本文選題：工程車輛 + 載荷譜��； 參考：《吉林大學(xué)》2017年碩士論文

【摘要】：工程機械作為裝備制造業(yè)的重要組成部分,所處的作業(yè)環(huán)境復(fù)雜多變,其關(guān)鍵零部件的可靠性和耐久性受多方面因素的影響,而這也一直是制約其質(zhì)量提升及品質(zhì)發(fā)展的關(guān)鍵。載荷譜是實現(xiàn)工程車輛服役性能測試、合理正向設(shè)計、室內(nèi)模擬加載試驗、壽命預(yù)測和疲勞分析等的重要參考。實現(xiàn)實測載荷的統(tǒng)計分析,外推方法的合理選擇以及外推方法的優(yōu)化,使得外推得到的長期載荷譜的準確性和真實性得到保障是載荷譜研究領(lǐng)域的重點同時也是難點。為提升國產(chǎn)裝載機的自主研發(fā)水平,本文依托項目“工程機械節(jié)能減排共性技術(shù)研究”(項目號:SQ2015BA0400198),結(jié)合隱馬爾科夫模型理論,以某型裝載機為例,對在載荷譜編制中具有不可忽略影響的人為因素進行了研究。同時,對由于分段作業(yè)產(chǎn)生的非平穩(wěn)載荷提出了處理方法。本文的主要研究內(nèi)容如下:1.本文以裝載機為研究對象,對裝載機載荷譜的測試方案進行了詳細的闡述。包含試驗樣機的情況、測試場地以及物料準備、測試方案的制定、采集子樣大小的確定、采集測點以及傳感器的安裝等。并以實測裝載機舉升缸壓力數(shù)據(jù)為例,完成了趨勢項消除、數(shù)字化濾波、奇異點檢測等數(shù)據(jù)預(yù)處理。2.針對工程車輛操作時人為操作頻繁,載荷特性受操作方式影響大的問題,本文綜合多方面影響因素,將駕駛員的操作類型分為普通型、粗暴型、溫和型三類。由于隱馬爾科夫模型在模式識別及故障診斷領(lǐng)域良好的表現(xiàn)將其應(yīng)用于駕駛員操作類型的識別上,首先采用Baum-Welch算法對載荷數(shù)據(jù)進行訓(xùn)練,然后進行對數(shù)似然率的匹配,識別駕駛員操作類型。針對三種不同類型的操作方式及載荷特點,分別選擇雨流矩陣外推、POT外推、參數(shù)估計外推。使駕駛員操作的人為因素在載荷譜外推方法的選擇中得到充分的考慮,實現(xiàn)外推方法的合理選擇。3.針對工程車輛由于工況復(fù)雜多變以及循環(huán)作業(yè)方式造成的載荷整體不平穩(wěn)的特點,采用分段方法實現(xiàn)測試載荷的平穩(wěn)化處理,對各段載荷的平穩(wěn)性進行檢驗。利用隱馬爾科夫模型對裝載機工作模式切換時產(chǎn)生的過渡載荷進行處理,將采用分段方法處理時被忽略的轉(zhuǎn)折點信息包含進載荷處理的過程中,并將兩種方法處理得到的全雨流矩陣以及期望雨流矩陣進行對比,驗證了方法的可行性。在編譜過程中包含更多對疲勞具有貢獻的信息,有利于提高編譜的精度。通過MATLAB開發(fā)了一款“工程車輛非平穩(wěn)載荷處理分析軟件V1.0”。為研發(fā)工作者提出了非平穩(wěn)載荷處理的方法,完成了載荷處理的便捷化和規(guī)范化。本文針對裝載機載荷特點,基于隱馬爾科夫模型對載荷譜的編制方法的合理選擇以及優(yōu)化進行了研究。實現(xiàn)了駕駛員操作特性的識別并提出了非平穩(wěn)特性載荷的處理方法。實現(xiàn)提高載荷譜編制精度,為工程機械零部件的可靠性分析設(shè)計提供準確依據(jù)的目的。
[Abstract]:As an important part of the equipment manufacturing industry, construction machinery is in a complex and changeable working environment. The reliability and durability of its key parts are affected by many factors, and this has been the key to its quality improvement and quality development. Load spectrum is an important reference for engineering vehicle service performance test, reasonable forward design, indoor simulated loading test, life prediction and fatigue analysis. To realize the statistical analysis of the measured load, the reasonable selection of extrapolation method and the optimization of extrapolation method, the accuracy and authenticity of the extrapolated long-term load spectrum are guaranteed, which is the emphasis and difficulty in the field of load spectrum research. In order to improve the level of independent research and development of domestic loaders, this paper relies on the project of "study on common technologies of energy saving and emission reduction of construction machinery" (project number: SQ2015BA0400198m), combining with the theory of hidden Markov model, taking a certain type of loader as an example. The human factors which can not be ignored in the compilation of load spectrum are studied. At the same time, the non-stationary load caused by subsection operation is treated. The main contents of this paper are as follows: 1. In this paper, the load spectrum test scheme of loader is described in detail. Including the situation of the test prototype, test site and material preparation, the formulation of the test plan, the determination of the size of the sampling sub-sample, the acquisition of measuring points and the installation of sensors, etc. Taking the measured data of lift cylinder pressure of loader as an example, the preprocessing of data, such as eliminating the trend term, digitizing filtering and detecting singularity, is completed. In view of the problem that the manual operation is frequent and the load characteristic is greatly influenced by the operation mode, the operating types of the driver are classified into three types: common type, rough type and mild type. Because of its good performance in the field of pattern recognition and fault diagnosis, Hidden Markov Model is applied to the identification of driver's operation type. First, the load data is trained by Baum-Welch algorithm, and then the logarithmic likelihood ratio is matched. Identify the driver's type of operation. According to three different operation modes and load characteristics, rain flow matrix extrapolation and parameter estimation extrapolation are selected respectively. The artificial factors of driver operation are fully considered in the selection of load spectrum extrapolation method, and the reasonable selection of extrapolation method is realized. In view of the complex and changeable working conditions of the construction vehicle and the unsteady load caused by the cyclic operation mode, a piecewise method is adopted to realize the stabilization of the test load, and the smoothness of the load in each segment is tested. Using Hidden Markov Model to deal with the transient load generated when the loader's working mode is switched, the information of the turning point which is ignored by the piecewise method is included in the process of load processing. The feasibility of the method is verified by comparing the total rain flow matrix and the expected rain flow matrix obtained by the two methods. More contributions to fatigue are included in the process of spectrum compilation, which is helpful to improve the accuracy of spectrum compilation. A non-stationary load processing software V1. 0 for engineering vehicles is developed by MATLAB. The method of nonstationary load processing is proposed for R & D workers, and the convenience and standardization of load processing are accomplished. Based on hidden Markov model, the reasonable selection and optimization of load spectrum are studied in this paper. The identification of driver's operating characteristics is realized and the method of dealing with non-stationary load is put forward. The purpose of improving the precision of load spectrum compilation and providing accurate basis for reliability analysis and design of construction machinery parts.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TH243

