Volume 18, Issue 2 (4-2018)                   Modares Mechanical Engineering 2018, 18(2): 19-29 | Back to browse issues page

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Hoseinzadeh M S, Esmaeilzadeh Khadem S, Sadooghi M S. Improving of the Hilbert-Huang transform using the nonlinear entropy-based features for early fault detection of a rotating machinery vibration simulator system. Modares Mechanical Engineering 2018; 18 (2) :19-29
URL: http://mme.modares.ac.ir/article-15-1483-en.html
1- tarbiat modares university
Abstract:   (7927 Views)
The main objective is to improve Hilbert-Huang transform using the advantages of non-linear entropy-based features in the time and frequency domain to reduce noise effects. In addition, applying appropriate entropy-based features lead to restrict information redundancy and overcome the need for dimension reduction, in the fault detection of a rotating system. To modify the Hilbert-Huang method, the effect of added noise on various types of nonlinear entropy-based features is investigated for each intrinsic mode functions (IMFs) which extracted by ensemble empirical mode decomposition algorithm. Considering the approximate entropy (ApEn) sensitivity to noise, an evaluation index is presented for selecting the proper amplitude of the added noise based on the approximate entropy and mutual information coefficient of the different IMFs. Subsequently, taking into account the high capability of permutation entropy (PeEn) and marginal Hilbert spectrum entropy (MHE) in the signal characteristic, a threshold is determined for fault detection based on their values associated to the main IMF which has the highest value of mutual information coefficient. As a result, the permutation entropy values and marginal Hilbert spectrum entropy of the main IMF can be used for detection of any deviation from normal operation of the rotor bearings system, regardless of the fault type. Consequently, to determine the type of defect, the higher-order spectra have been used.The bi-spectrum of envelope is calculated. This bi-spectrum is employed to identify the coupling between the rotating frequency and fault-characteristic frequencies, for misalignment and unbalanced fault diagnosis of a rotating machinery vibration simulation system
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Article Type: Research Article | Subject: Vibration
Received: 2017/09/9 | Accepted: 2018/01/5 | Published: 2018/01/23

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