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An investigation on bolt stress ultrasonic measurement based on acoustic time difference algorithm with adaptive hybrid extended Kalman filter.
- Source :
-
Measurement (02632241) . Dec2021, Vol. 186, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- • Acoustic time difference algorithm can reduce error of acoustic time difference. • Acoustic time difference algorithm can improve bolt stress detection accuracy. • Kalman nonlinear filter is constructed to select initial values and observe noise. • Filter and cross-correlation algorithm can estimate the acoustic time difference. Ultrasonic measurement is an effective technical method for the bolt stress detection of the precise structural connection. This paper proposed an acoustic time difference algorithm based on adaptive hybrid extended Kalman filter to reduce the calculation error of acoustic time difference in bolt stress ultrasonic measurement. The initial value is firstly selected by particle filter algorithm, and the noise variance is measured by the Sage-Husa estimator. Then, a Kalman nonlinear filter is constructed to adaptively select initial values and observe noise. Thirdly, the filter and cross-correlation algorithm are used to accurately estimate the acoustic time difference. Finally, the signal simulation method and the ultrasonic measurement platform of bolt axial stress are built, and the proposed algorithm and the traditional algorithm are respectively used to calibrate and measure the correspondence between acoustic time difference and axial stress of the M8 coarse tooth half-thread bolt. The bolt tightening experimental and simulation results showed that the processed signal algorithm is verified and can effectively improve the measurement accuracy of bolt axial stress. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02632241
- Volume :
- 186
- Database :
- Academic Search Index
- Journal :
- Measurement (02632241)
- Publication Type :
- Academic Journal
- Accession number :
- 153413644
- Full Text :
- https://doi.org/10.1016/j.measurement.2021.110223