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Study on the Prediction Method of Off-road Average Speed of Tracked Vehicles on Random Uneven Roads

QIAO Xinyong DUAN YU RUI Qiang JIANG Hongyuan YANG Hao

2019, 39 (1): 103-109. DOI: 10.3969/j.issn.1006-1355.2019.01.020

Abstract （379）

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In order to study the effect of road roughness on the off-road average speed of tracked vehicles, a multi-body dynamic model is established. The vibration response index is proposed and the credibility of the model is verified by the test. Based on the experimental design, a simulation model is made to establish the approximate model between vibration response and vehicle speed, road roughness. Taking the threshold value of the vibration response index as the constraint condition, the mathematical relationship between the roughness of the pavement and the speed of vehicle is fitted by the method of target optimization, and the prediction method of the off-road speed under the condition of random and uneven pavement is put forward. The method is used to calculate the test ground, and the results show that the model can reflect the impact of road roughness on the vehicle speed, and provide an effective quantitative means for vehicle mobility prediction.

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An Endpoint Extension Algorithm of EMD and Its Application in Gear Fault Diagnosis

LI Yue-xian;HAN Zhen-nan;GAO Jian-xin;YANG Hao-lin

2012, 32 (2): 108-111. DOI: 103969/j.issn.1006-1355-2012.02.026

Abstract （1109）

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EMD is an effective method for non-stable signal analysis, but the endpoint effect exists in the decomposition process. In this article, the GM (1, 1) model was used to predict and modify the extension values at the endpoints, which made the cubic interpolation envelope more effective in sifting process. In this way, the endpoint effect was effectively suppressed. The result of gear fault signal analysis shows that this method is correct and effective.

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Research of AANC Secondary Path Modeling Method

YANG Hao;WU Ya-feng;WANG Chun-yun;CHU Ni-Sheng

2011, 31 (3): 33-36. DOI: 10.3969/j.issn.1006-1355-2011.03.008

Abstract （7877）

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Secondary path modeling is a key issue of adaptive active noise control (AANC) system. An impulse response measurement based on time stretch pulse (TSP) signal is used in this paper. TSP signal has the characteristics of distributing the pulse energy in a period of time. The impulse response function of the tested system with TSP signal can be reconstructed by gathering the scattered energy in the response signal. The method is applied to secondary path modeling, and 20dB and 14dB noise reduction is respectively obtained in simulations and experiments. The results show that the secondary path modeling method based on TSP is simple, accurate and very suitable for practical ANC engineering test.