The Analysis of Gearbox Fault Diagnosis Research Based on the EMD and Hilbert Envelope Demodulation

Han, Guo Dong; Wan, Shu Ting; Lv, Zhan Jie; Liu, Rong Hai; Wang, Jin; Gui, Tang

doi:10.4028/www.scientific.net/amr.926-930.1800

Cited by 4 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The HHT method uses a time adaptive operation known as empirical mode decomposition (EMD) to decompose the signal into a group of complete and orthogonal components, denoted as intrinsic mode functions (IMFs), that represent the intrinsic oscillation modes of the fault-related components of a vibration signal. The HHT method was shown to outperform wavelet transform in rotational-machine fault diagnosis in [28][29][30]. To capture the advantages of the HHT, several fault detection tools combine EMD with other methods, such as envelope analysis and the wavelet-based technique.…”

Section: Introductionmentioning

confidence: 99%

A Reliable Fault Diagnosis Method for a Gearbox System with Varying Rotational Speeds

Nguyen

Prosvirin

Kim

2020

Sensors

View full text Add to dashboard Cite

The vibration signals of gearbox gear fault signatures are informative components that can be used for gearbox fault diagnosis and early fault detection. However, the vibration signals are normally non-linear and non-stationary, and they contain background noise caused by data acquisition systems and the interference of other machine elements. Especially in conditions with varying rotational speeds, the informative components are blended with complex, unwanted components inside the vibration signal. Thus, to use the informative components from a vibration signal for gearbox fault diagnosis, the noise needs to be properly distilled from the informational signal as much as possible before analysis. This paper proposes a novel gearbox fault diagnosis method based on an adaptive noise reducer–based Gaussian reference signal (ANR-GRS) technique that can significantly reduce noise and improve classification from a one-against-one, multiclass support vector machine (OAOMCSVM) for the fault types of a gearbox. The ANR-GRS processes the shaft rotation speed to access and remove noise components in the narrowbands between two consecutive sideband frequencies along the frequency spectrum of a vibration signal, enabling the removal of enormous noise components with minimal distortion to the informative signal. The optimal output signal from the ANR-GRS is then extracted into many signal feature vectors to generate a qualified classification dataset. Finally, the OAOMCSVM classifies the health states of an experimental gearbox using the dataset of extracted features. The signal processing and classification paths are generated using the experimental testbed. The results indicate that the proposed method is reliable for fault diagnosis in a varying rotational speed gearbox system.

show abstract

Section: Introductionmentioning

confidence: 99%

A Reliable Fault Diagnosis Method for a Gearbox System with Varying Rotational Speeds

Nguyen

Prosvirin

Kim

2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Some signal processing methods are applied in order to preprocess the raw vibration signals [12,[34][35][36]. Chibani et al [37] designed a novel filter in the finite frequency range to overcome the conservatism generated.…”

Section: Introductionmentioning

confidence: 99%

Rolling Bearing Incipient Fault Detection Based on a Multi-Resolution Singular Value Decomposition

Luo

Zhang

2019

Applied Sciences

View full text Add to dashboard Cite

The periodic impulse characteristics caused by rolling bearing damage are weak in the incipient failure stage. Thus, these characteristics are always drowned out by background noise and other harmonic interference. A novel approach based on multi-resolution singular value decomposition (MRSVD) is proposed in order to extract the periodic impulse characteristics for incipient fault detection. With the MRSVD method, the vibration signal is first decomposed to obtain a group of approximate signals and detailed signals with different resolutions. The first detail signal is mainly composed of noise and the last approximate signal is mainly composed of harmonic interference. Combined with the kurtosis index, the hidden periodic impulse signal will be extracted from the detail signals (in addition to the first detail signal). Thus, the incipient fault detection of a rolling bearing can be fulfilled according to the envelope demodulation spectrum of the extracted periodic impulse signal. The effectiveness of the proposed method has been demonstrated with both simulation and experimental analyses.

show abstract

Asymmetric optical links using monolithic III-nitride diodes

Wang

Gao

et al. 2021

Opt. Lett.

View full text Add to dashboard Cite

Multiple-quantum well (MQW) III-nitride diodes can both emit and detect light. In particular, a III-nitride diode can absorb shorter-wavelength photons generated from another III-nitride diode that shares an identical MQW structure because of the spectral overlap between the emission and detection spectra of the III-nitride diode, which establishes a wireless visible light communication system using two identical III-nitride diodes. Moreover, a wireless light communication system using a modulating retro-reflector (MRR) enables asymmetric optical links, which forms a two-way optical link using a single transmitter and receiver. Here, in association with an MRR, we propose, fabricate, and characterize asymmetric optical links using monolithic III-nitride diodes, where one III-nitride diode functions as a transmitter to emit light, an MRR reflects light with the encoded information, another monolithically integrated III-nitride diode serves as a receiver to absorb the reflected light to convert optical signals into electrical ones, and the encoded information is finally decoded. Advanced monolithic III-nitride asymmetric optical links can be developed toward Internet of Things (IoT) deployment based on such multifunction devices.

show abstract

The Analysis of Gearbox Fault Diagnosis Research Based on the EMD and Hilbert Envelope Demodulation

Cited by 4 publications

References 0 publications

A Reliable Fault Diagnosis Method for a Gearbox System with Varying Rotational Speeds

A Reliable Fault Diagnosis Method for a Gearbox System with Varying Rotational Speeds

Rolling Bearing Incipient Fault Detection Based on a Multi-Resolution Singular Value Decomposition

Asymmetric optical links using monolithic III-nitride diodes

Contact Info

Product

Resources

About