ISSN 
2013 Vol. 42, No. 4
2013, 42(4): 481-540.
doi: 10.3969/j.issn.1001-0548.2013.04.001
Abstract:
Quantitative analysis on human behavior, especially mining and modeling temporal and spatial regularities, is a common focus of statistical physics and complexity sciences. The in-depth understanding of human behavior helps in explaining many complex socio-economic phenomena, and in finding applications in public opinion monitoring, disease control, transportation system design, calling center services, information recommendation, and so on. This review article summarizes the state-of-the-art progresses of human dynamics, including the empirical analysis and modeling on human temporal activities, the empirical analysis and modeling on human mobility patterns, and the applications of human dynamics. Furthermore, this article reviews the advanced and insufficient points of related works, and points out some unsolved challenges in both theoretical and practical aspects.
Quantitative analysis on human behavior, especially mining and modeling temporal and spatial regularities, is a common focus of statistical physics and complexity sciences. The in-depth understanding of human behavior helps in explaining many complex socio-economic phenomena, and in finding applications in public opinion monitoring, disease control, transportation system design, calling center services, information recommendation, and so on. This review article summarizes the state-of-the-art progresses of human dynamics, including the empirical analysis and modeling on human temporal activities, the empirical analysis and modeling on human mobility patterns, and the applications of human dynamics. Furthermore, this article reviews the advanced and insufficient points of related works, and points out some unsolved challenges in both theoretical and practical aspects.
2013, 42(4): 541-545.
doi: 10.3969/j.issn.1001-0548.2013.04.002
Abstract:
In order to get the self-synchronizing scrambling information of the unknown lines in digital communication, a method of order estimation of self-synchronizing scrambling polynomial is presented. Through deeply studying the run property of self-synchronizing scrambled sequences, the corresponding relationship between the result of run statistic and the order of the self-synchronizing scrambling polynomial is gained. With this relationship, after calculating the run statistic with different length using the received scrambled sequence, the self-synchronizing scrambling polynomial order of the unknown line will be estimated through the distribution of the run extremums. The results of experiment verify the correctness of the theory analysis and the validity of the whole method.
In order to get the self-synchronizing scrambling information of the unknown lines in digital communication, a method of order estimation of self-synchronizing scrambling polynomial is presented. Through deeply studying the run property of self-synchronizing scrambled sequences, the corresponding relationship between the result of run statistic and the order of the self-synchronizing scrambling polynomial is gained. With this relationship, after calculating the run statistic with different length using the received scrambled sequence, the self-synchronizing scrambling polynomial order of the unknown line will be estimated through the distribution of the run extremums. The results of experiment verify the correctness of the theory analysis and the validity of the whole method.
2013, 42(4): 546-548,591.
doi: 10.3969/j.issn.1001-0548.2013.04.003
Abstract:
A weighted signal tensor subspace fitting algorithm is presented for vector hydrophone array based on higher order singular value decomposition (HOSVD). In this paper, the 3rd order tensor of the received signals from vector hydrophones array is modeled at first, then the signal tensor subspace is derived from HOSVD, and lastly, the DOA is estimated with the weighted signal subspace fitting. The 3rd tensor-based signal subspace estimation via HOSVD is a better estimate of the desired signal subspace than the subspace estimate obtained by the SVD of a matrix which exploits the structure inherent in the multi dimensional measurement data. Theoretical and simulation results show that the proposed method exhibits high resolution and robustness performance under scenarios of low signal noise ratio (SNR), non-correlative and tight-correlative signals with the same power.
A weighted signal tensor subspace fitting algorithm is presented for vector hydrophone array based on higher order singular value decomposition (HOSVD). In this paper, the 3rd order tensor of the received signals from vector hydrophones array is modeled at first, then the signal tensor subspace is derived from HOSVD, and lastly, the DOA is estimated with the weighted signal subspace fitting. The 3rd tensor-based signal subspace estimation via HOSVD is a better estimate of the desired signal subspace than the subspace estimate obtained by the SVD of a matrix which exploits the structure inherent in the multi dimensional measurement data. Theoretical and simulation results show that the proposed method exhibits high resolution and robustness performance under scenarios of low signal noise ratio (SNR), non-correlative and tight-correlative signals with the same power.
