY = 0;if (Float.isNaN(accelZ)) accelZ = 0;accelerometer.set(accelX, accelY, accelZ);dataReceived |= 2;lastDataTime = millis();} catch (Exception e) {println("Error parsing acceleration data: " + e.getMessage());}}}} catch(Exception e) {println("Serial Error: " + e.getMessage());}
}// 全局变量用于跟踪数据接收状态
int dataReceived = 0;
long lastDataTime = 0;void connectSerial(String portName) {if (port != null) {port.stop();}try {port = new Serial(this, portName, 115200);port.bufferUntil('\n');connected = true;println("Connected to: " + portName);} catch(Exception e) {println("Connection failed: " + e.getMessage());connected = false;}
}void keyPressed() {// 切换串口if (key == ' ') {if (serialPorts.length > 0) {selectedPort = (selectedPort + 1) % serialPorts.length;connectSerial(serialPorts[selectedPort]);}}// 切换调试输出if (key == 'P' || key == 'p') {printSerial = !printSerial;println("Serial print: " + (printSerial ? "ON" : "OFF"));}// 重置视角if (key == 'R' || key == 'r') {yaw = pitch = roll = 0;println("View reset");}// 发送校准命令if (key == 'C' || key == 'c') {if (port != null) {port.write('c');println("Sent calibration command");}}
}UI设计界面：左侧3D实时渲染区域，右侧数据展示、实时波形图显示历史数据趋势
2.5 加速度计完整代码
#include <Wire.h>// ADXL345 I2C地址
#define ADXL345_ADDRESS 0x53// ADXL345寄存器地址
#define ADXL345_REG_DEVID 0x00
#define ADXL345_REG_POWER_CTL 0x2D
#define ADXL345_REG_DATA_FORMAT 0x31
#define ADXL345_REG_DATAX0 0x32
#define ADXL345_REG_BW_RATE 0x2C
#define ADXL345_REG_OFSX 0x1E
#define ADXL345_REG_OFSY 0x1F
#define ADXL345_REG_OFSZ 0x20// 高级滤波参数
#define MOVING_AVG_SIZE 7 // 移动平均窗口大小
#define KALMAN_Q 0.01 // 卡尔曼滤波过程噪声
#define KALMAN_R 0.1 // 卡尔曼滤波测量噪声
#define STABILITY_THRESHOLD 0.02 // 稳定性阈值(g)// 校准参数
float xOffset = 0, yOffset = 0, zOffset = 0;
bool calibrated = false;// 滤波结构体
typedef struct {float q; // 过程噪声协方差float r; // 测量噪声协方差float x; // 估计值float p; // 估计误差协方差float k; // 卡尔曼增益
} KalmanFilter;KalmanFilter kalmanX, kalmanY, kalmanZ;// 移动平均滤波
float movingAvgBufferX[MOVING_AVG_SIZE];
float movingAvgBufferY[MOVING_AVG_SIZE];
float movingAvgBufferZ[MOVING_AVG_SIZE];
int movingAvgIndex = 0;// 稳定性检测
unsigned long lastStableTime = 0;
bool isStable = false;// 初始化卡尔曼滤波器
void initKalmanFilter(KalmanFilter *kf, float q, float r, float initialValue) {kf->q = q;kf->r = r;kf->x = initialValue;kf->p = 1.0;kf->k = 0;
}// 卡尔曼滤波更新
float updateKalmanFilter(KalmanFilter *kf, float measurement) {// 预测kf->p = kf->p + kf->q;// 更新kf->k = kf->p / (kf->p + kf->r);kf->x = kf->x + kf->k * (measurement - kf->x);kf->p = (1 - kf->k) * kf->p;return kf->x;
}// ADXL345初始化函数
void initADXL345() {Wire.begin();// 检查设备IDbyte deviceID = readRegister(ADXL345_REG_DEVID);if (deviceID != 0xE5) {Serial.println("Error: ADXL345 not found");while(1);}// 设置数据速率和带宽为100HzwriteRegister(ADXL345_REG_BW_RATE, 0x0B);// 设置数据格式为±4g，全分辨率模式writeRegister(ADXL345_REG_DATA_FORMAT, 0x09);// 启用测量模式writeRegister(ADXL345_REG_POWER_CTL, 0x08);Serial.println("ADXL345 initialized successfully");
}// 写入寄存器函数
void writeRegister(byte reg, byte value) {Wire.beginTransmission(ADXL345_ADDRESS);Wire.write(reg);Wire.write(value);Wire.endTransmission();
}// 读取寄存器函数
byte readRegister(byte reg) {Wire.beginTransmission(ADXL345_ADDRESS);Wire.write(reg);Wire.endTransmission();Wire.requestFrom(ADXL345_ADDRESS, 1);return Wire.read();
}// 读取加速度数据
