Banner Engineering’s Wireless Solution Kit enables the monitoring of parameters such as vibrations and temperature, forming the basis for predictive maintenance applications. The technology hosts simple construction, easy installation, and wireless networking, enabling plant engineers to collect remote data and visualize it through warnings and alarms.
The kit presents itself as a plug-and-play solution, requiring zero programming. Nodes can be bound through a GUI on the HMI screen, after which data collection can be carried out. The HMI also gives the user a comprehensive display of the collected data and allows warnings and alarms to be set.
The solution kit comes pre-programmed with a DXM100 wireless controller, a1 0.1-inch touchscreen, and a 5-port industrial ethernet switch. This allows the raw data to be transmitted to other aggregation sites such as a cloud server via the company’s VPN, from where it can be integrated into a pre-existing analytics system. The kit itself can show up to 7 days of data history while logging historical data for over 30 days in CSV format.
One particular application for the solutions kit is Vibration Monitoring which gives plant engineers the ability to monitor assets that involve rotating motion such as motors, pumps, fans, etc. Such monitoring capabilities are essential in today’s complex industrial landscape as it reduces unexpected downtime through early detection of potential faults. Furthermore, through efficient tracking mechanisms, a trend can be extended to other components of the factory floor as well.
Generally, two factors majorly determine the vibration characteristic of an asset:
Parameters are measured through Banner’s vibration sensors, which are then sent wirelessly to the DXM controller. The controller can be programmed, establishing baselines and warning thresholds for the collected data. The Wireless Solutions Kit collects data from the sensors and displays it on the interface of your choosing. Backward compatibility is embedded within the kit, meaning legacy systems can be integrated into the predictive maintenance cycle as well.
The advanced capabilities of the solutions kit come into play when the Machine Learning algorithm automatically establishes baseline using the first 300 data samples, followed by early warnings & alarm thresholds for poor asset conditions.
Furthermore, as data can be displayed both on the HMI screen as well as relayed to other storage, both machine operators and data engineers can tap into its potential to increase the operational efficiency of plant assets.
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