Vibration displacement of civil structures are crucial information for structural health monitoring (SHM). However, the challenges and costs associated with traditional physical sensors make displacement measurement difficult. In recent years computer vision (CV) techniques have been employed for measuring vibration displacement in civil structures. There has been a growing interest in CV-based three-dimensional (3D) displacement measurement, as it provides comprehensive information for structural health assessment. Most existing methods use multi-view geometry, requiring multiple cameras for depth measurement. This paper proposes a new system for measuring the 3D vibration displacement utilising a single camera. Instead of using multi-view geometry, deep neural networks are utilised to learn the depth of scenes from monocular images. Compared with the multi-view methods, the proposed 3D measurement system with monocular vision is more cost-effective and much more convenient to set up and use in practice, avoiding the complicated calibration and object matching between multiple cameras. Experimental tests are conducted in the laboratory to investigate the feasibility of the proposed system. Physical displacement sensors are equipped with the testing structure to provide the ground truth data. The results demonstrate that the proposed monocular 3D displacement system is able to produce reasonable 3D full-field displacement measurement, which makes monocular image based CV system a promising approach to achieve 3D displacement measurement, with its obvious advantages in cost and convenience compared to the traditional sensor-based or multi view CV-based methods.
GPS modernization provides a foundation for developing multi-frequency a ttitude determination receiver.To satisfy the attitude determination requiremen ts of platforms such as low orbit satellites,missiles,aircrafts and naval vess els,a general design scheme for multi-frequency attitude determination receive r is given,which is composed of antenna unit,measurement unit and attitude comp utation unit.Then,some key technologies are investigated,including real-time cycle slip detection and correction based on GPS multi-frequency combination no i se residual,and the ambiguity resolution algorithm for single epoch using geome try restriction.The computation equations and flows are described in detail.Fi nally,a static test is carried out for the GPS-based single frequency receiver and multi-frequency receiver for attitude determination.The test results indic a te that,as for the attitude determination accuracy and computation success rati o,the multi-frequency receiver shows better performance than that of the singl e-frequency receiver.
To ensure the safe operation of power system,operators must obtain timely knowledge of the power system disturbance and take appropriate countermeasures.This paper proposes an approach for detecting the disturbance based on mathematical morphology.The principle of mathematical morphology is produced;the selection of structural elements in disturbance detection is analyzed;the whole working flow of disturbance detection is formulated.Finally,simulation calculation and various detected disturbance data are used to verify that the approach can exactly and effectively detect the disturbance from the power system PMU signals,showing high practical value.
The multiphase PM synchronous motor drive systems have been developed rapidly in modern industry and agriculture. In this paper, an adaptive nonlinear control design is applied to a multiphase PM synchronous motor system. Based on the deduced mathematic model with both electrical and mechanical dynamics of motor, the back stepping and fuzzy neural network control schemes are used to design the speed controller due to the nonlinear characteristics of multiphase motor drive. The proposed control scheme is proved with Lyapunov stability theory by recursive manner, and its effectiveness is verified by simulation results at different operating conditions. Compared to the conventional PI speed controller, the developed adaptive nonlinear speed controller is robust to the uncertainties.
Summary Modern multifractured shale-gas/oil wells are horizontal wells completed with simultaneous-fracturing, zipper-fracturing, and (in particular) modified-zipper-fracturing techniques. An analytical model was developed in this study for predicting the long-term productivity of these wells under conditions of pseudosteady-state (PSSS) flow, considering the cross-bilinear flow in the rock matrix and hydraulic fractures. Performance of the model was verified with the well-productivity data obtained from a shale-gas well and a shale-oil well. Sensitivity analyses were performed to identify key parameters of hydraulic fracturing affecting well productivity. The conducted field case studies show that the analytical model overpredicts shale-gas-well productivity by 2.3% and underpredicts shale-oil productivity by 7.4%. A sensitivity analysis with the model indicates that well productivity increases with reduced fracture spacing, increased fracture length, and increased fracture width, but not proportionally. Whenever operational restrictions permit, more fractures with high density should be created in the hydraulic-fracturing process to maximize well productivity. The benefit of increasing fracture width should diminish as the fracture width becomes large. Increasing fracture length by pumping more fracturing fluid can increase well-production rate nearly proportionally. Therefore, it is desirable to create long fractures by pumping high volumes of fracturing fluid in the hydraulic-fracturing process.
