Matlab FFT分析 - 技术栈

1. 背景

在分析谐振或者三相电流波形的时候需要对数据或者波形进行FFT分析来确定波形成分。

2. 代码

输入时间和三相电流即可得到FFT的结果。

Matlab 复制代码

clc
clear
%%
file.name = "305 1500 10.csv";
data.raw = readtable(file.name);
% load("data.mat")
data.t = table2array(data.raw(15:end,1));
data.a = table2array(data.raw(15:end,2));
data.b = table2array(data.raw(15:end,3));
data.c = table2array(data.raw(15:end,4));
%% 
figure;
tab = 7799851;
plot(data.t(tab:end),data.a(tab:end),"DisplayName","A相电流");hold on;

plot(data.t(tab:end),data.b(tab:end),"DisplayName","B相电流");hold on;

plot(data.t(tab:end),data.c(tab:end),"DisplayName","C相电流");hold off;

xlabel('t/s')
legend;

%% 
Fs = 1/0.00000001;
N = length(data.a);
f = (0:N-1) * (Fs/N);
data.a_fft = fft(data.a);
figure;
plot(f(1:5000),2*abs(data.a_fft(1:5000)/N));
title('A相电流-FFT')
xlabel('f/Hz')
data.b_fft = fft(data.b);
figure;
plot(f(1:5000),2*abs(data.b_fft(1:5000)/N));
title('B相电流-FFT')
xlabel('f/Hz')
data.c_fft = fft(data.c);
figure;
plot(f(1:5000),2*abs(data.c_fft(1:5000)/N));
title('C相电流-FFT')
xlabel('f/Hz')
%% 
% a = func_FFT(data.t',data.a');
% plot(a)

Matlab 复制代码

function [f X label_even] = func_FFT(t, x)

[m, n] = size(x);
if length(t) ~= n
    error('input size not consistent!')
end
f_1st = 1 / (t(2) - t(1)) / length(t);
f = f_1st * ((1:length(t))-1);

for k=1:m
    input = x(k, :);
    if sum(sum(imag(input))) == 0
        fft_x = fft(input);
        if mod(n, 2) == 0
            fft_x = fft_x(1:(n/2+1));
            label_even = 1;
        else
            fft_x = fft_x(1:((n-1)/2+1));
            label_even = 0;
        end
        X(k, :) = 2 * fft_x / n;
        X(k, 1) = X(k, 1) / 2;
        if mod(n, 2) == 0
            X(k, length(fft_x)) = X(k, length(fft_x)) / 2;
        end
        f = f(1:length(fft_x));
    else
        warning('time domain signal contains imag part, complex FFT executed!')
        fft_x = fft(input) / n;
        if mod(n, 2) == 0
            fft_x(n/2+1) = fft_x(n/2+1) / 2;
            fft_x = [fft_x((n/2+1):n) fft_x(1:(n/2+1))];
            f = [-fliplr(f(2:(n/2+1))) f(1:(n/2+1))];
            label_even = 1;
        else
            fft_x = [fft_x(((n+1)/2+1):n) fft_x(1:((n+1)/2))];
            f = [-fliplr(f(2:((n+1)/2))) f(1:((n+1)/2))];
            label_even = 0;
        end
        X(k, :) = fft_x;
    end
end
plot(f(1:5000),abs(X(1:5000)))
% [mt, nt] = size(t)
% [mx, nx] = size(x)
% [mf, nf] = size(f)
% [mX, nX] = size(X)

% for k=1:m
%     fft_x = fft(x(k, :));
%     if mod(n, 2) == 0
%         fft_x = fft_x(1:(n/2+1));
%         label_even = 1;
%     else
%         fft_x = fft_x(1:((n-1)/2+1));
%         label_even = 0;
%     end
%     X(k, :) = 2 * fft_x / n;
%     X(k, 1) = X(k, 1) / 2;
%     if mod(n, 2) == 0
%         X(k, length(fft_x)) = X(k, length(fft_x)) / 2;
%     end
% end
% f = f(1:length(fft_x));