Iterative improvement in tacholess speed estimation using instantaneous error estimation for machine condition monitoring in variable speed

Abstract

Knowing the instantaneous angular speed (IAS) is crucial for monitoring the condition of variable speed rotating machinery. Thanks to advantages such as cost-saving, simplicity, and reduced installation difficulties, tacholess speed estimation (TSE) methods, based on the vibration signal itself, have attracted increasing attention in recent years. The major problem limiting the use of TSE methods in industry is that the accuracy of the IAS estimates is usually unknown. A less accurate IAS estimate implies errors in the extracted phase-time map. When this map is used for order tracking, it leads to a smeared order spectrum, thereby affecting subsequent vibration analysis. However, how the smearing of the order spectrum, introduced by phase modulation from the IAS error, can be used to further improve the accuracy of the estimated IAS has not been fully studied. This study first investigates the influence of the IAS error on the order tracked signal. It is realized that the instantaneous error of an estimated IAS can be estimated from the order tracked vibration signal. The estimated IAS can therefore be calibrated iteratively using the estimated instantaneous error in the IAS. The proposed method for iteratively improving accuracy of the estimated IAS based on the estimated instantaneous IAS error is validated using industrial data from wind turbines. While the method does add significant computational complexity, little additional human input is required beyond that of established methods. The results show the effectiveness of the method in producing IAS estimates that are several times more accurate than those given by existing methods.