振动舒适度的智能手机大数据研究

Big data investigation for vibration serviceability using smart phones

为了解决传统振动舒适度研究方法小样本代表性差、环境非真实等问题,设计了可在智能手机上运行的振动测试和问卷调查程序并开展网络推广,形成了真实环境下、真实感知的振动舒适度大数据调查新方法。通过对已获得的8521条数据进行分析,确定了数据清洗的若干标准,利用有效数据研究了受测者身高、年龄、性别、体重等个体特征和发生场所、振动方向、振动原因等环境因素对振动感受的影响,统计了不同特征因素对应的振动限值。研究表明:基于智能手机的振动舒适度大数据研究方法可行,所得结论与已有标准具有一致性,并可包含比传统方法更丰富的影响要素。

Traditional methods for investigating vibration serviceability are mostly based on small samples and unreal environment,which causes differences and incorrectness in previous researches.By designing programs running on smart phones and spreading them through internet,tests and questionnaires are carried out in real environment by people with real sensing capacity,which forms a new big data investigating method for vibration serviceability research.The analysis of 8521 data set provides principles for data cleaning and a multi-source heterogeneous data base.Over all the effective data collected?the results count the influences of biological characters(height/weight/age/gender)and environmental factors(situation/direction/sauce of vibration etc.)on vibration serviceability.Various vibration limits corresponding to different characters and factors are compatible and inclusive to previous researches.Furthermore,the conclusions are more abundant and precise than the ones drawn from traditional methods.