Real‐time prediction method of fatigue life of bridge crane structure based on digital twin

Author(s):  
Qing Dong ◽  
Bin He ◽  
Qisong Qi ◽  
Gening Xu
Author(s):  
Jinyan Guo ◽  
Zhaojun Yang ◽  
Chuanhai Chen ◽  
Wei Luo ◽  
Wei Hu

Abstract The functional parts of a machine tool determine its reliability level to a great extent. The failure prediction of the functional part is helpful to prepare the maintenance scheme in time, in order to ensure a stable manufacturing process and the required production quality. Due to the rise of digital twin (DT), which has the characteristics of virtual reality interaction and real-time mapping, a DT-based real-time prediction method of the remaining useful life (RUL) and preventive maintenance scheme is proposed in this study. In this method, a DT model of the manufacturing workshop is established based on real-time perceptual information obtained by the proposed acquisition method. Subsequently, the real-time RUL of the functional part is predicted by establishing a RUL prediction model based on the nonlinear-drifted Brownian motion, which takes the working conditions and measurement errors into consideration. On this basis, the optimal preventive maintenance scheme can be determined and fed back to the manufacturing workshop, in order to guide the maintenance of relevant parts. Finally, an example case study is presented to illustrate the feasibility and effectiveness of the proposed method.


2011 ◽  
Vol 94-96 ◽  
pp. 38-42
Author(s):  
Qin Liu ◽  
Jian Min Xu

In order to improve the prediction precision of the short-term traffic flow, a prediction method of short-term traffic flow based on cloud model was proposed. The traffic flow was fit by cloud model. The history cloud and the present cloud were built by historical traffic flow and present traffic flow. The forecast cloud is produced by both clouds. Then, combining with the volume of the short-term traffic flow of an intersection in Guangzhou City, the model was calculated and simulated through programming. Max Absolute Error (MAE) and Mean Absolute percent Error (MAPE) were used to estimate the effect of prediction. The simulation results indicate that this prediction method is effective and advanced. The change of the historical and real time traffic flow is taken into account in this method. Because the short-term traffic flow is dealt with as a whole, the error of prediction is avoided. The prediction precision and real-time prediction are satisfied.


2013 ◽  
Vol 321-324 ◽  
pp. 757-761 ◽  
Author(s):  
Chen Liang Song ◽  
Zhen Liu ◽  
Bin Long ◽  
Cheng Lin Yang

According to the real-time prediction for performance degradation trend, the commonly used method is just based on field data. But this methods prediction result will not be so much ideal when the fitting of degradation trend of field data is not good. To solve the problem, the paper introduces a new method which is not only based on field method but also based on reliability experimental data coming from the history experiment. We use the relationship between the field data and reliability experimental data to get the result of the two kinds of data respectively and then get the weights according to the two prediction results. Finally, the final real-time prediction result for performance degradation tendency can obtain by allocating the weights to the two prediction results.


2012 ◽  
Vol 170-173 ◽  
pp. 3102-3105
Author(s):  
Xiong Hu ◽  
Ming Wei

This paper aims to achieve a crane real-time software programming methodology for estimating the fatigue life,the core idea of this method is to capture the whole life cycle of real-time stress load,gets real-time fatigue life results by using JIS and FEM and compares the two results.The method is more accurate than the traditional one and has guiding significance for real-time fatigue life estimation of port machinery.


2012 ◽  
Vol 482-484 ◽  
pp. 736-740
Author(s):  
Xiao Mei ◽  
Da Shan Dong ◽  
Yuan Yuan Teng

Fatigue crack is very dangerous for safely operating of steel structures. To estimate precisely fatigue life of bridge cranes, the randomness of lifted load and trolley’s position should be considered. Therefore, bi-probability fatigue life prediction method, namely load and position probability, is put forward based on the miner linear cumulative damage theory. Stress cycle spectrum is constructed based on real-time monitoring data by rainflow counting method. This method can successfully explain the existence of girder cracks in a typical bridge crane RMG, so it would provide valuable reference for maintenance decision of in-service cranes.


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