• Smart Structures and Systems
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• v.14 no.2
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• pp.145-158
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• 2014

The objective of this study is to improve the survivability and reliability of the FBG sensor network in the structural health monitoring (SHM) system. Therefore, a model reconstruction soft computing recognition algorithm based on support vector regression (SVR) is proposed to achieve the high reliability of the FBG sensor network, and the grid search algorithm is used to optimize the parameters of SVR model. Furthermore, in order to demonstrate the effectiveness of the proposed model reconstruction algorithm, a SHM system based on an eight-point fiber Bragg grating (FBG) sensor network is designed to monitor the foreign-object low velocity impact of a CFRP composite plate. Simultaneously, some sensors data are neglected to simulate different kinds of FBG sensor network failure modes, the predicting results are compared with non-reconstruction for the same failure mode. The comparative results indicate that the performance of the model reconstruction recognition algorithm based on SVR has more excellence than that of non-reconstruction, and the model reconstruction algorithm almost keeps the consistent predicting accuracy when no sensor, one sensor and two sensors are invalid in the FBG sensor network, thus the reliability is improved when there are FBG sensors are invalid in the structural health monitoring system.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.4
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• pp.359-367
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• 2023

In order to ensure the high-integrity of reference stations of satellite navigation system, cycle slip should be precisely monitored and compensated. In this paper, we proposed a cycle slip algorithm for the integrity monitoring of the reference stations. Unlike the legacy method using the Melbourne-Wübbena (MW) combination and ionosphere combination, the proposed algorithm is based on ionosphere combination only, which uses high precision carrier phase observations without pseudorange observations. Two independent and complementary ionosphere combinations, Ionospheric Negative (IN) and Ionospheric Positive (IP), were adopted to avoid insensitive cycle slip pairs. In addition, a second-order time difference was applied to the IN and IP combinations to minimize the influence of ionospheric and tropospheric delay even under severe atmosphere conditions. Then, the cycle slip was detected by the thresholds determined based on error propagation rules, and the cycle slip was identified through weighted least square method. The performance of the proposed cycle slip algorithm was validated with the 1 Hz dual-frequency carrier phase data collected under the difference levels of ionospheric activities. For this experiment, 15 insensitive cycle slip pairs were intentionally inserted into the raw carrier phase observations, which is difficult to be detected with the traditional cycle slip approach. The results indicate that the proposed approach can successfully detect and compensate all of the inserted cycle slip pairs regardless of ionospheric activity. As a consequence, the proposed cycle slip algorithm is confirmed to be suitable for the reference station where real time high-integrity monitoring is crucial.

• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.305-317
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• 2015

Optimal sensor placement (OSP) is an integral component in the design of an effective structural health monitoring (SHM) system. This paper describes the implementation of a novel collaborative-climb monkey algorithm (CMA), which combines the artificial fish swarm algorithm (AFSA) with the monkey algorithm (MA), as a strategy for the optimal placement of a predefined number of sensors. Different from the original MA, the dual-structure coding method is adopted for the representation of design variables. The collaborative-climb process that can make the full use of the monkeys' experiences to guide the movement is proposed and incorporated in the CMA to speed up the search efficiency of the algorithm. The effectiveness of the proposed algorithm is demonstrated by a numerical example with a high-rise structure. The results show that the proposed CMA algorithm can provide a robust design for sensor networks, which exhibits superior convergence characteristics when compared to the original MA using the dual-structure coding method.

• Journal of Korean Society for Quality Management
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• v.45 no.1
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• pp.25-38
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• 2017

Purpose: Hot strip rolling mill consists of a lot of mechanical and electrical units. In condition monitoring and diagnosis phase, various units could be failed with unknown reasons. In this study, we propose an effective method to detect early the units with abnormal status to minimize system downtime. Methods: The early warning problem with various units is defined. K-means and PAM algorithm with Euclidean and Manhattan distances were performed to detect the abnormal status. In addition, an performance of the proposed algorithm is investigated by field data analysis. Results: PAM with Manhattan distance(PAM_ManD) showed better results than K-means algorithm with Euclidean distance(K-means_ED). In addition, we could know from multivariate field data analysis that the system reliability of hot strip rolling mill can be increased by detecting early abnormal status. Conclusion: In this paper, clustering-based monitoring and fault detection algorithm using Manhattan distance is proposed. Experiments are performed to study the benefit of the PAM with Manhattan distance against the K-means with Euclidean distance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.1030-1038
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• 2008

Traffic monitoring method is mainly loop detector and piezo sensor. But this method is only detecting the number of vehicle. Monitoring traffic volume is not checking the number of vehicle but checking the length of access road, width of road, number of passing people, passing vehicle, delayed vehicle. The traffic signal control cycle is not fixed by only passing vehicle number but all related traffic proposal. This paper proposed selecting common characteristic out of each unrelated traffic proposal through Analytic Hierachy Process and this characteristic is applied to compose fuzzy sensor algorithm which find out new traffic volume concept of confusion degree. The accumulated delayed vehicle time is shorter in new fuzzy sensor algorithm applied by AHP than other traffic method

