基于油液监测和灰色理论的变速箱磨损损伤评估及预测
发布时间：2018-12-14 17:46
【摘要】：变速箱作为工程机械的关键传动部件,其工作环境恶劣、载荷变化大、作业中循环动作频繁,从而导致故障频发。研究表明,80%的变速箱零部件都是因磨损而失效,又因为变速箱的关键零部件一般为无冗余设计,一旦发生故障往往引发严重的事故。因此,为了对变速箱的运行状态和磨损趋势有一个宏观、准确的把握,很有必要研究变速箱磨损损伤评估技术和磨损量预测方法,以实现对变速箱运行状态、磨损类型和磨损程度的监控与预测。本文以推土机变速箱为研究对象,基于油液监测技术和灰色系统理论研究变速箱磨损损伤评估技术和磨损量预测方法,主要研究内容如下:(1)基于油液监测技术进行了推土机变速箱磨损状态评估的实际试验研究。首先深入分析了变速箱的组成结构、主要磨损件、零部件构成元素和磨损磨粒特性,为应用油液监测技术进行变速箱磨损损伤评估奠定基础。之后,综合应用黏度分析、光谱分析和铁谱分析三种技术,对SD16型推土机变速箱内零部件的磨损状态和润滑油的污染情况进行了评估试验研究,所得结论与实际检修结果一致。该研究实现了变速箱磨损损伤部位、损伤类型、箱体密封情况以及油液润滑状态的判定,证明了油液监测技术实际应用的可行性与准确性。(2)建立了基于灰色GM(1,1)模型修正的变速箱磨损量灰色预测模型。选取推土机变速箱油液铁谱分析数据作为输入特征信息,综合考虑预测数据序列的非等间隔性、换油干扰等影响因素,在灰色预测理论中引入修正因子λ,建立修正的变速箱磨损量预测模型。经后验差法验证表明,该模型预测精度为一级精度。最后,逐步搜索最优λ值,实例分析表明,当λ=0.992时,修正后模型能实现三步准确预测,而原始灰色GM(1,1)预测模型只能实现一步准确预测,修正后模型提高了变速箱磨损量的预测精度。(3)设计并搭建了变速箱故障诊断试验台,并基于试验台在线黏度传感器研究了 15W40 CF-4型润滑油的黏温特性。为消除现场跟踪取样数据易随天气、推土机工作环境、操作人员水平等因素波动的影响,本文设计并搭建了变速箱故障诊断试验台。该试验台是通过润滑系统安装的在线黏度传感器来实时监测某一工况温度下油液的黏度,但该黏度并不是标准换油黏度。在实际工程应用中,需根据润滑油的黏温特性方程将某一温度的黏度转换成国家标准100℃时的换油黏度。为研究15W40 CF-4型润滑油黏温特性的变化规律,本文应用Andrade方程、Walther方程和Vogel方程对新油、在用油和废油在40℃～100℃时的运动黏度数据进行回归拟合,从拟合度和拟合标准差两个方面,分析和比较了3种黏温方程的拟合精度。分析表明,用Vogel方程来描述该润滑油的黏温特性更加准确,为在线监测的实时黏度换算提供了依据。
[Abstract]:As the key transmission part of construction machinery, the gearbox has a bad working environment, great load variation and frequent cyclic operation, which leads to frequent faults. The research shows that 80% of the gearbox parts fail because of wear and tear, and because the key parts of the gearbox are generally non-redundant design, once the fault occurs, it often leads to serious accidents. Therefore, in order to have a macroscopic and accurate grasp of the running state and wear trend of the gearbox, it is necessary to study the gearbox wear damage assessment technology and the method of predicting the wear quantity in order to realize the running state of the gearbox. Monitoring and prediction of wear type and wear degree. This paper takes the gearbox of bulldozer as the research object, based on the oil monitoring technology and the grey system theory, studies the gearbox wear damage assessment technology and the wear quantity forecast method. The main contents are as follows: (1) based on the oil monitoring technology, the actual experimental research on the evaluation of the wear status of the bulldozer gearbox is carried out. Firstly, the structure of gearbox, main wear parts, component elements and wear abrasive characteristics of gearbox are analyzed in depth, which lays a foundation for the application of oil monitoring technology to the gearbox wear damage assessment. After that, the wear status of parts in the gearbox of SD16 bulldozer and the pollution of lubricating oil are evaluated by using three techniques, viscosity analysis, spectrum analysis and ferrography analysis. The results are in agreement with the actual inspection and repair results. In this study, the gearbox wear damage location, damage type, sealing condition of the box and oil lubrication state are determined. The feasibility and accuracy of the application of oil monitoring technology are proved. (2) the grey prediction model of gearbox wear quantity based on grey GM (1t1) model is established. The iron-spectrum analysis data of bulldozer gearbox oil are selected as input characteristic information. Considering the influence factors such as the non-equal interval of prediction data sequence and oil exchange interference, the correction factor 位 is introduced into the grey prediction theory. A modified gearbox wear prediction model was established. The prediction accuracy of the model is proved to be a first order precision by a posteriori method. Finally, the optimal 位 value is searched step by step. The case analysis shows that the modified model can realize the three-step accurate prediction when 位 = 0.992, while the original grey GM (1 ~ 1) prediction model can only realize the one-step accurate prediction. The modified model improves the accuracy of the gearbox wear prediction. (3) the gearbox fault diagnosis test-bed is designed and built, and the viscosity and temperature characteristics of 15W40 CF-4 lubricating oil are studied based on the on-line viscosity sensor of the gearbox. In order to eliminate the influence of weather, bulldozer working environment and operator level on tracking sampling data, a gearbox fault diagnosis test-bed is designed and built in this paper. The on-line viscosity sensor installed in the lubricating system is used to monitor the viscosity of oil at a certain operating temperature in real time, but the viscosity is not the standard viscosity of oil exchange. In practical engineering application, the viscosity of a certain temperature should be converted into the oil exchange viscosity at 100 鈩，
