public static double[] getFFTResult(int[] data, int dx, int len = 1024)
{
double[] result = new double[len];
double[] resulti = new double[len];
for (int i = 0; i < len; i++)
{
int index = i + dx;
if (index >= 0 && index < data.Length)
{
result[i] = data[index];
}
else
{
result[i] = 0;
}
resulti[i] = 0;
}
result = addHanning(result);
TWFFT.FFT(result, resulti);
double[] result_len = new double[len];
for (int i = 0; i < len; i++)
{
result_len[i] = Math.Sqrt(result[i] * result[i] + resulti[i] * resulti[i]);
}
return(result);
}
/// <summary>
/// 来自iDAU的计算请求
/// </summary>
public static int CalcAndSave(int structid, int module, int channel, float fs, DateTime acqTime, float[] orgdata, out string err)
{
int affectCnt = 0;
double sensitivity = 1; // 灵敏度系数
int formulaid = 0; // 计算公式
err = "";
var sensorid = DataAccessHelper.GetSensorId(structid, module, channel);
if (sensorid == -1)
{
err = string.Format("传感器 {0}-{1}-{2} 不存在", structid, module, channel);
return(0);
}
if (!DataAccessHelper.GetSensorParameter1(sensorid, out sensitivity, out formulaid))
{
err = string.Format("传感器 {0}-{1}-{2} 参数不存在", structid, module, channel);
return(0);
}
double[] freq, ampl;
var org = new double[orgdata.Length];
for (int i = 0; i < org.Length; i++)
{
org[i] = orgdata[i];
}
PhisicalTrans(ref org, sensitivity);
if (formulaid == 21) // 包含滤波
{
org = RemoveDcAndFilterWave(org);
TWFFT.FFTData(org, fs, 1024, out ampl, out freq);//带平均的FFT
}
else
{
var tmp = (double[])org.Clone();
TWFFT.FFTData1(tmp, null, fs, out ampl, out freq);
ampl[0] = 0; // 消除频谱中的直流分量
}
CheckRedundancy(sensorid, acqTime);
#if USE_BULK_COPY
affectCnt = InsertDataBulk(sensorid, (int)fs, acqTime, org, freq, ampl);
#else
affectCnt = InsertData(sensorid, (int)fs, acqTime, org, freq, ampl);
#endif
return(affectCnt);
}
/// <summary>
/// 振动数据FFT计算/物理量转换
/// -- 来自数据接收的计算请求
/// </summary>
/// <param name="sensorid">传感器ID</param>
/// <param name="acqTime">采集时间</param>
/// <param name="filepath">文件路径</param>
/// <returns>共插入的振动数据个数(原始数据和FFT数据) -1:false </returns>
public static int CalcAndSave(int sensorid, DateTime acqTime, string filepath)
{
int affectCnt = 0;
double sensitivity = 1; // 灵敏度系数
int formulaid = 0; // 计算公式
var structId = DataAccessHelper.GetSensorStruct(sensorid);
if (!DataAccessHelper.GetSensorParameter1(sensorid, out sensitivity, out formulaid))
{
_logger.Warn(string.Format("计算振动数据时发生错误，传感器{0}未能找到计算系数", sensorid));
return(-1);
}
double[] freq, ampl;
double fs = ReadParam(filepath).diSampleFreq;
double[] org = ReadDatum(filepath);
PhisicalTrans(ref org, sensitivity);
// --FILTER BEGIN--
if (structId > 0)
{
var filter = ConfigHelper.GetAccFilter(structId);
string err = "";
if (filter != null && !filter.IsValid(org, out err))
{
throw new Exception(err);
}
}
// --FILTER END--
if (formulaid == 21) // 包含滤波
{
org = RemoveDcAndFilterWave(org);
TWFFT.FFTData(org, fs, 1024, out ampl, out freq);//带平均的FFT
}
else
{
var tmp = (double[])org.Clone();
TWFFT.FFTData1(tmp, null, fs, out ampl, out freq);
ampl[0] = 0; // 消除频谱中的直流分量
}
CheckRedundancy(sensorid, acqTime); // 检查数据库中是否有重复数据
#if USE_BULK_COPY
affectCnt = InsertDataBulk(sensorid, (int)fs, acqTime, org, freq, ampl);
