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  本文關(guān)鍵詞：車載動態(tài)治超監(jiān)控系統(tǒng)的研究與設(shè)計　出處：《太原理工大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

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【摘要】：隨著國民經(jīng)濟(jì)的發(fā)展,中國道路交通網(wǎng)加速建設(shè),公路運輸行業(yè)快速發(fā)展,但車輛超限超載的問題也隨之日益加劇,對行駛在道路上的車輛進(jìn)行超限超載檢測迫在眉睫。目前,國內(nèi)普遍采用靜態(tài)或動態(tài)稱重系統(tǒng)來治理車輛超限超載現(xiàn)象的發(fā)生,但是,現(xiàn)有的靜態(tài)或動態(tài)稱重系統(tǒng)的稱重設(shè)備與車輛分離,在偏遠(yuǎn)地方或者沒有稱重設(shè)備的地方無法測量貨車的重量,具有很大的局限性;同時,實際稱重過程中,稱重系統(tǒng)容易受到發(fā)動機(jī)轉(zhuǎn)動噪聲、車輛速度和加速度等因素的影響導(dǎo)致車載稱重系統(tǒng)測量精度不高。針對以上問題,本文在考察現(xiàn)有靜態(tài)或動態(tài)稱重系統(tǒng)所存在的不足之處,并充分了解車輛超限超載治理實際需求的基礎(chǔ)上,擬設(shè)計一種基于小波和BP神經(jīng)網(wǎng)絡(luò)的車載動態(tài)治超監(jiān)控系統(tǒng)。該系統(tǒng)以STM32單片機(jī)為核心,并借助GPS+GPRS DTU終端和DGUS智能顯示屏等外圍輔助設(shè)備,共同實現(xiàn)車載稱重數(shù)據(jù)采集處理、車輛信息實時存儲、GPS車輛定位跟蹤以及利用GPRS無線網(wǎng)絡(luò)與車輛遠(yuǎn)程監(jiān)控平臺進(jìn)行實時數(shù)據(jù)交換等功能;同時,本系統(tǒng)先采用小波變換對車載動態(tài)稱重信號進(jìn)行噪聲濾波預(yù)處理,然后建立以車輛速度信號、加速度信號和預(yù)處理車載稱重信號為輸入因子的BP神經(jīng)網(wǎng)絡(luò)模型來提高車載稱重系統(tǒng)的稱量精度。本文的主要研究內(nèi)容如下:一、車載動態(tài)治超監(jiān)控系統(tǒng)算法研究,主要包括小波和BP神經(jīng)網(wǎng)絡(luò)的理論分析、實際應(yīng)用和實驗仿真結(jié)果分析。二、車載動態(tài)治超監(jiān)控系統(tǒng)整體框架設(shè)計,主要包括車載數(shù)據(jù)采集系統(tǒng)和車載遠(yuǎn)程監(jiān)控平臺的總體設(shè)計方案和具體工作流程。三、車載數(shù)據(jù)采集系統(tǒng)設(shè)計,主要包括CPU模塊、稱重數(shù)據(jù)采集模塊、數(shù)據(jù)存儲模塊、無線通訊模塊、HMI人機(jī)交互模塊和電源模塊等各部分的硬件和軟件設(shè)計,主要實現(xiàn)車載稱重數(shù)據(jù)采集、GPS車輛實時定位跟蹤和人機(jī)交互顯示功能。四、車載遠(yuǎn)程監(jiān)控平臺設(shè)計,該平臺以Visual Studio 2008和SQL 2008數(shù)據(jù)庫為開發(fā)環(huán)境進(jìn)行設(shè)計,主要實現(xiàn)車輛基本信息查詢、車輛運行參數(shù)查詢、車輛實時位置查詢和車輛超載報表統(tǒng)計等功能。本論文的主要創(chuàng)新點:第一,本系統(tǒng)利用GPRS無線網(wǎng)絡(luò)傳輸技術(shù)將車載數(shù)據(jù)采集系統(tǒng)和車載遠(yuǎn)程監(jiān)控平臺進(jìn)行有效結(jié)合,便于工作人員對貨車載荷量進(jìn)行實時監(jiān)控管理,嚴(yán)格控制超限超載現(xiàn)象的發(fā)生。第二,本系統(tǒng)將小波變換和BP神經(jīng)網(wǎng)絡(luò)算法應(yīng)用于車載動態(tài)治超監(jiān)控系統(tǒng)來減小高頻噪聲、車輛速度和加速度對系統(tǒng)稱量精度的影響,與傳統(tǒng)車載稱重系統(tǒng)相比,該系統(tǒng)的車載稱量精度大大提高,具有很強的實用性。本系統(tǒng)已在山西省多個高速公路檢測站穩(wěn)定、正常運行,應(yīng)用本系統(tǒng)提出的算法處理后,車載動態(tài)稱重最大誤差小于2%,滿足《JT/T 794-2011》國家交通運輸行業(yè)標(biāo)準(zhǔn)規(guī)定的車載動態(tài)稱重誤差不高于5%的精度要求。
[Abstract]:With the development of the national economy, China road network to accelerate the construction, the rapid development of highway transportation industry, but the vehicle overload problem becomes increasingly intensified, the vehicles traveling on the road of imminent overloading detection. At present, the domestic commonly used static or dynamic weighing system to control the vehicle overloading phenomenon, however. Weighing equipment and vehicle separation of the existing static or dynamic weighing system, vehicle weight can not be measured in remote areas or without weighing equipment, has great limitations; at the same time, the actual process of weighing, weighing system is vulnerable to the engine rotation noise, vehicle speed and acceleration and other factors lead to the measurement accuracy of vehicle weighing system is not high. Aiming at the above problems, based on the shortcomings of the existing static or dynamic weighing system, and fully understand Based on the actual needs of the vehicle overloading governance, intends to design a vehicle dynamic overload monitoring