Good practices for designing and experimental testing of dynamically excited jointed structures: The Orion beam

Teloli, Rafael de Oliveira; Butaud, Pauline; Chevallier, Gaël; Silva, Samuel da

doi:10.1016/j.ymssp.2021.108172

Cited by 15 publications

(13 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 3 presents the experimental setup. The lap-joint structure, the so-called “Orion beam,” 25 consists of two assembly duraluminium beams with dimensions of 200 × 30 × 2 (mm) each one and connected by three M4 bolts spaced along a length of 30 mm, as depicted in Figure 3. The beam is in a cantilever configuration under base excitation.…”

Section: Resultsmentioning

confidence: 99%

“…Here, the restoring forces, which represent the whole nonlinear force that actuates on the sixth vibrating mode (the bending modes are uncoupled and allow such approach), are identified by approximating an equivalent reduced-order model based on the force-state mapping. 46,47 The dissipated energy caused by the hysteresis effect (such as the damping ratio) should also be a great feature as damage index; unfortunately, this parameter is difficult to 25 estimate and identify as it generally requires an a priori updated reduced-order model. In this sense, it is preferable and straightforward to use a simple modal parameter, such as the natural frequency, as a feature.…”

Section: Challenges For Damage Detection In Bolted Joints By Using Mo...mentioning

confidence: 99%

“…From the frequency spectrum of vibration signals, model features are estimated to implement a Gaussian Mixture Model (GMM) to classification and a Gaussian Process Regression (GPR) to quantify torque values in a testbed of an Orion beam. The benchmark proposed by Teloli et al 25,26 is an academic-scale specimen that provides controlled tightening torque conditions on the bolts that comprise the lap-joint. Nevertheless, the structure exhibits dynamic behavior typical to other bolted joint systems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Probabilistic machine learning for detection of tightening torque in bolted joints

Miguel

Teloli

Silva

et al. 2022

Structural Health Monitoring

Self Cite

View full text Add to dashboard Cite

Observing the loss of tightening torque using modal parameters is challenging due to the variability and nonlinear effects in bolted joints. Thus, this paper proposes a combined application of two probabilistic machine learning methods. First, a Gaussian mixture model (GMM) is learned using estimated natural frequencies, assuming the tightening torque in a safe situation. This probabilistic model can assuredly detect the lack of torque using indirect vibration measures in other unknown states by computing a damage index. A Gaussian process regression (GPR) is also learned considering a set of torque and damage index pairs in several conditions. The GPR model interpolates a curve to supply an estimative of the tightening torque for other conditions not used in this learning. An illustrative application is performed considering the Orion beam, an academic-scale specimen composed of a lap-joint configuration that retains the friction surface in contact patches. The structure is subjected to a random vibration with a controlled RMS level and several tightening torque conditions to identify the modal parameters. The probabilistic model learning via the GMM and GPR can detect adequately, with a low number of false diagnoses, the actual state of torque using an indirect measure of vibration, that is, without the need for a torque sensor on each bolt.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Challenges For Damage Detection In Bolted Joints By Using Mo...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Probabilistic machine learning for detection of tightening torque in bolted joints

Miguel

Teloli

Silva

et al. 2022

Structural Health Monitoring

Self Cite

View full text Add to dashboard Cite

show abstract

“…The ORION test rig (Figure 4) has been designed for the study of vibration damping and makes the vibration tests highly reproducible, as shown in [24,25]. It is a jointed structure made of two plates manufactured with 2024 aluminum alloy, linked together by three M4 bolts (Figure 4).…”

Section: Methodsmentioning

confidence: 99%

“…The dataset was obtained on a test rig called ORION [24,25]. It is constituted of a jointed structure, dynamically loaded with a vibration shaker and monitored with acoustic emission, force, and velocity sensors.…”

Section: Data Descriptionmentioning

confidence: 99%

Monitoring a Bolted Vibrating Structure Using Multiple Acoustic Emission Sensors: A Benchmark

Ramasso

Verdin

Chevallier

2022

Data

Self Cite

View full text Add to dashboard Cite

The dataset presented in this work, called ORION-AE, is made of raw AE data streams collected by three different AE sensors and a laser vibrometer during five campaigns of measurements by varying the tightening conditions of two bolted plates submitted to harmonic vibration tests. With seven different operating conditions, this dataset was designed to challenge supervised and unsupervised machine/deep learning as well as signal processing methods which are developed for material characterization or structural health monitoring (SHM). One motivation of this work was to create a common benchmark for comparing data-driven methods dedicated to AE data interpretation. The dataset is made of time series collected during an experiment designed to reproduce the loosening phenomenon observed in aeronautics, automotive, or civil engineering structures where parts are assembled together by means of bolted joints. Monitoring loosening in jointed structures during operation remains challenging because contact and friction in bolted joints induce a nonlinear stochastic behavior.

show abstract

Bypassing the Repeatability Issue in Nonlinear Experimental Modal Analysis of Jointed Structures by Using the RCT-HFS Framework

Gürbüz,

Karaağaçlı,

Özer

et al. 2023

Conference Proceedings of the Society for Experimental Mechanics Series

View full text Add to dashboard Cite

Good practices for designing and experimental testing of dynamically excited jointed structures: The Orion beam

Cited by 15 publications

References 42 publications

Probabilistic machine learning for detection of tightening torque in bolted joints

Probabilistic machine learning for detection of tightening torque in bolted joints

Monitoring a Bolted Vibrating Structure Using Multiple Acoustic Emission Sensors: A Benchmark

Bypassing the Repeatability Issue in Nonlinear Experimental Modal Analysis of Jointed Structures by Using the RCT-HFS Framework

Contact Info

Product

Resources

About