Research on the Prediction of Fatigue Life of Tower Crane Based on Gray System
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摘要: 由于塔机的疲劳寿命有很多不确定性因素的影响,笔者采用灰色系统模型进行塔机的疲劳寿命预测。运用GM(1,1)模型和GM(1,1)幂模型对QTZ630塔机起重臂实际工况载荷谱下的疲劳寿命进行预测,结果表明:传统的Miner方法预测误差达为43.7%;采用线性灰色GM(1,1)模型预测误差降到25.2%;而采用非线性灰色GM(1,1)幂模型预测误差降到23.2%。基于灰色预测的结果均偏向安全。说明灰色预测为塔机的疲劳寿命预测提供了一种途径,并具有较高的预测精度和可靠性,在塔机疲劳寿命预测领域有一定的应用前景。Abstract: As the fatigue life of tower crane is influenced by many uncertain factors, in this paper, the Grey System Theory is used to forecast the fatigue life of the tower crane. The model of GM ( 1,1 ) and the power model of GM ( 1,1 ) are respectively used to the prediction of fatigue life of lifting arm of QTZ630 under the load spectrum of actual conditions. It is shown that the life prediction error of the traditional Miner method is 43.7% ; and the error is decreased to 25.2% by using linear gray model of GM( 1,1 ) ; while the error based on the non-linear gray power model of GM( 1,1 ) is dropped to 23.2%. The life prediction result based on gray prediction method is inclined to safety, which indicates that the grey prediction offers a way to predict the fatigue life for tower crane. And it also have appropriate prospect in the life prediction field of tower crane for the high prediction accuracy and reliability.
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Key words:
- tower crane /
- gray prediction /
- gray model /
- fatigue life
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