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目录

1. 电感式传感器技术概述

主要优势：

2. C#集成电感式传感器方案

2.1 硬件接口层

2.2 SPI/I2C通信基础类

3. 德州仪器(TI) LDC系列集成

3.1 LDC1612/LDC1614 驱动程序

4. 位置传感应用程序

4.1 主控制界面

5. 校准工具

6. 高级功能 - 多传感器阵列

7. 部署和硬件连接

7.1 硬件连接示意图

7.2 系统要求

8. 性能优化建议

总结

电感式传感器AFE（模拟前端）和LDC（电感数字转换器）确实是高性能非接触式位置传感技术。让我为您详细介绍这些技术，并展示如何在C#中集成这类传感器。

1.电感式传感器技术概述

主要优势：

• ✅ 不受直流磁场干扰

• ✅ 非接触式测量，零机械磨损

• ✅ 亚微米级精度（可达0.01μm）

• ✅ 耐恶劣环境（油污、灰尘、湿度）

• ✅ 低功耗设计

2.C#集成电感式传感器方案

2.1 硬件接口层

public interface IInductiveSensor { /// <summary> /// 传感器配置参数 /// </summary> public class SensorConfig { public string SensorType { get; set; } = "LDC1612"; public int ChannelCount { get; set; } = 1; public double Frequency { get; set; } = 1.0; // MHz public double Resolution { get; set; } = 0.01; // μm public double MeasurementRange { get; set; } = 10.0; // mm } /// <summary> /// 位置数据 /// </summary> public class PositionData { public DateTime Timestamp { get; set; } public double Position { get; set; } // μm public double Temperature { get; set; } // °C public int Status { get; set; } // 状态码 public double SignalQuality { get; set; } // 0-1 } }

2.2 SPI/I2C通信基础类

public abstract class InductiveSensorBase : IInductiveSensor { protected ICommunicationInterface _communication; protected SensorConfig _config; protected CancellationTokenSource _cancellationTokenSource; protected bool _isMeasuring = false; // SPI通信示例 public class SpiInterface : ICommunicationInterface { private SpiDevice _spiDevice; public SpiInterface(string spiBus, int chipSelectLine) { var settings = new SpiConnectionSettings(chipSelectLine) { Mode = SpiMode.Mode0, ClockFrequency = 1000000, // 1MHz DataBitLength = 8 }; _spiDevice = SpiDevice.Create(settings); } public byte[] ReadRegister(byte register, int length) { byte[] writeBuffer = new byte[] { register }; byte[] readBuffer = new byte[length]; _spiDevice.TransferFullDuplex(writeBuffer, readBuffer); return readBuffer; } public void WriteRegister(byte register, byte[] data) { byte[] buffer = new byte[data.Length + 1]; buffer[0] = register; Array.Copy(data, 0, buffer, 1, data.Length); _spiDevice.Write(buffer); } public void Dispose() { _spiDevice?.Dispose(); } } // I2C通信示例 public class I2cInterface : ICommunicationInterface { private I2cDevice _i2cDevice; private byte _deviceAddress; public I2cInterface(string i2cBus, byte deviceAddress) { var settings = new I2cConnectionSettings(deviceAddress); _i2cDevice = I2cDevice.Create(i2cBus, settings); _deviceAddress = deviceAddress; } public byte[] ReadRegister(byte register, int length) { _i2cDevice.WriteByte(register); byte[] buffer = new byte[length]; _i2cDevice.Read(buffer); return buffer; } public void WriteRegister(byte register, byte[] data) { byte[] buffer = new byte[data.Length + 1]; buffer[0] = register; Array.Copy(data, 0, buffer, 1, data.Length); _i2cDevice.Write(buffer); } public void Dispose() { _i2cDevice?.Dispose(); } } }

