Automate VRM Testing with Python & SCPI: A Guide for Lab Measurements
- Marshall Haynes
- Jun 23
- 4 min read
Updated: Jun 24
The grind of repetitive lab tasks can be a major drain on an engineer's time and energy. Think about those hours spent manually collecting data for something like a Voltage Regulator Module's Vout vs. Iout characteristics, the process is tedious and prone to human error. Fortunately, the solution is closer than you may think. Today's test equipment is increasingly capable of automation, offering a powerful path to efficiency and accuracy. If you've been wondering how to get started, this blog post is for you. I'll walk you through my process of automating VRM testing using Python and standard SCPI commands, transforming a common headache into a streamlined workflow.
Setting Up Your Automated Lab Measurement Environment
First, start by installing Python. I will be using Python 3.13.3 for this example, but this should work with any version of Python 3.
Second, install a Python IDE to run the code in. I use PyCharm because it makes installing packages easy, but again, any IDE will work.
Next, install NI Max device communication, which is used to find devices connected to the computer. Locate the communication ports on your devices. Look for ports on the back of the devices, most USB (A or B), RS232, or GPIB ports will work for this example. Install the necessary device drivers for the port you wish to use, these can usually be found at the start of the “Remote Control” section of the device's user manual.
Set up your test by attaching the VRM to a power supply, then connecting the Vout to a digital load and digital multimeter to measure the output of the VRM. For this test, I will be using a Picotest P9610A Power Supply, a Keysight EL34143 Digital Load, and a Picotest 3500A Digital Multimeter. My Device Under Test (DUT) is a custom designed Picotest evaluation module with an ADI LTC7151S VRM.
Once you have your test instruments connected to your computer, use NI Max to find the addresses of the devices. Under the “Devices and Interfaces” dropdown, there will be a list of all of the external devices connected to the computer. Each instrument should have some general information about the device and its communication, as well as the "VISA Resource Name." This is the communication address you will need for communicating with your instrument (for GPIB instruments you will need to select the GPIB interface, then click “Scan for Instruments” in the toolbar).
Next, create a new project in your IDE with Python 3 as the compiler. Install any extra packages you will need for your project. For this test, the only non-native Python package I will need is PyVISA, which is used to communicate with the devices connected to the communication ports.
Programming Your Test Equipment for Automation
Now that everything is set up, create a new Python file in the project for your code. Import any Python packages for your program. I will be using the PyVISA package to communicate with the external instruments, the time package to add delays when needed, and the CSV package to save and export the file data.
Create an inputs section, where you will input device addresses and any other variables that the program will need.
Open communication with the instruments through the PyVISA resource manager. You can also request the ID of the instrument to verify that the correct device was connected.
Use the necessary SCPI commands to program your test procedure. For this example, I wrote a program to measure the voltage output of a VRM across its range of output current. Remember to test your code as you are programming and plan things out beforehand.
Close communication with the instruments and save your data.
Run the program to make sure everything is working as intended, then enjoy the extra time you have with your task now automated.
Wrapping Up
In an era where efficiency and data integrity are paramount, test equipment automation stands out as an indispensable tool for engineers. We've seen how dramatically it reduces the tediousness of manual measurements. Testing automation allows for the collection of more comprehensive and, crucially, more reliable data by removing the potential for human error. If the idea of automating your lab once felt like a complex hurdle, I sincerely hope this guide has provided you with the understanding and practical insights to make it feel genuinely achievable.
Embrace the efficiency. Embrace the accuracy. Begin your automation journey today! If you found this guide helpful or have further questions, please leave a comment. Let's build a more automated and efficient engineering community together.
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