Road load spectrum preparation method based on density peak machine learning algorithm

Abstract

The invention provides a road load spectrum preparation method based on a density peak machine learning algorithm. The method comprises the steps: testing the movement of a vehicle on an actual road,and obtaining an initial road load spectrum and speed information; performing statistical modeling on the load and the acceleration to obtain an acceleration signal-road load model; performing preprocessing such as low-pass filtering and resampling on the initial road load spectrum to obtain a preprocessed road load spectrum; based on a wavelet transform method, subjecting the preprocessed load spectrum to compression and noise reduction processing, and shortening the load spectrum time history while effective data is reserved; and performing clustering reconstruction on the compressed load spectrum based on a density peak clustering TNDP machine learning method to obtain an accurate road load spectrum. According to the method, real and accurate road load spectrums can be obtained on different test roads, the load spectrums can be collected only by installing an acceleration sensor in the test of the same type of vehicle model, the cost and the test complexity are greatly reduced, andfinally the compiled accurate load spectrum is obtained. The loaded conditions of automobile parts in the actual driving process can be rapidly reproduced for bench experiments, and high-precision load input is provided for automobile part fatigue reliability research.

Description

technical field [0001] The invention relates to manufacturing technology, in particular to a method for preparing a road load spectrum. Background technique [0002] With the continuous progress of modern automobile research and development and manufacturing technology, people have higher and higher requirements for the fatigue durability of automobile structures. The experimental verification of auto parts is an essential part of the development of automotive products. A lot of time is spent in the research and development process. Among them, the fatigue reliability performance test is particularly important, and it is the test that consumes the most time and cost. When the durability failure and fatigue damage of auto parts occur, the comfort and safety of the car will be greatly affected. The load on the parts reflects the load-time history of the actual working process of the product, which is the basis for structural fatigue experiments, strengthening experiments and ...

AI Technical Summary

Problems solved by technology

[0005] The invention provides a method for preparing road load spectrum, which is used to solve the problem that the existing empirical load of extreme working conditions is used as the vehicle load data, and the fatigue life of the vehicle body cannot be accurately predicted, resulting in the inability to effectively improve the fatigue durability of the vehicle body

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