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Feng Y.-X.,Zhejiang University | Mai Z.-Y.,Guangzhou Academy of Special Equipment Inspection and Testing | Tan J.-R.,Zhejiang University
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | Year: 2011

The Influencing factors which controlled mechanism motion output were analyzed on the premise of constant motion input. They were represented as kinematic pair chromosome number, kinematic pair feature gene and distance relationship vector gene respectively by borrowing several concepts and principles in genetics, and they were encoded at the same time. Mechanism chromosome model was established which was composed of mechanism chromosome relationship graph and mechanism chromosome matrix. Three kinematic pair chromosome gene recombination operations (dominance, translocation and metastasis) on mechanism chromosome model were proposed by using meiosis and chromosome variance in genetics for reference. Variant mechanism was acquired based on shaper original mechanism by using this method, and its practicality was demonstrated as well. Source


Xu H.-B.,South China University of Technology | Chen G.-H.,South China University of Technology | Wang X.-H.,Guangzhou Academy of Special Equipment Inspection and Testing
Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science) | Year: 2012

According to the nonlinear and non-Guassian characteristics of vibration signals of rolling bearings, a novel fault identification method based on the bispectrum distribution feature of auto-regressive moving average (ARMA) model and on the cluster analysis of fuzzy c-means (FCM) method is proposed. In this method, first, original vibration signals are modulated via the empirical mode decomposition (EMD), and an ARMA model of principal signal components is established. Then, a bispectrum estimation of the ARMA model is implemented. Finally, the binary images extracted from the bispectrum distribution are taken as the feature vectors and are used to construct a classifier of the class templates and the smallest-distance templates via the FCM clustering, thus implementing the fault identification successfully. Application results in the fault diagnosis of rolling bearings demonstrate that the proposed method is effective because it can accurately determine the actual conditions of rolling bearings. Source


Xu H.,South China University of Technology | Chen G.,South China University of Technology | Wang X.,Guangzhou Academy of Special Equipment Inspection and Testing
Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis | Year: 2012

In order to improve the recognition effect of structure damage, an effective damage evaluation method, based on stiffness variation index (SVI) and least squares support vector machine optimized by improved particle swarm optimization algorithm, is proposed. The method adopts a finite element model modified by modal testing to calculate SVI. Firstly, the SVI data are investigated to detect damage locations. Secondly, these SVI data serve as the feature vectors to be input to least squares support vector machine for calculating the hyperparameters and optimization model of the structure damage evaluation is established so as to predict the size of damage. Finally, a case study on a crane girder damage evaluation demonstrates that the method can accurately determine the actual conditions of the girder structure, and it enhances identification accuracy and convergence rate. It is an effective health evaluation method. Source


Song Y.,Zhejiang University | Xu B.,Zhejiang University | Yang H.,Zhejiang University | Liu Y.,Guangzhou Academy of Special Equipment Inspection and Testing
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | Year: 2014

It is a fact for the secondary source method that the pump source impedance can't be computed with the current estimation algorithm when the transducer length of the reference pipe is multiple times of the pressure wavelength, and the signal processing is complicated and time consuming, so the secondary source method is inapplicable in industry. For solving the problem, a new estimation algorithm of the pump source is discussed, and a signal processing software based on Matlab/GUI for secondary source method is designed. The test principle of the secondary source method is depicted, and then several evaluation methods of source impedance (such as the linear interpolation method, the weighted linear regression technique and the distributed-parameters method) and its application are discussed. With the Matlab/GUI, a signal processing software for the secondary source method is developed and then validated with test results. It can be concluded from the test results that compared with the distributed-parameter method, the computing time of the source impedance with the weighted linear regression Technique is reduced 70%. At the same test accuracy, the signal processing of the secondary source method is simplified and the computing time is reduced 80% by the software. Therefore, with the signal processing software, the application of the secondary source method in industry is possible. © 2014 Journal of Mechanical Engineering. Source


Chen G.,South China University of Technology | Lin Y.,South China University of Technology | Wang X.,Guangzhou Academy of Special Equipment Inspection and Testing | Liang J.,Guangzhou Academy of Special Equipment Inspection and Testing
Natural Gas Industry | Year: 2015

In order to evaluate objectively and systematically the explosion risk of explosion-proof electric apparatus in typical industrial sites, a complete index system was established for evaluating the risk possibility, and an explosion risk evaluation method was also put forward on the basis of combination weighting. The evaluation was divided into three steps. Firstly, with the opinions of industrial experts as reference, an evaluation index system of explosion risk possibility was established after an analysis was conducted on the critical technical parameters of explosion-proof electric apparatus. The weights for each index were obtained by means of combination weighting which combines AHP with CV, and state score for evaluation index was obtained through Delphi method and site investigation. Then, a calculation model was built for explosion risk possibility of the system composed of explosion-proof electric apparatus and their surroundings by using fuzzy mathematics and probability theory. Secondly, based on the features of different process equipment, explosion risk consequence was determined with the aid of process equipment classification, ETA and fire explosion hazard consequence model. Considering the explosion risk possibility and consequence, the risk of the whole system was characterized by using risk matrix. Finally, the above mentioned evaluation method was used to analyze the explosion risk of explosion-proof electric apparatus in typical industrial sites, and the corresponding risk decision program was put forward so as to provide the reference and guide for the site management and inspection of explosion-proof electric apparatus. ©, 2015, Natural Gas Industry Journal Agency. All right reserved. Source

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