2013, 42(4): 549-554.
doi: 10.3969/j.issn.1001-0548.2013.04.004
Abstract:
Based on overlay-underlay spectrum sharing model, a routing algorithm for hybrid cognitive radio networks is proposed to improve the existing spectrum sharing model and to solve the deficiency in processing interference and delay of other algorithms. Taking shortest path and link state as routing metric and minimum cumulative interference as channel assignment target, the algorithm uses coloring graph as routing analysis model to develop an end-to-end path selection and channel assignment method with power control. Simulation results and comparison with existing routing algorithm show that the proposed algorithm can improve network throughput, reduce packet loss rate and end-to-end delay.
Based on overlay-underlay spectrum sharing model, a routing algorithm for hybrid cognitive radio networks is proposed to improve the existing spectrum sharing model and to solve the deficiency in processing interference and delay of other algorithms. Taking shortest path and link state as routing metric and minimum cumulative interference as channel assignment target, the algorithm uses coloring graph as routing analysis model to develop an end-to-end path selection and channel assignment method with power control. Simulation results and comparison with existing routing algorithm show that the proposed algorithm can improve network throughput, reduce packet loss rate and end-to-end delay.
2013, 42(4): 555-558.
doi: 10.3969/j.issn.1001-0548.2013.04.005
Abstract:
Interferometric synthetic aperture radar (InSAR) measures the height of the object based on the distance difference reflected by the absolute phase difference of the corresponding pixels on two pieces of synthetic aperture radar (SAR). But in fact the phase difference is restricted to (-π,π), which causes phase wrap. The branch-cut method is one of the most important approaches for the phase unwrapping. In this paper, an improved branch-cut algorithm is proposed based on the Goldstein algorithm. The positive and the negative residues in the interference image are combined in this algorithm and then re-combined and replaced by using the length of the branch-cut as criteria so that the overall length of the branch-cut can be reduced gradually and the "isolated island phenomenon" in the unwrapping process can be overcome effectively. The proposed method has been verified through both the simulated and experimental data.
Interferometric synthetic aperture radar (InSAR) measures the height of the object based on the distance difference reflected by the absolute phase difference of the corresponding pixels on two pieces of synthetic aperture radar (SAR). But in fact the phase difference is restricted to (-π,π), which causes phase wrap. The branch-cut method is one of the most important approaches for the phase unwrapping. In this paper, an improved branch-cut algorithm is proposed based on the Goldstein algorithm. The positive and the negative residues in the interference image are combined in this algorithm and then re-combined and replaced by using the length of the branch-cut as criteria so that the overall length of the branch-cut can be reduced gradually and the "isolated island phenomenon" in the unwrapping process can be overcome effectively. The proposed method has been verified through both the simulated and experimental data.
2013, 42(4): 559-564.
doi: 10.3969/j.issn.1001-0548.2013.04.006
Abstract:
Target acceleration of SAR moving target detection results in three-phase, and affects stationary target suppression and the precision of parameter estimation. Aiming at this problem, a parameter estimation method based on three-phase compensation is proposed. According to the analysis of signal model, phase compensation is achieved by dechirp and one-dimensional search in time-chirp distribution. After the phase compensation, in order to overcome potential problem of target loss caused by peak overlap in time-frequency distribution, an improved FrFT is employed for parameter estimation and the method is given in detail. Finally, the computer simulation confirms the correctness and validity of the method.
Target acceleration of SAR moving target detection results in three-phase, and affects stationary target suppression and the precision of parameter estimation. Aiming at this problem, a parameter estimation method based on three-phase compensation is proposed. According to the analysis of signal model, phase compensation is achieved by dechirp and one-dimensional search in time-chirp distribution. After the phase compensation, in order to overcome potential problem of target loss caused by peak overlap in time-frequency distribution, an improved FrFT is employed for parameter estimation and the method is given in detail. Finally, the computer simulation confirms the correctness and validity of the method.
2013, 42(4): 565-570.
doi: 10.3969/j.issn.1001-0548.2013.04.007
Abstract:
An overview study was made on prime software reliability models proposed by the researchers in the last decades for accurate reliability analysis and forecasting. Firstly, the major models are classified into the analytic models and the heuristic models based on their mathematical theories. Secondly, studies and analyses on the model assumptions and main ideas are presented in this paper. Finally, the current trends and existing problems in the software reliability models are addressed.
An overview study was made on prime software reliability models proposed by the researchers in the last decades for accurate reliability analysis and forecasting. Firstly, the major models are classified into the analytic models and the heuristic models based on their mathematical theories. Secondly, studies and analyses on the model assumptions and main ideas are presented in this paper. Finally, the current trends and existing problems in the software reliability models are addressed.