【相似文獻】

相關(guān)期刊論文 前10條

1 馬寶山;朱義勝;;基于隱馬爾科夫模型的基因預(yù)測算法[J];大連海事大學(xué)學(xué)報;2008年04期

2 張慶生;齊勇;侯迪;趙季中;;基于隱馬爾科夫模型的上下文感知活動計算[J];西安交通大學(xué)學(xué)報;2006年04期

3 李曉琴;仁文科;劉岳;;利用隱馬爾科夫模型識別蛋白質(zhì)折疊類型[J];北京工業(yè)大學(xué)學(xué)報;2011年07期

4 羅志增;王占玉;;基于小波域隱馬爾科夫模型的肌電信號濾波[J];儀器儀表學(xué)報;2010年11期

5 劉曉飛;邸書靈;;基于隱馬爾科夫模型的文本分類[J];石家莊鐵道大學(xué)學(xué)報(自然科學(xué)版);2013年01期

6 苗強,Viliam Makis;基于隱馬爾科夫模型的故障診斷系統(tǒng)研究[J];航空學(xué)報;2005年05期

7 向東;劉虎;陳先橋;程艷芬;;半連續(xù)隱馬爾科夫模型脫機阿拉伯手寫識別[J];武漢理工大學(xué)學(xué)報(信息與管理工程版);2011年03期

8 邱英;謝鋒云;;基于小波包系數(shù)與隱馬爾科夫模型的刀具磨損監(jiān)測(英文)[J];機床與液壓;2014年12期

9 張潤丹;王瑩瑩;;量子隱馬爾科夫模型參數(shù)學(xué)習(xí)研究[J];科技視界;2014年16期

10 趙靜;黃厚寬;田盛豐;納躍躍;;基于轉(zhuǎn)移和頻率特征的協(xié)議異常檢測[J];北京交通大學(xué)學(xué)報;2009年05期

相關(guān)會議論文 前8條

1 肖鏡輝;劉秉權(quán);;一種非時齊的隱馬爾科夫模型及其在音字轉(zhuǎn)換中的應(yīng)用[A];全國第八屆計算語言學(xué)聯(lián)合學(xué)術(shù)會議（JSCL-2005）論文集[C];2005年

2 劉文壯;李均利;;一種基于隱馬爾科夫模型的脫機手寫漢字識別方法[A];2009系統(tǒng)仿真技術(shù)及其應(yīng)用學(xué)術(shù)會議論文集[C];2009年

3 彭子平;張嚴虎;潘露露;;隱馬爾科夫模型原理及其重要應(yīng)用[A];2008'中國信息技術(shù)與應(yīng)用學(xué)術(shù)論壇論文集（一）[C];2008年

4 王宏生;孫美玲;李家峰;;隱馬爾科夫模型在構(gòu)建語言模型中的應(yīng)用[A];創(chuàng)新沈陽文集（A）[C];2009年

5 張勁松;戴蓓倩;郁正慶;王長富;;漢語識別中隱馬爾科夫模型初始化的研究[A];第二屆全國人機語音通訊學(xué)術(shù)會議論文集[C];1992年

6 劉杰;梁曉輝;;基于Fused隱馬爾科夫模型的人體運動識別[A];第八屆和諧人機環(huán)境聯(lián)合學(xué)術(shù)會議（HHME2012)論文集CHCI[C];2012年

7 林晨;金蓓弘;龍震岳;陳海彪;;上下文感知的分布式事件分發(fā)研究[A];第18屆全國多媒體學(xué)術(shù)會議（NCMT2009）、第5屆全國人機交互學(xué)術(shù)會議（CHCI2009）、第5屆全國普適計算學(xué)術(shù)會議（PCC2009）論文集[C];2009年

8 楊s，

本文編號：1797055