Condition Monitoring Software

Condition Monitoring for Predictive and Preventive Maintenance

Machine Vibration Monitoring Application:

Objective: Monitor machine vibration to proactively identify potential issues and prevent failures. Challenges: Detect slight performance changes in multiple machines with rotating motion. Real-time access to information from machines located in remote and hard-to-reach areas. Solution: Leveraging QM30VT Vibration and Temperature Sensors, Q45VTP Wireless Sensor Nodes, and a DXM Wireless Controller.

Customer Benefits:

Cost Reduction: Early detection of potential problems enables scheduled full-spectrum vibration analysis and proactive service, reducing equipment failures and associated damages. Increased Uptime: Utilize collected data to optimize service schedules, minimizing unplanned downtime due to machine failures. Ease of Use: Wireless system facilitates communication with remote and inaccessible equipment without the need for extensive wiring. A machine learning algorithm simplifies establishing baseline values and setting alert thresholds.

Machine Vibration: A Precursor to Potential Issues

Machine vibration often results from imbalanced, misaligned, loose, or worn parts, potentially causing damage to the machine. Monitoring various assets such as motors, pumps, compressors, fans, blowers, and gearboxes for increased vibration levels helps detect problems before they escalate, mitigating additional damage or unplanned downtime.

Asset Monitoring and Data Access:

Pairing a QM30VT Vibration and Temperature sensor with a Q45VTP Wireless Sensor Node allows remote monitoring of rotating assets’ health, including motors, pumps, compressors, fans, blowers, and gearboxes. Installation is simplified using standard or magnetic brackets or two-sided thermal transfer mounting tape. The QM30VT measures temperature and RMS velocity by default, transmitting data to a DXM Wireless Controller via the Q45VTP Wireless Sensor Node.

Establishing Performance Baselines:

Each motor possesses unique vibration characteristics requiring individual baseline measurements. The DXM Wireless Controller employs a machine learning algorithm provided by Banner Engineering to establish unique performance baselines for each machine and define alert thresholds. If thresholds are exceeded, the DXM alerts staff via email or text. The Q45VTP Node’s onboard LED provides local alert indication, and a signal can be sent to a wireless TL70 Tower Light for high-visibility status indication.