system based on Wavelet and BP neural network. The system uses STM32 microcontroller as the core, and with the help of GPS+GPRS DTU and DGUS smart terminal display and other peripheral auxiliary equipment, to realize vehicle weighing data acquisition and processing, real-time vehicle information storage, GPS vehicle tracking and real-time data exchange function using the GPRS wireless network and remote vehicle monitoring platform; at the same time, the system adopts the wavelet transform of vehicle dynamic weighing signal noise filtering, and then based on the vehicle speed signal, the acceleration signal and pretreatment of vehicle weighing signal for the BP neural network model to improve the input factor. The weighing accuracy of vehicle weighing system. The main contents of this paper are as follows: a vehicle monitoring system, dynamic overload control algorithm research, the main To include wavelet analysis and BP neural network theory, application analysis and simulation results. Two, design the overall framework of vehicle dynamic overload monitoring system, including the overall design scheme of vehicle data acquisition system and the remote monitoring platform and the specific work process. Three, the design of vehicle data acquisition system, including CPU module, weighing the data acquisition module, data storage module, wireless communication module, hardware and software design of each part of HMI human-computer interaction module and power supply module, the main vehicle weighing data acquisition, interactive display function of GPS real-time vehicle positioning and tracking machine. Four, design of vehicle remote monitoring platform, the platform uses Visual Studio 2008 and SQL 2008 database for the development of environmental design, mainly to achieve the basic vehicle information query, query the vehicle operating parameters, real-time vehicle location query and overloading Report Statistics and other functions. The main innovation of this thesis: first, the system uses GPRS wireless network transmission technology of the vehicle data acquisition system and the remote monitoring platform for effective combination for staff to carry out real-time monitoring and management of goods vehicle loading, strict control over the limit of overloading. Second, the system of wavelet transform and BP neural network algorithm is applied to vehicle dynamic overload monitoring system to reduce the high frequency noise, vehicle speed and acceleration of the weighing accuracy, compared with the traditional vehicle weighing system, vehicle weighing accuracy of the system is greatly improved, and has a strong practicability. The system has been in a number of Shanxi Province highway inspection station stability the application of this system, the normal operation, the proposed algorithm processing, vehicle dynamic weighing the maximum error is less than 2%, to meet the national transportation industry standard. The fixed vehicle dynamic weighing error is not higher than 5% of the precision requirement.

【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP277

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本文編號：1422572

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