k-Wave User Forum » Topic: Unknown signal in simulation

k-Wave User Forum » Topic: Unknown signal in simulation http://www.k-wave.org/forum/topic/unknown-signal-in-simulation Support for the k-Wave MATLAB toolbox en-US Wed, 13 May 2026 15:10:57 +0000 http://bbpress.org/?v=1.0.2 <![CDATA[Search]]> q http://www.k-wave.org/forum/search.php Bradley Treeby on "Unknown signal in simulation" http://www.k-wave.org/forum/topic/unknown-signal-in-simulation#post-6012 Sun, 25 Jun 2017 19:14:18 +0000 Bradley Treeby 6012@http://www.k-wave.org/forum/ Hi George, There is no way to automatically spatially smooth a source time series. However, you can remove high temporal frequencies using the <code>filterTimeSeries</code> function. Alternatively, if you want to replicate the same behaviour as smoothing a p0 source, see the second part of the "Filtering A Delta Function Input Signal Example". Note, my previous post above was about smoothing the medium parameters, rather than the source. Hope that helps, Brad. galexop on "Unknown signal in simulation" http://www.k-wave.org/forum/topic/unknown-signal-in-simulation#post-6009 Fri, 23 Jun 2017 21:43:25 +0000 galexop 6009@http://www.k-wave.org/forum/ How does one turn smoothing on, especially for a binary source mask with a source time series (i.e. a source that cant simply be defined by source.p0)? Thanks, George jrtc on "Unknown signal in simulation" http://www.k-wave.org/forum/topic/unknown-signal-in-simulation#post-5131 Wed, 08 Jul 2015 16:30:17 +0000 jrtc 5131@http://www.k-wave.org/forum/ Thank you so much for your help. Bradley Treeby on "Unknown signal in simulation" http://www.k-wave.org/forum/topic/unknown-signal-in-simulation#post-5126 Wed, 08 Jul 2015 12:35:02 +0000 Bradley Treeby 5126@http://www.k-wave.org/forum/ Hi Rodrigo, This is related to the efficacy of the perfectly matched layer (PML). Your source frequency is quite close to the maximum supported frequency of the grid (the PML doesn't work that well close to 2 points per wavelength), and the PML is also quite thin. This means some of the energy from the source wraps around the domain from top to bottom. As the signal diffracted around the disc is already very low, this becomes very noticeable on your plot. Increasing the size of the PML, reducing your source frequency, or increasing the size of the grid will all act to reduce this early arriving signal. I'd also suggest turning smoothing on to reduce the staircasing effects of the cylinder. For example, using your code and changing scale to 2, increasing the size of the PML to 20, and setting 'Smooth', true generates the following trace: <img src="http://www.k-wave.org/images/2015-07-08-forum_question_jrtc.png" /> Brad. jrtc on "Unknown signal in simulation" http://www.k-wave.org/forum/topic/unknown-signal-in-simulation#post-5116 Wed, 01 Jul 2015 18:27:37 +0000 jrtc 5116@http://www.k-wave.org/forum/ Good day. I've been trying to simulate a aluminum circle immersed in water with 'pstdElastic2D' in order to see the behavior of an ultrasonic signal passing through it. I have used the following code for simulation: <pre><code>clc clear all close all % ========================================================================= % SIMULATION PARAMETERS % ========================================================================= % change scale to 2 to reproduce the higher resolution figures used in the % help file scale = 1; % create the computational grid PML_size = 10*scale; % size of the PML in grid points Nx = 220*scale - 2*PML_size; % number of grid points in the x direction Ny = 220*scale - 2*PML_size; % number of grid points in the y direction dx = 0.1e-3/scale; % grid point spacing in the x direction [m] dy = 0.1e-3/scale; % grid point spacing in the y direction [m] kgrid = makeGrid(Nx, dx, Ny, dy); % define the medium properties % === WATER cp1 = 1480; % compressional wave speed [m/s], 1540 === 1480 cs1 = 0; % shear wave speed [m/s] rho1 = 1000; % density [kg/m^3] alpha0_p1 = 0.0; % compressional wave absorption [dB/(MHz^2 cm)] alpha0_s1 = 0.0; % shear wave absorption [dB/(MHz^2 cm)] % === ALUMINUM cp2 = 6320; % compressional wave speed [m/s], 3000 === 6320 cs2 = 3100; % shear wave speed [m/s], 1400 === 3772 rho2 = 2720; % density [kg/m^3], 1850 alpha0_p2 = 1; % compressional wave absorption [dB/(MHz^2 cm)] alpha0_s2 = 1; % shear wave absorption [dB/(MHz^2 cm)] % create