README:

The following repository fetches data from both local and cloud databases to fetch data from sensors (acceleration and strains) and processes the data using the classes from another repository called Modal Engine for spectral analysis, modal analysis, and signal processing.

Request data from data base

from config import database_uri_local, connection_string, table_name
from orm_model import get_measurements_between_dates, Base, create_engine, sessionmaker , measurements_to_numpy ,create_measurement_class,get_latest_measurements

session = create_session(connection_string)
start_date = datetime(2024, 7, 27, 20, 25, 0, 0)
end_date = datetime(2024, 7, 27, 22, 25, 0, 0)
Measurement = create_measurement_class(table_name)
measurements = get_measurements_between_dates(start_date, end_date, session, Measurement)

data_array  = measurements_to_numpy(measurements) #Ndarray

Process data: Plot spectrogram

from Modal_Engine._engine import (SingleMeasurement,
                                  FFTDomain,
                                  DataVisualizer)


def plt_spectrogram(measurement: SingleMeasurement):
    fdomain = FFTDomain(measurement,NFFT=2**6)
    fdomain.fft()
    data_vis1 = DataVisualizer(fdomain)
    data_vis1.plot_spectrogram(cmap='jet')

file_name = "data/measurements_2024_7_27:20:25_2h.pkl"
data_set_time = "2024/7/27:20:25"
data_array = load_pickle(file_name)
filter = [0, 2, 4]
measurement_1 = SingleMeasurement(name =  f"{data_set_time} - Axis: X", fs = 100,file_path= None,
                                    description="2h test")
measurement_1 = measurement_1.set_data(data_array[:,filter]).resample(30)
plt_spectrogram(measurement_1)

Result