An explicit literature review on bearing materials and their defect detection techniques

Yadav, Ekta; Chawla, Vivek

doi:10.1016/j.matpr.2021.09.132

Cited by 16 publications

(9 citation statements)

References 60 publications

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“…Next, WSO-SVM is used to construct a fault diagnosis model. The highest recognition rate is calculated for the five types of hierarchical entropies under multi-feature extraction, as shown in 7, where (1,5) indicates the combination of nodes with the highest recognition rate for two features are node 1 and node 5, (1,5,6) indicates the combination of nodes with the highest recognition rate for three features are node 1, node 5 and node 6, and so on. It can be seen from Figure 12 that there is almost no overlap based on the WSO-HSlopEn, but the feature distributions of the BF2 and IRF2 samples are relatively low in clustering; for the other hierarchical entropies, the clustering of the feature distributions of the samples are very poor because of their approximate entropy distributions.…”

Section: Comparison Of Different Hierarchical Entropiesmentioning

confidence: 99%

“…The highest recognition rate is calculated for the five types of hierarchical entropies under multi-feature extraction, as shown in Table 7, where (1,5) indicates the combination of nodes with the highest recognition rate for two features are node 1 and node 5, (1,5,6) indicates the combination of nodes with the highest recognition rate for three features are node 1, node 5 and node 6, and so on. Table 7 shows that no matter how many features are extracted, the recognition rate of these ten types of bearing signals using WSO-HSlopEn is higher than that of other hierarchical entropies; additionally, the more features we select, the better the recognition effect we obtain; in the circumstances of multi-features, the recognition rates of WSO-HSlopEn are all higher than 97.5%, yet the highest recognition rates of other hierarchical entropies are all significantly below 97.5%; for WSO-HSlopEn, when five nodes are selected, that is, choosing nodes (1,5,6,7,11), the highest recognition rate of these ten types of bearing signals reaches 100%; however, the highest recognition rate of other entropies is, respectively, 3.80%, 10.53%, 16.73%, and 4.13% lower than that of WSO-HSlopEn. Through the above comparison, we can clearly find the significant advantages of the proposed method based on WSO-HSlopEn, and the recognition results applied to diagnose faults of rolling bearings are higher than those of classic methods.…”

Section: Comparison Of Different Hierarchical Entropiesmentioning

confidence: 99%

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A Dual-Optimization Fault Diagnosis Method for Rolling Bearings Based on Hierarchical Slope Entropy and SVM Synergized with Shark Optimization Algorithm

Tang

Huang

et al. 2023

Sensors

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Slope entropy (SlopEn) has been widely applied in fault diagnosis and has exhibited excellent performance, while SlopEn suffers from the problem of threshold selection. Aiming to further enhance the identifying capability of SlopEn in fault diagnosis, on the basis of SlopEn, the concept of hierarchy is introduced, and a new complexity feature, namely hierarchical slope entropy (HSlopEn), is proposed. Meanwhile, to address the problems of the threshold selection of HSlopEn and a support vector machine (SVM), the white shark optimizer (WSO) is applied to optimize both HSlopEn and an SVM, and WSO-HSlopEn and WSO-SVM are proposed, respectively. Then, a dual-optimization fault diagnosis method for rolling bearings based on WSO-HSlopEn and WSO-SVM is put forward. We conducted measured experiments on single- and multi-feature scenarios, and the experimental results demonstrated that whether single-feature or multi-feature, the WSO-HSlopEn and WSO-SVM fault diagnosis method has the highest recognition rate compared to other hierarchical entropies; moreover, under multi-features, the recognition rates are all higher than 97.5%, and the more features we select, the better the recognition effect. When five nodes are selected, the highest recognition rate reaches 100%.

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Section: Comparison Of Different Hierarchical Entropiesmentioning

confidence: 99%

Section: Comparison Of Different Hierarchical Entropiesmentioning

confidence: 99%

A Dual-Optimization Fault Diagnosis Method for Rolling Bearings Based on Hierarchical Slope Entropy and SVM Synergized with Shark Optimization Algorithm

Tang

Huang

et al. 2023

Sensors

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“…Much research has been done on the bearing materials. Yadav and Chawla (2021) summarized different bearing materials and different bearing performance detection methods. Yu et al (2005) focused on the properties of high carbon chromium type stainless bearing steel, high temperature stainless bearing steel, nitrogenbearing steel, and other stainless bearing materials, as well as the influence of different smelting processes on the materials.…”

Section: Open Access Edited Bymentioning

confidence: 99%

Investigation on characteristics and performance of bearing spacer ring

Guo,

Zhao,

Long

et al. 2023

Front. Mater.