void readAcceleration(float &x, float &y, float &z) {Wire.beginTransmission(ADXL345_ADDRESS);Wire.write(ADXL345_REG_DATAX0);Wire.endTransmission();// 检查是否有数据可用if (Wire.requestFrom(ADXL345_ADDRESS, 6) == 6) {// 读取原始数据int16_t xRaw = (Wire.read() | (Wire.read() << 8));int16_t yRaw = (Wire.read() | (Wire.read() << 8));int16_t zRaw = (Wire.read() | (Wire.read() << 8));// 转换为g值 (±4g范围，全分辨率模式)x = xRaw * 0.0078;y = yRaw * 0.0078;z = zRaw * 0.0078;// 应用校准偏移if (calibrated) {x -= xOffset;y -= yOffset;z -= zOffset;}} else {// 读取失败，设置为0x = y = z = 0;Serial.println("Error: Failed to read acceleration data");}
}// 应用移动平均滤波
void applyMovingAverageFilter(float &x, float &y, float &z) {// 更新缓冲区movingAvgBufferX[movingAvgIndex] = x;movingAvgBufferY[movingAvgIndex] = y;movingAvgBufferZ[movingAvgIndex] = z;movingAvgIndex = (movingAvgIndex + 1) % MOVING_AVG_SIZE;// 计算平均值float xSum = 0, ySum = 0, zSum = 0;for (int i = 0; i < MOVING_AVG_SIZE; i++) {xSum += movingAvgBufferX[i];ySum += movingAvgBufferY[i];zSum += movingAvgBufferZ[i];}x = xSum / MOVING_AVG_SIZE;y = ySum / MOVING_AVG_SIZE;z = zSum / MOVING_AVG_SIZE;
}// 应用卡尔曼滤波
void applyKalmanFilter(float &x, float &y, float &z) {x = updateKalmanFilter(&kalmanX, x);y = updateKalmanFilter(&kalmanY, y);z = updateKalmanFilter(&kalmanZ, z);
}// 检测稳定性
bool checkStability(float x, float y, float z, float prevX, float prevY, float prevZ) {float deltaX = abs(x - prevX);float deltaY = abs(y - prevY);float deltaZ = abs(z - prevZ);return (deltaX < STABILITY_THRESHOLD && deltaY < STABILITY_THRESHOLD && deltaZ < STABILITY_THRESHOLD);
}// 计算Roll和Pitch角度
void calculateAngles(float x, float y, float z, float &roll, float &pitch) {// 检查数据有效性，避免除零错误和NaNif (isnan(x) || isnan(y) || isnan(z)) {roll = pitch = 0;return;}// 使用改进的公式计算Roll和Pitchfloat denominator = sqrt(x*x + z*z);if (denominator < 0.001) denominator = 0.001; // 避免除零错误roll = atan2(y, denominator) * 180.0 / PI;denominator = sqrt(y*y + z*z);if (denominator < 0.001) denominator = 0.001; // 避免除零错误pitch = atan2(-x, denominator) * 180.0 / PI;
}// 自动校准函数
void autoCalibrate() {Serial.println("Start automatic calibration...");Serial.println("Please ensure that the sensor is placed horizontally and stationary");// 等待2秒让用户放置传感器delay(2000);float xSum = 0, ySum = 0, zSum = 0;const int samples = 200;int validSamples = 0;// 采集多个样本求平均值for (int i = 0; i < samples; i++) {float x, y, z;readAcceleration(x, y, z);// 检查数据有效性if (!isnan(x) && !isnan(y) && !isnan(z)) {xSum += x;ySum += y;zSum += z;validSamples++;}delay(10); // 每10ms采集一次}if (validSamples > 0) {// 计算偏移量xOffset = xSum / validSamples;yOffset = ySum / validSamples;zOffset = zSum / validSamples - 1.0; // 减去重力加速度// 设置硬件偏移寄存器writeRegister(ADXL345_REG_OFSX, (byte)(xOffset / 0.0156));writeRegister(ADXL345_REG_OFSY, (byte)(yOffset / 0.0156));writeRegister(ADXL345_REG_OFSZ, (byte)(zOffset / 0.0156));calibrated = true;Serial.println("Automatic calibration completed!");Serial.print("XOffset: "); Serial.print(xOffset, 6);Serial.print(" g, YOffset: "); Serial.print(yOffset, 6);Serial.print(" g, ZOffset: "); Serial.print(zOffset, 6);Serial.println(" g");} else {Serial.println("Calibration failure: No valid data can be obtained");}
}// 处理串口命令
