Publications

Automatic complex concrete crack detection and quantification based on point clouds and deep learning

A Label Embedding Method for Multi-label Classification via Exploiting Local Label Correlations

Real-Time Identification of Time-Varying Cable Force Using an Improved Adaptive Extended Kalman Filter

The real-time identification of time-varying cable force is critical for accurately evaluating the fatigue damage of cables and assessing the safety condition of bridges. In the context of unknown wind excitations and only one available accelerometer, this paper proposes a novel cable force identification method based on an improved adaptive extended Kalman filter (IAEKF). Firstly, the governing equation of the stay cable motion, which includes the cable force variation coefficient, is expressed in the modal domain. It is transformed into a state equation by defining an augmented Kalman state vector with the cable force variation coefficient concerned. The cable force variation coefficient is then recursively estimated and closely tracked in real time by the proposed IAEKF. The contribution of this paper is that an updated fading-factor matrix is considered in the IAEKF, and the adaptive noise error covariance matrices are determined via an optimization procedure rather than by experience. The effectiveness of the proposed method is demonstrated by the numerical model of a real-world cable-supported bridge and an experimental scaled steel stay cable. Results indicate that the proposed method can identify the time-varying cable force in real time when the cable acceleration of only one measurement point is available.

FEM Analysis of Initial Stiffness of Steel Portal Frame Joint

针对工程中应用广泛的门式刚架轻型房屋钢结构,给出节点初始刚度的计算公式,运用ANSYS分析了端板连接处的刚度,对影响其刚度的几种要素进行分类讨论,并讨论节点刚度对结构整体弯矩分布的影响.

Key Technologies for Health Management and Applications of Aero-Engine Based on Principal Component Analysis

Aero-Engine health management generally involves a series of activities over the period from the aerospace breaking down until it returning to normal, including signal processing, monitoring, health assessment, decision supporting, human-computer interaction, and so on. As one of the key technology of Aero-Engine health management, fault diagnosis plays a very important role on the safe operation of Aero-Engine. Currently, for effective challenging Aero-Engine health management, a fault diagnosis of Aero-Engine based on Principal Component Analysis (PCA) s proposed. Firstly, based on a variety of significant parameters of the collected information, principal component analysis model is established. Secondly, the fault diagnosis of engine operating conditions is realized by comparing the T 2 statistic and Squared Prediction Error (SPE) statistic as an engine running in good condition threshold limits. Finally, through the variable's cumulative contributions diagram with the behavior of SPE overrun, the fault variables are effectively worked out. Experimental results show that the proposed PCA method can efficiently come true Aero-Engine health management o and has some engineering applications values.

Efficient Uncertainty Quantification and Sensitivity Analysis on the Aerothermal Performance of Turbine Blade Squealer Tip

Abstract It is important to accurately estimate the impact of flow and geometric variations for engineering design and manufacture. In this paper, an efficient uncertainty quantification analysis framework based on the combination of Universal Kriging (UK) metamodels and sparse Polynomial Chaos Expansion (PCE) is proposed. A challenging analytical test function and an engineering test are considered to investigate the response performance of the UK-PCE method. Then, this method was applied to the uncertainty quantification on the aerodynamic and heat transfer performance of GE-E3 rotor blade squealer tip. Meanwhile, a global parameter sensitivity analysis using the Sobol Indice method is carried out to identify the key parameters for the aerothermal performance of the squealer tip. Wherein, the inlet total temperature is considered as flow condition uncertainty parameters and tip clearance and cavity depth are considered as geometrical uncertainty parameters. The results show that the UK-PCE method reduces the computational cost by more than 70% in comparison to the typical PCE method. Under the influence of the uncertain geometry and operating conditions, the heat flux of the squealer tip basically conforms to the normal distribution and the statistical mean value of it increased by 5.32% relative to the design value and the probability of it deviating from the design value by 5% is as high as 44.62%. The result of sensitivity analysis reveals that the uncertainty of the aerodynamic characteristics of the squealer tip is almost entirely caused by the tip clearance which accounts for 90.31% and 98.77% of the variance of the leakage flow rate and total pressure loss coefficient. And it is also a key variable for the uncertainty of the heat transfer performance considering that its variance indexes for tip heat flux and blade heat flux are 31.23% and 73.14%, respectively. Finally, the influence mechanisms of the uncertainty parameters on the aerothermal performance of the squealer tip are investigated by detailed flow and thermal field analysis.

Substructure damage identification based on wavelet-domain response reconstruction

This article presents experimental verification on damage identification of a substructure using a wavelet-domain response reconstruction technique. The response reconstruction is based on the unit impulse response function in the wavelet domain to form a transformation matrix between two different sets of time-domain response vectors. The initial finite element model updating is performed to achieve an accurate model in the intact stage as a baseline, and measured acceleration responses from the damaged substructure are used for the damage identification. Substructure damage identification is conducted by minimizing the discrepancy between a measured response vector and the reconstructed one. A dynamic response sensitivity-based model updating method is used for the identification of the target substructure. Local damage is identified as a change in the elemental stiffness factors. The adaptive Tikhonov regularization technique is adopted to improve the identification results with measured responses including measurement and environmental noises in laboratory. Experimental studies on a 7-storey plane frame structure are conducted to investigate the accuracy of the presented response reconstruction technique and the performance of substructure damage identification approach. Good response reconstruction accuracy is obtained with the baseline model, and the introduced damages in the substructure can be identified effectively. The damage locations are identified correctly with a close estimation of damage extents.

