基于机油检测方法动车组内然机磨损分析系统研究

发布时间：2018-01-08 18:14

本文关键词：基于机油检测方法动车组内然机磨损分析系统研究　出处：《东北石油大学》2013年博士论文　论文类型：学位论文

【摘要】：机械磨损是工业设备的主要问题，而润滑油是减少磨损的重要介质，多年来建立磨损与润滑油之间的关系是一个主要研究课题，也是目前研究热点。机械磨损检测涉及很多化学化工领域，也是其重要的研究问题，多年来人们致力于检测润滑油形态、组分等来监测机械设备磨损情况，并且建立许多方法，通过润滑油变化来分析检测机器设备的磨损情况。本文以DF11型内燃动车组为研究目标，基于机油检测方法研究分析内燃机的磨损，通过分析机车状态和润滑油的形态组分来确定机油检测因子，建立适合于DF11型内燃机的机油数据系统，用于此型内燃动车组的日常检测的磨损状况，并建立LSSVR模型和线性回归模型来分析预测内燃动车组两动车数据，对于两动车的磨合磨损对比情况有着重要的意义。全文共分五部分：首先介绍了油液检测技术在内燃动车组磨合磨损中的作用，综述了机油油液分析中铁谱、光谱以及油液理化指标等进展情况。第二部分阐明了内燃机磨损的原理和实验的操作方法并结合分析铁谱、直读铁谱、光谱、机油理化指标等建立了数学线性回归模型，通过内燃动车组各个动车在相同走行公里数的情况下光谱中各个元素的数值进行对比来推测判断各个动车的磨损速率情况；通过跟踪两车在某走行区段内直读铁谱中大、小磨粒的数值进行趋势图对比情况，可判断两动车的磨损严重程度。并利用最小二乘支持向量回归法对内燃动车组两动车的磨损情况建模，，对两动车的拟合差值进行了分析，预测结果与实际运行结果一致。第三部分对内燃动车组机油的检测进行了系统总体的设计，运用Delphi7软件实现了两动车柴油机基本信息查询、磨合油基本信息查询、润滑油基本信息查询、修程信息查询和柴油机性能参数数据查询等功能。第四部分对内燃动车组油液的铁谱、光谱、颗粒计数器、常规理化指标等相关参数进行了计算机的分析和判定，通过内燃动车组两动车的直读铁谱中大磨粒和小磨粒的测定，并赋予公式运算，对比了各个动车的总磨损量、磨损严重度、磨损严重度指数、累积磨损量、累积磨损严重度、铁谱大磨粒百分数、铁谱小磨粒百分数等。对两动车柴油机油理化指标中粘度、闪点、石油醚不溶物、碱、水痕量的测定对比可判断各动车的机油使用状态。第五部分通过对国产“新曙光”号内燃动车组、“跨越”号内燃动车组机车的相关数据进行跟踪，结合铁谱、光谱、物理和化学指标等，运用Delphi7软件辅助分析得到了同一坐标系中光谱和铁谱磨损线性回归对比图，并对两动车在某段走行区段内的磨损速率和磨损严重情况做了定量对比值的运算，对内燃动车组两动车的磨合磨损趋势进行了验证。
[Abstract]:Mechanical wear is the main problem of the industrial equipment, and lubricating oil is an important medium to reduce wear, the relationship between the years to build up wear and lubricating oil is a major research topic, is the current research focus. The mechanical wear testing involves a lot of chemistry and chemical engineering is an important research problem for many years, people committed to the detection of lubrication oil form, component to monitor the mechanical wear, and established many methods, to analyze the wear detection equipment by lubricating oil changes.
This paper takes DF11 type DMUs as the research object, analysis of internal combustion engine oil detection method based on the study of wear, to determine oil detection factor through morphological analysis of locomotive group state and lubricating oil, the establishment of oil data system suitable for DF11 type internal combustion engine, used to wear daily testing this type of DMUs, and the establishment of LSSVR model and linear regression model to analyze and predict the DMUs two car data, has important significance for the comparison of two train running in wear.
The full text is divided into five parts: the first introduces the oil detection technology in the role of DMUs in wear, summarized the oil liquid analysis of iron spectrum, spectrum and oil physical and chemical indicators of progress. The second part illustrates the operation principle and experimental method of engine wear and the combination of analytical ferrography, direct reading iron spectrum, spectrum, oil and other physical and chemical indicators to establish the mathematical model of linear regression, through numerical DMUs each in the same train traveling a few kilometers under the condition of the spectrum of each element were compared to estimate the judgment rate wear all train; by tracking the two car in a walking section in direct reading Ferrograph by contrast, trends of numerical particles, can determine the two train wear severity. And using the least squares support vector regression modeling method for wear of the group of two car DMUs, to Two Train fitting difference was analyzed. The prediction results and the actual operation results. Detection of the third part of the DMUs are oil system overall design, using Delphi7 software to achieve the basic information of the two car diesel engine running in the basic information query, oil, lubricating oil basic information query, information query and maintenance of diesel engine performance parameters for data query. The fourth part of the DMUs oil ferrography, spectroscopy, particle counter, relevant parameters of conventional physical and chemical indicators were analyzed and determined by computer, internal combustion determination of abrasive particles and the direct rail EMU EMU two spectrum, and gives the formula operation, compared to the total wear of each car, wear severity, wear severity index, the cumulative amount of wear, cumulative wear severity, ferrography abrasive large percentage, small grain percentage of iron spectrum. Physical and chemical indexes of viscosity, flash point two car diesel engine oil, petroleum ether insoluble, alkali, contrast determination of water traces each emu oil use judgment. The fifth part of the domestic "new dawn" DMUs, "crossing" DMUs locomotive related data tracking. Iron binding spectrum, spectrum, physical and chemical indicators, the use of Delphi7 aided analysis software has been wear linear regression comparison of spectra and iron in the same coordinate system, and the two train at a walk for wear rate and wear section made of quantitative ratio calculation, the wear trend two car DMUs are verified.

【学位授予单位】：东北石油大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：U266.1;TH117

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