Predictive Maintenance for Wastewater Treatment Plants (Turbine Case Study)

Keeping Wastewater Treatment Plants Running Smoothly

In the wastewater industry, any unplanned downtime can disrupt operations, increase energy costs, and risk compliance with regulatory standards. Sensfix works with wastewater plants to help the digitize and streamline key maintenance and operations processes to reduce downtime and speed up issue resolution. In this article, we’ll give an example of one use case – using predictive analytics to identify turbine (or motor) issues before the unit goes down.

In the water treatment and wastewater industries, turbines play a critical role in driving aeration systems and moving water through treatment stages. To address the risk of failure, Sensfix has developed a powerful AI-driven predictive maintenance solution that uses smart sensors and real-time analytics to detect problems before they happen.

The multi-modal predictive maintenance solution

At the heart of Sensfix’s approach is a custom-designed multi-sensor unit that combines data from four critical sources: acceleration, audio, temperature, and voltage. When mounted on a turbine, this sensor delivers a comprehensive snapshot of equipment health:

• Acceleration (Vibration): Detects early signs of imbalance, misalignment, or bearing wear — issues that often lead to catastrophic failure if left unchecked.
• Audio (Acoustic Signature): Captures subtle changes in sound patterns, allowing the system to distinguish between normal operational noise and anomalies like cavitation, grinding, or shaft looseness.
• Temperature: Monitors overheating due to friction or electrical faults, helping to prevent thermal damage or fire risk.
• Voltage: Tracks electrical load irregularities that may indicate motor stress, insulation breakdown, or power supply issues.

How Predictive Maintenance for WWTP Motors Works

Using these four inputs, the Sensfix AI engine analyzes patterns in real time to generate a predictive health score for each turbine. If the system detects abnormal vibration paired with a rise in temperature and a spike in voltage draw, it flags a potential bearing failure or shaft misalignment. The platform then automatically schedules a maintenance task, alerts the operations team, and provides actionable insights — all without manual inspection or guesswork.

The Result: Less Downtime, Lower Costs

By combining multiple sensor signals into a single AI-powered decision layer, Sensfix enables wastewater facilities to act before equipment fails. This approach helps:

• Reduce emergency repairs
• Extend equipment life
• Save energy
• Ensure consistent regulatory compliance

For municipalities and operators facing tight budgets and aging infrastructure, this type of predictive maintenance isn’t just smart — it’s essential. To learn more about this case (and the entire WWTP AI-based solution, click here to schedule a call with a representative).