2013, 42(4): 571-576.
doi: 10.3969/j.issn.1001-0548.2013.04.008
Abstract:
This paper presents a new comprehensive worm detection algorithm based on credit. Firstly, the parameters of connection success probability are optimized and set through detection contrast experiments. Secondly, the response strategy of the credit-based connection rate limiting algorithm is redesigned, and consequently the event response process of the algorithm is improved. On the basis of the above study, the new credit-based comprehensive worm detection (CBCWD) algorithm is designed to monitor network traffics, execute response strategy for monitoring events, and give the detection results through attack condition judge and comprehensive analysis. Five different frequencies attacks detection experiments on the NUST 2011 open dataset were conducted. The experiment results demonstrate that proposed algorithm has a higher detection rate and lower false positive rate.
This paper presents a new comprehensive worm detection algorithm based on credit. Firstly, the parameters of connection success probability are optimized and set through detection contrast experiments. Secondly, the response strategy of the credit-based connection rate limiting algorithm is redesigned, and consequently the event response process of the algorithm is improved. On the basis of the above study, the new credit-based comprehensive worm detection (CBCWD) algorithm is designed to monitor network traffics, execute response strategy for monitoring events, and give the detection results through attack condition judge and comprehensive analysis. Five different frequencies attacks detection experiments on the NUST 2011 open dataset were conducted. The experiment results demonstrate that proposed algorithm has a higher detection rate and lower false positive rate.
2013, 42(4): 577-580.
doi: 10.3969/j.issn.1001-0548.2013.04.009
Abstract:
To provide high quality streaming service, content distribution network (CDN) exploits the domain name system (DNS) to redirect users to the close-by content servers which are widely worldwide distributed. In recent years, the development of domain name system, especially the rising of IP Anycast based domain name system (e.g., Google Public DNS and Open DNS), will definitely impact the content distribution mechanism of CDN. Compared with other Internet services, streaming service requires relatively more network resource. The influence from DNS will be more obvious. This paper firstly states how IP Anycast based DNS impact the redirection of CDN networks, analyzes the factors that impact the QoS of streaming service, and finally compares the QoS of CDN streaming service when using different DNS resolving service.
To provide high quality streaming service, content distribution network (CDN) exploits the domain name system (DNS) to redirect users to the close-by content servers which are widely worldwide distributed. In recent years, the development of domain name system, especially the rising of IP Anycast based domain name system (e.g., Google Public DNS and Open DNS), will definitely impact the content distribution mechanism of CDN. Compared with other Internet services, streaming service requires relatively more network resource. The influence from DNS will be more obvious. This paper firstly states how IP Anycast based DNS impact the redirection of CDN networks, analyzes the factors that impact the QoS of streaming service, and finally compares the QoS of CDN streaming service when using different DNS resolving service.
2013, 42(4): 581-585.
doi: 10.3969/j.issn.1001-0548.2013.04.010
Abstract:
As the evaluation of quality of experience (QoE) is an ordinal multiple categories problem, the logistic regression model could be used to evaluate QoE. The regression model of QoE categories probability distribution is established based on the logistic regression model. This model relates cumulative probabilities of particular QoE categories to quality of service (QoS) parameters of network. Considering the tolerance of QoS parameters, a QoE evaluation method through QoE categories probability distribution regression model is proposed. This method eliminates the compensations among QoS parameters. It yields the category of QoE while giving a probability of each possible category. Finally, the QoE of Web service is estimated utilizing the proposed method and the result proves the method to be comprehensive and exact.
As the evaluation of quality of experience (QoE) is an ordinal multiple categories problem, the logistic regression model could be used to evaluate QoE. The regression model of QoE categories probability distribution is established based on the logistic regression model. This model relates cumulative probabilities of particular QoE categories to quality of service (QoS) parameters of network. Considering the tolerance of QoS parameters, a QoE evaluation method through QoE categories probability distribution regression model is proposed. This method eliminates the compensations among QoS parameters. It yields the category of QoE while giving a probability of each possible category. Finally, the QoE of Web service is estimated utilizing the proposed method and the result proves the method to be comprehensive and exact.
