Vibration-Based Diagnostics of Radial Clearances and Bolts Loosening in the Bearing Supports of the Heavy-Duty Gearboxes

Krot, Pavlo; Korennoi, Volodymyr; Zimroz, Radosław

doi:10.3390/s20247284

Cited by 19 publications

(12 citation statements)

References 96 publications

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“…Further research is associated with the utilisation of a designed FEM model for simulation of different kinds of failures of impellers disks and blades, to assess their influence on vibration signals registered on the shaft bearing supports by equipment monitoring systems, and to develop methods of its efficient diagnostics as shown in [55][56][57] for other minerals processing machines.…”

Section: Discussionmentioning

confidence: 99%

Materials Selection and Design Options Analysis for a Centrifugal Fan Impeller in a Horizontal Conveyor Dryer

et al. 2021

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Comparative strength analysis of two popular options of the radial centrifugal fan impeller design used in horizontal conveyor dryer for fine-grained raw materials is presented. Three types of materials for impeller manufacturing—ASTM A36 steel, Hardox 450 steel and aluminium alloy 6061-T6 are considered. The finite element method (FEM) has been used to investigate stresses and deformations of the impeller within the operational speed range. Analysis shows that the better design is the impeller made of Hardox 450 steel with a central disk. Although the maximum stress is slightly higher in the blades slot for central disk fitting for this design option, it has greatly reduced stresses in contact edges with two other disks (by 22–38%) and blades bending deformation (by 51%). For this design, the maximum operational rotation speed is 1135 min−1 according to the yield strength with a 15% safety factor, while for basic design, it is 1225 min−1. The rational choice of material depends on maximum value of the yield stress to density ratio as well as taking into account the operating conditions and required fan performance. Recommendations for manufacturing the centrifugal fan impeller related to chosen material are given.

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Section: Discussionmentioning

confidence: 99%

Materials Selection and Design Options Analysis for a Centrifugal Fan Impeller in a Horizontal Conveyor Dryer

et al. 2021

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“…Nevertheless, these elements of vibrators are subjected to high loads and cyclic fatigue. By the specification of the producer (SKF), bearings for the vibrating sieving screen have greater than normal clearances, which play the most important role in their durability [ 73 , 74 ].…”

Section: Methodsmentioning

confidence: 99%

Condition Monitoring of Horizontal Sieving Screens—A Case Study of Inertial Vibrator Bearing Failure in Calcium Carbonate Production Plant

et al. 2023

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Predictive maintenance is increasingly popular in many branches, as well as in the mining industry; however, there is a lack of spectacular examples of its practice efficiency. Close collaboration between Omya Group and Wroclaw University of Science and Technology allowed investigation of the failure of the inertial vibrator’s bearing. The signals of vibration are captured from the sieving screen just before bearing failure and right after repair, when it was visually inspected after replacement. The additional complication was introduced by the loss of stable attachment of the vibrator’s shield, which produced great periodical excitation in each place of measurement on the machine. Such anomalies in the signals, in addition to falling pieces of material, made impossible the diagnostics by standard methods. However, the implementation of advanced signal processing techniques such as time–frequency diagrams, envelope spectrum, cyclic spectral coherence, orbits analysis, and phase space plots allowed to undermine defects (pitting on the inner ring). After repair, the amplitudes of vibration from the damaged bearing side were reduced by five times, while sound pressure was only two times lower. The quantitative parameters of vibrations showed significant changes: time series RMS (−68%) median energy of spectrograms (89%), frequencies ratio of cyclic spectral coherence (−85%), and average amplitude of harmonics in envelope spectrum (−80%). The orbits demonstrated changes in inclination angle (16%) and sizes (−48 ... −96%), as well as phase space plots sizes (−28 ... −67%). Directions of further research are considered.

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“…Initially looseness will manifest itself as Type A, next as B, then as C, and finally only the noise floor will remain in the spectrum. Krot et al (2020) and He et al (2014) also found that bolt loosening is best diagnosed by using system natural frequencies.…”

Section: Mechanical Loosenessmentioning

confidence: 96%

Helicopter Bolt Loosening Monitoring using Vibrations and Machine Learning

Gildish¹,

Grebshtein²,

Aperstein

et al. 2022

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The existing helicopter Health and Usage Management Systems (HUMS) collect and process flight operational parameters and sensors data such as vibrations to provide health monitoring of the helicopter dynamic assemblies and engines. So far, structure-related mechanical faults, such as looseness in bolted structures, have not been addressed by vibration-based condition monitoring in existing HUMS systems. Bolt loosening was identified as a potential risk to flight safety demanding periodical visual monitoring, and increased maintenance and repair expenses. Its automatic identification in helicopters by using vibration measurements is challenging due to the limited number of known events and the presence of high-energy vibrations originating in rotating parts, which shadow the low-level signals generated by the bolt loosening. New developed bolt loosening monitoring approach was tested on HUMS vibrations data recorded from the IAF AH-64 Apache helicopters fleet. ML-based unsupervised anomaly detection was utilized in order to address the limited number of faulty cases. The predictive power of health features was significantly improved by applying the Harmonic filtering differentiating between the high-energy vibrations generated by rotating parts compared with the low-energy structural vibrations. Different unsupervised anomaly detection techniques were examined on the dataset. The experimental results demonstrate that the developed approach enable successful bolt loosening monitoring in helicopters and can potentially be used in other health monitoring applications.

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Vibration-Based Diagnostics of Radial Clearances and Bolts Loosening in the Bearing Supports of the Heavy-Duty Gearboxes

Cited by 19 publications

References 96 publications

Materials Selection and Design Options Analysis for a Centrifugal Fan Impeller in a Horizontal Conveyor Dryer

Materials Selection and Design Options Analysis for a Centrifugal Fan Impeller in a Horizontal Conveyor Dryer

Condition Monitoring of Horizontal Sieving Screens—A Case Study of Inertial Vibrator Bearing Failure in Calcium Carbonate Production Plant

Helicopter Bolt Loosening Monitoring using Vibrations and Machine Learning

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