public string PerformMeasure(MeasureType type, double[] data)
{
double value;
switch (type)
{
case MeasureType.DC:
value = ArrayCalculation.Average(data);
break;
case MeasureType.RMS:
value = ArrayCalculation.RMS(data);
break;
case MeasureType.PeakAmp:
case MeasureType.PeakFreq:
double dt = 1.0 / _oscilloscopeGlobalInfo.SampleRate;
double peakFreq, peakAmp;
Spectrum.PeakSpectrumAnalysis(data, dt, out peakFreq, out peakAmp);
value = (type == MeasureType.PeakFreq) ? peakFreq : peakAmp;
break;
default:
return(Constants.NotAvailable);
break;
}
return(Utility.GetShowValue(value));
}
public override void Fetch(ref double[,] fetchData)
{
double[,] data = new double[_samplesToRead, simChList.Count];
List <double[]> Data = new List <double[]>();
for (int i = 0; i < simChList.Count; i++)
{
double[] simData = new double[_samplesToRead];
double[] noise = new double[_samplesToRead];
Generation.UniformWhiteNoise(ref noise, 0.03);
if (i == 0)
{
Generation.SquareWave(ref simData, 1, 50, 10);
}
else
{
Generation.SineWave(ref simData, 1, 0, 10);
}
ArrayCalculation.Add(simData, noise, ref simData);
Data.Add(simData);
}
for (int i = 0; i < Data.Count; i++)
{
ArrayManipulation.ReplaceArraySubset(Data.ElementAt(i), ref data, i, ArrayManipulation.IndexType.column);
}
fetchData = data;
}
public string PerformMeasure(MeasureType type, double[] data)
{
string value;
switch (type)
{
case MeasureType.DC:
value = ArrayCalculation.Average(data).ToString();
break;
case MeasureType.RMS:
value = ArrayCalculation.RMS(data).ToString();
break;
case MeasureType.PeakAmp:
case MeasureType.PeakFreq:
double dt = 1.0 / _oscilloscopeGlobalInfo.SampleRate;
double peakFreq, peakAmp;
PeakSpectrum.PeakSpectrumAnalysis(data, dt, out peakFreq, out peakAmp);
value = (type == MeasureType.PeakFreq) ? peakFreq.ToString() : peakAmp.ToString();
break;
default:
value = "";
break;
}
return(value);
}
private void FetchLoop()
{
while (isRunning)
{
if (device.SelectedChannels.Length != 0)
{
if (device.ReadyToFetch)
{
device.Fetch(ref readData);
ArrayCalculation.MultiplyScale(ref readData, Double.Parse(_attenuation));
//isExecCompleted = true;
isRunning = false;
dataAvailable = true;
}
}
Thread.Sleep(1);
}
}
/// <summary>
/// 计算出信号的AC成分以及DC成分(单位：RMS)
/// </summary>
/// <param name="signalData">信号来源</param>
/// <param name="acTerm">AC成分</param>
/// <param name="dcTerm">DC成分</param>
public static void EstimateACDC(double[] signalData, out double acTerm, out double dcTerm)
{
double[] inputData = new double[signalData.Length];
double[] acData = new double[signalData.Length];
double[] hann_weighting = Window.Hann(signalData.Length);
double coeff_cg = 0.5; // cg=0.5, compensation for Hanning windowing
double coeff_enbw = 1.5; // enbw=1.5, compensation for Hanning windowing
//DC term extraction
//Hanning windowing the signal
ArrayCalculation.Multiply(hann_weighting, signalData, ref inputData);
//Get the mean value and compensated by the cg coeff
dcTerm = Statistics.Mean(inputData) / coeff_cg;
//AC term extraction
