Bearing Diagnostics of Hydro Power Plants Using Wavelet Packet Transform and a Hidden Markov Model with Orbit Curves

Abstract

The contribution of a medium-sized hydro power plant to the power grid can be either at base load or at peak load. When the latter is the most common operation mode, it increases the start and stop frequency, intensifying the hydro turbine components' degradation, such as the guide bearings. This happens due to more frequent operation in transient states, which means being outside the service point of the machines' nominal condition, consisting of speed, flow, and gross head. Such transient state operation increases the runner bearings' mechanical vibration. The readings are acquired during the runner start-ups and filtered by a DC component mean value and a wavelet packet transform. The filtered series are used to estimate the relationship between the maximum orbit curve displacement and the accumulated operating hours. The estimated equation associated with the ISO 7919-5 vibration standards establishes the sojourn times of the degradation states, sufficient to obtain the transition probability distribution. Thereafter, a triangular probability function is used to determine the observation probability distribution in each state. Both matrices are inputs required by a hidden Markov model aiming to simulate the equipment deterioration process, given a sequence of maximum orbit curve displacements.

Vibration monitoring of a hydroelectric power generation unit: Improved indicators of rotor health based on orbital analysis

“…Similar considerations arise in [19][20][21][22][23][24], where orbit shape (i.e., circular vs elliptical), directivity (i.e., forward or backward) and inclination (i.e., angle of the major axis of the ellipse with respect to one of the sensors) are recognized as relevant indicators for relative vibration analysis, as defects or faults can cause changes to the orbits [19].…”

Condition-based maintenance in hydroelectric plants: A systematic literature review

“…This type of vibration monitoring is usually adopted to identify shaft misalignment, mass imbalance, and degradation, as found in several studies. 28,64,65 When a unit runs under part-load conditions, the turbine cannot achieve optimum flow of the runner inlet and outlet, thus creating a vertex rope in the shaft system. During these unstable operating conditions, the vibration signals are very complex, and damage is more likely to occur to the runner and draft tube system.…”

“…This type of vibration monitoring is usually adopted to identify shaft misalignment, mass imbalance, and degradation, as found in several studies. 28,64,65…”

Artificial Intelligence Based Prognostic Maintenance of Renewable Energy Systems: A Review of Techniques, Challenges, and Future Research Directions

“…Based on gear run to failure and accelerated bearing degradation data, the authors reviewed the vibrations-based health indicators and their associated problems along with some suggestions for future work to further enrich the already reviewed methods. Pino, G. et al [41] devised a system to diagnose the deterioration in the guide bearings of Hydro Power Plants by using wavelet packet transform and HMM with orbit curves. The start and stop frequency of a medium-sized HPP is increased while operating at peak loads.…”