3.德州仪器(TI) LDC系列集成

3.1 LDC1612/LDC1614 驱动程序

public class LDC1612Sensor : InductiveSensorBase { // 寄存器地址 (根据LDC1612数据手册) private const byte REG_DATA_MSB = 0x00; private const byte REG_DATA_LSB = 0x01; private const byte REG_RCOUNT = 0x08; private const byte REG_OFFSET = 0x09; private const byte REG_SETTLECOUNT = 0x10; private const byte REG_CLOCK_DIVIDERS = 0x11; private const byte REG_STATUS = 0x18; private const byte REG_CONFIG = 0x1A; private const byte REG_MUX_CONFIG = 0x1B; public LDC1612Sensor(ICommunicationInterface comm, SensorConfig config) : base(comm, config) { InitializeSensor(); } private void InitializeSensor() { // 1. 重置传感器 ResetSensor(); // 2. 配置参考频率计数 // RCOUNT = fREF / (fSENSOR * 4) - 1 double referenceFreq = 40.0; // MHz double sensorFreq = _config.Frequency; ushort rcount = (ushort)((referenceFreq / (sensorFreq * 4)) - 1); WriteRegister(REG_RCOUNT, BitConverter.GetBytes(rcount)); // 3. 配置建立时间 byte settleCount = 0x0F; // 默认建立时间 WriteRegister(REG_SETTLECOUNT, new byte[] { settleCount }); // 4. 配置时钟分频器 byte clockDividers = 0x10; // fSENSOR = fIN / 1 WriteRegister(REG_CLOCK_DIVIDERS, new byte[] { clockDividers }); // 5. 配置MUX byte muxConfig = 0x02; // 启用通道0 WriteRegister(REG_MUX_CONFIG, new byte[] { muxConfig }); // 6. 配置主寄存器 byte[] configValue = new byte[] { 0x10, // 连续转换模式，自动扫描 0x00 // 默认设置 }; WriteRegister(REG_CONFIG, configValue); } private void ResetSensor() { // 发送复位命令 byte[] resetCmd = new byte[] { 0x80 }; WriteRegister(REG_CONFIG, resetCmd); Thread.Sleep(10); // 等待复位完成 } public double ReadInductance() { // 读取16位电感数据 byte[] dataMsb = ReadRegister(REG_DATA_MSB, 1); byte[] dataLsb = ReadRegister(REG_DATA_LSB, 1); ushort rawValue = (ushort)((dataMsb[0] << 8) | dataLsb[0]); // 转换为电感值 (公式来自数据手册) double inductance = CalculateInductance(rawValue); return inductance; } public PositionData ReadPosition() { double inductance = ReadInductance(); // 将电感值转换为位置 (需要校准曲线) double position = ConvertInductanceToPosition(inductance); // 读取传感器状态 byte[] status = ReadRegister(REG_STATUS, 1); return new PositionData { Timestamp = DateTime.Now, Position = position, Temperature = ReadTemperature(), Status = status[0], SignalQuality = CalculateSignalQuality(inductance) }; } private double CalculateInductance(ushort rawValue) { // L = (1 / (2πf)²) * (1 / C) * (DATA / 2^16)² double f = _config.Frequency * 1e6; // 转换为Hz double c = 100e-12; // 参考电容 100pF (根据实际电路) double normalizedValue = rawValue / 65536.0; // 16位分辨率 double inductance = 1.0 / (Math.Pow(2 * Math.PI * f, 2) * c * normalizedValue * normalizedValue); return inductance * 1e6; // 转换为μH } private double ConvertInductanceToPosition(double inductance) { // 实际应用中需要通过校准获得转换关系 // 这里使用简化线性模型 double baseInductance = 10.0; // μH (基准值) double sensitivity = 0.1; // μH/μm double position = (inductance - baseInductance) / sensitivity; return Math.Round(position, 3); // 保留3位小数 } private double ReadTemperature() { // LDC1612没有温度传感器，可外接或估算 // 这里返回环境温度估算值 return 25.0; } private double CalculateSignalQuality(double inductance) { // 计算信号质量 (0-1) // 基于电感值的稳定性和噪声 double minInductance = 5.0; double maxInductance = 15.0; if (inductance < minInductance || inductance > maxInductance) return 0.0; double normalized = (inductance - minInductance) / (maxInductance - minInductance); return Math.Max(0.0, Math.Min(1.0, normalized)); } public async Task StartContinuousMeasurement( Action<PositionData> onDataReceived, int intervalMs = 10) { _isMeasuring = true; _cancellationTokenSource = new CancellationTokenSource(); await Task.Run(async () => { while (_isMeasuring && !_cancellationTokenSource.Token.IsCancellationRequested) { try { var positionData = ReadPosition(); onDataReceived?.Invoke(positionData); await Task.Delay(intervalMs, _cancellationTokenSource.Token); } catch (OperationCanceledException) { break; } catch (Exception ex) { Console.WriteLine($"测量错误: {ex.Message}"); } } }); } public void StopMeasurement() { _isMeasuring = false; _cancellationTokenSource?.Cancel(); } }