Buffer.BlockCopy(signalData, 0, inputData, 0, signalData.Length * sizeof(double));
//Substract from the dc term
ArrayCalculation.SubtractOffset(ref inputData, dcTerm);
//Hanning windowing the signal
ArrayCalculation.Multiply(hann_weighting, inputData, ref acData);
//Get the variance data, compensated by coeff , and sqrt to derive ac term
acTerm = Math.Sqrt(Statistics.Variance(acData) / (coeff_cg * coeff_cg * coeff_enbw));
}
public virtual void Substract(double[] src1, double[] src2, ref double[] dest)
{
ArrayCalculation.Subtract(src1, src2, ref dest);
}
public virtual void Add(short[] src1, short[] src2, ref short[] dest)
{
ArrayCalculation.Add(src1, src2, ref dest);
}
public virtual void Add(float[] src1, float[] src2, ref float[] dest)
{
ArrayCalculation.Add(src1, src2, ref dest);
}
public virtual void Multiply(ref short[] srcDest, short scalar)
{
ArrayCalculation.MultiplyScale(ref srcDest, scalar);
}
public virtual double Sum(float[] src1)
{
return(ArrayCalculation.Sum(src1));
}
public virtual void Substract(ref double[] srcDest, double scalar)
{
ArrayCalculation.SubtractOffset(ref srcDest, scalar);
}
public virtual void Multiply(float[] src1, float[] src2, ref float[] dest)
{
ArrayCalculation.Multiply(src1, src2, ref dest);
}
public virtual void Multiply(double[] src1, double[] src2, ref double[] dest)
{
ArrayCalculation.Multiply(src1, src2, ref dest);
}
public virtual void Initialize(ref float[] dest, float initValue)
{
ArrayCalculation.InitializeArray(ref dest, initValue);
}
public virtual void Initialize(ref double[] dest, double initValue)
{
ArrayCalculation.InitializeArray(ref dest, initValue);
}
public virtual void Absolute(float[] src, ref float[] dest)
{
ArrayCalculation.Abs(src, ref dest);
}
public virtual void Absolute(double[] src, ref double[] dest)
{
ArrayCalculation.Abs(src, ref dest);
}
public virtual void Substract(float[] src1, float[] src2, ref float[] dest)
{
ArrayCalculation.Subtract(src1, src2, ref dest);
}
public virtual void Substract(short[] src1, short[] src2, ref short[] dest)
{
ArrayCalculation.Subtract(src1, src2, ref dest);
}
public virtual void Multiply(short[] src1, short[] src2, ref short[] dest)
{
ArrayCalculation.Multiply(src1, src2, ref dest);
}
public virtual void Substract(ref short[] srcDest, short scalar)
{
ArrayCalculation.SubtractOffset(ref srcDest, scalar);
}
private void ProcessQueue()
{
while (start)
{
Thread.Sleep(1);
if (myqueue.Count > 0)
{
qoutdata = myqueue.Dequeue();
if (lasttime.ToString("yyy_MM_dd_HH_mm_ss") == qoutdata.logtime.ToString("yyy_MM_dd_HH_mm_ss"))
{
qoutdata.logtime = qoutdata.logtime.AddSeconds(1);
}
if (qoutdata.averageindex == 1)
{
csvfilename = qoutdata.logtime.ToString("yyy_MM_dd_HH_mm_ss");
}
lasttime = qoutdata.logtime;
//显示波形需要做一次转置
if (Chcount == 1)
{
ArrayManipulation.GetArraySubset(qoutdata.RawData, 0, ref ch0RawValue, ArrayManipulation.IndexType.column);
ArrayCalculation.MultiplyScale(ref ch0RawValue, ch0sensivity);
Spectrum.PowerSpectrum(ch0RawValue, aitask.SampleRate, ref ch0sprectrumValue, out df, SpectrumUnits.V, WindowType.Hanning);