本文编号：2379045
[Abstract]:As the key transmission part of construction machinery, the gearbox has a bad working environment, great load variation and frequent cyclic operation, which leads to frequent faults. The research shows that 80% of the gearbox parts fail because of wear and tear, and because the key parts of the gearbox are generally non-redundant design, once the fault occurs, it often leads to serious accidents. Therefore, in order to have a macroscopic and accurate grasp of the running state and wear trend of the gearbox, it is necessary to study the gearbox wear damage assessment technology and the method of predicting the wear quantity in order to realize the running state of the gearbox. Monitoring and prediction of wear type and wear degree. This paper takes the gearbox of bulldozer as the research object, based on the oil monitoring technology and the grey system theory, studies the gearbox wear damage assessment technology and the wear quantity forecast method. The main contents are as follows: (1) based on the oil monitoring technology, the actual experimental research on the evaluation of the wear status of the bulldozer gearbox is carried out. Firstly, the structure of gearbox, main wear parts, component elements and wear abrasive characteristics of gearbox are analyzed in depth, which lays a foundation for the application of oil monitoring technology to the gearbox wear damage assessment. After that, the wear status of parts in the gearbox of SD16 bulldozer and the pollution of lubricating oil are evaluated by using three techniques, viscosity analysis, spectrum analysis and ferrography analysis. The results are in agreement with the actual inspection and repair results. In this study, the gearbox wear damage location, damage type, sealing condition of the box and oil lubrication state are determined. The feasibility and accuracy of the application of oil monitoring technology are proved. (2) the grey prediction model of gearbox wear quantity based on grey GM (1t1) model is established. The iron-spectrum analysis data of bulldozer gearbox oil are selected as input characteristic information. Considering the influence factors such as the non-equal interval of prediction data sequence and oil exchange interference, the correction factor 位 is introduced into the grey prediction theory. A modified gearbox wear prediction model was established. The prediction accuracy of the model is proved to be a first order precision by a posteriori method. Finally, the optimal 位 value is searched step by step. The case analysis shows that the modified model can realize the three-step accurate prediction when 位 = 0.992, while the original grey GM (1 ~ 1) prediction model can only realize the one-step accurate prediction. The modified model improves the accuracy of the gearbox wear prediction. (3) the gearbox fault diagnosis test-bed is designed and built, and the viscosity and temperature characteristics of 15W40 CF-4 lubricating oil are studied based on the on-line viscosity sensor of the gearbox. In order to eliminate the influence of weather, bulldozer working environment and operator level on tracking sampling data, a gearbox fault diagnosis test-bed is designed and built in this paper. The on-line viscosity sensor installed in the lubricating system is used to monitor the viscosity of oil at a certain operating temperature in real time, but the viscosity is not the standard viscosity of oil exchange. In practical engineering application, the viscosity of a certain temperature should be converted into the oil exchange viscosity at 100 鈩，
本文编号：2379045
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