A new fluctuation assessment method for the step response signals of pressure sensors. (1st March 2019)

• Record Type: Journal Article
• Authors: Wang, Zhongyu; Yao, Zhenjian; Li, Cheng; Lv, Jing; Fu, Huadong; Mourelatos, Zissimos P.
• Is Part Of: Mechanical systems and signal processing. Volume 118(2019)
• Page Start: 1
• Page End: 12
• Publication Date: 2019-03-01
• Subjects: Dynamic measurement -- Fluctuation -- Signal processing -- Step response -- Pressure sensor; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2018.08.035
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A method to assess the fluctuation of step response signals is proposed. A fluctuation measure indicator is defined to quantify the fluctuation. An ordered weighted mean method is proposed to obtain the overall signal fluctuation. Abstract: In dynamic measurement of a step pressure, the response signals from the sensor are usually influenced by mechanical vibrations. It is difficult to accurately describe the dynamic characteristics of step pressures by directly using the collected response signals therefore leading to unsatisfactory measurement results. In this paper, a new method is proposed to quantitatively assess the fluctuation characteristics of sensor step response signals. Firstly, the collected response signal is partitioned into subsequences, and a series of reconstructed sequences are obtained from each subsequence by introducing the delay and the embedding dimension. Then, an evaluation indicator named fluctuation measure is defined for each subsequence as the average of a specific fuzzy operator for any two reconstructed sequences. Finally, the composite fluctuation measure of the response signal is calculated by taking the ordered weighted mean of fluctuation measures of these subsequences. Measurement experiments with different sensors and vibration conditions are carried out to validate the performance of our method. The results show that the proposed method works well in quantifying the fluctuation characteristics of step response signals. Comparative experiments also demonstrate the superiority of the proposed method over existing approaches.