The shape structure of robot in complex environment is very important in protecting its core control system.It proposes a new robot shape design concept and method in order to protect the robot control system.It uses an adjustable weight balance system to keep robot active mechanical balance in motion,simulates a long time water logging in limited environment to choose the best material,builds the evaluation and modification system based on demands of product esthetics with 3Ds Max.The result shows that the proposed design concept and method can provide valuable reference for the manufacturing of prototype robot.
The smooth orthogonal decomposition method (SOD) is an efficient algorithm that can be used to extract modal matrix and frequencies of lightly damped vibrating systems. It uses the covariance matrices of output-only displacement and velocity responses to form a generalized eigenvalues problem (EVP). The mode shape vectors are estimated by the eigenvectors of the EVP. It is stated in this work that the accuracy of the SOD method is mainly affected by the correlation characteristic of modal coordinate responses. For the damped vibration systems, biases will be contained in the results of using the SOD. Therefore, an iterative smooth orthogonal decomposition (ISOD) method is proposed to identify modal parameters of the damped system from the covariance matrices of the displacement, velocity, and acceleration responses. The modal matrix given by the SOD method is updated in each iteration step using a transformation matrix. The transformation matrix can be efficiently computed using a set of analytical formulations. Meanwhile, natural frequencies and damping ratios are obtained by using a simple search method. The performance of the proposed ISOD method is verified by numerical and experimental studies. The results demonstrate that, by considering the correlation of modal responses, the ISOD method can be used to extract accurately the modal information of vibration systems with coupled modes.
Envelope tracking (ET) power supply provides the power amplifier (PA) with a dynamic supply voltage that tracks the envelope of the input signal to the PA, and the final PA efficiency can be greatly improved. With the ever-advancing tracking bandwidth, the switching frequencies of ET power supplies are pushed to be very high and even difficult to be implemented. To address this issue, the pulse edge independent distribution (PEID) method has been proposed. Based on the idea of alternatively working by sets, the control pulses for the multilevel converter are broken into independent rising and falling edges, and rematching them with optimized new sequences can achieve a 1/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n \in N$ </tex-math></inline-formula> ) ratio of the switching frequency over envelope bandwidth. However, each increase of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> by 1 means that a whole set of voltage cells is added, leading to a great increase in system complexity and cost, especially for high peak-to-average power ratio (PAPR) applications. Besides, due to the irregular and aperiodic feature of the real communication envelope, the PEID control logic may suffer from surplus and imbalance in switching frequency reduction. Thus, this article proposes an improved PEID method. Assisted by the digital control platform, the control logic is redesigned, which can realize a balanced distribution of the rising and falling edges for arbitrary envelopes. Moreover, it can extend the domain of the " <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> " to noninteger, achieving a more subtle resolution of PEID. On this basis, an evaluation function is constructed taking into account the efficiency, voltage-cell quantities, and switching frequency. With the desired weighted coefficients, an optimized comprehensive performance can be achieved. A prototype with 2–27-V output voltage range, 10- and 20-MHz tracking bandwidths, and 8.5-dB PAPR is fabricated and tested in the lab. The experimental results validate the proposed method.
