scholarly journals Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Lei Dong ◽  
Siyu Zhai ◽  
Bukang Wang ◽  
Liang Dong ◽  
Junyuan Wang ◽  
...  
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Regularization Method ◽  
Frequency Response Function ◽  
Cutting Speed ◽  
Vibration Signal ◽  
Maximum Load ◽  
Load Identification ◽  
Identification Method ◽  
Rock Load

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.

scholarly journals Single Pick Cutting Rock Load Identification Based on Improved Regularization Method

2020 ◽  
Author(s):  
Lei Dong ◽  
Siyu Zhai ◽  
Bukang Wang ◽  
Liang Dong ◽  
Junyuan Wang ◽  
...  
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Regularization Method ◽  
Frequency Response Function ◽  
Cutting Speed ◽  
Vibration Signal ◽  
Maximum Load ◽  
Load Identification ◽  
Identification Method ◽  
Rock Load

Abstract 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.

Load identification with regularized total least-squares method

2021 ◽  
pp. 107754632110248
Author(s):  
Zhonghua Tang ◽  
Zhifei Zhang ◽  
Zhongming Xu ◽  
Yansong He ◽  
Jie Jin
Keyword(s):  
Frequency Response ◽  
Least Squares ◽  
Response Function ◽  
Frequency Response Function ◽  
Least Squares Method ◽  
Total Least Squares ◽  
Load Identification ◽  
Acceleration Response ◽  
Regularized Total Least Squares ◽  
Function Matrix

Load identification in structural dynamics is an ill-conditioned inverse problem, and the errors existing in both the frequency response function matrix and the acceleration response have a great influence on the accuracy of identification. The Tikhonov regularized least-squares method, which is a common approach for load identification, takes the effect of the acceleration response errors into account but neglects the effect of the errors of the frequency response function matrix. In this article, a Tikhonov regularized total least-squares method for load identification is presented. First, the total least-squares method which can minimize the errors of the frequency response function matrix and acceleration response simultaneously is introduced into load identification. Then Tikhonov regularization is used to regularize the total least-squares method to improve the ill-conditioning of the frequency response function matrix. The regularization parameter is selected by the L-curve criterion. To validate the performance of the regularized total least-squares method, a load identification simulation with two excitation loads is studied on a plate based on the finite element method and a load identification experiment with two excitation loads is conducted on an aluminum plate. Both simulation and experiment results show that the excitation loads identified by the regularized total least-squares method match the actual loads well although there are errors existing in both the frequency response function matrix and acceleration response. In experiment, the average relative error of the regularized total least-squares method is 13.00% for excitation load 1 and 20.02% for excitation load 2, whereas the average relative error of the regularized least-squares method is 35.86% and 53.09% for excitation load 1 and excitation load 2, respectively. This result reveals that the regularized total least-squares method is more effective than the regularized least-squares method for load identification.

Frequency Response-Based Indirect Load Identification Using Optimum Placement of Strain Gages and Accelerometers

2019 ◽  
Vol 141 (3) ◽  
Author(s):  
Hana'a M. Alqam ◽  
Anoop K. Dhingra
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Structural Response ◽  
Mode Shapes ◽  
Load Identification ◽  
Strain Gages ◽  
Design Algorithm ◽  
Displacement Mode ◽  
Optimum Sensor

This paper presents an approach for indirect identification of dynamic loads acting on a structure through measurement of structural response at a finite number of optimally selected locations. Using the concept of frequency response function (FRF), the structure itself is considered as a load transducer. Two different types of sensors are investigated to measure the structural response. These include a use of accelerometers that leads to the identification of the displacement mode shapes. The second measurement approach involves a use of strain gages since strain measurements are directly related to imposed loads. A use of mixed strain-acceleration measurements is also considered in this work. Optimum sensor locations are determined herein using the D-optimal design algorithm that provides most precise load estimates. The concepts of indirect load identification, strain frequency response function (SFRF), displacement frequency response function (DFRF), along with the optimal locations for sensors are used in this paper. The fundamental theory for strain-based modal analysis is applied to help estimate imposed harmonic loads. The similarities and differences between acceleration-based load identification and strain-based load identification are discussed through numerical examples.

Substructure Damage Identification Based on Model Updating of Frequency Response Function

2021 ◽  
pp. 2150171
Author(s):  
Youliang Fang ◽  
Pengrui Su ◽  
Jingyu Shao ◽  
Jiaqi Lou ◽  
Ying Zhang
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Large Scale ◽  
Damage Identification ◽  
Model Updating ◽  
Mass Matrix ◽  
Frame Structure ◽  
Simplified Model ◽  
Identification Method

Model updating of large-scale structures is difficult to carry out when using a frequency response function (FRF) for damage identification, as the solutions for the global system matrices with too many degrees of freedom are required in each iteration. In this paper, a substructure damage identification method is proposed based on the model updating of the acceleration FRF. The original finite element model is divided into several substructures using the improved reduced system (IRS) by the dynamic condensation method, resulting in the simplified substructure model. The final simplified model is composed of the simplified mass matrix and stiffness matrix of the substructure considered. The damage acceleration FRF to be identified is used to iteratively update the simplified model. The locations and extents of the damage elements are obtained by updating the results, which reduces the number of uncertain parameters to be updated and leads to the rapid convergence of the optimization process. In the iteration, L1 norm regularization is introduced to solve the ill-posed problem, which improves the stability of the identification results. A numerical simulation of a six-story steel frame structure under various working conditions was carried out to verify the effectiveness of the proposed method, which was also validated by the experiments. The robustness and performance of the proposed damage identification method based on substructures have been demonstrated.

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