4.位置传感应用程序

4.1 主控制界面

public partial class InductiveSensorForm : Form { private LDC1612Sensor _sensor; private List<PositionData> _measurementData; private bool _isMeasuring = false; // UI组件 private Chart positionChart; private TextBox txtPosition; private TextBox txtResolution; private Button btnStart; private Button btnStop; private Button btnCalibrate; private DataGridView dataGridView; public InductiveSensorForm() { InitializeComponent(); InitializeSensor(); InitializeChart(); } private void InitializeSensor() { // 根据实际硬件配置 var config = new SensorConfig { SensorType = "LDC1612", ChannelCount = 1, Frequency = 1.0, // 1MHz Resolution = 0.01, // 10nm MeasurementRange = 10.0 // 10mm }; // 使用SPI通信 var spiInterface = new SpiInterface("SPI0", 0); _sensor = new LDC1612Sensor(spiInterface, config); _measurementData = new List<PositionData>(); } private void InitializeChart() { positionChart = new Chart { Dock = DockStyle.Fill, Location = new Point(0, 0), Size = new Size(800, 400) }; var chartArea = new ChartArea("MainArea"); chartArea.AxisX.Title = "时间 (s)"; chartArea.AxisY.Title = "位置 (μm)"; chartArea.AxisY.Minimum = 0; chartArea.AxisY.Maximum = 10000; // 10mm positionChart.ChartAreas.Add(chartArea); var series = new Series("位置数据") { ChartType = SeriesChartType.Line, Color = Color.Blue, BorderWidth = 2 }; positionChart.Series.Add(series); this.Controls.Add(positionChart); } private void btnStart_Click(object sender, EventArgs e) { if (!_isMeasuring) { _isMeasuring = true; btnStart.Enabled = false; btnStop.Enabled = true; // 清空历史数据 _measurementData.Clear(); positionChart.Series["位置数据"].Points.Clear(); // 开始连续测量 _sensor.StartContinuousMeasurement(OnSensorDataReceived, 10); } } private void btnStop_Click(object sender, EventArgs e) { if (_isMeasuring) { _isMeasuring = false; _sensor.StopMeasurement(); btnStart.Enabled = true; btnStop.Enabled = false; SaveMeasurementData(); } } private void OnSensorDataReceived(PositionData data) { // 跨线程更新UI if (this.InvokeRequired) { this.Invoke(new Action<PositionData>(OnSensorDataReceived), data); return; } // 添加数据到列表 _measurementData.Add(data); // 更新文本框 txtPosition.Text = $"{data.Position:F3} μm"; txtResolution.Text = $"{_sensor.Config.Resolution:F3} μm"; // 更新图表 var series = positionChart.Series["位置数据"]; double timeSeconds = (data.Timestamp - _measurementData[0].Timestamp).TotalSeconds; series.Points.AddXY(timeSeconds, data.Position); // 保持最近1000个数据点 if (series.Points.Count > 1000) { series.Points.RemoveAt(0); } // 更新数据表格 UpdateDataGridView(data); // 检查报警条件 CheckAlarmConditions(data); } private void UpdateDataGridView(PositionData data) { if (dataGridView.InvokeRequired) { dataGridView.Invoke(new Action<PositionData>(UpdateDataGridView), data); return; } // 添加新行 dataGridView.Rows.Add( data.Timestamp.ToString("HH:mm:ss.fff"), data.Position.ToString("F3"), data.Temperature.ToString("F1"), data.SignalQuality.ToString("P1"), GetStatusText(data.Status) ); // 保持最多100行 if (dataGridView.Rows.Count > 100) { dataGridView.Rows.RemoveAt(0); } // 自动滚动到最后一行 dataGridView.FirstDisplayedScrollingRowIndex = dataGridView.RowCount - 1; } private string GetStatusText(int status) { return status == 0 ? "正常" : "警告"; } private void CheckAlarmConditions(PositionData data) { // 位置超限报警 double upperLimit = 8000; // 8mm double lowerLimit = 2000; // 2mm if (data.Position > upperLimit || data.Position < lowerLimit) { ShowAlarm("位置超限", $"当前位置: {data.Position:F3} μm"); } // 信号质量报警 if (data.SignalQuality < 0.3) { ShowAlarm("信号质量差", $"信号质量: {data.SignalQuality:P1}"); } } private void ShowAlarm(string title, string message) { // 高优先级报警使用红色 var alarmForm = new Form { Text = $"⚠ {title}", Size = new Size(300, 150), StartPosition = FormStartPosition.CenterScreen, BackColor = Color.LightCoral }; var label = new Label { Text = message, Dock = DockStyle.Fill, TextAlign = ContentAlignment.MiddleCenter, Font = new Font("Arial", 12, FontStyle.Bold) }; alarmForm.Controls.Add(label); alarmForm.ShowDialog(); } private void SaveMeasurementData() { if (_measurementData.Count == 0) return; using (var saveDialog = new SaveFileDialog()) { saveDialog.Filter = "CSV文件 (*.csv)|*.csv|文本文件 (*.txt)|*.txt"; saveDialog.FileName = $"位置测量_{DateTime.Now:yyyyMMdd_HHmmss}"; if (saveDialog.ShowDialog() == DialogResult.OK) { using (var writer = new StreamWriter(saveDialog.FileName)) { // 写入标题 writer.WriteLine("时间戳,位置(μm),温度(°C),信号质量,状态"); // 写入数据 foreach (var data in _measurementData) { writer.WriteLine( $"{data.Timestamp:yyyy-MM-dd HH:mm:ss.fff}," + $"{data.Position:F3}," + $"{data.Temperature:F1}," + $"{data.SignalQuality:F3}," + $"{data.Status}"); } } MessageBox.Show($"数据已保存到: {saveDialog.FileName}", "保存成功", MessageBoxButtons.OK, MessageBoxIcon.Information); } } } private void btnCalibrate_Click(object sender, EventArgs e) { var calibrateForm = new CalibrationForm(_sensor); calibrateForm.ShowDialog(); if (calibrateForm.CalibrationSuccess) { MessageBox.Show("校准完成", "信息", MessageBoxButtons.OK, MessageBoxIcon.Information); } } }

