In industrial environments, unplanned downtime isn’t just inconvenient, it’s expensive. Equipment failures can halt production, compromise safety, and disrupt operations. While traditional maintenance strategies like reactive repair or scheduled servicing have long been the norm, they often fall short in efficiency and cost-effectiveness.
That’s why many engineers and system designers are turning to predictive maintenance (PdM) – a proactive, data-driven approach that uses real-time monitoring and analytics to anticipate failures before they happen. By identifying early warning signs of wear or malfunction, PdM enables smarter maintenance decisions, reduces downtime, and extends equipment life.
At Digilent, we support this shift by providing accessible, high-performance tools that help engineers prototype, test, and deploy predictive maintenance systems. Whether you’re building a proof-of-concept in the lab or developing an edge-ready IIoT solution, our hardware and software platforms are designed to help you get there faster and with confidence.
This guide explores how Digilent products can support each stage of a PdM system from data acquisition to real-time analysis and visualization.
The Architecture of a Predictive Maintenance System
A successful PdM system typically includes three core components:
- Data Acquisition
- Processing and Analysis
- Connectivity and Visualization
Digilent products are well-suited to support each of these stages.
Data Acquisition
The first step in PdM is capturing high-fidelity data from industrial assets. This includes vibration, temperature, current, and other signals that may indicate wear or failure.
- Analog Discovery Pro ADP3450
A professional-grade mixed-signal oscilloscope with 4 analog channels and 16 digital channels. It supports up to 0.5 GS/s sampling and 14-bit resolution, making it ideal for capturing subtle changes in vibration or current signals. It also includes a waveform generator, logic analyzer, and more, all accessible via Digilent’s free Waveforms software. - Analog Discovery 3
A compact, USB-powered device offering similar core functionality for educational or portable setups. It’s ideal for lab-based PdM experiments or classroom demonstrations.
These tools can interface with sensors such as accelerometers (for vibration), thermocouples (for temperature), and current clamps. For example, a failing motor bearing may show a shift in its vibration frequency, which is something the ADP3450 can detect with precision.
Processing and Analysis
Raw sensor data must be processed to extract meaningful insights. Real-time edge processing is often essential to reduce latency and handle large datasets efficiently.
- Eclypse Z7
Features a Zynq-7000 SoC combining an ARM processor with an Artix-7 FPGA. This hybrid architecture supports high-speed data acquisition and real-time analysis, such as Fast Fourier Transforms (FFT) for vibration spectral analysis. - Nexys A7
A versatile FPGA board ideal for implementing custom logic for anomaly detection, signal filtering, and other PdM algorithms. - Waveforms Software
Enables real-time visualization, scripting (Python, JavaScript), and automation. Engineers can set up threshold-based alerts or create custom analysis routines.
This stage transforms raw data into actionable intelligence by detecting anomalies before they become failures.
Connectivity and Visualization
Once analyzed, data must be communicated to a central system for monitoring and decision-making.
Digilent devices support USB and Ethernet connectivity, allowing integration with cloud dashboards, SCADA systems, or enterprise platforms. Importantly, they can transmit processed data, reducing bandwidth usage and improving scalability.
WaveForms also supports scripting and remote control, enabling integration with custom dashboards or alert systems.
Example Workflow: Vibration-Based Predictive Maintenance
Here’s a simplified PdM workflow using Digilent tools:
- Sensor Integration: An accelerometer connects to the ADP3450’s analog input.
- Baseline Capture: The ADP3450 records the vibration profile of a healthy motor.
- Real-Time Analysis: An FPGA (Eclypse Z7 or Nexys A7) performs FFT on incoming vibration data.
- Anomaly Detection: The system compares live data to the baseline. Deviations trigger alerts.
- Notification: The ARM processor on the Zynq-7000 SoC sends alerts via Ethernet to a dashboard or maintenance system.
This setup allows maintenance teams to intervene before a failure occurs, which means saving you time, money, and resources.
Why Digilent?
Digilent’s test and measurement tools are designed for flexibility, precision, and accessibility. Whether you’re building a PdM system for industrial deployment or teaching students about IIoT, our products offer:
- High-resolution, multi-channel data acquisition
- Real-time edge processing with FPGA and SoC platforms
- Intuitive software for visualization and automation
- Scalable connectivity options
Ready to Get Started?
Whether you’re exploring predictive maintenance for the first time or looking to enhance an existing system, Digilent provides the tools to help you move from concept to implementation. Browse our full catalog of products, and start building smarter, more reliable systems today.
If you have questions or want to share your PdM project, we’d love to hear from you! Reach out to our team with questions on our forum!