the time array cfl = 0.1; t_end = 15e-6; kgrid.t_array= makeTime(kgrid, cp2, cfl, t_end); % define position of heterogeneous slab slab = zeros(Nx, Ny); r = 22*scale; a = Nx/2; b = Ny/2; for i = a-r+1: a+r y1 = b - sqrt(r^2 - (i-a)^2); % == (i-(a-r)) y2 = b + sqrt(r^2 - (i-a)^2); % == (i-(a-r)) slab(i, floor(y1): floor(y2)) = 1; end % slab(Nx/2:3*Nx/4, Nx/2:3*Nx/4) = 1; % define the source properties source_freq = 5e6; % [Hz] source_strength = 1e3; % [Pa] source_cycles = 5; % number of tone burst cycles for j = 3: 3 % === Transmisor TX TX = zeros(Nx, Ny); dT = 24*scale; aT = 0; % 5 % === Distancias para dx dxT = [ (Nx/2) - r - dT; % ==== Máximo a la izquierda (Nx/2) - (r/2) - dT; % ==== Medio a la izquierda (Nx/2) - dT/2; % ==== Centro (Nx/2) + (r/2); % ==== Medio a la derecha (Nx/2) + r ]; % ==== Máximo a la derecha dy = (Ny/2) - 80*scale; TX(dy-aT: dy, dxT(j): dxT(j) + dT) = 1; % source_mask = zeros(Nx, Ny); source_mask = TX; % define the sensor to record the maximum particle velocity everywhere % sensor.record = {'u_max_all'}; sensor.record = {'p', 'p_final', 'p_max', 'u_max_all'}; % === Receptor RX RX = zeros(Nx, Ny); dxR = [ (Nx/2) - r - dT ; % ==== Máximo a la izquierda (Nx/2) - (r/2) - dT ; % ==== Medio a la izquierda (Nx/2) - dT/2 ; % ==== Centro (Nx/2) + (r/2) ; % ==== Medio a la derecha (Nx/2) + r ];% ==== Máximo a la derecha dy = (Ny/2) + 80*scale; RX(dy: dy+aT, dxR(j): dxR(j) + dT) = 1; sensor.mask =(RX); % ===== % sensor.record = {'p', 'p_final', 'p_max', 'u_max_all'}; % set the input arguments input_args = {'PMLSize', PML_size, 'PMLAlpha', 2, 'PlotPML', false, ... 'PMLInside', false, 'PlotScale', [-1, 1]*source_strength, ... 'DisplayMask', 'off', 'DataCast', 'single'}; % ========================================================================= % ELASTIC SIMULATION % ========================================================================= % define the medium properties clear medium medium.sound_speed_compression = cp1*ones(Nx, Ny); medium.sound_speed_compression(slab == 1) = cp2; medium.sound_speed_shear = cs1*ones(Nx, Ny); medium.sound_speed_shear(slab == 1) = cs2; medium.density = rho1*ones(Nx, Ny); medium.density(slab == 1) = rho2; medium.alpha_coeff_compression = alpha0_p1*ones(Nx, Ny); medium.alpha_coeff_compression(slab == 1) = alpha0_p2; medium.alpha_coeff_shear = alpha0_s1*ones(Nx, Ny); medium.alpha_coeff_shear(slab == 1) = alpha0_s2; % assign the source clear source source.s_mask = source_mask; % source.p0 = -source_strength*toneBurst(1/kgrid.dt, source_freq, source_cycles); source.sxx = source_strength*toneBurst(1/kgrid.dt, source_freq, source_cycles); source.syy = source.sxx; source.s_mode = 'dirichlet'; clear sensor sensor.mask =(RX); sensor.record = {'p', 'p_final', 'p_max', 'u_max_all', 'p_max_all'}; % run the elastic simulation sensor_data_elastic = pstdElastic2D(kgrid, medium, source, sensor, input_args{:}); % ========================================================================= % VISUALISATION % ========================================================================= % define plot vector x_vec = kgrid.x_vec(1 + PML_size:end - PML_size)*1e3; y_vec = kgrid.y_vec(1 + PML_size:end - PML_size)*1e3; % calculate square of velocity magnitude u_e = sensor_data_elastic.ux_max_all.^2 + sensor_data_elastic.uy_max_all.^2; % u_f = sensor_data_fluid.ux_max_all.^2 + sensor_data_fluid.uy_max_all.^2; figure(5) imagesc(y_vec, x_vec, 20*log10(u_e./max(u_e(:)))); xlabel('y [mm]'); ylabel('x [mm]'); axis image; colorbar; caxis([-50, 0]); title('Elastic Model'); colormap(jet(256)); % === Gráfica de la señal recibida SDE{1} = zeros(1, size(sensor_data_elastic.p, 2)); for i = 1: size(sensor_data_elastic.p, 2) SDE{j}(i) = sum(sensor_data_elastic.p(:, i))/size(sensor_data_elastic.p, 1); end figure(12) set(gca, 'nextplot', 'replacechildren', 'FontSize', 14) plot(kgrid.t_array, SDE{j}, 'r-'); xlabel('Time [s]'); ylabel('Signal Amplitude'); axis([kgrid.t_array(1) kgrid.t_array(end) min(SDE{j})*1.2 max(SDE{j})*1.2]) title('Sensor Pressure Signal'); end</code></pre> After running the simulation i obtain a signal like this one: <a href="http://imgur.com/loWvn3s"><img src="http://i.imgur.com/loWvn3s.png?1" title="source: imgur.com" /></a> I cannot identify that signal, i have no idea what it is. If some one could help me out and tell me what i am looking at would deeply appreciate it. Thanks in advanced. Rodrigo