5.校准工具

public class CalibrationForm : Form { private LDC1612Sensor _sensor; private List<CalibrationPoint> _calibrationPoints; private bool _calibrationSuccess = false; public bool CalibrationSuccess => _calibrationSuccess; public class CalibrationPoint { public double KnownPosition { get; set; } // μm public double MeasuredInductance { get; set; } // μH public DateTime Timestamp { get; set; } } public CalibrationForm(LDC1612Sensor sensor) { _sensor = sensor; _calibrationPoints = new List<CalibrationPoint>(); InitializeUI(); } private void InitializeUI() { this.Text = "传感器校准"; this.Size = new Size(400, 300); var lblInstruction = new Label { Text = "1. 将传感器移动到已知位置\n2. 点击'记录点'\n3. 重复至少3个不同位置\n4. 点击'计算校准曲线'", Location = new Point(20, 20), Size = new Size(350, 80) }; var txtKnownPosition = new TextBox { Location = new Point(20, 120), Size = new Size(150, 25), Text = "0" }; var btnRecordPoint = new Button { Text = "记录校准点", Location = new Point(180, 120), Size = new Size(150, 25) }; var btnCalculate = new Button { Text = "计算校准曲线", Location = new Point(20, 160), Size = new Size(310, 30), Enabled = false }; var dataGridView = new DataGridView { Location = new Point(20, 200), Size = new Size(350, 200), AutoSizeColumnsMode = DataGridViewAutoSizeColumnsMode.Fill }; dataGridView.Columns.Add("Position", "已知位置 (μm)"); dataGridView.Columns.Add("Inductance", "测量电感 (μH)"); btnRecordPoint.Click += (s, e) => { if (double.TryParse(txtKnownPosition.Text, out double knownPosition)) { double inductance = _sensor.ReadInductance(); var point = new CalibrationPoint { KnownPosition = knownPosition, MeasuredInductance = inductance, Timestamp = DateTime.Now }; _calibrationPoints.Add(point); dataGridView.Rows.Add(knownPosition, inductance); // 至少有3个点才能计算 btnCalculate.Enabled = _calibrationPoints.Count >= 3; } }; btnCalculate.Click += (s, e) => { if (CalculateCalibrationCurve()) { _calibrationSuccess = true; MessageBox.Show("校准成功完成", "成功", MessageBoxButtons.OK, MessageBoxIcon.Information); this.Close(); } }; this.Controls.AddRange(new Control[] { lblInstruction, txtKnownPosition, btnRecordPoint, btnCalculate, dataGridView }); } private bool CalculateCalibrationCurve() { if (_calibrationPoints.Count < 3) { MessageBox.Show("需要至少3个校准点", "错误", MessageBoxButtons.OK, MessageBoxIcon.Error); return false; } // 使用最小二乘法拟合线性关系 double sumX = 0, sumY = 0, sumXY = 0, sumX2 = 0; int n = _calibrationPoints.Count; foreach (var point in _calibrationPoints) { double x = point.MeasuredInductance; double y = point.KnownPosition; sumX += x; sumY += y; sumXY += x * y; sumX2 += x * x; } // 计算斜率和截距 double slope = (n * sumXY - sumX * sumY) / (n * sumX2 - sumX * sumX); double intercept = (sumY - slope * sumX) / n; // 保存校准参数到配置文件 SaveCalibrationParameters(slope, intercept); return true; } private void SaveCalibrationParameters(double slope, double intercept) { var calibrationData = new { SensorType = _sensor.Config.SensorType, CalibrationDate = DateTime.Now, Slope = slope, Intercept = intercept, CalibrationPoints = _calibrationPoints, CorrelationCoefficient = CalculateCorrelationCoefficient() }; string json = JsonConvert.SerializeObject(calibrationData, Formatting.Indented); string filePath = Path.Combine( AppDomain.CurrentDomain.BaseDirectory, "Calibration", $"calibration_{DateTime.Now:yyyyMMdd_HHmmss}.json"); Directory.CreateDirectory(Path.GetDirectoryName(filePath)); File.WriteAllText(filePath, json); } private double CalculateCorrelationCoefficient() { // 计算相关系数R² double meanX = _calibrationPoints.Average(p => p.MeasuredInductance); double meanY = _calibrationPoints.Average(p => p.KnownPosition); double sumNum = 0, sumDenX = 0, sumDenY = 0; foreach (var point in _calibrationPoints) { double diffX = point.MeasuredInductance - meanX; double diffY = point.KnownPosition - meanY; sumNum += diffX * diffY; sumDenX += diffX * diffX; sumDenY += diffY * diffY; } return sumNum / Math.Sqrt(sumDenX * sumDenY); } }

6.高级功能 - 多传感器阵列

public class MultiSensorArray { private List<LDC1612Sensor> _sensors; private bool _isSynchronized = false; public MultiSensorArray(int sensorCount, ICommunicationInterface[] interfaces) { _sensors = new List<LDC1612Sensor>(); for (int i = 0; i < sensorCount; i++) { var config = new SensorConfig { SensorType = "LDC1612", ChannelCount = 1, Frequency = 1.0 + i * 0.1, // 不同频率避免干扰 Resolution = 0.01, MeasurementRange = 10.0 }; _sensors.Add(new LDC1612Sensor(interfaces[i], config)); } } public List<PositionData> ReadAllSensors() { var results = new List<PositionData>(); // 并行读取所有传感器 Parallel.ForEach(_sensors, sensor => { var data = sensor.ReadPosition(); lock (results) { results.Add(data); } }); return results.OrderBy(d => d.Timestamp).ToList(); } public async Task StartSynchronizedMeasurement( Action<List<PositionData>> onDataReceived, int intervalMs = 10) { _isSynchronized = true; while (_isSynchronized) { var startTime = DateTime.Now; var allData = ReadAllSensors(); onDataReceived?.Invoke(allData); // 计算平面度/平整度 if (allData.Count >= 3) { CalculateFlatness(allData); } // 保持精确的采样间隔 var elapsed = (DateTime.Now - startTime).TotalMilliseconds; if (elapsed < intervalMs) { await Task.Delay((int)(intervalMs - elapsed)); } } } private void CalculateFlatness(List<PositionData> sensorData) { // 计算平面度 (最大偏差) double[] positions = sensorData.Select(d => d.Position).ToArray(); double max = positions.Max(); double min = positions.Min(); double flatness = max - min; // 计算倾斜角度 if (sensorData.Count >= 2) { double distanceBetweenSensors = 50.0; // 传感器间距 mm double angle = Math.Atan2(positions[1] - positions[0], distanceBetweenSensors) * 180 / Math.PI; Console.WriteLine($"平面度: {flatness:F3} μm, 倾斜角度: {angle:F2}°"); } } public void StopSynchronizedMeasurement() { _isSynchronized = false; } }

