Differential Amplifier for mV/V Instrumentation

Overview

This project showcases the design and calibration of a differential amplifier for mV/V instrumentation, such as load cells. The amplifier provides a gain of approximately 100 and shifts the output so that 2.5V corresponds to 0 differential voltage. This configuration makes it compatible with analog-to-digital converters (ADCs) that have an input range of 0 to 5V, such as those used in Arduino.

Key Features

High Gain: The amplifier provides a gain of around 100, making it suitable for millivolt-range signals from load cells and other precision sensors.
Offset Shifting: Shifts the output to 2.5V when the differential input voltage is 0, allowing for full utilization of ADCs with a 0-5V range.
Calibration via Analog Discovery 3: Uses the Analog Discovery 3's signal generator and scope to calibrate the amplifier across a range of input voltages.

Calibration Process

The calibration of the amplifier is automated using the Analog Discovery 3 and Python. Here's how the calibration is carried out:

1. Signal Injection

The Analog Discovery 3 generates small differential voltages to simulate the load cell signals, sweeping from -20mV to +20mV in custom increments (e.g., 0.5mV steps).
It logs the generated input signal and the amplifier's output using its own scope.

2. Sampling and Logging

Over a 1-second period, the system samples both the input signal and the amplifier's output.
It calculates the average value of each during this period.

3. Multiple Sweeps

The system performs multiple sweeps through the input range (e.g., -20mV to +20mV), repeating this process for a specified number of loops to ensure consistent data.

4. Linear Regression and Analysis

Once the data is collected, Python performs a linear regression on each sweep to calculate:
- Average Amplification: The gain of the amplifier.
- Offset: Any static offset in the output.
The results include both the average amplification and offset, along with their uncertainties, providing a thorough calibration of the system.

Python Script Overview

The Python script used for calibration automates the process of sweeping, logging, and analyzing data from the Analog Discovery 3. Key functions include:

Signal Generation: Customizable step sizes, voltage range, and number of sweeps.
Data Collection: Logs both input and output voltages during each sweep.
Linear Regression: Fits a line to the data for each sweep to calculate the amplifier's gain and offset.
Uncertainty Analysis: Reports uncertainties in both the amplification and offset.

Example Workflow:

Run the script to initiate the calibration process.
Set the input sweep parameters: range, step size, and number of loops.
Log the data: Input and output values are sampled and averaged.
Perform regression: Python analyzes the data, calculates gain and offset, and reports results with uncertainties.

3.0 KiB Raw Blame History