Technical Management Office of Naval Defense Engineering

Beijing, China

Technical Management Office of Naval Defense Engineering

Beijing, China

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He C.,PLA University of Science and Technology | Xing J.,PLA University of Science and Technology | Li J.,Technical Management Office of Naval Defense Engineering | Yang Q.,PLA University of Science and Technology | And 2 more authors.
Mathematical Problems in Engineering | Year: 2015

Optimal sensor placement (OSP) is an important part in the structural health monitoring. Due to the ability of ensuring the linear independence of the tested modal vectors, the minimum modal assurance criterion (minMAC) is considered as an effective method and is used widely. However, some defects are present in this method, such as the low modal energy and the long computation time. A new OSP method named IAGA-MMAC is presented in this study to settle the issue. First, a modified modal assurance criterion (MMAC) is proposed to improve the modal energy of the selected locations. Then, an improved adaptive genetic algorithm (IAGA), which uses the root mean square of off-diagonal elements in the MMAC matrix as the fitness function, is proposed to enhance computation efficiency. A case study of sensor placement on a numerically simulated wharf structure is provided to verify the effectiveness of the IAGA-MMAC strategy, and two different methods are used as contrast experiments. A comparison of these strategies shows that the optimal results obtained by the IAGA-MMAC method have a high modal strain energy, a quick computational speed, and small off-diagonal elements in the MMAC matrix. © 2015 Can He et al.


He C.,PLA University of Science and Technology | Xing J.,PLA University of Science and Technology | Li J.,Technical Management Office of Naval Defense Engineering | Yang Q.,PLA University of Science and Technology | And 2 more authors.
International Journal of Distributed Sensor Networks | Year: 2013

Optimal sensor placement is an important part in the structural health monitoring of bridge structures. However, some defects are present in the existing methods, such as the focus on a single optimal index, the selection of modal order and sensor number based on experience, and the long computation time. A hybrid optimization strategy named MSE-AGA is proposed in this study to address these problems. The approach firstly selects modal order using modal participation factor. Then, the modal strain energy method is adopted to conduct the initial sensor placement. Finally, the adaptive genetic algorithm (AGA) is utilized to determine the optimal number and locations of the sensors, which uses the root mean square of off-diagonal elements in the modal assurance criterion matrix as the fitness function. A case study of sensor placement on a numerically simulated bridge structure is provided to verify the effectiveness of the MSE-AGA strategy, and the AGA method without initial placement is used as a contrast experiment. A comparison of these strategies shows that the optimal results obtained by the MSE-AGA method have a high modal strain energy index, a short computation time, and small off-diagonal elements in the modal assurance criterion matrix. © 2013 Can He et al.


Wang H.,PLA University of Science and Technology | Xing J.,PLA University of Science and Technology | Li J.,Technical Management Office of Naval Defense Engineering | Yang Q.,PLA University of Science and Technology | And 3 more authors.
IEICE Transactions on Information and Systems | Year: 2016

Web Service Business Process Execution Language (BPEL) has become the de facto standard for developing instant service-oriented workflow applications in open environment. The correctness and reliability of BPEL processes have gained increasing concerns. However, the unique features (e.g., dead path elimination (DPE) semantics, parallelism, etc.) of BPEL language have raised enormous problems to it, especially in path feasibility analysis of BPEL processes. Path feasibility analysis of BPEL processes is the basis of BPEL testing, for it relates to the test case generation. Since BPEL processes support both parallelism and DPE semantics, existing techniques can't be directly applied to its path feasibility analysis. To address this problem, we present a novel technique to analyze the path feasibility for BPEL processes. First, to tackle unique features mentioned above, we transform a BPEL process into an intermediary model - BPEL control flow graph, which is proposed to abstract the execution flow of BPEL processes. Second, based on this abstraction, we symbolically encode every path of BPEL processes as some Satisfiability formulas. Finally, we solve these formulas with the help of Satisfiability Modulo Theory (SMT) solvers and the feasible paths of BPEL processes are obtained. We illustrate the applicability and feasibility of our technique through a case study. Copyright © 2016 The Institute of Electronics, Information and Communication Engineers.


