Quality aware operational transfer path analysis for gas turbines

Abstract

Operational transfer path analysis (OTPA) is a promising methodology for evaluating vibration transmission in mechanical equipment at industrial sites. However, its accuracy requires high-quality vibration data. The long-standing absence of true benchmarks due to practical constraints has hindered the assessment and improvement of data quality (DQ) for OTPA. Motivated by data quality awareness, this paper proposes quality aware OTPA, which addresses this gap by defining and optimizing a heuristic DQ index. First, based on the central limit theorem, we analyze the statistical distribution characteristics of potential data errors and identify factors affecting transmissibility error. Then, by constructing the DQ index as the objective function, we iteratively optimize it to update both the data subset and transmissibility synchronously. Finally, the iteration terminates when the data subset stabilizes, and this final subset serves as input for OTPA. Validation was performed on simulation, test bed, and gas turbine vibration datasets. Comparative results indicate that the proposed method is more accurate and robust. Without additional experimental work, it improves the analysis accuracy and reliability of OTPA. In summary, this method advances the maturity and practical applicability of OTPA for large equipment like gas turbines, supporting vibration reduction and health management.