Abstract This article is the second part of a robustness analysis of the aerothermal performance of the winglet structure. A challenging analytical test function and an engineering test are considered to further investigate the response performance of the efficient uncertainty quantification framework proposed in Part 1. Then, a series of original visualizing uncertainty quantities are proposed in this article and applied to the study of uncertainty quantification of the winglet structure. Finally, this efficient framework is applied to the uncertainty quantification of the effect of the conventional squealer tip and three different winglet squealer tips on the heat transfer performance of the GE-E3 rotor blade. According to the results of the uncertainty quantification calculation, in actual operation, the setting of the winglet structures will diminish rather than increase the heat transfer performance of the blade tip. This conclusion is completely opposite to the prediction of the deterministic calculation. The heat flux increase and standard deviation of squealer tip with pressure-side winglet are the highest among the four tip structures, which means that the robustness of heat transfer performance of squealer tip with pressure-side winglet is the worst. The parameter that has the greatest influence on the uncertainty of the heat transfer performance of the four tip structures is the tip clearance. But the influence of the inlet total temperature fluctuation must also be taken into account. So a satisfactory control system should be designed for the actual operation of the gas turbine so that the fluctuation of inlet total temperature can be attenuated rapidly. A positive correlation between the heat flux of the blade tip mean value and the standard deviation is revealed by the uncertainty quantification, which implies that reducing the heat flux of the blade tip mean value in the robust design of the blade tip tends to reduce the heat flux fluctuation as well. Therefore, the objective of the robust design of the blade tip can be either one of reducing the mean value of heat flux of the blade tip mean value or reducing the heat flux of the blade tip standard deviation without multi-objective optimization. It is worth noting that, like the aerodynamic performance uncertainty, there is an antagonistic relationship between the pressure-side cavity and suction-side cavity on the heat transfer performance uncertainty of the blade tip. Therefore, a reasonable ratio of pressure-side cavity to suction-side cavity in the turbine design can also lead to a blade tip with strong heat transfer performance robustness.
The availability of high-quality datasets is increasingly critical in the field of computer vision-based civil structural health monitoring, where deep learning approaches have gained prominence. However, the lack of specialized datasets for such tasks poses a significant challenge for training a reliable model. To address this challenge, a framework, 3DGEN, is proposed to swiftly generate realistic synthetic 3D datasets which can be targeted for specific tasks. The framework is based on diverse 3D civil structural models, rendering them from various angles and providing depth information and camera parameters for training neural networks. By employing mathematical methods, such as analytical solutions and/or numerical simulations, deformation of civil engineering structures can be generated, ensuring a reliable representation of their real-world shapes and characteristics in the 3D datasets. For texture generation, a generative 3D texturing method enables users to specify desired textures using plain English sentences. Two successful experiments are conducted to (1) assess the efficiency of generating the 3D datasets using two distinct structures, (2) train a monocular depth estimation network to perform 3D surface reconstruction with the generated dataset. Notably, 3DGEN is not limited to 3D surface reconstruction; it can also be used for training neural networks for various other tasks. The code and dataset are available at: https://github.com/YANDA-SHAO/Beam-Dataset-SE
The basic geological characteristics of shear quarzs ribbon vein type gold deposits are summarized in the respects of geological structure,ore deposit origin,the rules of mineralization concentration and so on by taking Laijia gold deposit as an example.The prospects of prospecting and developing of shear quarzs ribbon vein type gold deposits which are of wide distribution in the northeast of Jiangxi are discussed also.
Abstract The single-phase charge-control smart energy meter adopts the most advanced energy meter ASIC, microprocessor materials, non-volatile memory, permanently stored information, wide-screen LCD and other advanced technologies. A set of high-accuracy, wide-load, high-sensitivity, low-power-consumption, which is used for measuring the rated frequency of single-phase power grid 50 / 60Hz, in AC active energy meters. This single-phase electricity meter integrates multiple functions in one to realize active and active measures for energy to achieve remote real-time voltage, current, neutral current, power, power factor, and the use of remote systems to achieve sales of electricity users Pre-emptive prepayment. It can flexibly set various functions: free electricity consumption, fault alarm, automatic power off, record opening, automatic meter reading.
