Dynamic Load Identification and Displacement Prediction Based on FBG for a Cantilever Beam

Song, Xuegang; Zhai, Hong-Qi; Liang, Dakai

doi:10.1007/s42417-019-00091-7

Cited by 9 publications

(5 citation statements)

References 14 publications

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“…e test device is a single pick and single swing device; hence, it can be simplified to a cantilever beam. e free mode and working mode of the cantilever beam could be obtained in [21,22]. erefore, the solution of the natural frequency response function of the test device simplified as a cantilever beam will not be explained in detail in this paper.…”

Section: Load Identification Methodsmentioning

confidence: 99%

Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

Li¹,

Zhai²,

Wang³

et al. 2021

Shock and Vibration

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To explore the relationship between the cutting vibration and the cutting load of a single pick, this paper studied a new method for a single pick cutting rock load identification. This paper improved the low accuracy problem of the regularization method in the inverse process of frequency response function in the traditional load identification method by introducing a filter operator. By combining the inverse pseudoexcitation method and the improved regularization method, the identification of the load dependent on the vibration signal was realized. A single pick cutting rock test equipment was built, which could simulate the actual working conditions of pick cutting rock in the underground or tunnel. By changing cutting speed, cutting angle, cutting spacing, and cutting depth of the single pick, the change trends of real cutting load and identification load were obtained. The load identification method proposed in this paper was consistent with the change trend of the real load under the single pick cutting state. Therefore, the method had good recognition accuracy and the maximum load recognition error was 17.35%. Compared with other traditional load identification methods, the identification error was reduced by a maximum of 1.98%. This method can identify the cutting load of single pick and modify the morbidity problem of frequency response function matrix. The method has a better recognition effect on the cutting load of the pick than the traditional recognition methods. The research could benefit the design of the cutting system and the arrangement of the pick on the coal mine or tunneling machinery.

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Section: Load Identification Methodsmentioning

confidence: 99%

Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

Li¹,

Zhai²,

Wang³

et al. 2021

Shock and Vibration

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show abstract

“…The specific process of Kalman filtering can be described as follows: First, the current state and error covariance matrix of the system are predicted through the system state of the last moment, such as Eqs. ( 10) and (11). Then, Kalman gain is calculated through Eq.…”

Section: Theorymentioning

confidence: 99%

“…9,10 Meanwhile, KF can also be applied in the field of fiber optic sensing, such as predicting the displacement of cantilever beams and reducing noise in dynamic strain FBG sensor networks. 11 At the same time, in some medical applications required precise operations such as retinal surgery and vitrectomy, FBG can use KF to improving the measurement method of tool insertion depth. 12 This paper presents a demodulation scheme of FBG using KF algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…It can effectively reduce the impact of system noise by establishing appropriate system dynamics model and has been widely used in navigation and positioning 9 , 10 . Meanwhile, KF can also be applied in the field of fiber optic sensing, such as predicting the displacement of cantilever beams and reducing noise in dynamic strain FBG sensor networks 11 . At the same time, in some medical applications required precise operations such as retinal surgery and vitrectomy, FBG can use KF to improving the measurement method of tool insertion depth 12 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Kalman filter for dynamic and static measurement of fiber Bragg grating

Mao,

Peng,

Yuan

et al. 2024

Opt. Eng.

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A fast interrogation scheme for fiber Bragg grating (FBG) using Kalman filter (KF) algorithm is presented. The resolution of the system using KF algorithm is tested, and the dynamic interrogation of the system is verified using vibration signals.Meanwhile, different degrees of static pressure were applied to the FBG, and the static interrogation of the system is verified. Experimental verification shows that the Bragg wavelength resolution of the proposed algorithm can reach 0.3 pm and is relatively stable as the wavelength resolution of the system decreases. In addition, the antinoise performance of KF algorithm is compared with that of direct peak search algorithm. Compared with other commonly used FBG peak search algorithms, the innovative algorithm has the characteristics of low computational cost, high sensitivity, and stability.

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“…Tessler et al from Langley Research Center (NASA) introduced the least square variations equations to develop an inverse finite element method (IFEM) for reconstruction problems [20]. Song et al proposed a new method to reconstruct the dynamic deformation of beam structures by using fiber Bragg grating sensors and iFEM [21]. Zhao et al proposed a real-time monitoring method of the wing state using the inverse finite element method.…”

Section: Introductionmentioning

confidence: 99%

A Highly Accurate Method for Deformation Reconstruction of Smart Deformable Structures Based on Flexible Strain Sensors

Gao

Liao

et al. 2022

Micromachines

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Smart deformable structures that integrate designing, sensing, and controlling technology have been widely applied in the fields of aerospace, robotics, and biomedical engineering due to their multi-functional requirements. The deformation reconstruction method essential for security monitoring and shape controlling, especially for the large deflection deformation, remains a challenge on accuracy and efficiency. This paper takes a wind tunnel’s fixed-flexible nozzle (FFN) plate as the research object to develop a highly accurate deformation reconstruction method based on sensing information from flexible strain sensors. The mechanical behaviors of the FFN plate with large deflection deformation, which is modeled as a cantilever beam, are studied to analyze the relationship of the strain and moment. Furthermore, the large deflection factor and shell bending theory are creatively utilized to derive and modify the strain–moment based reconstruction method (SMRM), where the contour of the FFN plate is solved by particular elliptic integrals. As a result, structural simulation based on ABAQUS further demonstrates that the reconstruction error of SMRM is 21.13% less than that of the classic Ko-based reconstruction method (KORM). An FFN prototype accompanied by customized flexible sensors is developed to evaluate the accuracy and efficiency of the SMRM, resulting in a maximum relative error of 3.97% that is acceptable for practical applications in smart deformable structures, not limited to the FFN plate.

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Dynamic Load Identification and Displacement Prediction Based on FBG for a Cantilever Beam

Cited by 9 publications

References 14 publications

Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

Kalman filter for dynamic and static measurement of fiber Bragg grating

A Highly Accurate Method for Deformation Reconstruction of Smart Deformable Structures Based on Flexible Strain Sensors

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