A New Method for Precision Measurement of Wall-Thickness of Thin-Walled Spherical Shell Parts

Guo, Jun; Xu, Yuanyuan; Pan, Bo; Zhang, Juntao; Kang, Ren Ke; Huang, Wen; Du, Dongxing

doi:10.3390/mi12050467

Cited by 6 publications

(2 citation statements)

References 14 publications

(12 reference statements)

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“…The bases of damage progression define a wide range of physical principles and diagnostic methods that are currently used for wear identification in linear rolling guides. These principles and methods follow up on knowledge of rolling bearing diagnostics, which is mainly based on vibration, noise, or rolling resistance measurements [ 6 , 7 , 8 ] in the context of various types of signal processing [ 9 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Method of Failure Diagnostics to Linear Rolling Guides in Handling Machines

Jírová

Pešík

Žuľová

et al. 2023

Sensors

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Linear rolling guides, used in production machines for the realisation of linear motion, demand in industrial practice early damage identification to prevent production outages and losses. Therefore, the article aims for early damage diagnostics that use the principle of a load-free diagnostic part integrated into the carriage of the linear rolling guide. This principle was employed for developing an innovative method of damage identification to a guiding profile or rolling elements. The proposed innovative method is based on analysing vibration acceleration measured on the diagnostic part in the context of carriage position. In addition, a unique connection of an acceleration sensor to the diagnostic part through a mechanical component with defined parameters of stiffness and mass was designed. The innovative method was verified by laboratory testing on a designed functional sample of the diagnostic system. The computed reliability of the proposed diagnostic method reached 98%.

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Section: Introductionmentioning

confidence: 99%

Method of Failure Diagnostics to Linear Rolling Guides in Handling Machines

Jírová

Pešík

Žuľová

et al. 2023

Sensors

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“…Thin-walled workpieces such as aero-engine blades, casings, and impellers are widely used in the aerospace industry [ 1 ] because of their light weight, high strength, and heavy load-bearing characteristics [ 2 , 3 ]. However, machining chatter and dimensional error caused by the problem of low rigidity occur in the milling of a thin-walled workpiece, which can affect the surface quality, machining productivity, and tool life [ 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Output-Only Time-Varying Modal Parameter Identification Method Based on the TARMAX Model for the Milling of a Thin-Walled Workpiece

Yan

et al. 2022

Micromachines

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The process parameters chosen for high-performance machining in the milling of a thin-walled workpiece are determined by a stability prediction model, which needs accurate modal parameters of the machining system. However, the in-process modal parameters are different from the offline modal parameters and are difficult to precisely obtain due to material removal. To address this problem, an accurate time-dependent autoregressive moving average with an exogenous input (TARMAX) method is proposed for the identification of the modal parameters in the milling of a thin-walled workpiece. In this process, a TARMAX model considering external force excitation is constructed to characterize the actual condition in the milling of a thin-walled workpiece. Then, recursive method and sliding window recursive method are used to identify TARMAX model parameters under time-varying cutting conditions. Subsequently, a three-degree of freedom (3-DOF) time-varying structure numerical model under theoretical milling forces and white-noise excitation is established, and the computational results show that the predicted natural frequencies using the proposed method are in close agreement with the simulated values. Finally, several experiments are designed and carried out to validate the effectiveness of the proposed method. The experimental results show that the predicted accuracy of the proposed method using actual cutting forces is 95.68%. Good agreement has been drawn in the numerical simulation and machining experiments. Our further research objectives will focus on the prediction of the damping ratios, modal stiffness, and modal mass.

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Ultracompact Optical Fiber Sensor for Inner Diameter Measurement

Wang,

Wang

2023

Fiber and Integrated Optics

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A New Method for Precision Measurement of Wall-Thickness of Thin-Walled Spherical Shell Parts

Cited by 6 publications

References 14 publications

Method of Failure Diagnostics to Linear Rolling Guides in Handling Machines

Method of Failure Diagnostics to Linear Rolling Guides in Handling Machines

Output-Only Time-Varying Modal Parameter Identification Method Based on the TARMAX Model for the Milling of a Thin-Walled Workpiece

Ultracompact Optical Fiber Sensor for Inner Diameter Measurement

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