High fidelity vibration acquisition platform for condition monitoring
Abstract
This paper shows how recent advances in MEMS technology have brought acceleration sensors to the forefront to compete with piezoelectric sensors in condition monitoring applications; We’ll also discuss how to use the new development platform that makes all this possible.
Introduction to Condition Monitoring (CbM) and Predictive Maintenance (PdM)
Condition monitoring (CbM) involves the use of sensors to measure the current health status in order to monitor a machine or asset. Predictive maintenance (PdM) requires a combination of techniques such as CbM, machine learning, and analytics to predict future asset maintenance cycles or possible failures. Global device health monitoring is expected to evolve significantly, making it imperative to know and understand key trends. More and more CbM companies began to adopt PdM to improve their product differentiation advantages. When it comes to CbM, maintenance and equipment managers now have new options, such as wireless units, as well as lower-cost, high-performance units. While the infrastructure of most CbM systems remains the same, we can now integrate new MEMS technologies directly into systems that previously used primarily piezoelectric sensors or were not monitored due to cost barriers.
Condition monitoring – Engineering challenges and design decisions
In a typical CbM signal chain design, many different engineering specifications and techniques need to be considered, all of which are constantly improving and increasing in complexity. There are now various types of customers who may have expertise in one area, such as algorithm development (software only) or hardware design (hardware only), but are not always proficient in both.
For developers who want to focus on algorithm development, they require a data repository that accurately predicts asset failures and downtime. They don’t want to design hardware or fix data integrity failures; You want to use really high fidelity data. Similarly, for hardware engineers looking to improve system reliability or reduce costs, they need a solution that can be easily connected to existing infrastructure so that existing solutions can be benchmarked. They need to access the data in a readable format that is easy to use and export, so as not to waste time evaluating performance.
Many system-level challenges can be solved with a platform approach – from sensors to algorithm development – to support all types of customers.
What is CN0549? How does it help extend the life of the device?
CN0549 CbM development platform
The CN0549 Condition Monitoring platform is a high-performance, off-the-shelf hardware and software solution for transferring high-fidelity vibration data streams from assets to algorithmic/machine learning development environments. The platform provides hardware experts with a tested and proven system solution that provides highly accurate data acquisition, reliable mechanical coupling to assets, and high-performance wideband vibration sensors. All hardware design files are also available to help you easily integrate into the products you design. The CN0549 is also attractive to software experts, as it Outlines the hardware challenges of the condition monitoring signal chain, allowing software teams and data experts to directly start developing machine learning algorithms. Important features and benefits include:
Easy to install into assets while maintaining the integrity of mechanically coupled signals
Wideband wide MEMS accelerometer sensor with IEPE data output format
IEPE, high-fidelity Data acquisition (DAQ) solution with analog input bandwidth from DC to 54 kHz
Embedded gateways capture and store raw data for local or networked processing
Real-time display of frequency domain data using ADI’s IIO oscilloscope applications
Stream sensor data directly to popular data analysis tools such as Python and MATLAB®