Identification of Dynamic Loads Based on Second-Order Taylor-Series Expansion Method

Li, Xiao-Wang; Deng, Zhongliang

doi:10.1155/2016/6461427

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…Load identification methods can be roughly divided into three categories: time domain, frequency domain, and modern intelligence [6][7][8]. Time domain method includes series expansion method, Kalman filter method, and inverse system method [9][10][11].…”

Section: Introductionmentioning

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: Introductionmentioning

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

“…Liu et al [26] combined Gegenbauer polynomial and Tikhonov regularization method to identify dynamic force acting on the stochastic structure. Li and Deng [27] proposed the second-order Taylor-series expansion method to identify the dynamic force in time domain, and the simulation study on a cantilever model shows that the proposed method has high identification accuracy. Li et al [28] developed a comprehensive algorithm combining Taylor polynomial iteration and cubic Catmull-Rom spline interpolation to identify the distributed dynamic excitation in the domain.…”

Section: Introductionmentioning

confidence: 99%

Regularized Cubic B-Spline Collocation Method With Modified L-Curve Criterion for Impact Force Identification

Liu

Xie

et al. 2020

IEEE Access

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The time history of the impact force, especially for the peak force, is vital to monitor the performance of mechanical products over the lifetime. However, considering the limitation of sensing technology and inaccessibility of installing, it is always difficult or even impossible to measure the force directly in engineering practice. Therefore, a regularized cubic B-spline collocation (RCBSC) method combined with the modified L-curve criterion (RCBSC-ML) is presented to identify the impact force by easily measurable dynamic response. Because the profile of cubic B-spline is close to that of impact force, a linear combination of cubic B-spline functions is used to approximate the unknown impact force. Then the force identification equation is reformed, wherein the unknown variable changes from impact force vector to weight coefficient vector. Furthermore, the modified L-curve criterion is developed to select the optimal number of collocation points which is the regularization parameter of RCBSC method. Rich simulation studies on a five degree-of-freedoms structure and experimental studies on a simplified artillery test-bed are performed to validate the performance of RCBSC-ML method. The results illustrate that RCBSC-ML method can be used to accurately identify the unknown impact force, and compared with modified generalized cross validation criterion, the presented modified L-curve criterion is more suitable to determine the optimal regularization parameter of RCBSC method. Furthermore, compared with classical Tikhonov regularization method, RCBSC-ML method is more efficient and accurate in impact force identification. INDEX TERMS Cubic B-spline, impact force identification, ill-posed inverse problem, modified L-curve criterion.

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“…Load identification methods can be roughly divided into three categories: time domain method (Liu et al 2016), frequency domain method (Wu et al 2018) and modern intelligent method (Lee and Liu 2014). Time domain method includes series expansion method (Li and Deng 2016), Kalman filter method (Zhi et al 2018) and inverse system method (Wang et al 2016). The application in complex mechanical systems has great limitations, because the input and output of the time domain system are relatively complicated convolution relationship and the amount of calculation after discretization is too large.…”

Section: Introductionmentioning

confidence: 99%

Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

Dong

Zhai

Wang

et al. 2020

Preprint

View full text Add to dashboard Cite

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 pseudo excitation 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 underground or tunnel. By changing cutting speed, cutting angle, cutting line 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 the traditional load identification method, 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 method. The research could benefit for the design of the cutting system and the arrangement of the pick on the coal mine or tunneling machinery.

show abstract

Identification of Dynamic Loads Based on Second-Order Taylor-Series Expansion Method

Cited by 5 publications

References 22 publications

Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

Regularized Cubic B-Spline Collocation Method With Modified L-Curve Criterion for Impact Force Identification

Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

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