void processSerialCommands() {if (Serial.available()) {char command = Serial.read();if (command == 'c' || command == 'C') {autoCalibrate();} else if (command == 'r' || command == 'R') {// 重置校准数据calibrated = false;xOffset = 0;yOffset = 0;zOffset = 0;writeRegister(ADXL345_REG_OFSX, 0);writeRegister(ADXL345_REG_OFSY, 0);writeRegister(ADXL345_REG_OFSZ, 0);Serial.println("The calibration data has been reset");} else if (command == 's' || command == 'S') {// 显示状态Serial.print("校准状态 : ");Serial.println(calibrated ? "Calibrated Resistance" : "Uncalibrated");Serial.print("XOffset: "); Serial.println(xOffset, 6);Serial.print("YOffset: "); Serial.println(yOffset, 6);Serial.print("ZOffset: "); Serial.println(zOffset, 6);}}
}void setup() {Serial.begin(115200);// 初始化I2CWire.begin();// 初始化滤波缓冲区for (int i = 0; i < MOVING_AVG_SIZE; i++) {movingAvgBufferX[i] = 0;movingAvgBufferY[i] = 0;movingAvgBufferZ[i] = 0;}// 初始化卡尔曼滤波器initKalmanFilter(&kalmanX, KALMAN_Q, KALMAN_R, 0);initKalmanFilter(&kalmanY, KALMAN_Q, KALMAN_R, 0);initKalmanFilter(&kalmanZ, KALMAN_Q, KALMAN_R, 1.0); // Z轴初始值为1ginitADXL345();Serial.println("The ADXL345 attitude sensor is ready");Serial.println("Available commands:");Serial.println("c - START CALIBRATION");Serial.println("r - RESET the Calibration Data");Serial.println("s - DISPLAY STATUS");Serial.println("DATA FORMAT: Or: yaw pitch roll");Serial.println(" Accel: x y z");
}void loop() {// 处理串口命令processSerialCommands();static float prevX = 0, prevY = 0, prevZ = 0;float x, y, z;// 读取加速度数据readAcceleration(x, y, z);// 检查数据有效性if (isnan(x) || isnan(y) || isnan(z)) {Serial.println("Warning: Invalid acceleration data");delay(100);return;}// 应用移动平均滤波applyMovingAverageFilter(x, y, z);// 应用卡尔曼滤波applyKalmanFilter(x, y, z);// 检测稳定性isStable = checkStability(x, y, z, prevX, prevY, prevZ);if (isStable) {lastStableTime = millis();}// 计算Roll和Pitch角度float roll, pitch;calculateAngles(x, y, z, roll, pitch);// 检查角度数据有效性if (isnan(roll) || isnan(pitch)) {Serial.println("Warning: Invalid angle data");roll = pitch = 0;}// 输出数据到ProcessingSerial.print("Or: ");Serial.print(0); // Yaw始终为0Serial.print(" ");Serial.print(pitch);Serial.print(" ");Serial.println(roll);Serial.print("Accel: ");Serial.print(x);Serial.print(" ");Serial.print(y);Serial.print(" ");Serial.println(z);prevX = x;prevY = y;prevZ = z;delay(20); // 50Hz更新率
}
三、校准过程及展示
3.1 校准过程
（1）将设备水平放置在稳定表面
打开操作窗口，按下键盘'C'键发送校准命令
（2）等待校准完成提示和偏移量
Sent calibration command
Raw: Start automatic calibration...
Raw: Please ensure that the sensor is placed horizontally and stationary
Raw: Automatic calibration completed!
Raw: XOffset: 0.438828 g, YOffset: 0.470731 g, ZOffset: 1.747395 g
（3）查看串口输出校准后的加速度计数值
3.2 上位机界面展示
Processing上位机端代码运行后：
左侧显示三维立方体效果、右侧展示数据面板
3.3 视频演示
ADXL345加速度计进行Processing上位机展示
倾斜改变ADXL345传感器的不同方向实时观察上位机3D模型姿态变化
四、ADXL345寄存器工作原理
4.1 DATA_FORMAT寄存器(0x31)
控制数据的表示寄存器0x32到0x37，同时设置分辨率
4.2 BW_RATE寄存器(0x2C)
输出数据速率为200HZ(BW_RATE寄存器中的LOW_POWER位（D4) = 0，速率位(D3:D0) = 0xB）
4.3 POWER_CTL寄存器(0x2D)
设置POWER_CTL寄存器为0x08测量模式
4.4 加速度计I2C通信
若将 CS 引脚接至 V DD I/O，ADXL345 便会进入 I2C 模式，此时仅需简单的 2 线式连接即可。
当 ALT ADDRESS 引脚为高电平时，器件的 7 位 I2C 地址为 0x1D，后续紧跟 R/W 位，对应写入地址为 0x3A，读取地址为 0x3B。若把 ALT ADDRESS 引脚（即引脚 12）接地，则可选用备用 I2C 地址 0x53（后续同样紧跟 R/W 位），相应的写入地址为 0xA6，读取地址为 0xA7。
五、常见问题解答
Q1: 传感器数据出现NaN值怎么办？
A: 检查硬件连接是否稳定，确保I2C通信正常。代码中已添加NaN检测和保护机制。
Q2: 如何提高角度计算精度？
A: 可以进行多次校准，确保校准时设备完全水平静止。也可以调整滤波参数优化性能。
Q3: 为什么三维立方体显示不全或位置不正确？
A: 需要调整Processing中的坐标系变换参数，确保模型在视图中心，并正确设置旋转顺序。
项目资源：
上位机平台下载：Processing官网
加速度计技术手册：ADXL345 (Rev. G)
结论： 通过精心设计的滤波算法和自动校准机制，有效解决了MEMS加速度计的噪声和漂移问题。
