Developed for hydropower
We understand the unique dynamics and constraints of small hydropower plants.
Conventional vibration monitoring systems typically rely on simple vibration velocity threshold values and operate without considering the highly variable operating conditions of a hydropower plant. They provide binary “in/out of limit” alerts – but no context, no interpretation, and no early warning based on trends. As a result, critical issues are often detected too late, or not at all. In many cases, such systems are offered by various manufacturers – often focusing only on generator components. They ignore other key components like turbine bearings or gearboxes and do not incorporate the system-wide mechanical and operational interrelations, resulting in a fragmented view of the plant’s condition.
This leads to three main issues:
- Lack of operational context: The same vibration levels may be harmless in one operating condition and critical in another.
- Momentary snapshots only: Many existing systems still rely on manual, periodic measurements. These can miss faults that develop under specific load conditions or environmental influences.
- No root cause diagnosis: Typical systems can’t distinguish whether vibration is caused by mechanical wear, hydraulic instability, or environmental noise.
Global Hydro takes a different approach – monitoring the entire system with deep hydropower-specific expertise.
General information: Vibration analysis is a core method for monitoring the health of rotating machinery – including turbines, generators, and gearboxes in hydropower plants. It helps detect issues such as imbalance, misalignment, bearing defects, or hydraulic instabilities before they lead to failure. There are two primary types of vibration analysis:
- Time-Domain Analysis: Measures overall vibration over time – the total “feel” of the machine. Useful for identifying general anomalies, but limited in pinpointing root causes.
- Frequency-Domain Analysis: Breaks down vibrations into individual frequency components using Fast Fourier Transform (FFT). This allows for more precise fault identification – e.g. differentiating between bearing wear, looseness, or hydraulic cavitation.
⚠️ Limitation of conventional methods:
Conventional systems typically rely on static thresholds in the time domain. They alert operators only after symptoms become obvious. That’s why early-stage detection is often missed - especially in systems with fluctuating operating conditions, like hydropower plants.
