Abstract
This paper investigates an improved noise reduction method and its application on gearbox vibration signal de-noising. A hybrid de-noising algorithm based on local mean decomposition (LMD), sample entropy (SE), and time-frequency peak filtering (TFPF) is proposed. TFPF is a classical filter method in the time-frequency domain. However, there is a contradiction in TFPF, i.e., a good preservation for signal amplitude, but poor random noise reduction results might be obtained by selecting a short window length, whereas a serious attenuation for signal amplitude, but effective random noise reduction might be obtained by selecting a long window length. In order to make a good tradeoff between valid signal amplitude preservation and random noise reduction, LMD and SE are adopted to improve TFPF. Firstly, the original signal is decomposed into PFs by LMD, and the SE value of each product function (PF) is calculated in order to classify the numerous PFs into the useful component, mixed component, and the noise component; then short-window TFPF is employed for the useful component, long-window TFPF is employed for the mixed component, and the noise component is removed; finally, the final signal is obtained after reconstruction. The gearbox vibration signals are employed to verify the proposed algorithm, and the comparison results show that the proposed SE-LMD-TFPF has the best de-noising results compared to traditional wavelet and TFPF method.
Highlights
A gear transmission is the basic form of mechanical transmission, so the gear system is an important component of mechanical systems which have been widely used in machine tools, vehicles, construction machinery, and other equipment [1,2]
Design of sample entropy (SE)-local mean decomposition (LMD)-time-frequency peak filtering (TFPF) algorithm, there are three components are expected to be obtained, which named as the useful component, mixed component,are andexpected the noiseto be
A novel de-noising algorithm based on LMD, SampEn, and TFPF is proposed for reducing the random noise of a gear transmission system
Summary
A gear transmission is the basic form of mechanical transmission, so the gear system is an important component of mechanical systems which have been widely used in machine tools, vehicles, construction machinery, and other equipment [1,2]. The running state of the gear system is directly related to the entire mechanical equipment. Due to the reasons of complex structure and poor working conditions, the gear system is very prone to breakage, damage, and other faults. The failure analysis and fault diagnosis of the gear system are important research areas and many signal processing methods have been developed [3,4]. Signal noise greatly influences the failure analysis and fault diagnosis, which has attracted popularity to the research on noise reduction for gear systems [5,6] and many excellent achievements have been reported [7,8]. Many studies about noise reduction for gear systems have been carried out. The standard approach for extracting useful signals from a noisy background is designing an appropriate filter, Entropy 2016, 18, 414; doi:10.3390/e18110414 www.mdpi.com/journal/entropy
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