#else
affectCnt = InsertData(sensorid, (int)fs, acqTime, org, freq, ampl);
#endif
return(affectCnt);
}
/// <summary>
/// 用倒谱获得频谱包络
/// </summary>
/// <param name="data"></param>
/// <returns></returns>
private static double[] GetEnvelopeFD(double[] data)
{
int n = data.Length;
double[] data1 = new double[n];
double[] data1i = new double[n];
for (int i = 0; i < n; i++)
{
data1[i] = Math.Log(data[i]);
}
for (int i = 0; i < n; i++)
{
data1i[i] = 0;
}
TWFFT.FFT(data1, data1i);
double therehold = 100;
double[] data2 = new double[n];
double[] data2i = new double[n];
// 低通滤波
for (int i = 0; i < n; i++)
{
if (i < therehold || i > n - therehold)
{
data2[i] = data1[i];
data2i[i] = data1i[i];
}
else
{
data2[i] = 0;
data2i[i] = 0;
}
}
//for (int i = 0; i < n; i++) data2i[i] = 0;
TWFFT.IFFT(data2, data2i);
var res = FToneAnalysis.MiddleFilter(data2, 3);
for (int i = 0; i < n; i++)
{
res[i] = Math.Pow(Math.E, res[i]);
}
return(res);
}
private ArrayList FFTList(ArrayList lfft)
{
float[] resource = new float[max];
int x = 0;
foreach (string fft in lfft)
{
if (x == max)
{
break;
}
float f = float.Parse(fft);
resource[x] = f;
x++;
}
ArrayList time_out = TWFFT.getArrayWithDivision(512.0f, 0.0f, 1024.0f);
ArrayList result = TWFFT.FFTMagic(time_out, TWFFT.FFTAbs(TWFFT.FFT(resource, getZero())), 1025);
return(result);
}
public static Image getFFTImage(int[] data)
{
int w = 2000;
int h = 1000;
Bitmap bitmap = new Bitmap(w, h);
Graphics g = Graphics.FromImage(bitmap);
g.SmoothingMode = System.Drawing.Drawing2D.SmoothingMode.AntiAlias;
//draw fft
int n = 4096;
double[] datas = new double[n];
double[] datas2 = new double[n];
double[] datamod = new double[n];
//if (data.Length <= n) return null;
for (int i = 0; i < n; i++)
{
datas2[i] = 0;
if (i > data.Length - 1)
{
datas[i] = 0;
}
else
{
datas[i] = data[i];
}
}
TWFFT.FFT(datas, datas2);
for (int i = 0; i < n; i++)
{
datamod[i] = Math.Sqrt(datas[i] * datas[i] + datas2[i] * datas2[i]);
}
int time = 2;
for (int i = 1; i < n / time; i++)
{
g.DrawLine(new Pen(Color.Black, 1),
new Point((int)((double)(i - 1) / n * time * bitmap.Width), (int)(h - datamod[i - 1] / w)),
new Point((int)((double)i / n * time * bitmap.Width), (int)(h - datamod[i] / w)));
}
double[] datad = new double[n];
double[] datad2 = new double[n];
for (int i = 0; i < n; i++)
{
datad2[i] = 0;
}
for (int i = 0; i < n; i++)
{
datad[i] = Math.Log(datamod[i]);
}
for (int i = 1; i < n / time; i++)
{
g.DrawLine(new Pen(Color.Red, 1),
new Point((int)((double)(i - 1) / n * time * bitmap.Width), (int)(h - datad[i - 1] * 50)),
new Point((int)((double)i / n * time * bitmap.Width), (int)(h - datad[i] * 50)));
}
TWFFT.FFT(datad, datad2);
for (int i = 0; i < n; i++)
{
datamod[i] = Math.Log(Math.Sqrt(datad[i] * datad[i] + datad2[i] * datad2[i]));
}
double therehold = 100;
double[] rdata = new double[n];
double[] rdata2 = new double[n];
for (int i = 0; i < n; i++)
{
if (i < therehold || i > n - therehold)
{
rdata[i] = datad[i];
}
else
{
rdata[i] = 0;
}
}
for (int i = 0; i < n; i++)
{
rdata2[i] = datad2[i];
}
TWFFT.IFFT(rdata, rdata2);
for (int i = 1; i < n / time; i++)
{
