Access OPC UA data from MATLAB and Simulink
OPC Unified Architecture (OPC UA) is an industrial communication standard developed by the OPC Foundation. OPC is vendor independent and supports all major industrial automation platforms.
OPC UA is a data exchange standard for safe, reliable, manufacturer-independent, and platform-independent industrial communication. It enables secure data exchange between hardware platforms from different vendors and across operating systems. Engineers need to access data from PLCs and industrial PCs in order to analyze the productivity of production lines, optimize machine parameters, or plan service intervals (predictive maintenance). OPC Unified Architecture is a standard protocol for accessing plant and manufacturing data.
When accessing data from PLCs or industrial PCs, engineers usually have to deal with vendor-specific industrial fieldbuses or implement Ethernet-based data exchange mechanisms (e.g., over TCP/IP or UDP). Reading data in MATLAB® or Simulink® and writing parameters to industrial devices becomes easy and vendor independent with OPC UA. This approach enables the user to directly benefit from performing data-science and other capabilities with MATLAB.
Industrial IoT with OPC UA
In the development of industrial Internet of Things (IIoT) applications, OPC UA plays an important role in IT/OT communication, controller to field device communication, controller to controller communication, secure remote access, and cloud integration. Machine (M2M) interactions using OPC UA offer wide interoperability for IoT systems. Big data solutions can easily be implemented within the MATLAB workflow.
Predictive Maintenance with OPC UA
OPC UA is supported in Industrial Communication Toolbox™. With this toolbox, engineers can make secure connections to OPC servers and easily acquire machine data for use with statistical, machine learning, and system identification methods from MATLAB in order to create algorithms for predictive maintenance.
Examples and How To
- System Identification and Control Using OPC Data (17:58)
- Detect Abrupt System Changes Using Identification Techniques (Example)
- Time Series Prediction and Forecasting for Prognosis (Example)
- Read and Write Current OPC UA Server Data (Example)
- Read Historical OPC UA Server Data (Example)
- Visualize and Preprocess OPC UA Data (Example)
- Install an OPC UA Simulation Server for OPC Examples (Example)
- Browse OPC UA Server Namespace (Example)
- Virtual Commissioning using Simulink – Part 2: Virtual Commissioning (29:45)
- Connecting Simulink Models to SIMATIC PLCSIM Advanced via OPC UA: (Example)
- Selecting PLC variables to be publicly accessible using OPC UA (Example)
- How can I interface to PLCs like the Modicon or Allen Bradley PLC with MATLAB or Simulink? - MATLAB Answers - MATLAB Central (mathworks.com) (Example)
See also: data science, big data with MATLAB, Internet of Things, predictive maintenance