基于表面肌電的草原公路駕駛員局部肌肉疲勞研究
本文選題:表面肌電 + 草原公路; 參考:《內(nèi)蒙古農(nóng)業(yè)大學(xué)》2015年碩士論文
【摘要】:內(nèi)蒙古自治區(qū)“十二五”規(guī)劃公路里程將突破6000公里。內(nèi)蒙古境內(nèi)草原覆蓋面大,已建或待建公路不可避免的穿越草原,形成在景觀與線形方面獨(dú)具特點(diǎn)的草原公路。草原公路一般具有縱坡度小、曲線半徑大、長(zhǎng)直線多、線形變化小和景觀單一等特點(diǎn)。致使駕駛員駕駛過(guò)程中的操作轉(zhuǎn)換率極低。不合理的安靜狀態(tài)和單調(diào)乏味、無(wú)刺激性的駕駛?cè)蝿?wù)必定會(huì)使駕駛員出現(xiàn)疲勞。連續(xù)執(zhí)行這樣的駕駛?cè)蝿?wù)時(shí),駕駛員局部肌肉處在靜態(tài)施力狀態(tài),導(dǎo)致駕駛員乏力、工作效率降低、操作速度變緩、動(dòng)作協(xié)調(diào)性和靈活性降低、操作錯(cuò)誤的概率及事故發(fā)生率上升等。由人機(jī)工程學(xué)研究表明體力疲勞是駕駛過(guò)程中駕駛員主要的疲勞狀態(tài)。本文針對(duì)草原公路特點(diǎn),在實(shí)駕實(shí)驗(yàn)基礎(chǔ)上,運(yùn)用反映駕駛員肌肉疲勞的生理指標(biāo),結(jié)合駕駛員疲勞量表調(diào)查。對(duì)駕駛員行車時(shí)的局部肌肉表面肌電信號(hào)進(jìn)行數(shù)據(jù)采集和分析,深入的研究了草原公路駕駛員肌肉疲勞特點(diǎn)。在此基礎(chǔ)上,建立草原公路駕駛過(guò)程中駕駛員局部肌肉疲勞模型。該研究對(duì)豐富和完善我國(guó)公路交通行車規(guī)范、改善和優(yōu)化草原公路線形組合、提高草原公路的路用性能、減輕駕駛員疲勞和增強(qiáng)行車安全等都有著較強(qiáng)的現(xiàn)實(shí)意義。運(yùn)用表面肌電方法分析草原公路駕駛員肌肉疲勞得出以下結(jié)論:(1)駕駛員在草原道路駕駛時(shí)肩部、腰部中值頻率與駕駛速度無(wú)關(guān)。與駕駛時(shí)間呈現(xiàn)負(fù)相關(guān)。(2)隨著駕駛時(shí)間的延長(zhǎng)駕駛員肌肉功率譜圖均出現(xiàn)頻譜左移現(xiàn)象,表明駕駛員出現(xiàn)疲勞感。(3)建立草原公路駕駛員肩部肌肉疲勞回歸模型。(4)建立草原公路駕駛員腰部肌肉疲勞回歸模型。(5)確定草原公路連續(xù)駕駛過(guò)程中肌肉疲勞起始時(shí)間為40min,更深層次的疲勞出現(xiàn)在75min。(6)主觀問(wèn)卷調(diào)查驗(yàn)證了駕駛疲勞的產(chǎn)生。疲勞等級(jí)的統(tǒng)計(jì)分析證明了駕駛員局部肌肉疲勞的重要性。
[Abstract]:The highway mileage of Inner Mongolia Autonomous region will exceed 6000 km during the 12th five-year Plan. Inner Mongolia has a large grassland coverage, built or to be built road inevitably across the grassland, formed in the landscape and linear unique characteristics of the grassland highway. Steppe highway generally has the characteristics of small longitudinal slope, large curve radius, long straight line, small linear change and single landscape. As a result, the operating conversion rate of the driver is very low during the driving process. Unreasonable quiet and monotonous, non-irritating driving tasks are bound to make the driver tired. When performing such a driving task continuously, the driver's local muscles are in a static state of force, which results in a driver's fatigue, reduced work efficiency, slower operation speed, lower coordination and flexibility. The probability of operation error and the increase of accident rate etc. The results of ergonomics show that physical fatigue is the main fatigue state of drivers. According to the characteristics of steppe highway and on the basis of actual driving experiment, this paper applies the physiological index which reflects the fatigue of driver's muscle, and combines with the investigation of driver's fatigue scale. To collect and analyze the data of local muscle surface electromyography (EMG) signals while driving, the fatigue characteristics of steppe drivers are studied in depth. On this basis, the local muscle fatigue model of steppe highway driver was established. This study is of great practical significance to enrich and perfect the traffic regulation of highway in China, improve and optimize the alignment of grassland highway, improve the road performance of grassland highway, reduce driver fatigue and enhance driving safety. Using the surface electromyography (EMG) method to analyze the muscle fatigue of the steppe road drivers, the following conclusions are drawn: 1) the median frequency of the waist is not related to the driving speed when the driver is driving on the prairie road. There was a negative correlation between driving time and driving time. It shows that the driver has fatigue feeling. 3) establish the regression model of shoulder muscle fatigue of the steppe highway driver. 4) establish the regression model of the waist muscle fatigue of the steppe highway driver. 5) determine the beginning of muscle fatigue in the continuous driving process of the prairie highway. The time is 40 min, and the deeper fatigue occurs at 75 min. 6) subjective questionnaire survey verifies the occurrence of driving fatigue. The statistical analysis of fatigue grade proves the importance of local muscle fatigue.
【學(xué)位授予單位】:內(nèi)蒙古農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2015
【分類號(hào)】:U491.25
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