g.DrawLine(new Pen(Color.Blue, 1),
new Point((int)((double)(i - 1) / n * time * bitmap.Width), (int)(h - rdata[i - 1] * 50)),
new Point((int)((double)i / n * time * bitmap.Width), (int)(h - rdata[i] * 50)));
}
return(bitmap);
}
public static Image getDFFTImage(int[] data, int beginx, int len, double pitch = 1)
{
int w = 2000;
int h = 1000;
Bitmap bitmap = new Bitmap(w, h);
Graphics g = Graphics.FromImage(bitmap);
g.SmoothingMode = System.Drawing.Drawing2D.SmoothingMode.AntiAlias;
//draw fft
int n = 4096;
double[] datas = new double[n];
double[] datasi = new double[n];
double[] datamod = new double[n];
//if (data.Length <= n) return null;
for (int i = 0; i < n; i++)
{
datasi[i] = 0;
if (i > data.Length - 1)
{
datas[i] = 0;
}
else
{
datas[i] = data[i];
}
}
TWFFT.FFT(datas, datasi);
for (int i = 0; i < n; i++)
{
datamod[i] = Math.Sqrt(datas[i] * datas[i] + datasi[i] * datasi[i]);
}
var ddataenv = GetEnvelopeFD(datamod);
int time = 2;
for (int i = 1; i < n / time; i++)
{
g.DrawLine(new Pen(Color.Black, 1),
new Point((int)((double)(i - 1) / n * time * bitmap.Width), (int)(h - datamod[i - 1] / w)),
new Point((int)((double)i / n * time * bitmap.Width), (int)(h - datamod[i] / w)));
}
double[] ddatabase = new double[n];
double[] ddataibase = new double[n];
for (int i = 0; i < n; i++)
{
ddatabase[i] = datas[i] / ddataenv[i];
}
for (int i = 0; i < n; i++)
{
ddataibase[i] = datasi[i] / ddataenv[i];
}
double[] ddatabaser = new double[n];
double[] ddataibaser = new double[n];
// 对称共轭，所以分两半分别压缩
ddatabaser[0] = datas[0];
ddataibaser[0] = datasi[0];
pitch = 2.4;
for (int i = 1; i <= n / 2; i++)
{
ddatabaser[i] = getResampleValue(ddatabase, (double)i / pitch);
ddatabaser[n - i] = ddatabaser[i];
ddataibaser[i] = getResampleValue(ddataibase, (double)i / pitch);
ddataibaser[n - i] = -ddataibaser[i];
}
for (int i = 0; i < n; i++)
{
ddatabaser[i] = ddatabaser[i] * ddataenv[i];
}
for (int i = 0; i < n; i++)
{
ddataibaser[i] = ddataibaser[i] * ddataenv[i];
}
for (int i = 0; i < n; i++)
{
datamod[i] = Math.Sqrt(ddatabaser[i] * ddatabaser[i] + ddataibaser[i] * ddataibaser[i]);
}
for (int i = 1; i < n / time; i++)
{
g.DrawLine(new Pen(Color.Red, 1),
new Point((int)((double)(i - 1) / n * time * bitmap.Width), (int)(h - datamod[i - 1] / w)),
new Point((int)((double)i / n * time * bitmap.Width), (int)(h - datamod[i] / w)));
}
return(bitmap);
}
private void ThreadReadExample1()
{
//float[] Qc = new float[graphDt.Rows.Count];
//float[] Qh = new float[graphDt.Rows.Count];
float[] Qm = new float[graphDt.Rows.Count];
//float[] Tc = new float[graphDt.Rows.Count];
//float[] Th = new float[graphDt.Rows.Count];
float[] Tm = new float[graphDt.Rows.Count];
//float[] Tm2 = new float[graphDt.Rows.Count];
//float[] Pc = new float[graphDt.Rows.Count];
//float[] Ph = new float[graphDt.Rows.Count];
//float[] Pm = new float[graphDt.Rows.Count];
//float[] Qm5 = new float[graphDt.Rows.Count];
//float[] Wh = new float[graphDt.Rows.Count];
DateTime[] dateTime = new DateTime[graphDt.Rows.Count];
DateTimeFormatInfo dtFormat = new DateTimeFormatInfo();
dtFormat.ShortDatePattern = "yyyy-MM-dd hh:mm:ss:fff";
//加载流量数据
for (int i = 0; i < graphDt.Rows.Count; i++)
