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An accurate instantaneous angular speed estimation method based on a dual detector setup

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Abstract Instantaneous angular speed (IAS), or ‘true IAS’, is an inherent signature directly related to the mechanical dynamics of rotor systems and has been employed extensively in different rotating machines.… Click to show full abstract

Abstract Instantaneous angular speed (IAS), or ‘true IAS’, is an inherent signature directly related to the mechanical dynamics of rotor systems and has been employed extensively in different rotating machines. Due to various uncertainties, such as manufacturing error or the inaccurate installation of encoders, the acquired IAS signals often contains significant contents of ‘false IAS’ which can mask the small variations of IAS, lead to low accuracy and consequently affect the understanding of the dynamic behaviour of a rotor system. This study proposes a dual detector method to minimize the influence of encoder errors and hence obtain more accurate IAS estimation. Through theoretical study, it is proved that the false IAS induced by encoder errors from the two detectors have the same amplitudes but with a phase difference, whereas the true IAS components from the two detectors are identical. On this basis, an algorithm is developed firstly to acquire the encoder errors through a phase alignment operation and then estimate the true IAS after removing the estimated encoder errors. The proposed method is evaluated by both numerical simulations and experimental studies. The results show that the proposed method can more significantly suppress the encoder errors associated with encoder eccentricities in comparison with conventional reference methods, thereby yielding an accurate true IAS from the measurement. The proposed method can be particularly effective when the encoder has very low accuracy, allowing a more cost-effective IAS monitoring system to be achieved.

Keywords: true ias; method; instantaneous angular; angular speed; dual detector; encoder errors

Journal Title: Mechanical Systems and Signal Processing
Year Published: 2020

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