Zhang X.,PLA University of Science and Technology | Li J.,Technical Management Office of Naval Defense Engineering | Xing J.,PLA University of Science and Technology | Wang P.,PLA University of Science and Technology | And 3 more authors.
Mathematical Problems in Engineering | Year: 2014

Optimal sensor placement is a key issue in the structural health monitoring of large-scale structures. However, some aspects in existing approaches require improvement, such as the empirical and unreliable selection of mode and sensor numbers and time-consuming computation. A novel improved particle swarm optimization (IPSO) algorithm is proposed to address these problems. The approach firstly employs the cumulative effective modal mass participation ratio to select mode number. Three strategies are then adopted to improve the PSO algorithm. Finally, the IPSO algorithm is utilized to determine the optimal sensors number and configurations. A case study of a latticed shell model is implemented to verify the feasibility of the proposed algorithm and four different PSO algorithms. The effective independence method is also taken as a contrast experiment. The comparison results show that the optimal placement schemes obtained by the PSO algorithms are valid, and the proposed IPSO algorithm has better enhancement in convergence speed and precision. © 2014 Xun Zhang et al.


He C.,PLA University of Science and Technology | Xing J.,PLA University of Science and Technology | Li J.,Technical Management Office of Naval Defense Engineering | Qian W.,Technical Management Office of Naval Defense Engineering | Zhang X.,PLA University of Science and Technology
Open Civil Engineering Journal | Year: 2015

Excitation makes a great influence on the wavelet energy distribution of the response signal, this deficiency leads that the traditional structural damage identification method based on wavelet energy has a low precision. In order to solve this problem, a new structural damage identification method based on wavelet packet energy entropy (WPEE) of impulse response is presented in this paper. Firstly, natural excitation technique (NExT) is adopted to extract structural impulse response. Then, WPEE of the impulse response is computed, and the change rate of WPEE is used to construct the structural damage index. An experiment of damage identification on a pile structure is provided to verify the effectiveness of the proposed method. Experiment results show that this method can accurately identify the single damage and multi-damage. © He et al.


Wang S.,PLA University of Science and Technology | Xing J.,PLA University of Science and Technology | Li J.,Technical Management Office of Naval Defense Engineering | Yang Q.,PLA University of Science and Technology | Yang Q.,Nanjing University
Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015 | Year: 2015

A decentralized flat control system is introduced into the intelligent building, where each zone of the intelligent building autonomously makes decisions through information exchange with their adjacent regions in a large scale control network. We formulate the decentralized control as a constrained optimization and decompose it into decentralized subproblems, then convert the centralized optimization into multi-objective problem. A decentralized algorithm for minimizing the sum of all the functions is proposed. The convergence property of decentralized algorithm is theoretically analyzed which considers both convex and non-convex systems with constraints, and then validates through simulation results. © 2015 IEEE.


He C.,PLA University of Science and Technology | Xing J.,PLA University of Science and Technology | Li J.,Technical Management Office of Naval Defense Engineering | Yang Q.,PLA University of Science and Technology | Wang R.,PLA University of Science and Technology
Mathematical Problems in Engineering | Year: 2015

Thresholding function is an important part of the wavelet threshold denoising method, which can influence the signal denoising effect significantly. However, some defects are present in the existing methods, such as function discontinuity, fixed bias, and parameters determined by trial and error. In order to solve these problems, a new wavelet thresholding function based on hyperbolic tangent function is proposed in this paper. Firstly, the basic properties of hyperbolic tangent function are analyzed. Then, a new thresholding function with a shape parameter is presented based on hyperbolic tangent function. The continuity, monotonicity, and high-order differentiability of the new function are theoretically proven. Finally, in order to determine the final form of the new function, a shape parameter optimization strategy based on artificial fish swarm algorithm is given in this paper. Mean square error is adopted to construct the objective function, and the optimal shape parameter is achieved by iterative search. At the end of the paper, a simulation experiment is provided to verify the effectiveness of the new function. In the experiment, two benchmark signals are used as test signals. Simulation results show that the proposed function can achieve better denoising effect than the classical hard and soft thresholding functions under different signal types and noise intensities. © 2015 Can He et al.


He C.,PLA University of Science and Technology | Xing J.,PLA University of Science and Technology | Li J.,Technical Management Office of Naval Defense Engineering | Yang Q.,PLA University of Science and Technology | Wang R.,PLA University of Science and Technology
Mathematical Problems in Engineering | Year: 2015

Due to simple calculation and good denoising effect, wavelet threshold denoising method has been widely used in signal denoising. In this method, the threshold is an important parameter that affects the denoising effect. In order to improve the denoising effect of the existing methods, a new threshold considering interscale correlation is presented. Firstly, a new correlation index is proposed based on the propagation characteristics of the wavelet coefficients. Then, a threshold determination strategy is obtained using the new index. At the end of the paper, a simulation experiment is given to verify the effectiveness of the proposed method. In the experiment, four benchmark signals are used as test signals. Simulation results show that the proposed method can achieve a good denoising effect under various signal types, noise intensities, and thresholding functions. © 2015 Can He et al.

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