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Operational Modal Analysis of a Ship Model in the Presence of Harmonic Excitation 被引量:1
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作者 Junchen Xu Ming Hong Xiaobing Liu 《Journal of Marine Science and Application》 2013年第1期38-44,共7页
A ship is operated under an extremely complex environment, and waves and winds are assumed to be the stochastic excitations. Moreover, the propeller, host and mechanical equipment can also induce the harmonic response... A ship is operated under an extremely complex environment, and waves and winds are assumed to be the stochastic excitations. Moreover, the propeller, host and mechanical equipment can also induce the harmonic responses. In order to reduce structural vibration, it is important to obtain the modal parameters information of a ship. However, the traditional modal parameter identification methods are not suitable since the excitation information is difficult to obtain. Natural excitation technique-eigensystem realization algorithm (NExT-ERA) is an operational modal identification method which abstracts modal parameters only from the response signals, and it is based on the assumption that the input to the structure is pure white noise. Hence, it is necessary to study the influence of harmonic excitations while applying the NExT-ERA method to a ship structure. The results of this research paper indicate the practical experiences under ambient excitation, ship model experiments were successfully done in the modal parameters identification only when the harmonic frequencies were not too close to the modal frequencies. 展开更多
关键词 natural excitation technique (NExT) eigensystem realization algorithm (ERA) ship structure harmonic excitation signal processing modal parameters identification ship model operational model analysis
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Use of Hi-resolution data for evaluating accuracy of traffic volume counts collected by microwave sensors
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作者 David K.Chang Mitsuru Saito +1 位作者 Grant G.Schultz Dennis L.Eggett 《Journal of Traffic and Transportation Engineering(English Edition)》 2017年第5期423-435,共13页
Over the past few years, the Utah Department of Transportation has developed the signal performance metrics (SPMs) system to evaluate the performance of signalized in- tersections dynamically. This system currently ... Over the past few years, the Utah Department of Transportation has developed the signal performance metrics (SPMs) system to evaluate the performance of signalized in- tersections dynamically. This system currently provides data summaries for several per- formance measures, one of them being turning movement counts collected by microwave sensors. As this system became public, there was a need to evaluate the accuracy of the data placed on the SPMs. A large-scale data collection was carried out to meet this need. Vehicles in the Hi-resolution data from microwave sensors were matched with the vehicles by ground-truth volume count data. Matching vehicles from the microwave sensor data and the ground-truth data manually collected required significant effort, A spreadsheet- based data analysis procedure was developed to carry out the task. A mixed model analysis of variance was used to analyze the effects of the factors considered on turning volume count accuracy. The analysis found that approach volume level and number of approach lanes would have significant effect on the accuracy of turning volume counts but the location of the sensors did not significantly affect the accuracy of turning volume counts. In addition, it was found that the location of lanes in relation to the sensor did not significantly affect the accuracy of lane-by-lane volume counts. This indicated that accu- racy analysis could be performed by using total approach volumes without comparing specific turning counts, that is, left-turn, through and right-turn movements. In general, the accuracy of approach volume counts collected by microwave sensors were within the margin of error that traffic engineers could accept. The procedure taken to perform the analysis and a summary of accuracy of volume counts for the factor combinations considered are presented in this paper. 展开更多
关键词 Traffic volume Microwave signal Performance Accuracy Mixed model analysis of variance
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