spectrumcalculation(1, qoutdata.averageindex, ch0sprectrumValue);
CsvData(filepath, "CH0_", csvfilename, qoutdata.averageindex, qoutdata.logtime, FFTdf, ch0sprectrumValue, ch0averagesprectrumValue);
if (qoutdata.averageindex == averagetimes)
{
if (mqtt_client.IsConnected)
{
WriteChannelData(1);
}
copyalarmfile(filepath, qoutdata.logtime);
}
}
else if (Chcount == 2)
{
ArrayManipulation.GetArraySubset(qoutdata.RawData, 0, ref ch0RawValue, ArrayManipulation.IndexType.column);
ArrayCalculation.MultiplyScale(ref ch0RawValue, ch0sensivity);
ArrayManipulation.GetArraySubset(qoutdata.RawData, 1, ref ch1RawValue, ArrayManipulation.IndexType.column);
ArrayCalculation.MultiplyScale(ref ch1RawValue, ch1sensivity);
Spectrum.PowerSpectrum(ch0RawValue, aitask.SampleRate, ref ch0sprectrumValue, out df, SpectrumUnits.V, WindowType.Hanning);
Spectrum.PowerSpectrum(ch1RawValue, aitask.SampleRate, ref ch1sprectrumValue, out df, SpectrumUnits.V, WindowType.Hanning);
spectrumcalculation(1, qoutdata.averageindex, ch0sprectrumValue);
spectrumcalculation(2, qoutdata.averageindex, ch1sprectrumValue);
CsvData(filepath, "CH0", csvfilename, qoutdata.averageindex, qoutdata.logtime, FFTdf, ch0sprectrumValue, ch0averagesprectrumValue);
CsvData(filepath, "CH1", csvfilename, qoutdata.averageindex, qoutdata.logtime, FFTdf, ch1sprectrumValue, ch1averagesprectrumValue);
if (qoutdata.averageindex == averagetimes)
{
if (mqtt_client.IsConnected)
{
WriteChannelData(2);
}
copyalarmfile(filepath, qoutdata.logtime);
}
}
else if (Chcount == 3)
{
ArrayManipulation.GetArraySubset(qoutdata.RawData, 0, ref ch0RawValue, ArrayManipulation.IndexType.column);
ArrayCalculation.MultiplyScale(ref ch0RawValue, ch0sensivity);
ArrayManipulation.GetArraySubset(qoutdata.RawData, 1, ref ch1RawValue, ArrayManipulation.IndexType.column);
ArrayCalculation.MultiplyScale(ref ch1RawValue, ch1sensivity);
ArrayManipulation.GetArraySubset(qoutdata.RawData, 2, ref ch2RawValue, ArrayManipulation.IndexType.column);
ArrayCalculation.MultiplyScale(ref ch2RawValue, ch2sensivity);
Spectrum.PowerSpectrum(ch0RawValue, aitask.SampleRate, ref ch0sprectrumValue, out df, SpectrumUnits.V, WindowType.Hanning);
Spectrum.PowerSpectrum(ch1RawValue, aitask.SampleRate, ref ch1sprectrumValue, out df, SpectrumUnits.V, WindowType.Hanning);
Spectrum.PowerSpectrum(ch2RawValue, aitask.SampleRate, ref ch2sprectrumValue, out df, SpectrumUnits.V, WindowType.Hanning);
spectrumcalculation(1, qoutdata.averageindex, ch0sprectrumValue);
spectrumcalculation(2, qoutdata.averageindex, ch1sprectrumValue);
spectrumcalculation(3, qoutdata.averageindex, ch2sprectrumValue);
CsvData(filepath, "CH0_", csvfilename, qoutdata.averageindex, qoutdata.logtime, FFTdf, ch0sprectrumValue, ch0averagesprectrumValue);
CsvData(filepath, "CH1_", csvfilename, qoutdata.averageindex, qoutdata.logtime, FFTdf, ch1sprectrumValue, ch1averagesprectrumValue);
CsvData(filepath, "CH2_", csvfilename, qoutdata.averageindex, qoutdata.logtime, FFTdf, ch2sprectrumValue, ch2averagesprectrumValue);