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.276-285
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• 2008

Traffic monitoring method is mainly loop detector and piezo sensor. But this method is only detecting the number of vehicle. Monitoring traffic volume is not checking the number of vehicle but checking the length of access road, width of road, number of passing people,passing vehicle,delayed vehicle. The traffic signal control cycle is not fixed by only passing vehicle number but all related traffic proposal. This paper proposed selecting common characteristic out of each unrelated traffic proposal through Analytic Hierachy Process and this characteristic is applied to compose fuzzy sensor algorithm which find out new traffic volume concept of confusion degree. The accumulated delayed vehicle time is shorter in new fuzzy sensor algorithm applied by AHP than other traffic method

• Smart Structures and Systems
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• v.8 no.1
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• pp.119-137
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• 2011

A bio-inspired two-mode structural health monitoring (SHM) system based on the Na$\ddot{i}$ve Bayes (NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to be superior in disease detection, two types of array expression data have been proposed for the development of the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process. Preliminary verification has demonstrated that the structure health condition can be precisely detected by the proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing the bio-inspired two-mode SHM practically has been successfully demonstrated.

• Computational Structural Engineering
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• v.10 no.3
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• pp.157-165
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• 1997

This research aims to develop an algorithm of optimal transducer placement for health monitoring of large structural system. The structural vibration response-based health monitoring is considered one of the best for the system which requires a long-term, continuous monitoring. In its experimental modal testing, however, it is difficult to decide on the measurement locations and their number, especially for complex structures, which have a major influence on the quality of the results. In order to minimize the number of sensing operations and optimize the transducer location while maximizing the accuracy of results, this paper discusses about an optimum transducer placement criterion suitable for the identification of structural damage for continuous health monitoring. As a criterion algorithm, it proposes the Kinetic Energy Optimization Technique (EOT), and then addresses the numerical issues which are subsequently applicable to actual experiment where a bridge model is used. By using the experimental data, it compares the EOT with the EIM(Effective Indefence Method) which is generally used to optimize the transducer placement for the damage identification and control purposes. The comparison conclusively shows that the EOT algorithm proposed in this paper is preferable when a structure is to be instrumented with fewer sensors for monitoring purpose.

• Smart Structures and Systems
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• v.15 no.1
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• pp.151-167
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• 2015

Instrumentation on structural health monitoring system imposes critical issues for applying the structural monitoring system to real world structures, for which not only on the configuration and geometry, but also aesthetics on the system to be monitored should be considered. To illustrate this point, two real world structural health monitoring systems, the structural health monitoring system of Shenzhen Vanke Center and the structural health monitoring system of Shenzhen Bay Stadium in China, are presented in the paper. The instrumentation on structural health monitoring systems of real world structures is addressed by providing the description of the structure, the purpose of the structural health monitoring system implementation, as well as details of the system integration including the installations on the sensors and acquisition equipment and so on. In addition, an intelligent algorithm on stress identification using measurements from multi-region is presented in the paper. The stress identification method is deployed using the fuzzy pattern recognition and Dempster-Shafer evidence theory, where the measurements of limited strain sensors arranged on structure are the input data of the method. As results, at the critical parts of the structure, the stress distribution evaluated from the measurements has shown close correlation to the numerical simulation results on the steel roof of the Beijing National Aquatics Center in China. The research work in this paper can provide a reference for the design and implementation of both real world structural health monitoring systems and intelligent algorithm to identify stress distribution effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1708-1734
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• 2022

In the development of logistics system, the breakthrough of important technologies such as technology platform for logistics information management and control is the key content of the study. Based on Javascript and JQuery, the logistics system realizes real-time monitoring, collection of historical status data, statistical analysis and display, intelligent recommendation and other functions. In order to strengthen the cooperation of warehouse storage, enhance the utilization rate of resources, and achieve the purpose of real-time and visual supervision of transportation equipment and cargo tracking, this paper studies the VNF dynamic deployment and SFC routing problem in the network load change scenario based on the logistics system. The BIP model is used to model the VNF dynamic deployment and routing problem. The optimization objective is to minimize the total cost overhead generated by each SFCR. Furthermore, the application of the SFC mapping algorithm in the routing topology solving problem is proposed. Based on the concept of relative cost and the idea of topology transformation, the SFC-map algorithm can efficiently complete the dynamic deployment of VNF and the routing calculation of SFC by using multi-layer graph. In the simulation platform based on the logistics system, the proposed algorithm is compared with VNF-DRA algorithm and Provision Traffic algorithm in the network receiving rate, throughput, path end-to-end delay, deployment number, running time and utilization rate. According to the test results, it is verified that the test results of the optimization algorithm in this paper are obviously improved compared with the comparison method, and it has higher practical application and promotion value.