船舶柴油机在线油液监测传感器的安装设计

论述常见的在线水分/黏度/磨损颗粒量传感器的选取及设计安装.针对船舶柴油机干式和湿式润滑系统的特点,提出不同的在线油液监测传感器的设计安装方法,并进行试验研究.结果表明,按该方法设计安装的柴油机在线油液监测传感器测试稳定性好,不仅满足油液在线监测的取样要求,且大大降低了传感器加工安装的难度.     

油液在线监测传感器技术

油液在线监测是设备润滑磨损状态监测与实时诊断技术的重要发展方向,而监测仪器的开发与选择是这一故障诊断技术实现准确监测应用的关键。在对当前国内外油液磨损颗粒在线监测传感器、油质在线监测传感器、油液多信息集成在线监测仪器及应用技术介绍基础上,给予了当前油液在线监测传感器技术的相关评述,为油液在线监测技术的研究、应用及推广提供一定帮助。     

基于长期油液监测的海上钻采平台柴油机故障特点研究与对策

制定海上平台柴油机监测方案,通过对海上平台柴油机连续5年的监测与故障分析,在将近30%的监测样品中发现柴油机和所用油品的潜在故障,获得柴油机的主要故障特征,包括油液清净能力下降、柴油机进水、柴油机轴瓦异常磨损等故障,结合现场的设备运行维护情况,提出综合处理建议措施,包括现场正确换油用油、改善柴油机防水防尘密封、增加故障机组的监测频率等。     

基于网络的远程油液监测中心服务器端的功能设计

利用当前的油液监测和计算机网络等技术,设计和开发了基于网络的油液监测诊断中心服务器端部分功能。阐述了远程油液监测诊断中心的基本结构框架设计、系统各功能模块的划分和实现方法。     

重大机电设备润滑磨损故障诊断判据的研究

在油液监测的综合诊断方法中,诊断判据划分为理化检测项目的定量诊断判据和磨粒图库的定性诊断判据。在大量的油液监测数据和故障诊断案例的基础上,对传统的诊断判据界限值计算公式进行了修正,开发了相应的诊断判据计算和磨粒图库管理软件,研究制定了电力、钢铁、港口等10多个行业的30多种重大机电设备的油液监测诊断判据,并在油液监测的市场服务过程中取得了明显效果。     

船艇设备监测中的故障树分析

油液监测已成为机械设备故障诊断与状态监测的重要方法。通过油液监测中的光谱技术对船艇设备油液进行监测,运用故障树分析的方法分析故障源与成因,从机械故障诊断学角度分析故障原因以便对船艇进行更好的监测。     

油液监测技术在船舶主柴油机中的应用及其维修决策研究

本以4条港口作业船舶上的7台主柴油机为研究对象,开展了油液监测技术应用研究,并在油液监测的基础上建立了维修决策的模型,论还简要介绍了研究工作的主要内容和研究结果。     

工程机械诊断技术讲座第九讲油液分析与状态监测

油液分析技术包括油液本身物理化学性能分析和油液中不溶性物质的分析。润滑剂的性能与状态直接影响机器摩擦副的磨损状态,对磨屑与污染物的检测是监测摩擦副本身工作状态的手段。通过油液分析监测和诊断工程机械故障情况,无需拆机或安装传感器,易操作,信息量大,但需要有一个抽取油样和信息反馈的较严密的管理体系,还要建立一个数据库,以完成大量数据的处理和应用。 １．油液分析原理 利用油液分析技术进行工程机械状态监测与诊断的工作流程如图１所示。油液分析内容主要有以下５项。 （１）油液理化性能的监测 检测油的粘度、水分、…     

OMIS软件的设计与开发

把计算机技术于油液监测中，是这一监测方法的发展趋势。本文讨论了所研制的油液监测信息系统的设计原则和功能，阐述了系统中关于磨损状太怕描述方法与诊断规则。     

盾构机主轴承油液监测数据分析与阈值确定

油液监测是盾构机主轴承状态监测与故障诊断的重要手段之一,然而其现行诊断阈值多为经验数据,且对监测所得的大量数据缺乏系统性分析。为制定盾构机主轴承油液监测故障诊断的合理阈值,设计盾构机主轴承油液监测方案,提出油液监测的取样方法、取样周期及特殊情况下的取样周期,并获取大量油液监测数据;采用统计方法分析得出监测项目的基准值、警告值、危险值,与现行通过经验值制定的监测阈值指标吻合,从理论证明了现行监测阈值的合理性;采用线性回归法对掘进里程与监测数据进行回归分析,探寻各监测数据与掘进里程的关系,更合理地确定了主轴承在全生命周期里各阶段的监测阈值,与统计法计算出的阈值互为补充;通过相关性分析,得出油液监测中各项数据变化的内在联系,指出油液中水分含量为状态监测中首要控制因素。     

内燃机车机油光谱数据特征分析与故障诊断

机油光谱分析技术已广泛用于内燃机车柴油机的磨损状态监测 ,但是 ,受现场补换油不确定性的影响 ,光谱数据所反映的系统磨损信息受到严重干扰。本文以 DF4内燃机车机油光谱分析为对象 ,在研究补换油影响、样本总体分布、柴油机磨损机理的基础上 ,提出了分析柴油机主要摩擦付磨损状况的特征量 ,并将这些特征量用于实例分析     

Application of grey modeling method to fitting and forecasting wear trend of marine diesel engines

Oil monitoring is an important and useful method for predicting wear failure, and has been used in diesel engines successfully. The diesel engine is the key power equipment in ships and it is a complicated tribological system with uncertainty and indetermination. Grey system theory is suitable for systems in which some information is clear and some is not, so it is feasible to study the wear process of diesel engines with this theory. The unequal interval revised grey model (UIRGM) (1,1) is presented in this paper, which is applicable to original series with unequal intervals and sharp variation. The model that is built is applied to fit and predict element concentration as determined by oil spectrometric analysis. It is proved that UIRGM (1,1) determines the exact turning point, and the fitting and prediction results are acceptable.     