2013, 42(4): 586-591.
doi: 10.3969/j.issn.1001-0548.2013.04.011
Abstract:
The correct location information of vehicles plays an important role in the maintenance of the normal operation of vehicle Ad-hoc networks (VANETs) and the position spoofing from malicious node will seriously affect many applications of VANETs. Therefore, the detection of the position spoofing by location verification is an important issue. The traditional location algorithm in WSN and MANET no longer applies to VANETs. In this paper, a vehicle trajectory-based location verification scheme is proposed to locate and track continuously the vehicle and draw the trajectory. The inosculation is calculated and the position spoofing is detected by comparing with the trajectory and speed of the neighbor vehicle. The simulation results show that false negative rate and false positive rate are low. When the cheating distance of malicious node is 30 m, false negative and false positive rate are close to 0.
The correct location information of vehicles plays an important role in the maintenance of the normal operation of vehicle Ad-hoc networks (VANETs) and the position spoofing from malicious node will seriously affect many applications of VANETs. Therefore, the detection of the position spoofing by location verification is an important issue. The traditional location algorithm in WSN and MANET no longer applies to VANETs. In this paper, a vehicle trajectory-based location verification scheme is proposed to locate and track continuously the vehicle and draw the trajectory. The inosculation is calculated and the position spoofing is detected by comparing with the trajectory and speed of the neighbor vehicle. The simulation results show that false negative rate and false positive rate are low. When the cheating distance of malicious node is 30 m, false negative and false positive rate are close to 0.
2013, 42(4): 592-596.
doi: 10.3969/j.issn.1001-0548.2013.04.012
Abstract:
Aiming at the high computational cost issue for large data sets in kernel space, the non-linear support vector machine (NSVM) is proposed to reduce training data of classifier. First, a subset of training classifier is extracted from full training data by using NSVM, kernel principal component analysis (KPCA), and greedy kernel principal component analysis (GKPCA), respectively. Then, the classifier is trained by those subsets, respectively. Finally, the classification results are evaluated by the error rate of the training and test data. The classification performance of the classifier trained by the subsets from the KPCA method is inferior to those of from the NSVM and the GKPCA methods, but the generalization of the classifier trained by the subset from the GKPCA method is inferior to those of from the NSVM method for two data sets through two the classifiers. Simulation results indicate that the classifier trained by the subset from the NSVM method not only ensures the generalization ability of classifier, but also reduces the computational complexity of the classification algorithm.
Aiming at the high computational cost issue for large data sets in kernel space, the non-linear support vector machine (NSVM) is proposed to reduce training data of classifier. First, a subset of training classifier is extracted from full training data by using NSVM, kernel principal component analysis (KPCA), and greedy kernel principal component analysis (GKPCA), respectively. Then, the classifier is trained by those subsets, respectively. Finally, the classification results are evaluated by the error rate of the training and test data. The classification performance of the classifier trained by the subsets from the KPCA method is inferior to those of from the NSVM and the GKPCA methods, but the generalization of the classifier trained by the subset from the GKPCA method is inferior to those of from the NSVM method for two data sets through two the classifiers. Simulation results indicate that the classifier trained by the subset from the NSVM method not only ensures the generalization ability of classifier, but also reduces the computational complexity of the classification algorithm.
2013, 42(4): 597-602.
doi: 10.3969/j.issn.1001-0548.2013.04.013
Abstract:
To solve the shortcomings of the AISG protocol, an antenna line device (ALD) scanning algorithm based on binary scanning tree is proposed. In leaf scanning phase for existing ALDs, leaf nodes are scanned directly with scanning codes corresponding to the identified nodes from the previous scanning, while in root scanning phase for new arriving ALDs, we start scanning from the root node. By utilization of an adaptive collision avoidance mechanism and the leaf-root scanning method, the collision frequency during ALD scanning is effectively reduced. The results of simulation show that the proposed algorithm can effectively shorten the ALD scanning time and increase the efficiency of ALD search.
To solve the shortcomings of the AISG protocol, an antenna line device (ALD) scanning algorithm based on binary scanning tree is proposed. In leaf scanning phase for existing ALDs, leaf nodes are scanned directly with scanning codes corresponding to the identified nodes from the previous scanning, while in root scanning phase for new arriving ALDs, we start scanning from the root node. By utilization of an adaptive collision avoidance mechanism and the leaf-root scanning method, the collision frequency during ALD scanning is effectively reduced. The results of simulation show that the proposed algorithm can effectively shorten the ALD scanning time and increase the efficiency of ALD search.
