# 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:

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