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Lookup NU author(s): Dr Xiang XieORCiD
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Transit-time multipath ultrasonic flow meters (TM-UFMs) have been widely employed for measuring flowrate of gas and liquid. However, its applicability is still dragged by the difficulties to describe the physical model by precise mathematical expressions and to reduce the deviations led by the simplified principle models. Besides, fault-tolerance, including fault diagnosis and measure maintaining method, namely, rectification, is of great value in practical engineering, but there are few effective methods provided ever since to provide a solution for faulty UFMs. Therefore, data integration for TM-UFMs is one of the complications to obtain the accurate measurements, except for precise transit-time detection and improved transducers and circuits. This paper proposes a novel data integration method for TM-UFM calibration, as well as fault diagnosis and rectification based on particle swarm optimized support vector machines (PSO-SVM). Besides, extensive experiments have been conducted on a platform of TM-UFMs, and the results have illustrated the effectiveness of this method. The PSO-SVM-based models trained by the proposed method lead to a decrease of deviations to ±1% (full scale) in normal state for data integration, compared with ±2% deviations when a traditional method is adopted. When there exist one or two dysfunctional acoustic paths, the method diagnoses the faulty paths and maintains the measurement with deviations below ±2%.
Author(s): Tang XY, Xie X, Fan B, Sun YX
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Instrumentation and Measurement
Online publication date: 05/02/2018
Acceptance date: 06/12/2017
ISSN (print): 0018-9456
ISSN (electronic): 1557-9662
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