7.部署和硬件连接

7.1 硬件连接示意图

┌─────────────────────┐ ┌─────────────────────┐ │ 电感线圈 │ │ C#应用程序 │ │ ┌─────────────┐ │ │ ┌─────────────┐ │ │ │ 目标物体 │ │ │ │ 实时显示 │ │ │ │ │◄──┼─────┼───┤ 位置数据 │ │ │ └─────────────┘ │ │ └─────────────┘ │ │ │ │ │ │ │ │ 非接触测量 │ │ 数据记录和分析 │ └─────────┼───────────┘ └─────────┼───────────┘ │ │ ▼ ▼ ┌─────────────────────┐ ┌─────────────────────┐ │ LDC1612传感器 │ │ SPI/I2C接口 │ │ ┌─────────────┐ │ │ ┌─────────────┐ │ │ │ AFE + LDC │ │ │ │ USB转SPI │ │ │ │ ├───┼─────┼───► │ │ │ └─────────────┘ │ │ └─────────────┘ │ │ │ │ │ │ │ │ 参考电容 │ │ PC/嵌入式系统 │ └─────────────────────┘ └─────────────────────┘

7.2 系统要求

软件要求： - .NET Framework 4.8+ 或 .NET Core 3.1+ - Visual Studio 2019+ - SPI/I2C驱动库 硬件要求： - LDC1612/LDC1614评估板 - 电感线圈 (5-30μH) - 参考电容 (100pF) - SPI/I2C接口适配器

8.性能优化建议

public class OptimizedSensorController { // 使用环形缓冲区减少内存分配 private CircularBuffer<PositionData> _dataBuffer; private object _lockObject = new object(); // 使用高性能定时器 private System.Threading.Timer _measurementTimer; private long _measurementCount = 0; public OptimizedSensorController(int bufferSize = 10000) { _dataBuffer = new CircularBuffer<PositionData>(bufferSize); } public void StartHighSpeedMeasurement(int intervalUs = 100) { // 使用高精度定时器 _measurementTimer = new System.Threading.Timer( MeasurementCallback, null, 0, intervalUs / 1000); // 转换为毫秒 } private void MeasurementCallback(object state) { var data = ReadSensorData(); lock (_lockObject) { _dataBuffer.PushBack(data); _measurementCount++; } // 实时处理 ProcessDataInRealTime(data); } private void ProcessDataInRealTime(PositionData data) { // FFT分析 if (_dataBuffer.Count >= 1024) { PerformFFTAnalysis(); } // 移动平均滤波 double filtered = ApplyMovingAverage(data.Position); // 异常检测 DetectAnomalies(data); } private void PerformFFTAnalysis() { // 对位置数据进行频谱分析 double[] samples = _dataBuffer.GetRecentSamples(1024); // 使用Math.NET Numerics进行FFT // var spectrum = Fourier.Forward(samples); // 检测振动频率 // ... } private double ApplyMovingAverage(double newValue) { // 滑动窗口平均 const int windowSize = 10; double[] window = new double[windowSize]; // 实现移动平均逻辑 return newValue; // 简化返回 } private void DetectAnomalies(PositionData data) { // 使用统计方法检测异常 double mean = CalculateMean(); double stdDev = CalculateStandardDeviation(); if (Math.Abs(data.Position - mean) > 3 * stdDev) { LogAnomaly(data); } } }

总结

这个C#实现方案提供了：

1. 完整的硬件抽象层：支持SPI/I2C通信

2. 高精度测量：亚微米级位置检测

3. 实时数据处理：图表显示、数据记录、报警

4. 校准工具：确保测量精度

5. 多传感器支持：阵列测量和同步

6. 性能优化：环形缓冲区、实时处理

电感式传感器AFE和LDC转换器的非接触、高精度特性使其非常适合：

• 精密机械定位

• 振动监测

• 厚度测量

• 平面度检测

• 工业自动化控制