Recently, wide attention has been paid to develop deep learning-based models for structural damage identification. However, in most of the studies, the pure deep learning-based structural damage identification methods lack physical interpretability and scientific consistency for generalization. Therefore, although such methods can achieve good damage identification results when data with similar damage patterns used for training and testing the network model, they usually give poor predictions in the unseen domain, i.e., the network's extrapolation ability is limited. In this research, a physics-guided deep learning neural network (PGDLNN) is proposed by incorporating the physical loss constructed by structural modal parameters sensitivity analysis into the original Convolutional Neural Network (CNN) for structural damage identification. The model's physical interpretability is improved, which can lead to more accurate damage identification results, especially in the domain with unseen damage patterns in training the network model. Numerical and experimental studies on simply supported beams are carried out to demonstrate the feasibility and effectiveness of the proposed method. The influences of measurement noise and incomplete measurements are also investigated. The results show that the incorporation of physical knowledge to deep learning model can enhance the generalization of the network, and hence improve the accuracy of damage severity quantification. This study not only performs damage localization and quantification simultaneously using the physics-guided deep learning neural network, but also demonstrates the superiority of incorporating physical knowledge into data-driven deep learning models for structural health monitoring.
Casing deformation is evident during the development of shale oil and gas wells in the Sichuan and Junggar Basins in China. Their casing deformation characteristics, distribution law of deformation points, and main controlling factors were analyzed. According to the analysis results, shear is the main cause of casing deformation of shale oil and gas wells in the Sichuan and Junggar Basins in China and has the characteristics of “a dense heel end and a sparse toe end”. Faults account for 75% of casing deformation points, and fault slip caused by multi-stage fracturing is the primary factor responsible. The calculation model for fault slip that takes into account fracturing fluid invasion was established, and the dynamic variation law of fault slip was clarified: the fracturing fluid intruded into the fault, the relative dislocation of the damaged fault was caused by gravity, and the fault slippage was caused by the increase in fault activation length. This resulted in a linear increase in fault slippage, and the slippage reached its maximum when the fracturing fluid completely penetrated the fault and reached the fault boundary. The slip amount has a positive correlation with the fault length and the in situ stress difference; it increases first and then decreases with the increase in the fault dip angle. The slip amount reaches its maximum when the fault dip angle reaches 45°.
A commonly occurring problem in reliability testing is how to combine pass/fail test data that is collected from disparate environments. We have worked with colleagues in aerospace engineering for a number of years where two types of test environments in use are ground tests and flight tests. Ground tests are less expensive and consequently more numerous. Flight tests are much less frequent, but directly reflect the actual usage environment. We discuss a relatively simple combining approach that realizes the benefit of a larger sample size by using ground test data, but at the same time accounts for the difference between the two environments. We compare our solution with what look like more sophisticated approaches to the problem in order to calibrate its limitations. Overall, we find that our proposed solution is robust to its inherent assumptions, which explains its usefulness in practice. Copyright © 2017 John Wiley & Sons, Ltd.
According to the curing process of composite laminate, a simplified one-dimensional (1D) transient heat conduction model for the composite laminate is established. Based on a typical curing technological curve, the relationships are studied among the processing conditions including convective heat transfer coefficient, the thickness of the part, Fourier number and surplus temperature etc. Furthermore, the useful engineering charts for the center surplus temperature of the composite laminate in the thickness direction are given. Also based on the simplified 1D model, temperature field for the three-dimensional (3D) laminate structure under the hold stage which lay on top of a conforming mold is determined. Then based on the temperature field, the internal strain and curvature distribution of the curing composite laminate are calculated.
A novel Colored Petri Nets (CP-nets) model based test case generation approach is proposed to makes the best of advantages of the ioco testing theory and the CP-nets modeling, where the Conformance Testing orientated CP-nets (CT-CPN) is proposed for modeling certain software systems, and PN-ioco relation is defined as a new conformance relation, and finally test cases are generated through simulating the system CT-CPN models. CP-nets model simulation based test generation approach reflects the data-dependent control flow of the system behaviors, so all test cases are completely feasible for the actual test executions. Besides, better formal modeling and analytic capabilities in CP-nets modeling quite facilitate validating the accuracy of the system CT-CPN model. For effectively extending the applicability of the Petri nets based testing technologies, our novel CT-CPN model based test generation approach may well become a competent choice.
