[问答]

如何利用arm-DSP库进行FFT计算获得信号的频谱/幅值及相位?

1183 DSP库

问答对人有帮助，内容完整，我也想知道答案 0 如何利用arm-DSP库进行FFT计算获得信号的频谱/幅值及相位? 0
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答案对人有帮助，有参考价值 0 代码终于要来了，那么咱们就一步一步来。核心代码就三个文件——data.c data.h ffttest.c,其中data.c data.h为数据的准备部分，数据当然来自Matlab。ffttest.c里才是干货。(没看过上的自行翻阅) 一.data.c/data.h数据准备 data.h #ifndef _DATA_H #define _DATA_H #include "arm_math.h" #include #define SAMPLE_N 64 #define SAMPLE_FS 3200 #define FFT_DPI (SAMPLE_FS / SAMPLE_N); extern float32_t data2handle[SAMPLE_N * 2]; extern float32_t FFT_Output[SAMPLE_N]; extern float32_t xiebo[SAMPLE_N]; extern float32_t phaseA[SAMPLE_N]; extern float32_t phaseB[SAMPLE_N]; extern float32_t phaseC[SAMPLE_N]; #endif data.c #include "data.h" float32_t data2handle[SAMPLE_N * 2] = {0}; float32_t FFT_Output[SAMPLE_N] = {0}; float32_t xiebo[SAMPLE_N] = {0,12.0830468476080,23.0625562988315,31.9767233645297,38.1266205974219,41.1592650408757,41.1008388582348,38.3357763183915,33.5355339059327,27.5483591934343,21.2671323190531,15.4955017031488,10.8326010981529,7.59361568157981,5.77782765517063,5.08838180836849,5,4.86346545835348,4.03002514886167,1.97578767574228,-1.59380577304000,-6.67628905966528,-12.9524361960277,-19.8182546598069,-26.4644660940673,-31.9918434767550,-35.5451365280388,-36.4452976726157,-34.2997862737710,-29.0738765919851,-21.1116530786703,-11.1028754443124,-1.40834381901946e-14,11.1028754443124,21.1116530786703,29.0738765919851,34.2997862737710,36.4452976726157,35.5451365280388,31.9918434767550,26.4644660940672,19.8182546598069,12.9524361960277,6.67628905966530,1.59380577303998,-1.97578767574228,-4.03002514886168,-4.86346545835348,-5,-5.08838180836849,-5.77782765517063,-7.59361568157980,-10.8326010981529,-15.4955017031488,-21.2671323190531,-27.5483591934343,-33.5355339059328,-38.3357763183915,-41.1008388582348,-41.1592650408757,-38.1266205974219,-31.9767233645297,-23.0625562988315,-12.0830468476080}; float32_t phaseA[SAMPLE_N] = {0,0.490085701647803,0.975451610080641,1.45142338627231,1.91341716182545,2.35698368412999,2.77785116509801,3.17196642081823,3.53553390593274,3.86505226681368,4.15734806151273,4.40960632174178,4.61939766255643,4.78470167866105,4.90392640201615,4.97592363336099,5,4.97592363336099,4.90392640201615,4.78470167866104,4.61939766255643,4.40960632174178,4.15734806151273,3.86505226681368,3.53553390593274,3.17196642081823,2.77785116509801,2.35698368412999,1.91341716182545,1.45142338627231,0.975451610080641,0.490085701647802,6.12323399573677e-16,-0.490085701647803,-0.975451610080642,-1.45142338627231,-1.91341716182545,-2.35698368412999,-2.77785116509801,-3.17196642081823,-3.53553390593274,-3.86505226681369,-4.15734806151273,-4.40960632174178,-4.61939766255643,-4.78470167866104,-4.90392640201615,-4.97592363336099,-5,-4.97592363336098,-4.90392640201615,-4.78470167866105,-4.61939766255643,-4.40960632174178,-4.15734806151273,-3.86505226681368,-3.53553390593274,-3.17196642081823,-2.77785116509801,-2.35698368412999,-1.91341716182545,-1.45142338627231,-0.975451610080639,-0.490085701647803}; float32_t phaseB[SAMPLE_N] = {-4.33012701892219,-4.55431912460588,-4.73465064747553,-4.86938489638667,-4.95722430686905,-4.99732293738183,-4.98929461619302,-4.93321666042440,-4.82962913144534,-4.67952963378663,-4.48436370766344,-4.24601090763289,-3.96676670145618,-3.64932036348918,-3.29672907550034,-2.91238848433901,-2.50000000000000,-2.06353514902197,-1.60719732651581,-1.13538131517186,-0.652630961100256,-0.163595414108879,0.327015646150717,0.814477366972946,1.29409522551260,1.76125023960617,2.21144345109501,2.64033925325184,3.04380714504361,3.41796151011436,3.75919903739489,4.06423