Study on Variation Law of In-Situ Stress Around Well Under Different Fracturing Technology of Shale Gas Platform Well

In recent years, shale gas development in Fengnan 4 well area of Xinjiang Oilfield is dominated by platform wells. In contrast to conventional fracturing development, the zipper fracturing is primarily used in this block. In this paper, the finite element model of platform well fracturing is established by establishing the mathematical model of multi-cluster fractures interacting with each other, considering the condition of multi-well and multi-fracture. The sequential fracturing of platform wells and the zipper fracturing (well alternating fracturing, fracturing stage alternating fracturing) are simulated in this paper, and the variation law of induced stress and horizontal principal s are established by establishing the mathematical model of multi-cluster fractures interacting with each other, taking into consideration the condition of multi-well and multi-fracture. Considered is the variance of in-situ stress in various fracturing techniques. The results show that: 1) In the fracturing of platform wells, due to the mutual interference of adjacent well fracturing, the non-uniformity of fracture propagation is high, which results in a non-uniform change of in-suit stress; 2) Under each fracturing process condition, the in-suit stress increases to some extent, with the minimum principal stress increasing the most, followed by the vertical principal stress and the maximum horizontal principal stress. 3) Zipper fracturing has a bigger impact than sequential fracturing on the platform intermediate well's peripheral stress value. The research results may be useful for optimizing the well fracturing mode on a shale gas platform.

Research on Sensorless Control Method of Permanent Magnet DC Linear Motor Based on Line Back EMF

A sensorless commutation control method based on the zero crossing principle of line back EMF is proposed for permanent magnet DC linear motor with distortion of opposite EMF. Through qualitative analysis of waveform and quantitative derivation of series theory formula, it is proved that even if the opposite potential is distorted, the zero point of line back potential is still consistent with the actual electronic commutation point of the system. At the same time, in order to avoid missing the zero point of line back EMF, a commutation control method based on s function is constructed. The simulation results show that the method meets the system requirements.

A linear fractional transform (LFT) based model for interconnect parametric uncertainty

As we scale toward nanometer technologies, the increase in interconnect parameter variations will bring significant performance variability. New design methodologies will emerge to facilitate construction of reliable systems from unreliable nanometer scale components. Such methodologies require new performance models which accurately capture the manufacturing realities. In this paper, we present a Linear Fractional Transform (LFT) based model for interconnect Parametric Uncertainty. This new model formulates the interconnect parameter uncertainty as a repeated scalar uncertainty structure. With the help of generalized Balanced Truncation Realization (BTR) based on Linear Matrix Inequalities (LMI's), the new model reduces the order of the original interconnect network while preserves the stability. This paper also shows that the LFT based model even guarantees passivity if the BTR reduction is based on solutions to a pair of Linear Matrix Inequalities (LMI's) which generalizes Lur'e equations.

The effect of initial deflection on nonlinear lateral vibration of drill stem

In the past study of the lateral vibration of drill stem, the effect of the initial deflection was ignored. For this reason, the nonlinear lateral free vibration of drill stem with initial deflection is investigated by the method of perturbation. The first perturbation formulas of the first frequency and vib ration are derived. The influence of the initial deflection on the nonlinear lateral free vibration of drill stem is discussed. The result shows that, the initial deflection is not the effect on linear vibration of drill stem, the first frequency of nonlinear vibration decreases with the initial deflection of the drill stem increased.The effect of initial deflection on the first frequency increased with either the length of drill stem or the axial compressive force on the drill stem increases.It is indicated that, in analyzing the nonlinear lateral vibration of drill stem,the initial deflection should be taken into consideration if the initial deflection is larger and the drill stem is longer or the axial compressive force is stronger.

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Using Convolutional Layer Features for Indoor Human Activity Recognition based on Spatial Location Information

Identifying human actions has great importance for various applications, especially in the smart home, fitness tracking and health monitoring domains. However, human activity recognition still remains a challenging task. This is mainly due to the broad range of human activities as well as the rich variation of a given activity can be performed. In this paper, we dealt with the problem by making use of spatial location information of three different parts of a human body, which are derived via three UWB (ultrawide band) tags and an Ubisense positioning system. In order to improve the accuracy, we proposed a recognition method: convolutional layer features plus SVM (Support Vector Machine). We pre-process the raw spatial location data and transfer them into motion feature, frequency feature and statistic feature. These features are input into the CNN (Convolutional Neural Network) to generate the convolutional layer features, and then we use SVM to classify these features. By comparing the experimental results, the best recognition rate of different experimenters is 89.75%, which shows its feasibility.

Temperature Field Characteristics of Concrete Box Girders in Rigid-Frame Bridges Based on Fine Simulation and Monitoring

Finite Element Analysis for Brittle and Ductile Fracture Using a Unified Cohesive Zone Model

A unified cohesive zone model is proposed. By introducing a parameter which denotes the ductility of the material, the proposed model can be used to simulate both brittle and ductile fracture. No fitting experimental data is needed in calibrating the parameters of the proposed model, and this leads to a high predictive ability of the model. Several numerical examples for brittle and ductile materials are given using finite element method. The good agreement between numerical results and experimental data proves the applicability and accuracy of the proposed cohesive zone model.

Study on the effect of fractures on conventional induction log based on physical and numerical simulation

Review of Using Operational Modal Analysis for Condition Monitoring

Model based fault diagnosis for drillstring washout using iterated unscented Kalman filter