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adjusted the symmetry score computation in vibration analysis

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This commit is contained in:
Félix Boisselier
2024-04-02 15:47:45 +02:00
parent 617a47f968
commit c2c05e51ae
1 changed files with 27 additions and 25 deletions
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52
K-ShakeTune/scripts/graph_vibrations.py
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@@ -152,35 +152,36 @@ def compute_speed_powers(spectrogram_data, smoothing_window=15):
return min_values_smooth, max_values_smooth, avg_values_smooth, composite_variance_smooth
# This function uses a nuanced approach to allow the computation of a score that reflect both the shape
# similarity of a signal (via cross-correlation) and the energy level consistency across the signal
def compute_symmetry_analysis(all_angles, angles_energy):
# Split the signal in half
first_half_indices = (0 <= all_angles) & (all_angles < 90)
second_half_indices = (90 <= all_angles) & (all_angles < 180)
x1, y1 = all_angles[first_half_indices], angles_energy[first_half_indices]
x2, y2 = all_angles[second_half_indices], angles_energy[second_half_indices]
# This function allow the computation of a symmetry score that reflect the spectrogram apparent symmetry between
# measured axes on both the shape of the signal and the energy level consistency across both side of the signal
def compute_symmetry_analysis(all_angles, spectrogram_data, measured_angles=[0, 90]):
total_angles = len(all_angles)
angles_per_degree = total_angles / 360
midpoint_angle = np.mean(measured_angles)
# Reverse the second signal to compare them on a real symmetry
x2, y2 = x2[::-1], y2[::-1]
# Extend the spectrogram by adding half to the beginning (in order to not get an out of bounds error later)
half_spectrogram_length = total_angles // 2
extended_spectrogram = np.concatenate((spectrogram_data[-half_spectrogram_length:],
spectrogram_data), axis=0)
# Compute the similarity (using cross-correlation of the signals)
similarity_factor = compute_curve_similarity_factor(x1, y1, x2, y2, CURVE_SIMILARITY_SIGMOID_K)
# Calculate the split index in center part of the extended spectrogram and get the segments bounds
split_index = int(midpoint_angle * angles_per_degree + half_spectrogram_length)
start_index = split_index - half_spectrogram_length // 2
end_index = split_index + half_spectrogram_length // 2
# Because the signal of both half have approximately the same shape, this is not enough and we need to
# add the total energy of each side in the equation to help discriminate differences in the symmetry
energy_first_half = np.sum(y1**2)
energy_second_half = np.sum(y2**2)
energy_gap = np.abs(energy_first_half/energy_second_half - 1)
# Slice out the two segments for comparison and flatten them for comparison
segment_1 = extended_spectrogram[start_index:split_index]
segment_2 = extended_spectrogram[split_index:end_index]
segment_1_flattened = segment_1.flatten()
segment_2_flattened = segment_2.flatten()
# Compute an adjustement factor where close energies slightly increase the score and farther energies decrease the score
if energy_gap <= 0.1: adjustment_factor = 1 + energy_gap
else: adjustment_factor = 1 / (1 + 3 * (energy_gap - 0.1))
# Compute the correlation coefficient between the two halves of spectrogram
correlation = np.corrcoef(segment_1_flattened, segment_2_flattened)[0, 1]
adjusted_correlation = np.power(correlation, 0.75)
percentage_correlation_biased = (100 * adjusted_correlation) + 10
return np.clip(0, 100, percentage_correlation_biased)
# Adjust the similarity factor with the energy disparity
adjusted_similarity_factor = similarity_factor * adjustment_factor
return np.clip(adjusted_similarity_factor, 0, 100)
######################################################################
# Graphing
@@ -442,7 +443,8 @@ def vibrations_profile(lognames, klipperdir="~/klipper", kinematics="cartesian",
sp_min_energy, sp_max_energy, sp_avg_energy, sp_composite_variance = compute_speed_powers(spectrogram_data)
motor_profiles, global_motor_profile = compute_motor_profiles(target_freqs, psds, all_angles_energy, main_angles)
symmetry_factor = compute_symmetry_analysis(all_angles, all_angles_energy)
# symmetry_factor = compute_symmetry_analysis(all_angles, all_angles_energy)
symmetry_factor = compute_symmetry_analysis(all_angles, spectrogram_data, main_angles)
print_with_c_locale(f"Machine estimated vibration symmetry: {symmetry_factor:.1f}%")
# Analyze low variance ranges of vibration energy across all angles for each speed to identify clean speeds