Ferrography applied to diesel engine oil analysis

Ferrography, developed over 10 years ago, has to date had restricted usage in the field of condition monitoring of diesel engines. A number of applications are illustrated where this technique has now been effectively utilized and reasons are also suggested for its restricted use in comparison with other existing techniques such as spectrographic oil analysis. Cases are also described where ferrography used in conjunction with spectroscopy has provided a powerful technique in the diesel engine condition monitoring field.     

Effects of refined palm oil (RPO) fuel on wear of diesel engine components

In this particular research work, the effects of refined palm oil (RPO), as alternative fuel, on wear of diesel engine components are assessed. Fleet testing is carried for the qualifying candidates diesel fuel replacement, i.e. 100% RPO fuel or 50% RPO and 50% conventional diesel fuel mixture. The base line of the fleet testing is using pure conventional petroleum diesel fuel as an energy source in one of the tested vehicles in the fleet. Analysis of used engine lubrication oil, taken when the oil was changed on the vehicles, was compared to the analysis of used oil samples pulled from 100% diesel fuel engines. The finding suggested that the pure RPO and RPO blended fueled engines were wearing at a normal rate.     

OIL MONITORING DIAGNOSTIC CRITERIONS BASED ON MAXIMUM ENTROPY PRINCIPLE

A method of applying maximum entropy probability density estimation approach to constituting diagnostic criterions of oil monitoring data is presented. The method promotes the precision of diagnostic criterions for evaluating the wear state of mechanical facilities, and judging abnormal data. According to the critical boundary points defined, a new measure on monitoring wear state and identifying probable wear faults can be got. The method can be applied to spectrometric analysis and direct reading ferrographic analysis. On the basis of the analysis and discussion of two examples of 8NVD48A-2U diesel engines, the practicality is proved to be an effective method in oil monitoring.     

Optimization of ferrographic oil analysis for diesel engine wear monitoring

An experimental investigation of the effectiveness of ferrographic methods applied to diesel engine wear monitoring was carried out. A series of car engines running in service were considered and the wear phenomena were studied on the basis of total particle density and large particle concentration trends determined through ferrographic analysis of oil samples.Results have shown that ferrography can be successfully used in this specific application.     

Ferrographic analysis of wear debris generated in locomotive diesel engines

A preliminary trial in which ferrography was applied to the condition monitoring of locomotive diesel engines is described in this paper. Typical particles generated by locomotive diesel engines are illustrated. Results of observations of those particles are discussed.     

Performance and emission studies on an agriculture engine on neat Jatropha oil

Diesel engines have proven their utility in the transportation, agriculture, and power sectors in India. They are also potential sources of decentralized energy generation for rural electrification. Concerns on the long-term availability of petroleum diesel and the stringent environmental norms have mandated the search for a renewable alternative to diesel fuel to address these problems. Vegetable oils have been considered good alternatives to diesel in the past couple of years. However, there are many issues related to the use of vegetable oils in diesel engine. Jatropha curcas has been promoted in India as a sustainable substitute to diesel fuel. This study aims to develop a dual fuel engine test rig for evaluating the potential suitability of Jatropha oil as diesel fuel and for determining the performance and emission characteristics of an engine with Jatropha oil. The experimental results suggest that engine performance using Jatropha oil is slightly inferior to that of diesel fuel. The thermal efficiency of the engine was lower, while the brake-specific fuel consumption was higher with Jatropha oil compared with diesel fuel. The levels of nitrogen oxides (NOx) from Jatropha oil during the entire duration of the experiment were lower than those of diesel fuel. The reduction of NOx was found to be an important characteristic of Jatropha oil as NOx emission is the most harmful gaseous emission from engines; as such, its reduction is always the goal of engine researchers and makers. During the entire experiment, carbon monoxide (CO), hydrocarbon (HC), and carbon dioxide (CO₂) emissions in the case of using Jatropha oil were higher than when diesel fuel was used. The higher density and viscosity of Jatropha oil causes lower thermal efficiency and higher brakespecific fuel consumption. The performance and emission characteristics found in this study are significant for the study of replacing diesel fuel from fossils with Jatropha oil in rural India, where the availability of diesel has always been a problem.     

A review of condition monitoring and fault diagnosis for diesel engines

Technical advances and environmental legislation in recent years have stimulated the development of a number of techniques for condition monitoring and fault diagnosis (CMFD) in diesel engines. This paper firstly summarises common faults, fault mechanisms and their effect on diesel engine performance. Corresponding measurands are presented. Standard CMFD methods for parameters and CMFD systems for diesel engines are reviewed. Finally, some advanced CMFD techniques, including neural networks and fuzzy logic, which may be more powerful, are discussed.