Working Fluid Level Extraction Technique Using Time-frequency Peak Filtering Based on Voice Activity Detection

doi:10.11885/j.issn.1674-5086.2017.04.04.01

Abstract

Abstract: Several types of noises are generated in an oil jacket annulus, which complicates the fluid level reflection signal measurement. The real position of the fluid level reflection wave could not be accurately identified owing to interference. Thus, the time-frequency peak filtering (TFPF) method is applied, along with the voice activity detection (VAD) method in voice signal processing, to perform effective extraction of the working fluid level wave. The VAD-TFPF method first uses the short-time energy and double-threshold VAD method with a zero-crossing rate, divides the oil well signal measured using the acoustic method, and determines the effective signal data segment and data segment close to zero; then, TFPF with different window lengths is applied to perform filtering to two types of data segments. The filtering experiment and analysis are carried out to measured data under different noise intensities; the results indicate that this method has a stronger identification ability toward working fluid level waves than the wavelet threshold filtering method and is preferable for background noise suppression or for effective wave extraction.

Key words: working fluid level, time-frequency peak filtering, voice activity detection, filtering extraction, noise suppression

CLC Number:

TE19

LIU Yanping, WU Jie, CHEN Yanjun, LIU Li. Working Fluid Level Extraction Technique Using Time-frequency Peak Filtering Based on Voice Activity Detection[J]. 西南石油大学学报(自然科学版), 2018, 40(2): 169-175.

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URL: http://journal15.magtechjournal.com/Jwk_xnzk/EN/10.11885/j.issn.1674-5086.2017.04.04.01

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