A Novel Comparative Study of European, Chinese and American Codes on Bolt Tightening Sequence Using Smart Bolts

You, Runzhou; Ren, Liang; Song, Gangbing

doi:10.1007/s13296-020-00331-7

Cited by 10 publications

(6 citation statements)

References 32 publications

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“…In addition, the force acting on the bolt by the installed sensor is static and small, the influence on bolt connection can be ignored. Compared with the relevant FBGbased clamping force monitoring method [38][39][40][41][42], the installation of the FBG curvature sensor is simple, and almost no effects on bolt connections, which can be expediently reused and easy to form a quasi-distributed sensing network.…”

Section: Discussionmentioning

confidence: 99%

“…The typical application of fiber optic sensors in bolt looseness detection is clamping force monitoring of bolts. In these methods, the fiber Bragg grating (FBG) strain sensors are commonly bonded on [38,39] or embedded into [40][41][42] bolts to define clamping force by measuring the strain. The method based on the FBG strain sensor can monitor the variation of clamping force with high accuracy, however, it requires to destruct the bolt structure, which may reduce the bearing capacity of the bolt.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Proof-of-concept study of bolt connection status monitoring using fiber Bragg grating curvature sensor

Deng¹,

Wang²,

Tan³

et al. 2022

Smart Mater. Struct.

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For connection status monitoring of bolted joint groups, a novel method with fiber Bragg grating (FBG) based curvature sensor is proposed. An FBG curvature sensor with an inextensible elastic matrix and an offset grating is adopted and clamped between a fixed support and the monitored bolt in a plane bending status. Based on the shape deformation of the FBG curvature sensor induced by the bolt loosening, the bending curvature change of the elastic matrix is measured by the FBG. By detecting the wavelength shift of the FBG induced by the matrix curvature variation, the relationship between the bolt loosening angle and the wavelength shift of FBG can be obtained, and hence the bolt connection status can be determined by the wavelength shift of FBG. Details of the proposed method are presented, and a surface-bonded FBG curvature sensor is designed, fabricated, and experimentally studied to verify the proposed method, and the parameters on sensing performance are also investigated. Experimental results show that the proposed method can monitor bolt loosening angle with high sensitivity and linear output by adjusting the parameters of the FBG curvature sensor. The looseness angle resolution of the proposed sensor can reach 0.0767°. This paper presents the first attempt to monitor bolt loosening angle using an FBG curvature sensor. With the advantages of high sensitivity and resolution, strong applicability, convenience and reusability for the maintenance of bolts, and ease of forming distributed sensor networks, the proposed method is able to provide a general solution for the on-line monitoring of bolt connection status for large-span distributed bolted-joint groups.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Proof-of-concept study of bolt connection status monitoring using fiber Bragg grating curvature sensor

Deng¹,

Wang²,

Tan³

et al. 2022

Smart Mater. Struct.

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show abstract

“…For example, vibration transmissibility function is determined as a more reliable parameter to identify the state of the joint while natural frequency and modal damping in lower modes appeared less reliable. Strain measurements are carried out using fibre Bragg-grating (FBG) sensors [54,55] and optimal tightening sequence is determined in multi-bolt connections [56]. In other studies [57][58][59][60], theoretical and experimental studies have been conducted for an assessment of modal properties and frequency response functions applicability for detection of structural bolted joint degradation [61].…”

Section: Diagnostics Of Bearing Supports and Bolts Looseningmentioning

confidence: 99%

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

Krot

Korennoi

Zimroz

2020

Sensors

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The problem solved in this research is the diagnosis of the radial clearances in bearing supports and the loosening of fastening bolts due to their plastic elongation (creep) or weak tightening using vibration signals. This is an important issue for the maintenance of the heavy-duty gearboxes of powerful mining machines and rolling mills working in non-stationary regimes. Based on a comprehensive overview of bolted joint diagnostic methods, a solution to this problem based on a developed nonlinear dynamical model of bearing supports is proposed. Diagnostic rules are developed by comparing the changes of natural frequency and its harmonics, the amplitudes and phases of shaft transient oscillations. Then, the vibration signals are measured on real gearboxes while the torque is increasing in the transmission during several series of industrial trials under changing bearings and bolts conditions. In parallel, dynamical torque is measured and its interrelation with vibration is determined. It is concluded that the radial clearances are the most influencing factors among the failure parameters in heavy-duty gearboxes of industrial machines working under impulsive and step-like loading. The developed diagnostics algorithm allows condition monitoring of bearings and fastening bolts, allowing one to undertake timely maintenance actions to prevent failures.

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“…Methods to monitor bolt looseness are based mainly on structural health-monitoring principles, which include, but are not limited to, the vibration-based method (Amerini et al, 2010;Li and Jing, 2020), the optical fiber sensing-based method (Guarino and Hamilton, 2017;You et al, 2020), the percussion-based method (Wang et al, 2019;Wang et al, 2020b;, the electromechanical impedance (EMI) method (Ritdumrongkul et al, 2003;Huo et al, 2017b;Wang et al, 2017), and methods based on the contact acoustic theory. Each of the methods mentioned above have unique limitations.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Monitoring of Bolt Looseness Using Multichannel Piezoelectric Active Sensing and CBAM-Based Convolutional Neural Network

et al. 2021

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The bolted connection is widely utilized in engineering to practically and rigidly couple structural components. The integrity of the connection is paramount to the safety of the structure and has prompted the development of many monitoring methods, including the piezoelectricity-based active sensing method. However, the active sensing method cannot quantify bolt looseness due to the unclear relationship between bolt looseness and the single monitoring index typically used in the active sensing method. Thus, the authors propose the unique combination of a one-dimensional convolutional neural network (1DCNN) and multichannel active sensing for quantitative monitoring of bolted connections. In an experiment, piezoelectric ceramic transducer (PZT) patches are bonded on steel plates connected by a bolt. Each patch is wired to a multichannel active sensing monitoring system. After obtaining multichannel stress wave signals at different looseness levels, a looseness vector is calculated to generate training and validation datasets. A baseline 1DCNN model and a novel model improved using the convolutional block attention module (CBAM) are used to monitor the bolt looseness. Finally, the authors verify that the multichannel active sensing method combined with the 1DCNN model can accurately perform quantitative monitoring of bolt looseness, and the monitoring accuracy of the baseline 1DCNN model is above 91.07% in three different specimens. Compared with the baseline 1DCNN model, the monitoring accuracy of the CBAMCNN model improved by approximately 5%. Overall, the method proposed in this article offers a new and highly accurate approach for quantitative monitoring of bolted connections.

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A Novel Comparative Study of European, Chinese and American Codes on Bolt Tightening Sequence Using Smart Bolts

Cited by 10 publications

References 32 publications

Proof-of-concept study of bolt connection status monitoring using fiber Bragg grating curvature sensor

Proof-of-concept study of bolt connection status monitoring using fiber Bragg grating curvature sensor

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

Quantitative Monitoring of Bolt Looseness Using Multichannel Piezoelectric Active Sensing and CBAM-Based Convolutional Neural Network

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