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Mechanical engineers design and utilize sensors in products and systems, with applications ranging from consumer products to engines to biomedical instruments to manufacturing. As they make the parts, they have to test them to validate they work as they should. One example of these tests could be material testing, where the test evaluates the mechanical properties of materials. For example, fatigue tests involve repeatedly applying stress to determine durability under cyclic loading. Automating tests like these would be a useful practice for speed, cost saving, and scalability. By collecting data regularly from these tests, one can precisely record and analyze it for detailed insights. This will identify potential issues early in the development cycle, allowing for timely adjustments and improvements.
Let’s take an MPU6050 sensor as a hobbyist example. This digital 6-axis accelerometer and gyroscope can read linear acceleration and angular velocity, which is helpful for mechanical engineers tracking vibrations and movements in their engines to detect misfires or other issues or in their suspension systems to enhance vehicle stability and safety. This can be quickly configured as a movement sensor through the Viam app.
Using these sensors, you can characterize what regular operation is in terms of acceleration and what an anomaly would look like. To illustrate, if you have a laundry machine with a movement sensor attached to it, you can collect data on how a typical load would make the machine move and use that data to figure out what nominal readings look like before testing different materials to analyze how it affects the sensor output. So, if you accidentally put four duvets in the machine, you can detect this overloaded state by looking at the data anomalies and can stop the laundry session if needed.
For industrial applications, higher-end sensors and specialist acquisition systems would be better than the MPU6050 to get more precise and higher-frequency measurements. The MPU6050 is only $1, whereas industrial-grade sensors, such as General-Purpose Piezoelectric Accelerometers, can be up to $1000.
Analysis of big datasets from sensors has primarily been specialized to the role of data scientists, but it’s clear to see how it complements traditional mechanical engineering requirements to improve reliability, predict failures, and innovate next-gen equipment development. Viam’s Data Management service allows for configurable data capture from various sensors and streamlines data handling with querying capabilities. This opens up a world of possibilities for mechanical engineers:
- It enables detailed sensor data analysis to validate new designs' performance and reliability, leading to better products.
- It speeds up the prototyping process by quickly providing insights from sensor data, allowing for rapid iterations and improvements.
- It helps identify the root causes of failures or defects by analyzing data patterns, leading to more robust designs. It also allows for predicting equipment failures before they occur, reducing downtime and maintenance costs.
- It facilitates filtering large datasets to focus on specific parameters or timeframes, making data analysis more manageable and targeted. No mechanical engineer enjoys looking at an Excel sheet with two thousand columns and a hundred rows, right?
All of these lead to more robust, innovative designs and efficient data handling, significantly improving decision-making and reducing maintenance costs. Beyond the built-in sensor drivers, support for specialized testing instruments like a strain gauge or thermocouple can also be added through a custom module. Start using Viam today to select appropriate sensors for your specific applications and learn how to query their data. It’s time to optimize!
Technical content review by: Raymond Bjorkman, Christopher Payne, Nick Hehr
