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Information Journal Paper

Title

IMPROVING OF THE HILBERT-HUANG TRANSFORM USINGTHE NONLINEAR ENTROPY-BASED FEATURES FOR EARLY FAULT DETECTION OF A ROTATING MACHINERY VIBRATION SIMULATOR SYSTEM

Pages

  19-29

Abstract

 Employing the powerful and adaptive method in time-frequency domain as well as proper and fault-related feature extraction is one of the most important subjects in the processing of nonlinear and non-stationary signals. The main objective of this paper 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 of 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 associating 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 ofthe 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 which is obtained from applying Hilbert transformto the main IMF 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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    APA: Copy

    HOSEINZADEH, MOHAMMAD SADEGH, ESMAEIL ZADEH KHADEM, SIAMAK, & SADOOGHI, MOHAMMAD SALEH. (2018). IMPROVING OF THE HILBERT-HUANG TRANSFORM USINGTHE NONLINEAR ENTROPY-BASED FEATURES FOR EARLY FAULT DETECTION OF A ROTATING MACHINERY VIBRATION SIMULATOR SYSTEM. MODARES MECHANICAL ENGINEERING, 18(2 ), 19-29. SID. https://sid.ir/paper/178668/en

    Vancouver: Copy

    HOSEINZADEH MOHAMMAD SADEGH, ESMAEIL ZADEH KHADEM SIAMAK, SADOOGHI MOHAMMAD SALEH. IMPROVING OF THE HILBERT-HUANG TRANSFORM USINGTHE NONLINEAR ENTROPY-BASED FEATURES FOR EARLY FAULT DETECTION OF A ROTATING MACHINERY VIBRATION SIMULATOR SYSTEM. MODARES MECHANICAL ENGINEERING[Internet]. 2018;18(2 ):19-29. Available from: https://sid.ir/paper/178668/en

    IEEE: Copy

    MOHAMMAD SADEGH HOSEINZADEH, SIAMAK ESMAEIL ZADEH KHADEM, and MOHAMMAD SALEH SADOOGHI, “IMPROVING OF THE HILBERT-HUANG TRANSFORM USINGTHE NONLINEAR ENTROPY-BASED FEATURES FOR EARLY FAULT DETECTION OF A ROTATING MACHINERY VIBRATION SIMULATOR SYSTEM,” MODARES MECHANICAL ENGINEERING, vol. 18, no. 2 , pp. 19–29, 2018, [Online]. Available: https://sid.ir/paper/178668/en

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