342295808,4.33012701892219,4.55431912460588,4.73465064747553,4.86938489638667,4.95722430686905,4.99732293738183,4.98929461619302,4.93321666042440,4.82962913144534,4.67952963378663,4.48436370766344,4.24601090763289,3.96676670145617,3.64932036348918,3.29672907550034,2.91238848433901,2.50000000000000,2.06353514902197,1.60719732651581,1.13538131517187,0.652630961100256,0.163595414108880,-0.327015646150719,-0.814477366972946,-1.29409522551261,-1.76125023960617,-2.21144345109501,-2.64033925325184,-3.04380714504361,-3.41796151011436,-3.75919903739489,-4.06423342295808}; float32_t phaseC[SAMPLE_N] = {4.33012701892219,4.06423342295808,3.75919903739489,3.41796151011436,3.04380714504360,2.64033925325184,2.21144345109501,1.76125023960617,1.29409522551261,0.814477366972945,0.327015646150716,-0.163595414108881,-0.652630961100257,-1.13538131517187,-1.60719732651581,-2.06353514902197,-2.50000000000000,-2.91238848433901,-3.29672907550034,-3.64932036348918,-3.96676670145617,-4.24601090763289,-4.48436370766344,-4.67952963378663,-4.82962913144534,-4.93321666042440,-4.98929461619302,-4.99732293738183,-4.95722430686905,-4.86938489638667,-4.73465064747553,-4.55431912460588,-4.33012701892220,-4.06423342295808,-3.75919903739489,-3.41796151011436,-3.04380714504360,-2.64033925325184,-2.21144345109501,-1.76125023960617,-1.29409522551260,-0.814477366972945,-0.327015646150718,0.163595414108876,0.652630961100260,1.13538131517187,1.60719732651581,2.06353514902197,2.50000000000000,2.91238848433901,3.29672907550035,3.64932036348918,3.96676670145617,4.24601090763289,4.48436370766344,4.67952963378663,4.82962913144534,4.93321666042440,4.98929461619302,4.99732293738183,4.95722430686905,4.86938489638667,4.73465064747553,4.55431912460588}; 无非就是准备了几个数组： 1.float32_t data2handle[SAMPLE_N * 2]，这个用来装处理后的采样数据，所谓处理就是之气那说的虚部填上0，所以对于SAMPLE_N 采样点，这个数组的长度为SAMPLE_N 2; 2.float32_t FFT_Output[SAMPLE_N],这个就是FFT输出的频谱数组，咋看之前都讲过了； 3.float32_t xiebo[SAMPLE_N]，就是那个50Hz、100Hz、200Hz叠加后的信号； 4.float32_t phaseA、B、C[SAMPLE_N]，就是标准三相电的信号；二.ffttest.c数据处理 ffttest.c #include "data.h" #include "arm_const_structs.h" #include "app_serial.h" #include "os.h" void Create_data2handle(float32_t p) { for(int i = 0;i < SAMPLE_N; i++) { data2handle[2 * i] = p; data2handle[2 * i + 1] = 0; } } void CalXiebo(void) { Create_data2handle(xiebo); arm_cfft_f32(&arm_cfft_sR_f32_len64, data2handle, 0, 1); arm_cmplx_mag_f32(data2handle, FFT_Output, SAMPLE_N); App_SerPrintf("/******************************************************************************/n"); for(int i = 0,j = 0; i < SAMPLE_N;i++,j++) { App_SerPrintf("%.8ft",FFT_Output); if(j >= 5) { App_SerPrintf("n"); j = -1; } } App_SerPrintf("n/*****************************************************************************/n"); } void CalPhase(float32_t phase,char phase_name) { int Index_50Hz = 50 / FFT_DPI; float32_t Real,Imaginary,hudu,jiaodu; Create_data2handle(phase); arm_cfft_f32(&arm_cfft_sR_f32_len64, data2handle, 0, 1); arm_cmplx_mag_f32(data2handle, FFT_Output, SAMPLE_N); Real = data2handle[Index_50Hz * 2]; Imaginary = data2handle[Index_50Hz * 2 + 1]; hudu = atan2(Imaginary , Real); jiaodu = hudu * 180.0 / 3.1415926; App_SerPrintf("%c相相位:%f°n",phase_name,jiaodu); } void FFTtest(void) { CalXiebo(); CalPhase(phaseA,'A'); CalPhase(phaseB,'B'); CalPhase(phaseC,'C'); } 三.万事俱备，只差测试怎么样。。。在串口助手里打印出来还算能看吧。。将输出的FFT_Output复制到Matlab里画图可以看到，在分辨率50Hz的情况下，0代表的是直流分量，1为50Hz分量，2为100Hz分量，4为200Hz分量。之前50、100、200设置的幅值分别是5、30、15，那么用上一篇中所说的计算实际幅值的办法，160/32 = 5；960/32=30；480/32=15,完全OK。那么再来看相位，A相-90°，B相150°，C相30°，向量图如下图，凑活看吧。跟设置的相位一毛一样。所以给定一个信号，用FFT就能分解出你想看的分量的全部信息，即频率、幅值、相位，可以说非常给力了。

2021-11-22 11:27:40 评论举报程家文