A hybrid method based on Band Pass Filter and Correlation Algorithm to improve debris sensor capacity. (1st January 2017)

• Record Type: Journal Article
• Authors: Hong, Wei; Wang, Shaoping; Liu, Haokuo; Tomovic, Mileta M.; Chao, Zhang
• Is Part Of: Mechanical systems and signal processing. Volume 82(2017)
• Page Start: 1
• Page End: 12
• Publication Date: 2017-01-01
• Subjects: Inductive debris sensor -- Real-time oil monitoring -- Signal processing -- Correlation Algorithm -- Band Pass Filter; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2015.10.002
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: The inductive debris detection is an effective method for monitoring mechanical wear, and could be used to prevent serious accidents. However, debris detection during early phase of mechanical wear, when small debris (<100 um) is generated, requires that the sensor has high sensitivity with respect to background noise. In order to detect smaller debris by existing sensors, this paper presents a hybrid method which combines Band Pass Filter and Correlation Algorithm to improve sensor signal-to-noise ratio (SNR). The simulation results indicate that the SNR will be improved at least 2.67 times after signal processing. In other words, this method ensures debris identification when the sensor's SNR is bigger than −3 dB. Thus, smaller debris will be detected in the same SNR. Finally, effectiveness of the proposed method is experimentally validated. Highlights: We build correlation model to study interference elimination for debris sensors. We present a hybrid method to improve debris sensor capacity. The SNR will be improved to at least 2.67 times by this method. Smaller debris can be detected by this method in same initial SNR.