This paper presents a development and application of decision tree-based ensemble technique, extremely randomised tree (ERT) as a multi-output regression model in structural damage quantification of civil engineering structures. Acceleration responses are measured from structures when an impact force is applied. Impulse response functions as structural vibration properties are extracted from the acceleration responses and are processed as input to the ERT. Moving averaging with a suitable window size is performed to reduce the effect of noise, and principal component analysis is performed further for the dimensionality reduction. The damage level is defined in terms of elemental stiffness reduction. Both numerical and experimental studies are conducted to investigate the capability of using the proposed approach for structural damage identification and quantification. The numerical studies are carried out on a simply supported beam and experimental validations on a steel frame structure in the laboratory. From the results, the proposed method can provide good elemental structural damage quantification results. The computational time for the proposed approach is much less than random forest (RF) technique that has been used for the same application using acceleration responses. The performance of the proposed approach is compared with RF in terms of identification accuracy and training efficiency.
Abstract Accurately assessing the robustness of the aerothermal performance of the blade tip is important considering that uncertainty is inevitable in the actual operation of turbines. However, the conventional uncertainty quantification methods are computationally inefficient for such an expensive black-box problem as turbine aerothermal performance prediction. In this paper, an efficient framework that is based on the combination of the sparse polynomial chaos expansion (PCE) and universal Kriging (UK) metamodel is applied to the uncertainty quantification of the effect of the conventional squealer tip and three different winglet squealer tips on the aerodynamic performance of the GE-E3 rotor blade tip. However, the inlet total pressure, inlet total temperature, and inlet flow angle are considered to flow condition uncertainty parameters and tip clearance is considered a geometrical uncertainty parameter. According to the results of the uncertainty quantification, in actual operation, although the setup of the winglet structure can still reduce the leakage flowrate, its effect will be much lower than predicted by deterministic calculations. The parameter that has the greatest influence on the uncertainty of the aerodynamic performance of the four tip structures is the tip clearance. Therefore, the geometric accuracy of the tip clearance should be strictly ensured in the turbine blade assembly and marching process. The uncertainty quantification calculations reveal that there is an antagonistic relationship between the pressure side cavity and suction side cavity on the aerodynamic performance uncertainty of the blade tip, which indicates a reasonable ratio of pressure side cavity and suction side cavity can make the fluctuation of the aerodynamic performance of the pressure side cavity vortex and suction side cavity vortex completely cancel, and thus design the winglet squealer tip with strong aerodynamic performance robustness.
Bridge damage detection is crucial for ensuring the safety and integrity of the bridge structure.Traditional methods for damage detection often rely on manual inspections or sensor-based measurements, which can be time-consuming and costly.In recent years, computer vision techniques have shown promise in bridge displacement measurement and damage detection.The objective of this study is to extract reliable features from displacement measured with computer vision-based method that are sensitive to structural condition change while robust to the variation of operational condition.In particular, this research paper presents a novel approach for bridge damage detection using an indicator defined based on the transverse influence ratio (DTIR) from computer vision-based displacement measurements.The proposed method utilizes computer vision algorithms to extract bridge girder displacement responses under moving load.The DTIR indicator, defined as the vehicle-induced bridge quasi-static displacement ratio between two adjacent girders, is extracted as the damage-sensitive feature.Theoretical derivation proves that DTIR indicator is only related to the structural condition and the transverse position of a vehicle over the deck, while independent of the variation of vehicle weight and speed.To validate the effectiveness of the proposed method, a series of drive-by experiments were performed on a multi-girder beam bridge with different structural conditions.The results demonstrated the capability of the proposed approach in accurately detecting the occurrence and possible location of structural damage.Furthermore, the paper discusses the advantages and limitations of the DTIR indicator for bridge damage detection, as well as how to generalize the proposed method to bridges with more than two traffic lanes.In conclusion, the proposed method offers a promising solution for low cost, easy deployable and scalable health monitoring solution for bridges under operating conditions.
In this paper,for the case of one domestic self-elevating drilling unit,mainly introduce rack repair methods,in order to achieve the communication and reference.
The paper introduced the procedure of casting in place of single box and room wide flange plat box beam,process and main points of quality control for reference.
In this paper we consider the Schwarz radical of linear algebraic semigroups as defined in semigroup theory. We give some new characterizations of the complete regularity, regularity and solvability of irreducible linear algebraic monoids in terms of Schwarz radical data. Moreover, we give a generalization about the results of the kernel to the results of completely regular $$\mathscr {J}$$ -classes.