{
try
{
//Qc[i] = (float)Convert.ToDouble(graphDt.Rows[i][1]);
//Qh[i] = (float)Convert.ToDouble(graphDt.Rows[i][2]);
Qm[i] = (float)Convert.ToDouble(graphDt.Rows[i][3]);
//Tc[i] = (float)Convert.ToDouble(graphDt.Rows[i][4]);
//Th[i] = (float)Convert.ToDouble(graphDt.Rows[i][5]);
Tm[i] = (float)Convert.ToDouble(graphDt.Rows[i][6]);
//Tm2[i] = (float)Convert.ToDouble(graphDt.Rows[i][7]);
//Pc[i] = (float)Convert.ToDouble(graphDt.Rows[i][7]);
//Ph[i] = (float)Convert.ToDouble(graphDt.Rows[i][8]);
//Pm[i] = (float)Convert.ToDouble(graphDt.Rows[i][9]);
//Qm5[i] = (float)Convert.ToDouble(graphDt.Rows[i][10]);
//Wh[i] = (float)Convert.ToDouble(graphDt.Rows[i][11]);
// dateTime[i] = Convert.ToDateTime(dt.Rows[i][0],dtFormat);
dateTime[i] = DateTime.ParseExact((string)graphDt.Rows[i][0], "yyyy-MM-dd hh:mm:ss:fff", dtFormat);
}
catch (Exception ex) {
Log.Error(ex.ToString());
return;
}
}
//快速傅里叶变化滤波
Console.WriteLine("1:" + Qm.Length);
Qm = TWFFT.FFT_filter(Qm);
Tm = TWFFT.FFT_filter(Tm);
Console.WriteLine("2:" + Qm.Length);
for (int i = 0; i < graphDt.Rows.Count; i++)
{
}
DateTime start = dateTime[0];
DateTime PointA = dateTime[0].AddSeconds(2);
TimeSpan ts = new TimeSpan(1);
// 显示出数据信息来
Invoke(new Action(() =>
{
//总流量达到6L加载数据
if (false)
{
hslCurveHistory1.Text = "累计流量未达到6L...";
hslCurveHistory1.RemoveAllCurve();
}
else
{
hslCurveHistory1.Text = "正在加载数据...";
hslCurveHistory1.RemoveAllCurve();
hslCurveHistory1.SetLeftCurve("出水流量Qm", Qm, Color.DodgerBlue, true, "{0:F2} L/min");//布尔变量：是否开启曲线平滑
//hslCurveHistory1.SetLeftCurve("冷水流量Qc", Qc, Color.Tomato, true, "{0:F2} L/min");
//hslCurveHistory1.SetLeftCurve("热水流量Qh", Qh, Color.GreenYellow, true, "{0:F2} L/min");
//hslCurveHistory1.SetLeftCurve("Qm5", Qm5, Color.Purple, true, "{0:F2} L/min");
//hslCurveHistory1.SetLeftCurve("出水压力Pm", Pm, Color.Red, true, "{0:F2} Bar");
//hslCurveHistory1.SetLeftCurve("热水压力Ph", Ph, Color.Orange, true, "{0:F2} Bar");
//hslCurveHistory1.SetLeftCurve("冷水压力Pc", Pc, Color.Yellow, true, "{0:F2} Bar");
hslCurveHistory1.SetLeftCurve("出水温度Tm", Tm, Color.Red, true, "{0:F2} ℃");
//hslCurveHistory1.SetLeftCurve("出水温度Tm2", Tm2, Color.Yellow, true, "{0:F2} ℃");
//hslCurveHistory1.SetRightCurve("热水温度Th", Th, Color.Honeydew, true, "{0:F2} ℃");
//hslCurveHistory1.SetRightCurve("冷水温度Tc", Tc, Color.Pink, true, "{0:F2} ℃");
//hslCurveHistory1.SetRightCurve("液面高度Wh", Tc, Color.Blue, true, "{0:F2} mm");
hslCurveHistory1.SetDateTimes(dateTime);
// 增加一个三角形的线段标记示例 Points的每个点的X是数据索引，Y是数据值（需要选对参考坐标轴，默认为左坐标轴）
// 添加一个活动的标记
HslControls.HslMarkForeSection active = new HslControls.HslMarkForeSection()
{
StartIndex = 1000,
EndIndex = 1500,
Height = 0.9f,
};
//active.CursorTexts.Add("条码", "A123123124ashdiahsd是的iahsidasd");
//active.CursorTexts.Add("工号", "asd2sd123dasf");
//hslCurveHistory1.AddMarkActiveSection(active);
//hslCurveHistory1.SetCurveVisible("步序", false); // 步序不是曲线信息，不用显示出来
//hslCurveHistory1.ValueMaxLeft = 10;
//hslCurveHistory1.ValueMinLeft = 0;
SetTempLight(28);
SetTempLight(29);
SetTempLight(30);
SetRemark(29f, 28f, Tm);
hslCurveHistory1.SetScaleByXAxis((float)0.1);
hslCurveHistory1.RenderCurveUI();
}
}
));
}