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基于加速度的汽車懸架位移實(shí)時(shí)測(cè)試方法試驗(yàn)研究
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國(guó)家自然科學(xué)基金資助項(xiàng)目(51105001)和安徽省高等學(xué)校省級(jí)自然科學(xué)研究重點(diǎn)資助項(xiàng)目(KJ2011A101)


Experiment on Real-time Test Method for Automotive Suspension Distance Based on Acceleration
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    摘要:

    采用虛擬實(shí)時(shí)控制器實(shí)現(xiàn)基于加速度信號(hào)的汽車懸架位移的實(shí)時(shí)測(cè)量,。硬件測(cè)試系統(tǒng)采集器選用了工業(yè)級(jí)嵌入式系統(tǒng)CompactRIO及其C模塊,傳感器選用了ICP加速度傳感器、拉線位移傳感器和GPS系統(tǒng),。基于LabVIEW完成了FPGA編程、控制器編程,編程時(shí)采用了多線程和FIFO技術(shù),、采樣數(shù)據(jù)打包時(shí)均包含了時(shí)間信息,有效提高了數(shù)據(jù)傳輸?shù)目焖傩院蛿?shù)據(jù)處理的準(zhǔn)確性,。在控制器中實(shí)現(xiàn)了基于LabVIEW的小波濾波和支持向量機(jī)(SVM)模型的懸架位移實(shí)時(shí)預(yù)測(cè)輸出(CAN,,100 Hz)。根據(jù)懸架下測(cè)點(diǎn)的加速度均方根值對(duì)7種典型路面等級(jí)進(jìn)行了劃分,,并將路面等級(jí)信息作為SVM模型的輸入元素,。對(duì)7種路面系統(tǒng)試驗(yàn)和數(shù)據(jù)分析表明:選用的ε-SVR算法,取ε=0.01時(shí),,控制器小波濾波一個(gè)點(diǎn)和預(yù)測(cè)一次懸架位移耗時(shí)小于1 ms,,滿足實(shí)時(shí)性要求;懸架位移模型預(yù)測(cè)曲線與實(shí)際測(cè)量曲線相關(guān)系數(shù)基本在0.90以上,,滿足精度要求,。

    Abstract:

    Real-time measurement for automotive suspension distance based on acceleration was carried out by using virtual real-time controller. This paper set up a test system, in which the industrial embedded system CompactRIO and several C modules were employed as its hardware collector, besides typical ICP acceleration sensor, displacement sensor and GPS system were also employed. FPGA programming and controller programming using the multi-threading and FIFO method were completed in LabVIEW. The time information was contained in every sample data package, which effectively improved the speed of data transmission and the accuracy of data processing. Wavelet filter and support vector machine (SVM) model were built and embedded in CompactRIO to predict and output suspension distance (CAN, 100 Hz) in real time. The grade of seven kinds of typical roads was determined according to the RMS value of acceleration of suspension’s lower measuring point, which was employed as input element of the SVM model. The road way tests and data analyses indicated that the controller consumes less than 1 ms when completing one point’s wavelet filtering and predicting in which ε=0.01 for ε-SVR algorithm. The relationship coefficient of the suspension displacement curves of predicted by SVR model and measured in road way tests were more than 0.90 primarily. So the system could meet the requirements of accuracy and real-time control. 

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張小龍,潘登,姜山,陳彬,曹成茂.基于加速度的汽車懸架位移實(shí)時(shí)測(cè)試方法試驗(yàn)研究[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2013,44(10):15-22. Zhang Xiaolong, Pan Deng, Jiang Shan, Chen Bin, Cao Chengmao. Experiment on Real-time Test Method for Automotive Suspension Distance Based on Acceleration[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(10):15-22.

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  • 在線發(fā)布日期: 2013-10-14
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