【摘要】：在世界各國交通事故的法醫(yī)學(xué)調(diào)查中,酒后駕駛是導(dǎo)致交通事故發(fā)生的重要原因,醉酒駕駛的檢測(cè)與預(yù)防越來越受到世界各國的重視。目前,較為成熟的酒精檢測(cè)方式為呼氣式酒精檢測(cè)和抽血檢驗(yàn),由于抽血檢驗(yàn)屬于有創(chuàng)傷的檢測(cè)方法,呼氣法檢測(cè)又存在檢測(cè)精度的問題,而近紅外光譜法作為一種快速、準(zhǔn)確、無損的檢測(cè)方式,與現(xiàn)有的技術(shù)相比,有不可替代的優(yōu)勢(shì)。近紅外光譜法已經(jīng)被廣泛的用來檢測(cè)人體內(nèi)的物質(zhì),如葡萄糖、血氧等含量的檢測(cè),可以說該技術(shù)已經(jīng)進(jìn)入到了成熟發(fā)展階段,但是國內(nèi)外近紅外光譜法檢測(cè)駕駛員血液中酒精含量尚處于研究階段。 本文的目的是實(shí)現(xiàn)駕駛員體內(nèi)酒精含量的近紅外光譜法無損檢測(cè),并與汽車駕駛系統(tǒng)結(jié)合,實(shí)現(xiàn)防醉酒駕駛。利用小波分析與偏最小二乘法對(duì)人體內(nèi)酒精的近紅外漫反射光譜進(jìn)行了分析與研究,并在此基礎(chǔ)上分析血液酒精在人體內(nèi)隨時(shí)間衰減以及吸收的規(guī)律,建立了偏最小二乘法檢測(cè)人體組織內(nèi)酒精含量的定量模型,并對(duì)所建立模型的預(yù)測(cè)精度及穩(wěn)定性進(jìn)行檢驗(yàn)。 人體內(nèi)酒精近紅外光譜信號(hào)含有較強(qiáng)的噪聲,特別是直接在人體皮膚表面采集的信號(hào),噪聲干擾十分強(qiáng)烈,不能直接用于建立模型,本文采用采用小波變換以及數(shù)據(jù)平滑對(duì)酒精近紅外光光譜進(jìn)行預(yù)處理。選擇硬閾值條件下,matlab缺省去噪方法,對(duì)所得光譜數(shù)據(jù)進(jìn)行了去噪處理,并確定了酒精的透射特征光譜波長(zhǎng)范圍在1550nm-1800nm左右。 根據(jù)小波分析等預(yù)處理之后的光譜數(shù)據(jù),采用了偏最小二乘法建立定量校正模型,留一交叉驗(yàn)證法確定最佳主成分?jǐn)?shù)。采用相關(guān)系數(shù)(R)、均方根誤差(RMSEC)作為校正模型的評(píng)價(jià)參數(shù),未知樣本的預(yù)測(cè)結(jié)果采用預(yù)測(cè)均方差(RMSEP)及平均相對(duì)誤差(MREP)進(jìn)行評(píng)價(jià),并對(duì)模型的重復(fù)性進(jìn)行驗(yàn)證,實(shí)現(xiàn)了對(duì)未知酒精濃度的檢測(cè)。 最后,設(shè)計(jì)了防醉酒的駕駛預(yù)警系統(tǒng)。在硬件方面,使用S3C2410A作為主控節(jié)點(diǎn)的微控制器,選擇MCP2515作為ARM主控節(jié)點(diǎn)的CAN控制器,選擇PCA82C250作為CAN收發(fā)器,繪制了相關(guān)的電路,并編寫了對(duì)應(yīng)執(zhí)行機(jī)構(gòu)軟件程序,實(shí)現(xiàn)了當(dāng)駕駛員體內(nèi)酒精含量超標(biāo)時(shí),完成發(fā)出報(bào)警提示音、點(diǎn)亮報(bào)警燈以及緊急制動(dòng)等動(dòng)作,從而有效的防止醉酒駕駛,避免不必要的損失。
[Abstract]:In the forensic investigation of traffic accidents all over the world, drunk driving is an important cause of traffic accidents. The detection and prevention of drunken driving has been paid more and more attention by many countries all over the world. At present, the more mature methods of alcohol detection are expiratory alcohol detection and blood sampling test. Because the blood sampling test belongs to the invasive detection method, the detection accuracy of breath method is also a problem, and the near infrared spectroscopy is a fast method. Accurate, non-destructive testing method, compared with the existing technology, has irreplaceable advantages. Near infrared spectroscopy (NIR) has been widely used to detect substances in human body, such as glucose, blood oxygen, etc. It can be said that the technology has entered the mature stage of development. However, near infrared spectroscopy (NIR) is still in the research stage to detect the alcohol content in the driver's blood at home and abroad. The purpose of this paper is to realize the nondestructive detection of alcohol content in the driver's body by near infrared spectroscopy (NIR), and combine it with the automobile driving system to realize the anti-drunken driving. The near infrared diffuse reflectance spectrum of alcohol in human body was analyzed and studied by wavelet analysis and partial least square method. On the basis of the analysis, the attenuation and absorption of blood alcohol in human body with time were analyzed. A quantitative model for the determination of alcohol content in human tissues by partial least square method was established and the prediction accuracy and stability of the model were tested. The near infrared spectrum signal of alcohol in human body contains strong noise, especially the signal collected directly on the surface of human skin. The noise interference is very strong and can not be used to establish the model directly. In this paper, wavelet transform and data smoothing are used to pre-process the near-infrared spectrum of alcohol. Under the condition of hard threshold, the matlab default de-noising method is selected, and the spectral data are de-noised, and the wavelength range of the transmission characteristic spectrum of alcohol is determined to be about 1550nm-1800nm. According to the pre-processed spectral data such as wavelet analysis, the partial least square method is used to establish the quantitative correction model, and a cross-check method is used to determine the optimal principal fraction. The correlation coefficient (R), root mean square error (RMSEC) is used as the evaluation parameter of the calibration model. The prediction results of the unknown samples are evaluated by the prediction mean variance (RMSEP) and the average relative error (MREP), and the repeatability of the model is verified. The detection of unknown alcohol concentration is realized. Finally, an anti-drunken driving warning system is designed. In the aspect of hardware, S3C2410A is used as the microcontroller of the main control node, MCP2515 is chosen as the CAN controller of the ARM master node, and PCA82C250 is chosen as the CAN transceiver. The relevant circuits are drawn, and the software program of the corresponding executing mechanism is programmed. When the alcohol content of the driver exceeds the standard, the actions such as issuing alarm tone, lighting the alarm light and emergency braking are completed, so as to effectively prevent drunken driving and avoid unnecessary loss.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U492.8;TN219

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