Reliability evaluation method of anti-loosening performance of bolted joints

Lin, Qingyuan; Zhao, Yong; Sun, Qingchao; Chen, Kunyong

doi:10.1016/j.ymssp.2021.108067

Cited by 26 publications

(6 citation statements)

References 30 publications

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“…In theory, the bolt joint is kept stable by rotating the nut and bolt relative to each other, elongating the bolt and compressing the joint part to form a frictional self-locking. In this case, the bolt tension is the pressure on the contact surface of the joint and the bolt [6]. In fact, the bolt tension decreases due to repeated relative sliding wear of the joint or plastic deformation of the bolt and the joint, which can directly lead to the loss of function of the joint [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A Detection Method of Bolts on Axlebox Cover Based on Cascade Deep Convolutional Neural Network

Wang¹,

Li²,

Zheng³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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This paper proposes a cascade deep convolutional neural network to address the loosening detection problem of bolts on axlebox covers. Firstly, an SSD network based on ResNet50 and CBAM module by improving bolt image features is proposed for locating bolts on axlebox covers. And then, the A 2 -PFN is proposed according to the slender features of the marker lines for extracting more accurate marker lines regions of the bolts. Finally, a rectangular approximation method is proposed to regularize the marker line regions as a way to calculate the angle of the marker line and plot all the angle values into an angle table, according to which the criteria of the angle table can determine whether the bolt with the marker line is in danger of loosening. Meanwhile, our improved algorithm is compared with the pre-improved algorithm in the object localization stage. The results show that our proposed method has a significant improvement in both detection accuracy and detection speed, where our mAP (IoU = 0.75) reaches 0.77 and fps reaches 16.6. And in the saliency detection stage, after qualitative comparison and quantitative comparison, our method significantly outperforms other state-of-the-art methods, where our MAE reaches 0.092, F-measure reaches 0.948 and AUC reaches 0.943. Ultimately, according to the angle table, out of 676 bolt samples, a total of 60 bolts are loose, 69 bolts are at risk of loosening, and 547 bolts are tightened.

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Section: Introductionmentioning

confidence: 99%

A Detection Method of Bolts on Axlebox Cover Based on Cascade Deep Convolutional Neural Network

Wang¹,

Li²,

Zheng³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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“…In practical engineering applications, the questions of how to prevent loosening and improve the integrity and reliability of bolted joints are highly significant [31]. Some antiloosening bolted connections are applied in place of regular bolted joints only consisting of nuts and bolts, as shown in Figure 2.…”

Section: Introductionmentioning

confidence: 99%

Study on Tightening, Anti-Loosening, and Fatigue Resistance Performances of Bolted Joints with Different Anti-Loosening Washers and Nuts

Zhao,

Liu,

Gong

et al. 2023

Applied Sciences

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Loosening failure of bolted joints often occurs in a vibration environment. This may induce the separation of clamped components and even result in catastrophic consequences in certain situations. Various anti-loosening bolted connections have been developed and widely applied to prevent loosening. Tightening and fatigue resistance performances are also two important characteristics of anti-loosening bolted connections. However, a comprehensive comparison study of the tightening, anti-loosening, and fatigue resistance performances of typical anti-loosening bolted connections is lacking, meaning that there is a lack of material to assist in the selection of anti-loosening bolted connections in engineering. In this study, accurate three-dimensional finite element models of typical anti-loosening bolted connections with the forms of washers or nuts are established. The processes of tightening, vibration-induced loosening, and fatigue are simulated via finite element analysis (FEA). Based on the results of FEA, the tightening, anti-loosening, and fatigue resistance performances of regular bolted joints and several anti-loosening bolted connections are comprehensively compared. The results reveal that bolted joints installed with both a variable-diameter nut and an eccentric double nut are difficult to tighten. We confirm that the researched structures all have superior anti-loosening capacities compared to regular bolted joints. Additionally, the results show that the regular bolted joint achieved the worst fatigue resistance performance, i.e., the application of anti-loosening bolted connections improves fatigue resistance. Finally, the effects of preload distributions on the two nuts in bolted joints with double nuts are discussed in terms of tightening, anti-loosening, and fatigue resistance performances.

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“…At the same time, in order to ensure that the preload of bolted joint remains stable during working, many scholars have also done studies on the anti-loosening performance. 9,10 It can be found that local slip and plastic deformation occur on the bearing surface and thread fitting surface under the action of lateral load. 11 The thread damage mechanism was analyzed using X-ray, and the change mechanism of the preload under the plastic cyclic load was determined.…”

Section: Introductionmentioning

confidence: 99%

Torsional and compressive properties of bolted joint under forward-reverse tightening

Tan

Chen

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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Obtaining the stress evolution law of bolted joint during the assembly process is of great significance for tightening process design and improving assembly performance. In this study, the bolt tightening analytical model is used to obtain the deformation coordination mechanism. Then, the evolution law of the stress during assembly process are obtained by FEA model, and the influence of different assembly parameters on the stress change is analyzed. Finally, the bolt tightening experiment is carried out, which verified the theoretical hypothesis and the FEA model. The results show that: in addition to the tensile normal stress, the thread torque also generates torsional shear stress that causes the torsional deformation of the screw during the tightening process. The torsional shear stress can be reduced by forward-reverse tightening process. Meanwhile, the utilization rate of bolted joint can be improved. This can increase the assembly design margin and improve the assembly performance.

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Reliability evaluation method of anti-loosening performance of bolted joints

Cited by 26 publications

References 30 publications

A Detection Method of Bolts on Axlebox Cover Based on Cascade Deep Convolutional Neural Network

A Detection Method of Bolts on Axlebox Cover Based on Cascade Deep Convolutional Neural Network

Study on Tightening, Anti-Loosening, and Fatigue Resistance Performances of Bolted Joints with Different Anti-Loosening Washers and Nuts

Torsional and compressive properties of bolted joint under forward-reverse tightening

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