Mass Flow Meter

Mass Flow Meter

Recorded Data

The Mass Flow Meter records the following attribute during operation:

  • ml_min: The mass flow value of the mass flow meter in mL/min.

Python API

The Mass Flow Meter can be controlled and monitored using the Aqueduct Python API. The Python code for interacting with the balance can be found in the aqueduct-py repository.

The module provides functions and classes to control the mass flow meter and retrieve mass flow readings. You can use this API to perform measurements and integrate the mass flow meter into your Python applications and automation scripts.

To use the Python API, you can import the MassFlowMeter class from the module and create an instance of the mass flow meter. Then, you can call the available methods to retrieve mass flow readings and perform other operations.

Here's an example of how to use the MassFlowMeter API:

import time

from import Aqueduct
from import InitParams
from aqueduct.core.units import MassFlowUnits
from aqueduct.devices.mass_flow import MassFlowMeter

# Parse the initialization parameters from the command line
params = InitParams.parse()

# Initialize the Aqueduct instance with the provided parameters
aq = Aqueduct(params.user_id, params.ip_address, params.port)

# Perform system initialization if specified

# Set the command delay for the Aqueduct instance

# Get the mass flow meter device from the Aqueduct instance
mass_flow_meter: MassFlowMeter = aq.devices.get("mass_flow_meter_000001")

mass_flow_meter.set_sim_values((10.0,), MassFlowUnits.UL_MIN)
mass_flow_meter.set_sim_rates_of_change((0.5,), MassFlowUnits.UL_MIN)

# Continuously perform operations on the mass flow meter devices
while True:
    # Get and print the mass flow reading from the mass flow meter device
    print(f"Mass Flow: {mass_flow_meter.ul_min[0]:.3f}ul/min")

    # Pause for 5 seconds

Please refer to the aqueduct-py repository for more details on how to use the Python API with the Mass Flow Meter.

Supported Hardware