if (qoutdata.averageindex == averagetimes)
{
if (mqtt_client.IsConnected)
{
WriteChannelData(3);
}
copyalarmfile(filepath, qoutdata.logtime);
}
}
else
{
ArrayManipulation.GetArraySubset(qoutdata.RawData, 0, ref ch0RawValue, ArrayManipulation.IndexType.column);
ArrayCalculation.MultiplyScale(ref ch0RawValue, ch0sensivity);
ArrayManipulation.GetArraySubset(qoutdata.RawData, 1, ref ch1RawValue, ArrayManipulation.IndexType.column);
ArrayCalculation.MultiplyScale(ref ch1RawValue, ch1sensivity);
ArrayManipulation.GetArraySubset(qoutdata.RawData, 2, ref ch2RawValue, ArrayManipulation.IndexType.column);
ArrayCalculation.MultiplyScale(ref ch2RawValue, ch2sensivity);
ArrayManipulation.GetArraySubset(qoutdata.RawData, 3, ref ch3RawValue, ArrayManipulation.IndexType.column);
ArrayCalculation.MultiplyScale(ref ch3RawValue, ch3sensivity);
Spectrum.PowerSpectrum(ch0RawValue, aitask.SampleRate, ref ch0sprectrumValue, out df, SpectrumUnits.V, WindowType.Hanning);
Spectrum.PowerSpectrum(ch1RawValue, aitask.SampleRate, ref ch1sprectrumValue, out df, SpectrumUnits.V, WindowType.Hanning);
Spectrum.PowerSpectrum(ch2RawValue, aitask.SampleRate, ref ch2sprectrumValue, out df, SpectrumUnits.V, WindowType.Hanning);
Spectrum.PowerSpectrum(ch3RawValue, aitask.SampleRate, ref ch3sprectrumValue, out df, SpectrumUnits.V, WindowType.Hanning);
spectrumcalculation(1, qoutdata.averageindex, ch0sprectrumValue);
spectrumcalculation(2, qoutdata.averageindex, ch1sprectrumValue);
spectrumcalculation(3, qoutdata.averageindex, ch2sprectrumValue);
spectrumcalculation(4, qoutdata.averageindex, ch3sprectrumValue);
CsvData(filepath, "CH0_", csvfilename, qoutdata.averageindex, qoutdata.logtime, FFTdf, ch0sprectrumValue, ch0averagesprectrumValue);
CsvData(filepath, "CH1_", csvfilename, qoutdata.averageindex, qoutdata.logtime, FFTdf, ch1sprectrumValue, ch1averagesprectrumValue);
CsvData(filepath, "CH2_", csvfilename, qoutdata.averageindex, qoutdata.logtime, FFTdf, ch2sprectrumValue, ch2averagesprectrumValue);
CsvData(filepath, "CH3_", csvfilename, qoutdata.averageindex, qoutdata.logtime, FFTdf, ch3sprectrumValue, ch3averagesprectrumValue);
if (qoutdata.averageindex == averagetimes)
{
if (mqtt_client.IsConnected)
{
WriteChannelData(4);
}
copyalarmfile(filepath, qoutdata.logtime);
}
}
this.Invoke((MethodInvoker) delegate
{
if (radioButtonCH0.Checked == true)
{
easyChartTime.Plot(ch0RawValue);
easyChartFFT.Plot(ch0sprectrumValue);
}
if (radioButtonCH1.Checked == true)
{
easyChartTime.Plot(ch1RawValue);
easyChartFFT.Plot(ch1sprectrumValue);
}
if (radioButtonCH2.Checked == true)
{
easyChartTime.Plot(ch2RawValue);
easyChartFFT.Plot(ch2sprectrumValue);
}
if (radioButtonCH3.Checked == true)
{
easyChartTime.Plot(ch3RawValue);
easyChartFFT.Plot(ch3sprectrumValue);
}
textBox1.Text = myqueue.Count.ToString();
});
}
}
}
public virtual void Add(double[] src1, double[] src2, ref double[] dest)
{
ArrayCalculation.Add(src1, src2, ref dest);
}
public virtual void Multiply(ref double[] srcDest, double scalar)
{
ArrayCalculation.MultiplyScale(ref srcDest, scalar);
}