2013, 42(4): 603-608.
doi: 10.3969/j.issn.1001-0548.2013.04.014
Abstract:
In this paper, an invariant moment based robust image copy detection algorithm in discrete cosine transformation (DCT) domain is proposed. Low and middle frequency coefficients which are calculated from full DCT transformation on luminance component of image are used as the image eigenvector in DCT domain. The query image and its angle normalized image eigenvector in DCT domain are computed, then correlation values of two eigenvectors of the query image and those of test image are respectively computed and the larger one is used to judge whether the query image is a copy or not. Full DCT coefficients are verified to have high robustness against common signal attacks and regularly vary with scaling attacks, thus the DCT eigenvector constructed by middle and low frequency full DCT coefficients can resist signal attacks and scaling distortion. The characteristic angle estimated by the image scale invariant moment is used to normalize the image to counteract the rotation distortion, so the angle normalized image can resist rotation distortion. The experimental results show that the algorithm is superior to Ling's methods in terms of rotation distortion.
In this paper, an invariant moment based robust image copy detection algorithm in discrete cosine transformation (DCT) domain is proposed. Low and middle frequency coefficients which are calculated from full DCT transformation on luminance component of image are used as the image eigenvector in DCT domain. The query image and its angle normalized image eigenvector in DCT domain are computed, then correlation values of two eigenvectors of the query image and those of test image are respectively computed and the larger one is used to judge whether the query image is a copy or not. Full DCT coefficients are verified to have high robustness against common signal attacks and regularly vary with scaling attacks, thus the DCT eigenvector constructed by middle and low frequency full DCT coefficients can resist signal attacks and scaling distortion. The characteristic angle estimated by the image scale invariant moment is used to normalize the image to counteract the rotation distortion, so the angle normalized image can resist rotation distortion. The experimental results show that the algorithm is superior to Ling's methods in terms of rotation distortion.
Evaluating Convenience of Medical Resource Based on GIS and Improved Data Envelopment Analysis Model
2013, 42(4): 609-614.
doi: 10.3969/j.issn.1001-0548.2013.04.015
Abstract:
For allocating the limited medical resource rationally, evaluating the convenience of the medical resource scientifically is important. Firstly, the characters of evaluating objects, service contents, and spatial and temporal dimensions of community medical facility are analyzed. Then the convenience evaluating index system is then built up from the convenience of service which the medical facilities provide and the community acquires respectively. According to the data envelopment analysis (DEA) model, the evaluation index is improved with no-input and the methods of evaluating the convenience of community and medical facility are presented. On the basis of this, taking into account of the road traffic, the distribution of population, and medical facilities, the convenience value of medical resource in town is calculated using the network analysis and overlay functions of GIS. The above method applied in the convenience evaluation of medical resource in Beijing suburbs is validated well
For allocating the limited medical resource rationally, evaluating the convenience of the medical resource scientifically is important. Firstly, the characters of evaluating objects, service contents, and spatial and temporal dimensions of community medical facility are analyzed. Then the convenience evaluating index system is then built up from the convenience of service which the medical facilities provide and the community acquires respectively. According to the data envelopment analysis (DEA) model, the evaluation index is improved with no-input and the methods of evaluating the convenience of community and medical facility are presented. On the basis of this, taking into account of the road traffic, the distribution of population, and medical facilities, the convenience value of medical resource in town is calculated using the network analysis and overlay functions of GIS. The above method applied in the convenience evaluation of medical resource in Beijing suburbs is validated well
2013, 42(4): 615-620.
doi: 10.3969/j.issn.1001-0548.2013.04.016
Abstract:
The approach aircraft landing scheduling problem in the terminal area is discussed in this paper. Taking the flights' minimum total delay as the objective function, this paper proposes an implicit enumeration sorting algorithm with packet-based max position shift (MPS) = 1. It takes into account a variety of air traffic control constraints. Firstly the flights in same route bound to group lock, and then the position-matrix is initialized according to constraints, finally the solution space tree is built to search the optimal solution. The computing speed of the algorithm is improved effectively by selecting the boundary conditions, judging the invalid branch, and eliminating second-best series out. The results indicate that the algorithm can apply to complicated air traffic control (ATC) environment, and can greatly reduce the delay and increase airspaces' availability.
The approach aircraft landing scheduling problem in the terminal area is discussed in this paper. Taking the flights' minimum total delay as the objective function, this paper proposes an implicit enumeration sorting algorithm with packet-based max position shift (MPS) = 1. It takes into account a variety of air traffic control constraints. Firstly the flights in same route bound to group lock, and then the position-matrix is initialized according to constraints, finally the solution space tree is built to search the optimal solution. The computing speed of the algorithm is improved effectively by selecting the boundary conditions, judging the invalid branch, and eliminating second-best series out. The results indicate that the algorithm can apply to complicated air traffic control (ATC) environment, and can greatly reduce the delay and increase airspaces' availability.
