Infrasonic leakage signal processing of PE pipeline based on improved AOK-TFR analysis
Source abstract
Abstract
Aiming at the problem of cross-interference and low resolution of PE (polyethylene) pipeline leakage infrasound signal, a PE pipeline infrasound leakage signal processing method based on improved AOK-TFR (adaptive optimal kernel time-frequency distribution) analysis is proposed. Firstly, the original signal of infrasonic wave is collected by experiment and the leakage signal is preliminarily identified. Then, the leakage signal of denoising preprocessing is adaptively decomposed by LCD. The KPCA method and convex hull estimation method in genetic algorithm are used to quantitatively calculate the optimal kernel function volume α value and the optimal expansion function σΨ value in the constraint condition of AOK-TFR analysis, and the improved AOK-TFR analysis method is obtained. Then, the improved AOK-TFR is used to calculate the LCD decomposition signal step by step. Finally, through Fourier transform and MATLAB software processing, a clearer signal time-frequency spectrum is obtained. The results show that compared with the preliminary identification of leakage signals, the WVD distribution method and the improved AOK-TFR method, the improved AOK-TFR analysis improves the overall average identification accuracy of the leakage signal by 47.48%, 26.23% and 22.13%, respectively, and reaches 85.87%, which enhances the suppression effect of cross-interference of the signal, thereby improving the identification effect of pipeline leakage.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Non-Destructive Testing Techniques · Water Systems and Optimization · High voltage insulation and dielectric phenomena
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Changzhou University
Changzhou Branch of Jiangsu Special Equipment Safety Supervision and Inspection Institute
Funding
Jiangsu Province Carbon Peak Carbon Neutral Science and Technology Innovation Fund · Basic Science (Natural Science) Research Project of Jiangsu Province
References (28)
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