The hydraulic excitation acting on a hydro-turbine generator unit exhibits obvious non-stationary characteristics.In order to account for these characteristics,this study focuses on the non-stationary random vibration...The hydraulic excitation acting on a hydro-turbine generator unit exhibits obvious non-stationary characteristics.In order to account for these characteristics,this study focuses on the non-stationary random vibration reliability of the hydro-turbine generator unit.Firstly,the non-stationary characteristics of the hydraulic excitation are analyzed,and a mathematical ex-pression is constructed using the virtual excitation method.Secondly,a dynamic model of the unit is established to demonstrate the non-stationary random vibration characteristics under hydraulic excitation.Thirdly,an active learning non-stationary vibration reliability analysis method AK-MCS-T-H is proposed combining the Kriging model,the Monte Carlo simulation(MCS)method,and the information entropy learning function H.This method reveals the influence of the non-stationary hydraulic excitation on the random vibration reliability of the hydro-turbine generator unit.Finally,an example is presented to analyze the random vibration reliability.The study shows that the AK-MCS-T-H proposed in this paper can solve the problem of non-stationary random vibration reliability of the Francis hydro-turbine generator unit more effectively.展开更多
To analyze the dynamic response and reliability of a continuous beam bridge under the action of an extra heavy vehicle, a vehicle–bridge coupled vibration model was established based on the virtual work principle and...To analyze the dynamic response and reliability of a continuous beam bridge under the action of an extra heavy vehicle, a vehicle–bridge coupled vibration model was established based on the virtual work principle and vehicle–bridge displacement compatibility equation, which can accurately simulate the dynamic characteristics of the vehicle and bridge. Results show that deck roughness has an important function in the effect of the vehicle on the bridge. When an extra heavy vehicle passes through the continuous beam bridge at a low speed of 5 km/h, the impact coefficient reaches a high value, which should not be disregarded in bridge safety assessments. Considering that no specific law exists between the impact coefficient and vehicle speed, vehicle speed should not be unduly limited and deck roughness repairing should be paid considerable attention. Deck roughness has a significant influence on the reliability index, which decreases as deck roughness increases. For the continuous beam bridge in this work, the reliability index of each control section is greater than the minimum reliability index. No reinforcement measures are required for over-sized transport.展开更多
For random vibration of airborne platform, the accurate evaluation is a key indicator to ensure normal operation of airborne equipment in flight. However, only limited power spectral density(PSD) data can be obtaine...For random vibration of airborne platform, the accurate evaluation is a key indicator to ensure normal operation of airborne equipment in flight. However, only limited power spectral density(PSD) data can be obtained at the stage of flight test. Thus, those conventional evaluation methods cannot be employed when the distribution characteristics and priori information are unknown. In this paper, the fuzzy norm method(FNM) is proposed which combines the advantages of fuzzy theory and norm theory. The proposed method can deeply dig system information from limited data, which probability distribution is not taken into account. Firstly, the FNM is employed to evaluate variable interval and expanded uncertainty from limited PSD data, and the performance of FNM is demonstrated by confidence level, reliability and computing accuracy of expanded uncertainty. In addition, the optimal fuzzy parameters are discussed to meet the requirements of aviation standards and metrological practice. Finally, computer simulation is used to prove the adaptability of FNM. Compared with statistical methods, FNM has superiority for evaluating expanded uncertainty from limited data. The results show that the reliability of calculation and evaluation is superior to 95%.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.51465001 and 51905113)the Natural Science Foundation of Changsha City(Grant No.kq2208085)。
文摘The hydraulic excitation acting on a hydro-turbine generator unit exhibits obvious non-stationary characteristics.In order to account for these characteristics,this study focuses on the non-stationary random vibration reliability of the hydro-turbine generator unit.Firstly,the non-stationary characteristics of the hydraulic excitation are analyzed,and a mathematical ex-pression is constructed using the virtual excitation method.Secondly,a dynamic model of the unit is established to demonstrate the non-stationary random vibration characteristics under hydraulic excitation.Thirdly,an active learning non-stationary vibration reliability analysis method AK-MCS-T-H is proposed combining the Kriging model,the Monte Carlo simulation(MCS)method,and the information entropy learning function H.This method reveals the influence of the non-stationary hydraulic excitation on the random vibration reliability of the hydro-turbine generator unit.Finally,an example is presented to analyze the random vibration reliability.The study shows that the AK-MCS-T-H proposed in this paper can solve the problem of non-stationary random vibration reliability of the Francis hydro-turbine generator unit more effectively.
基金Project(50779032)supported by the National Natural Science Foundation of ChinaProject(20090451330)supported by the Postdoctoral Foundation of ChinaProject(BS2013SF007)supported by Shandong Scientific Research Award Foundation for Outstanding Young Scientists,China
文摘To analyze the dynamic response and reliability of a continuous beam bridge under the action of an extra heavy vehicle, a vehicle–bridge coupled vibration model was established based on the virtual work principle and vehicle–bridge displacement compatibility equation, which can accurately simulate the dynamic characteristics of the vehicle and bridge. Results show that deck roughness has an important function in the effect of the vehicle on the bridge. When an extra heavy vehicle passes through the continuous beam bridge at a low speed of 5 km/h, the impact coefficient reaches a high value, which should not be disregarded in bridge safety assessments. Considering that no specific law exists between the impact coefficient and vehicle speed, vehicle speed should not be unduly limited and deck roughness repairing should be paid considerable attention. Deck roughness has a significant influence on the reliability index, which decreases as deck roughness increases. For the continuous beam bridge in this work, the reliability index of each control section is greater than the minimum reliability index. No reinforcement measures are required for over-sized transport.
基金supported by Aeronautical Science Foundation of China (No. 20100251006)Technological Foundation Project of China (No. J132012C001)
文摘For random vibration of airborne platform, the accurate evaluation is a key indicator to ensure normal operation of airborne equipment in flight. However, only limited power spectral density(PSD) data can be obtained at the stage of flight test. Thus, those conventional evaluation methods cannot be employed when the distribution characteristics and priori information are unknown. In this paper, the fuzzy norm method(FNM) is proposed which combines the advantages of fuzzy theory and norm theory. The proposed method can deeply dig system information from limited data, which probability distribution is not taken into account. Firstly, the FNM is employed to evaluate variable interval and expanded uncertainty from limited PSD data, and the performance of FNM is demonstrated by confidence level, reliability and computing accuracy of expanded uncertainty. In addition, the optimal fuzzy parameters are discussed to meet the requirements of aviation standards and metrological practice. Finally, computer simulation is used to prove the adaptability of FNM. Compared with statistical methods, FNM has superiority for evaluating expanded uncertainty from limited data. The results show that the reliability of calculation and evaluation is superior to 95%.