Fault Diagnosis of Rotating Machine

Królczyk, Grzegorz; Li, Zhixiong; Antonino-Daviu, José A.

doi:10.3390/app10061961

Cited by 6 publications

(4 citation statements)

References 54 publications

(27 reference statements)

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“…The common deployment of rotating machines is still increasing since they are the heart of production systems in a wide variety of industries, such as manufacturing tools [1], electric motors [2,3], wind turbines [4,5], aero-engines [6,7], mining machines [8,9], marine propulsions [10,11], and autonomous vehicles [12,13]. They frequently operate from 1 to 10,000 rpm in a harsh working environment and under different operating conditions and are exposed to faults that lead to failure.…”

Section: Introductionmentioning

confidence: 99%

Remaining Useful Life Prediction of Broken Rotor Bar Based on Data-Driven and Degradation Model

2021

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Rotating machines such as induction motors are crucial parts of most industrial systems. The prognostic health management of induction motor rotors plays an essential role in increasing electrical machine reliability and safety, especially in critical industrial sectors. This paper presents a new approach for rotating machine fault prognosis under broken rotor bar failure, which involves the modeling of the failure mechanism, the health indicator construction, and the remaining useful life prediction. This approach combines signal processing techniques, inherent metrics, and principal component analysis to monitor the induction motor. Time- and frequency-domains features allowing for tracking the degradation trend of motor critical components that are extracted from torque, stator current, and speed signals. The most meaningful features are selected using inherent metrics, while two health indicators representing the degradation process of the broken rotor bar are constructed by applying the principal component analysis. The estimation of the remaining useful life is then obtained using the degradation model. The performance of the prediction results is evaluated using several criteria of prediction accuracy. A set of synthetic data collected from a degraded Simulink model of the rotor through simulations is used to validate the proposed approach. Experimental results show that using the developed prognostic methodology is a powerful strategy to improve the prognostic of induction motor degradation.

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Section: Introductionmentioning

confidence: 99%

Remaining Useful Life Prediction of Broken Rotor Bar Based on Data-Driven and Degradation Model

2021

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“…Many rotating machine failures are related to bearing faults [1][2][3][4][5]. Journal bearings (JB) are usually found in heavy industries that include large rotating machines, whose early fault identification can yield a favorable impact on plant availability [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Identification of Babbitt Damage and Excessive Clearance in Journal Bearings through an Intelligent Recognition Approach

Gómez¹,

Montero²,

Gomez-Mancilla³

et al. 2021

IJACSA

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Journal bearings play an important role on many rotating machines placed on industrial environments, especially in steam turbines of thermoelectric power plants. Babbitt damage (BD) and excessive clearance (C) are usual faults of steam turbine journal bearings. This paper is focused on achieving an effective identification of these faults through an intelligent recognition approach. The work was carried out through the processing of real data obtained from an industrial environment. In this work, a feature selection procedure was applied in order to choose the features more suitable to identify the faults. This feature selection procedure was performed through the computation of typical testors, which allows working with both quantitative and qualitative features. The classification tasks were carried out by using Nearest Neighbors, Voting Algorithm, Naïve Associative Classifier and Assisted Classification for Imbalance Data techniques. Several performance measures were computed and used in order to assess the classification effectiveness. The achieved results (e.g., six performance measures were above 0.998) showed the convenience of applying pattern recognition techniques to the automatic identification of BD and C.

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“…IR thermography [36] is a technique which is suitable and very useful for recording the dynamics of the manufacturing process and operation and safety processes. The IR technique has also been applied to other mechanical applications, both for the diagnosis of faults and as a complement to other fault detection techniques [36][37][38]. This technique can be used for the diagnosis of kinematic pairs in the rotary mowers [39] or for the analysis of the extrusion process stability of microporous polyvinyl chloride (PVC) [40] and as a diagnostic tool for the assessment of the accumulation of discontinuities of the structure of polyester-glass pipes [41].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Thermal Stability and Surface Characteristics of Thermoplastic Polyurethane V-Belt

et al. 2020

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This article proposes thermography as a non-contact diagnostic tool for assessing drive reliability. The application of this technique during the operation of the belt transmission with a heat-welded thermoplastic polyurethane V-belt was presented. The V-belt temperature changes depending on the braking torque load at different values of the rotational speed of the active pulley, which were adopted as diagnostic characteristics. In this paper, the surface morphology of the polyurethane (PU) belts was assessed on the basis of microscopic and hardness tests. A surface roughness tester was used to evaluate the surface wear. The surface morphology and topography of the materials was determined by scanning electron microscopy (SEM) and optical microscopy. It was found that the most favorable operating conditions occurred when the temperature values of active and passive connectors were similar and the temperature difference between them was small. The mechanical and structure results indicate that the wear of the PU belt was slight, which provided stability and operational reliability for V-belt transmission. The microscopic images lacked clear traces of cracks and scratches on the surface, which was confirmed by the SEM observations.

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Fault Diagnosis of Rotating Machine

Abstract: Rotating machines have been used in a wide variety of industries, such as manufacturing tools [...]

Cited by 6 publications

References 54 publications

Remaining Useful Life Prediction of Broken Rotor Bar Based on Data-Driven and Degradation Model

Remaining Useful Life Prediction of Broken Rotor Bar Based on Data-Driven and Degradation Model

Identification of Babbitt Damage and Excessive Clearance in Journal Bearings through an Intelligent Recognition Approach

Evaluation of the Thermal Stability and Surface Characteristics of Thermoplastic Polyurethane V-Belt

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