2013, 42(4): 621-624.
doi: 10.3969/j.issn.1001-0548.2013.04.017
Abstract:
The traditional K-means algorithm is widely used because of its simplicity and efficiency. However, it is sensitive to the initial point and easy to fall into local optimum. In this paper, we use cosine measure to evaluate the similarity between objects and construct a new fitness function of genetic algorithm and the new convergence criterion for K-means algorithm. Experimental results show that the new method enhances the clustering accuracy and stability for the combination of K-means and genetic algorithm.
The traditional K-means algorithm is widely used because of its simplicity and efficiency. However, it is sensitive to the initial point and easy to fall into local optimum. In this paper, we use cosine measure to evaluate the similarity between objects and construct a new fitness function of genetic algorithm and the new convergence criterion for K-means algorithm. Experimental results show that the new method enhances the clustering accuracy and stability for the combination of K-means and genetic algorithm.
2013, 42(4): 625-629.
doi: 10.3969/j.issn.1001-0548.2013.04.018
Abstract:
A class of cellular neural networks with multi-proportional delays is studied in this paper. The transformation zi(t)=yi(et) transforms cellular neural networks with multi-proportional delays into cellular neural networks with variable coefficient and constant delays, and then constructing Lyapunov functionals, some delay-independent sufficient conditions are given. These new sufficient conditions can ensure global uniform asymptotic stability of this system. An example is given to illustrate the correctness of obtained results.
A class of cellular neural networks with multi-proportional delays is studied in this paper. The transformation zi(t)=yi(et) transforms cellular neural networks with multi-proportional delays into cellular neural networks with variable coefficient and constant delays, and then constructing Lyapunov functionals, some delay-independent sufficient conditions are given. These new sufficient conditions can ensure global uniform asymptotic stability of this system. An example is given to illustrate the correctness of obtained results.
2013, 42(4): 630-634.
doi: 10.3969/j.issn.1001-0548.2013.04.019
Abstract:
The accuracy and reliability of magnetostrictive displacement sensors (MDS) are both directly determined by the properties of the magnetostrictive line (ML). The magnetic and electrical properties of the ML, which lack of study in literatures, are researched by taking Fe57Ni43 for example. Besides the material characteristics of Fe57Ni43, the ML magnetic field characteristics are studied by a 3-D finite element model established by ANSYS, and the echo electrical signal is analyzed by establishing electronic information system based on DSP. The results achieved in this paper will provide a theoretical basis for the ML to be applied to MDS from the point of magnetic and electrical properties.
The accuracy and reliability of magnetostrictive displacement sensors (MDS) are both directly determined by the properties of the magnetostrictive line (ML). The magnetic and electrical properties of the ML, which lack of study in literatures, are researched by taking Fe57Ni43 for example. Besides the material characteristics of Fe57Ni43, the ML magnetic field characteristics are studied by a 3-D finite element model established by ANSYS, and the echo electrical signal is analyzed by establishing electronic information system based on DSP. The results achieved in this paper will provide a theoretical basis for the ML to be applied to MDS from the point of magnetic and electrical properties.
2013, 42(4): 635-640.
doi: 10.3969/j.issn.1001-0548.2013.04.020
Abstract:
An efficient prognostics technique based on physics-of-failure is proposed to predict life of printed circuit board (PCB) in the ship-borne electronic products. By the case study of a PCB in typical ship-borne electronic products, the life prediction process of ship-borne PCB is presented. The typical life cycle environmental profile of the PCB is formed by considering three weak parts and the working environment of the PCB. After loading the environmental profile, the PCB life with its variation is obtained by the finite element analysis on temperature distribution and structural dynamic. In addition, two influencing factors Lair and RH from electromagnetic relays on the PCB life are analyzed in the models.
An efficient prognostics technique based on physics-of-failure is proposed to predict life of printed circuit board (PCB) in the ship-borne electronic products. By the case study of a PCB in typical ship-borne electronic products, the life prediction process of ship-borne PCB is presented. The typical life cycle environmental profile of the PCB is formed by considering three weak parts and the working environment of the PCB. After loading the environmental profile, the PCB life with its variation is obtained by the finite element analysis on temperature distribution and structural dynamic. In addition, two influencing factors Lair and RH from electromagnetic relays on the PCB life are analyzed in the models.