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Bearings are widely used in the industry due to their ability to support the movement of rotating bodies. The spacer rings are a key component of double-row roller bearings; therefore, the characteristics and properties of the spacer rings have a significant impact on the bearing functions. However, the lack of the characteristics and performance analysis of the spacer ring limits the improvement of bearing performance. To analyze the characteristics of spacer rings and establish a basis for improving their performance, a new testing method for the characteristics and performance of the spacer ring was presented and corresponding experiments were developed. The test procedure entails the evaluation of basic characteristics, surface properties, and serviceability. Basic characteristics were determined through element testing and cross-section morphological observation; surface properties were assessed through surface morphology and surface roughness detection; and serviceability was identified by cross-section hardness and frictional wear tests. The results show that the proposed test method can comprehensively characterize the performance of the spacer rings. The spacer ring composition mainly contains Fe, Al, P, Si, Ca, and S, which contribute to excellent wear resistance, hardness, strength, and corrosion resistance. The cross-sectional morphology exhibits porous characteristics, which enhance lubricity. In terms of surface property, the surface of the spacer ring is relatively flat, and the surface roughness is generally less than 0.6 μm Sa. The average friction coefficient is 0.85, and the friction and wear properties of the spacer ring are good. This study contributes to establishing the testing and evaluation criteria for the performance of spacer rings in engineering, which helps to improve the performance of bearings.

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“…4 Si 3 N 4 exhibits good wear properties, as evidenced by its adoption as rolling bearing balls for hybrid bearings. 5 Monolithic Si 3 N 4 is effective in bearing balls because of the design of the hybrid bearing, which employs the monolithic ceramic in the form of well-polished balls which are under compressive load during operation. However, the authors have shown previously that the Si 3 N 4 balls can cause increased wear of the metal rings in a hybrid bearing.…”

Section: Introductionmentioning

confidence: 99%

Improving the damage tolerance of Si₃N₄ by forming laminate composites with refractory metals

Mitchell

Mecholsky

2022

Journal of Composite Materials

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The objective of this research was to demonstrate that the damage tolerance of Si3N4 could be significantly improved by forming laminate composites with refractory metals, providing materials that undergo graceful failure, rather than the fast-fracture mechanism exhibited by monolithic Si3N4. A damage tolerant Si3N4 could be used as a ring material in an all-ceramic bearing, decreasing the chance for catastrophic failure if the ring is stressed in tension during operation. The technical approach formed a laminate composite material using alternating Si3N4-metallic layers, with both outer layers being Si3N4 to take advantage of its greater wear resistance, chemical stability, and thermal stability. The metallic layers are designed to arrest any cracks in the outer layers, thus producing a toughened Si3N4 and avoiding the catastrophic failure behavior exhibited by monolithic ceramics. The laminate composites were fabricated using a combination of tape-casting Si3N4 and metals from slurries, as well as metal foils, followed by hot pressing at 1500°C. The metallic materials employed were chromium, titanium, and tantalum. Analysis confirmed that the interfaces were well formed, and the laminates with chromium and titanium formed intermetallic compounds more readily than the composites with tantalum. The Si3N4-Ta laminates demonstrated crack deflection and bridging behavior during failure and flexural strength of 800–900 MPa. The hardness and elastic modulus of Si3N4-Ta laminates measured by nanoindentation were similar to those reported in literature. The hardness across the interface of the Si3N4-Ta composite varied according to the composition of the interface, which displayed a profile indicative of a diffusion bond.

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An explicit literature review on bearing materials and their defect detection techniques

Cited by 16 publications

References 60 publications

A Dual-Optimization Fault Diagnosis Method for Rolling Bearings Based on Hierarchical Slope Entropy and SVM Synergized with Shark Optimization Algorithm

A Dual-Optimization Fault Diagnosis Method for Rolling Bearings Based on Hierarchical Slope Entropy and SVM Synergized with Shark Optimization Algorithm

Investigation on characteristics and performance of bearing spacer ring

Improving the damage tolerance of Si₃N₄ by forming laminate composites with refractory metals

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An explicit literature review on bearing materials and their defect detection techniques

Cited by 16 publications

References 60 publications

A Dual-Optimization Fault Diagnosis Method for Rolling Bearings Based on Hierarchical Slope Entropy and SVM Synergized with Shark Optimization Algorithm

A Dual-Optimization Fault Diagnosis Method for Rolling Bearings Based on Hierarchical Slope Entropy and SVM Synergized with Shark Optimization Algorithm

Investigation on characteristics and performance of bearing spacer ring

Improving the damage tolerance of Si3N4 by forming laminate composites with refractory metals

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Product

Resources

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Improving the damage tolerance of Si₃N₄ by forming laminate composites with refractory metals