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Tools/ecl_ekf: fix vibe_metrics usage (moved to vehicle_imu_status instances)

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Daniel Agar
2022-04-13 10:36:45 -04:00
parent b4158c1b48
commit 9c381a60b5
6 changed files with 84 additions and 60 deletions
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Tools/ecl_ekf/analysis/checks.py
+1 -1
View File
@@ -55,7 +55,7 @@ def perform_imu_checks(
# perform the vibration check
imu_status['imu_vibration_check'] = 'Pass'
for imu_vibr_metric in ['imu_coning', 'imu_hfdang', 'imu_hfdvel']:
for imu_vibr_metric in ['imu_coning', 'imu_hfgyro', 'imu_hfaccel']:
mean_metric = '{:s}_mean'.format(imu_vibr_metric)
peak_metric = '{:s}_peak'.format(imu_vibr_metric)
if imu_metrics[mean_metric] > check_levels['{:s}_warn'.format(mean_metric)] \
Tools/ecl_ekf/analysis/metrics.py
+20 -10
View File
@@ -144,17 +144,27 @@ def calculate_imu_metrics(ulog: ULog, multi_instance, in_air_no_ground_effects:
imu_metrics[result] = calculate_stat_from_signal(
estimator_status_data, 'estimator_status', signal, in_air_no_ground_effects, np.median)
# calculates peak and mean for IMU vibration checks
for signal, result in [('vibe[0]', 'imu_coning'),
('vibe[1]', 'imu_hfdang'),
('vibe[2]', 'imu_hfdvel')]:
peak = calculate_stat_from_signal(
estimator_status_data, 'estimator_status', signal, in_air_no_ground_effects, np.amax)
if peak > 0.0:
imu_metrics['{:s}_peak'.format(result)] = peak
imu_metrics['{:s}_mean'.format(result)] = calculate_stat_from_signal(
estimator_status_data, 'estimator_status', signal,
in_air_no_ground_effects, np.mean)
for imu_status_instance in range(4):
try:
vehicle_imu_status_data = ulog.get_dataset('vehicle_imu_status', imu_status_instance).data
if vehicle_imu_status_data['accel_device_id'][0] == estimator_status_data['accel_device_id'][0]:
for signal, result in [('delta_angle_coning_metric', 'imu_coning'),
('gyro_vibration_metric', 'imu_hfgyro'),
('accel_vibration_metric', 'imu_hfaccel')]:
peak = calculate_stat_from_signal(vehicle_imu_status_data, 'vehicle_imu_status', signal, in_air_no_ground_effects, np.amax)
if peak > 0.0:
imu_metrics['{:s}_peak'.format(result)] = peak
imu_metrics['{:s}_mean'.format(result)] = calculate_stat_from_signal(vehicle_imu_status_data, 'vehicle_imu_status', signal, in_air_no_ground_effects, np.mean)
except:
pass
# IMU bias checks
estimator_states_data = ulog.get_dataset('estimator_states', multi_instance).data