A fault diagnosis method for planetary gearboxes under non-stationary working conditions using improved Vold-Kalman filter and multi-scale sample entropy

Li, Yongbo; Feng, Ke; Liang, Xiaodong; Zuo, Ming J.

doi:10.1016/j.jsv.2018.09.054

Cited by 109 publications

(52 citation statements)

References 35 publications

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“…Substituting Eqs. (6), (7) and (9) into Eq. (4), balancing the terms multiplied by sin( t) and cos( t) , and neglecting all the time derivatives terms, the following equations are obtained: Substituting Eqs.…”

Section: Theoretical Solutions Of the Output Voltage Of The Behmentioning

confidence: 99%

“…As the rapid development of new materials and electronics in the last 10 years, more and more low-powered embedded electromechanical devices and wireless sensors are used for structural health monitoring [1][2][3][4]. In order to power them continuously and realize autonomic health monitoring, energy harvesting techniques and fault diagnosis methods have been developed recently [5][6][7][8]. For example, different flow energy harvesters were designed to power the sensors embedded in high buildings or underwater environments [9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty Analysis of Bistable Vibration Energy Harvesters Based on the Improved Interval Extension

Zhou

Litak

2019

J. Vib. Eng. Technol.

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Purpose High-energy interwell oscillations of the bistable energy harvester (BEH) lead to large-amplitude output voltage. For processing and manufacturing of the BEH, small errors and deviations in the final structure cannot be totally eliminated in practice, which will make the output voltage to be apart away from the design value. Therefore, the geometrical variables, material properties and other parameters should be treated as uncertainties in analysis and are bound to their design. Method This paper presents uncertainty analysis of the BEH to reveal the influence of the uncertain system parameters on the energy harvesting performance. The improved interval extension based on the first-order Taylor series is used to predict the lower and upper bounds of the stable high-energy interwell output voltage of the BEH. In detail, uncertain mass, nonlinear stiffness term, damping, capacitance and electromechanical coupling coefficient are considered. Meanwhile, the Monte Carlo simulation is employed to verify the suitability and the accuracy of this method. Especially, this method allows researchers to define the number of the parameter α j according to the categories of uncertain variables. Results The research works show that interval of the output voltage of the BEH can be limited by reducing the number of uncertain variables, and the uncertainty of the output voltage is more sensitive to the electrical uncertain variables than the structural uncertainties. Conclusion Designers of the BEH should pay enough attention to the errors and tolerances of the electrical output design variables. Specifically, in the design of the BEH, it is more effective to improve the accuracy of the output voltage by limiting the uncertainties of electric parameters than structural parameters. Reducing the number of uncertain parameters through increasing processing precision in production of the BEH can also improve the accuracy of the output voltage.

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Section: Theoretical Solutions Of the Output Voltage Of The Behmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Uncertainty Analysis of Bistable Vibration Energy Harvesters Based on the Improved Interval Extension

Zhou

Litak

2019

J. Vib. Eng. Technol.

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“…If the fault cannot be diagnosed in a timely way, it may cause a shutdown of the whole system and even catastrophic failure. Therefore, it is significant to detect faults early and assess the fault level as early as possible to avoid catastrophic accidents and ensure the safe operation of the machinery [11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery

Wei

et al. 2019

Entropy

174

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Rotating machinery is widely applied in various types of industrial applications. As a promising field for reliability of modern industrial systems, early fault diagnosis (EFD) techniques have attracted increasing attention from both academia and industry. EFD is critical to provide appropriate information for taking necessary maintenance actions and thereby prevent severe failures and reduce financial losses. A massive amounts of research work has been conducted in last two decades to develop EFD techniques. This paper reviews and summarizes the research works on EFD of gears, rotors, and bearings. The main purpose of this paper is to serve as a guidemap for researchers in the field of early fault diagnosis. After a brief introduction of early fault diagnosis techniques, the applications of EFD of rotating machine are reviewed in two aspects: fault frequency-based methods and artificial intelligence-based methods. Finally, a summary and some new research prospects are discussed.

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“…Therefore, how to extract the incipient fault feature of a PG has become a challenging problem. In recent years, various advanced signal processing approaches have been used to extract fault features from the vibration signal of a PG [8][9][10][11][12][13][14]. For instance, G. He et al exploited a two-dimensional, centralized model for the PG, with a floating sun gear [8].…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Planetary Gearbox Based on Adaptive Order Bispectrum Slice and Fault Characteristics Energy Ratio Analysis

Shen

Shi

Zhen

et al. 2020

Sensors

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The vibration of a planetary gearbox (PG) is complex and mutually modulated, which makes the weak features of incipient fault difficult to detect. To target this problem, a novel method, based on an adaptive order bispectrum slice (AOBS) and the fault characteristics energy ratio (FCER), is proposed. The order bispectrum (OB) method has shown its effectiveness in the feature extraction of bearings and fixed-shaft gearboxes. However, the effectiveness of the PG still needs to be explored. The FCER is developed to sum up the fault information, which is scattered by mutual modulation. In this method, the raw vibration signal is firstly converted to that in the angle domain. Secondly, the characteristic slice of AOBS is extracted. Different from the conventional OB method, the AOBS is extracted by searching for a characteristic carrier frequency adaptively in the sensitive range of signal coupling. Finally, the FCER is summed up and calculated from the fault features that were dispersed in the characteristic slice. Experimental data was processed, using both the AOBS-FCER method, and the method that combines order spectrum analysis with sideband energy ratio (OSA-SER), respectively. Results indicated that the new method is effective in incipient fault feature extraction, compared with the methods of OB and OSA-SER.

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A fault diagnosis method for planetary gearboxes under non-stationary working conditions using improved Vold-Kalman filter and multi-scale sample entropy

Cited by 109 publications

References 35 publications

Uncertainty Analysis of Bistable Vibration Energy Harvesters Based on the Improved Interval Extension

Uncertainty Analysis of Bistable Vibration Energy Harvesters Based on the Improved Interval Extension

A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery

Fault Diagnosis of Planetary Gearbox Based on Adaptive Order Bispectrum Slice and Fault Characteristics Energy Ratio Analysis

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