Dynamics of rectangular laminated composite plates with selective layer-wise fillering rested on elastic foundation using higher-order layer-wise theory

The rapid development of urbanization has changed the traffic and transportation in the central area. The change of the surrounding rock and structural stress state of the project under construction caused by the tunnel construction in the same period has caused great harm to its safe use and casualties. Shield construction technology can achieve safe excavation and lining, with high degree of automation. And it is a relatively common construction method at present. But its adaptability to section size and section environmental conditions is poor. In view of this, from the analysis of construction monitoring data, the study established a longitudinal model considering lateral effects from the perspective of lateral characteristics. It also achieved stress assessment and improvement through lateral deformation calculation, segment ring bolt calculation and formula correction. The experimental results showed that the opening at the circumferential seam of the right line of the test tunnel under this method is 8.9 mm. The radius of curvature is 758 mm, and the safety assessment level of longitudinal deformation is 3. This method can effectively guarantee the safety of shield tunnel construction and has good guiding value for tunnel management and maintenance.

Section: Related Workmentioning

confidence: 99%

Longitudinal deformation of Shield tunnel based on construction monitoring data

Yao¹

2023

“…The main bearing RUL prediction methods based on vibration signals are model-based method and data-driven method [7]. The former can accurately predict the residual life of rolling bearings, but it has some disadvantages such as difficult modeling and low prediction accuracy for complex mechanical systems [8][9][10]. The data-driven method can study the mapping law between data features and residual life through machine learning method, which has the advantages of good universality and high economy, so it has become the focus of current RUL prediction [11].…”

Section: Introductionmentioning

confidence: 99%

Life prediction method of rolling bearing based on CNN-LSTM-AM

Huang,

Chen,

Chen

et al. 2024

Bearing is the key component to determine the health of machinery, and it is of great significance to monitor its working status in real time and predict its remaining useful life. In recent years, the RUL prediction method based on deep learning has been widely used and achieved good prediction results. Here, a bearing life prediction method based on convolution neural network (CNN), long short term memory (LSTM) and attention mechanism (AM) is proposed. First of all, the time domain and frequency domain features of the original vibration signals of rolling bearings are extracted, and the extracted feature set is normalized as the input of CNN. The main function of CNN is to extract spatial features and reduce the dimension of the data. Then, using LSTM to extract the information that may be ignored by CNN, the feature information extracted by CNN-LSTM is input to the attention mechanism for weighting, and the key information is screened. And then more accurately represent the degradation characteristics of the equipment, and finally get the bearing remaining life. The performance of the model is verified by two sets of public data sets, and the experimental results show that it is compared with the CNN-LSTM method. The root mean square error (RMSE) index based on CNN-LSTM-AM method is reduced by 14.6 % and 13.8 % respectively, and the score index is increased by 2.0 % and 2.4 % respectively. The results show that the proposed method has higher accuracy in bearing RUL prediction.

“…Jena, Parhi and other authors [10][11][12][13][14][15] studied cracked structures subjected to moving mass problems. Besides, Parida, Jena and others [16][17][18][19][20][21] investigated the dynamic and static problems of composite structures.…”

Section: Introductionmentioning

confidence: 99%

Dynamic response of a space flexible arm with a moving mass

Zhao¹

2023

The dynamic characteristic of a space rotating flexible arm with moving mass were investigated. The space arm with moving mass can rotate around the fixed end in horizontal and vertical planes simultaneously. And the lateral deflections of the arm in the two planes were considered. The equations of the structure were derived by the Lagrange’s equation with the assumed mode method. And a system of binary second order linear differential equations is gotten. Based on the central difference method, a conditionally stable algorithm for solving the equations is established. Due to the coupling of lateral displacements of the arm in horizontal and vertical planes, the increase of the angular velocity in one plane will increase the lateral displacements in the other plane. When the angle between the arm and the horizontal plane increases, the component of gravity along the normal direction of the beam will decrease, resulting in a decrease in lateral displacements in vertical plane, however, it will lead to a decrease in stiffness in horizontal plane and thus an increase in lateral displacements. Compared with moving mass, moving load ignores the influence of inertial force, so the calculation results of moving mass and moving load are different. The conclusions provide calculation basis for the design of similar structures.