Drilling platform rising and falling unit transmission efficiency simulation method and system based on weighting

Abstract

The invention relates to a drilling platform rising and falling unit transmission efficiency simulation method and system based on weighting. The method comprises the following steps: (1) modeling a drilling platform rising and falling unit transmission device; (2) introducing the model into an Adams mechanical system, and processing the model according to needs analyzed by the Adams mechanical system; (3) carrying out virtual prototype simulation, and outputting simulation data into a text file; (4) sampling the simulation data at an equally-spaced interval of time so as to obtain multiple groups of discrete data points, and carrying out initial calculation on an efficiency value; (5) fitting the obtained efficiency value by a weighted least-squares method, thereby obtaining an efficiency curve. The method and the system have the advantages that being different from evaluation criteria to the data dispersion degree of the existing methods, the influence caused by the data points with high dispersion degree is weakened, data information with lower dispersion degree is emphasized, the interference resistance of a calculating process is correspondingly enhanced, and an obtained efficiency curve calculated result is more actual.

Description

technical field [0001] The invention relates to the technical field of drilling platform simulation, in particular to a weighted-based simulation method and system for the transmission efficiency of the drilling platform lifting unit. Background technique [0002] At present, the use of multi-body dynamics analysis software can simulate the model of the planetary gear mechanism of the drilling platform lifting unit, and obtain the input / output speed and input / output torque of the gear mechanism, but the contact caused by the collision and meshing of the gear teeth Due to force changes and errors in numerical calculations, the obtained simulation data fluctuates and there are several extreme points. [0003] In the existing technology, a set of simulation data points is obtained by sampling once in a certain period of time, and then the obtained multiple sets of discrete data points are fitted by the least square method to obtain an efficiency curve. The disadvantage of the ...

AI Technical Summary

Problems solved by technology

The disadvantage of the least squares method is that all data are treated with equal weights. The point with a greater degree of data dispersion will have a greater difference from the average value, and it will be further enlarged after squared; the point with a smaller degree of data dispersion will have the opposite effect, so the minimum The square method is easily affected by extreme points, and there is a single evaluation standard for the degree of data dispersion, inconsistent results, and unsatisfactory simulation results.

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