Machinery Monitoring and Predictive Maintenance using MCC 172 and MCC 134 with Raspberry Pi

Thinaer is a US-based supplier of innovative IoT technology. Customers use its advanced analytics to optimize their processes and improve efficiency.

In this article, you will learn how Thinaer can provide an always-on system for collecting and monitoring data from a variety of machines and motors through their HUMS (Health Usage Monitoring System). This cost-effective solution is based on a Raspberry Pi together with an MCC 172 IEPE Measurement DAQ HAT and an MCC 134 Thermocouple Measurement DAQ HAT and uses a mix of MCC and Thinaer hard- and software.

To acquire the data, this IoT platform combines machine data with human feedback to collect data, such as vibration, temperature, voltage and current, pressure, and more. In their system, the Raspberry Pi node communicates with smart sensors via Bluetooth Low Energy. But, the temperature measurements and the vibration data provided by the smart sensors are not accurate enough. However, the high-precision analysis needed for predictive maintenance requires an outstanding accuracy of the measurements. This is where the MCC DAQ HATs come in.

The MCC 172 IEPE HAT has two channels for vibration and sound measurement using IEPE sensors such as accelerometers and microphones. The board has one 24-bit, 51.2 kS/s analog-to-digital converter per channel.

The MCC 134 has four analog inputs specifically designed for thermocouples. In addition to a resolution of 24 bits, which provides best-in-class accuracy, the MCC 134 also has a detection for broken or unconnected thermocouples. Developers can configure each channel individually to match the element connected.

The two HATs measure temperatures and vibrations, thus collecting data for analysis and strategy. The ability to stack the DAQ HATs permits Thinaer to scale its system without having to change platforms or to design and build its own hardware. Thinaer programmed the system using the C and Python libraries provided by MCC. These allow for continuous data sampling across multiple HATs.

Thanks to the use of the MCC DAQ HATs and the associated libraries, Thinaer saved both time and labor. Moreover, because of their small mechanical dimensions, the HATs fit into the existing housing. By using a proven standard product, Thinaer could avoid developing its own solution. This allows the company to concentrate on its core competence: data processing and analysis, and strategy consulting.

Get all the application notes on the MCC website.