Rational Resampling Ratio as Enhancement to Shaft Imbalance Detection

Trend analysis is one of the most powerful techniques for monitoring the technical condition of individual mechanical components of rotating machinery. It is based on extraction of characteristic signal components according to kinetostatic configuration of the machine drivetrain. It has been used for decades and is well-understood. However, classical trend analysis is based on some assumptions which have resulted from the limited computational power of embedded systems years ago. This paper tries to answer a question on whether the assumption of a single signal resampling path for calculation of signal components generated by shafts with rational transmission ratio is valid. The study was conducted using an extensive imbalance test on a medium-power test rig. The paper originally demonstrates that application of an advanced resampling algorithm does not significantly influence the overall trend increase, but it is of utmost importance when trend variance is of interest.

Electrolyte Imbalance Determination of a Vanadium Redox Flow Battery by Potential-Step Analysis of the Initial Charging

Vanadium redox flow batteries (VRFB) suffer from capacity fades owing to side reactions and crossover effects through the membrane. These processes lead to a deviation of the optimal initial average oxidation state (AOS=+3.5) of vanadium species in both half-cell electrolytes. To rebalance the electrolyte solutions, it is first necessary to determine the current AOS. In this study, a new method was developed that enables an accurate determination of the AOS. A potential-step analysis was performed with mixed electrolyte solutions of both half-cells during the initial charging. The potential was recorded with a simple open-circuit voltage (OCV) cell, and the potential-steps were analyzed. A correlation between the duration of the potential plateaus in the OCV and the amount of vanadium ions of a certain oxidation state in the half-cell electrolytes was found and used to precisely determine the AOS with a maximum error of 3.6 %.