Prognostics of multiple failure modes in rotating machinery using a pattern-based classifier and cumulative incidence functions

Ragab, Ahmed; Yacout, Soumaya; Ouali, Mohamed-Salah; Osman, Hany

doi:10.1007/s10845-016-1244-8

Cited by 48 publications

(21 citation statements)

References 49 publications

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“…LAD was used to predict the estimated time to failure and the remaining useful life (RUL) of equipment working under different operating conditions and subjected to either single or multiple failure modes [42,93,94].…”

Section: Fault Prognosis With Ladmentioning

confidence: 99%

“…Ragab et al proposed a methodology for multiple failure modes prognostics in rotating machinery in [94]. The methodology merges multi-class LAD with a set of non-parametric cumulative incidence functions.…”

Section: Fault Prognosis With Ladmentioning

confidence: 99%

“…A prognostic methodology that exploits all condition monitoring data collected from a group of systems during their life spans, both normal and failure observations, was proposed in [94]. This methodology captures the effect of the instantaneous conditions on the health state of the monitored system.…”

Section: Fault Prognosis With Ladmentioning

confidence: 99%

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Recent advances in the theory and practice of Logical Analysis of Data

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Section: Fault Prognosis With Ladmentioning

confidence: 99%

Section: Fault Prognosis With Ladmentioning

confidence: 99%

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Recent advances in the theory and practice of Logical Analysis of Data

Lejeune

Lozina

Ragab

et al. 2019

European Journal of Operational Research

Self Cite

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show abstract

“…For instance, in [27,28], different cumulative damage models are constructed to describe the system degradation process by considering different degradation paths and distributions, and a preventive maintenance policy is obtained to minimize the maintenance cost. In [29], a nonparametric model called cumulative incidence functions and logical analysis are integrated to solve the problem of multi-failure-mode in prognosis. The curves of cumulative incidence functions are calculated to reflect the running time on the degradation status of the monitored bearing by using the lifetime data of different failure modes.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

An Integrated Cumulative Transformation and Feature Fusion Approach for Bearing Degradation Prognostics

Duan

Zhao

Wang

et al. 2018

Shock and Vibration

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Aimed at degradation prognostics of a rolling bearing, this paper proposed a novel cumulative transformation algorithm for data processing and a feature fusion technique for bearing degradation assessment. First, a cumulative transformation is presented to map the original features extracted from a vibration signal to their respective cumulative forms. The technique not only makes the extracted features show a monotonic trend but also reduces the fluctuation; such properties are more propitious to reflect the bearing degradation trend. Then, a new degradation index system is constructed, which fuses multidimensional cumulative features by kernel principal component analysis (KPCA). Finally, an extreme learning machine model based on phase space reconstruction is proposed to predict the degradation trend. The model performance is experimentally validated with a whole-life experiment of a rolling bearing. The results prove that the proposed method reflects the bearing degradation process clearly and achieves a good balance between model accuracy and complexity.

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“…Although fruitful research has been performed on the prognostics of mechanical and rotational equipment [1][2][3][4][5][6][7][8], there are few reports on the predictive maintenance of hydraulic system parts. In the case of a tractor, the hydraulic system is commonly subjected to regular maintenance.…”

Section: Introductionmentioning

confidence: 99%

In-field failure assessment of tractor hydraulic system operation via pseudospectrum of acoustic measurements

Gupta¹,

Khosravy²,

Gupta³

et al. 2019

Turk J Elec Eng & Comp Sci

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Hydrological working conditions are critical indicators for the maintenance of tractor mechanical systems. This research presents a pseudospectrum approach to analyze the particle pollution level of the hydraulic filter in its aging process and thus on-time prediction and diagnosis of weak or faulty conditions. The practical experiments of pseudospectrum analysis are performed on oil filter sound records. For mobile application purposes, besides deployment of advanced audio recording equipment, three popular brands of cell phones are used. The soundtracks are recorded in different incremental stages of fluid contamination by pollutive particles until being choked based on the ISO4406 standard. The pseudospectrum of the oil filter acoustics leads to two numerical features: the low-band energy and 12.5 kHz relative peak energy (12.5RPE). This manuscript proposes these two features for efficient on-line monitoring of the liquid cleanliness level as well as the prediction and diagnosis of choked condition of the tractor hydraulic system.

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Prognostics of multiple failure modes in rotating machinery using a pattern-based classifier and cumulative incidence functions

Cited by 48 publications

References 49 publications

Recent advances in the theory and practice of Logical Analysis of Data

Recent advances in the theory and practice of Logical Analysis of Data

An Integrated Cumulative Transformation and Feature Fusion Approach for Bearing Degradation Prognostics

In-field failure assessment of tractor hydraulic system operation via pseudospectrum of acoustic measurements

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