Table 4 Fitting results and regression coefficient of PPV power function curve.

From: A multi-parameters assessment method and prediction model for ground vibration under the high-speed railway bridge

Operating condition

Fitting equation

Regression coefficient(R2)

In the direction of l1

 100 km/h (G3695)

y = 0.832x− 0.7934

0.9843

 150 km/h (G3696)

y = 0.943x− 0.8177

0.9896

 200 km/h (G3654)

y = 1.3178x− 0.8339

0.9963

 300 km/h (G924)

y = 1.9471x− 0.7986

0.8532

In the direction of l2

 100 km/h (G3695)

y = 0.6475x− 0.8108

0.9803

 150 km/h (G3696)

y = 0.747x− 0.7923

0.9663

 200 km/h (G3654)

y = 1.299x− 0.8182

0.9816

 300 km/h (G924)

y = 1.384x− 0.7914

0.8093

In the direction of l3

 100 km/h (G3695)

y = 0.734x− 0.8184

0.9812

 150 km/h (G3696)

y = 0.823x− 0.8377

0.9731

 200 km/h (G3654)

y = 1.3178x− 0.8339

0.9822

 300 km/h (G924)

y = 1.4471x− 0.8034

0.8265

  1. Note: The x was the independent variable of the PPV power function curve, and represented the distance away from the high-speed railway; The y was the dependent variable of the PPV power function curve, and represented the value of PPV.
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