Application of non-equal interval GM(1,1)model in oil monitoring of internal combustion engine

The basic difference non-equal interval model GM(1,1) in grey theory was used to fit and forecast data series with non-equal lengths and different inertias, acquired from oil monitoring of internal combustion engines. The fitted and forecasted results show that the length or inertia of a sequence affects its precision very much, i.e. the bigger the inertia of a sequence is, or the shorter the length of a series is, the less the errors of fitted and forecasted results are. Based on the research results, it is suggested that short series should be applied to be fitted and forecasted; for longer series, the newer datum should be applied instead of the older datum to be analyzed by non- equalinterval GM(1,1) to improve the forecasted and fitted precision, and that data sequence should be verified to satisfy the conditions of grey forecasting.

Study on Lubricating Oil Monitoring Technology

Lubricating oil monitoring has been proven to be an effective method for detecting and diagnosing machinery failures and essential for realizing condition based maintenance. In this paper, mathematical statistics methods for determining the oil parameters featuring machinery failures and the parameters＇ probability distribution functions and their thresholds are put forward.

OIL MONITORING DIAGNOSTIC CRITERIONS BASED ON MAXIMUM ENTROPY PRINCIPLE

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

Oil monitoring methods based on information theory

To evaluate the wear condition of machines accurately,oil spectrographic entropy,mutual information and ICA analysis methods based on information theory are presented. A full-scale diagnosis utilizing all channels of spectrographic analysis can be obtained. By measuring the complexity and correlativity,the characteristics of wear condition of machines can be shown clearly. The diagnostic quality is improved. The analysis processes of these monitoring methods are given through the explanation of examples. The availability of these methods is validated and further research fields are demonstrated.

Progress and trend of sensor technology for on-line oil monitoring

Oil monitoring constitutes an important and essential component of condition monitoring technologies and has distinguished advantages in revealing wear,lubrication and friction conditions of tribo-pairs.Newly developed on-line/in-line oil monitoring technologies extend the merits into real-time applications and demonstrate significant benefits in maintenance and management of equipment.This paper comprehensively reviews the progress of on-line/in-line oil monitoring techniques including sensor technologies,their scopes and industrial applications.Based on the existing developments and applications of the sensors for oil quality and wear debris measurements,the trends for future sensor developments are discussed with focuses on accurate,integrated and intelligent features along with exploring a fundamental issue,that is,acquiring the knowledge on degradation mechanisms which has not received sufficient attention until now.Current status of applications of on-line oil monitoring is also reviewed.Although limited reports have been found on this topic,increasing awareness and encouraging progress in on-line monitoring techniques are recognized in applications such as aircraft,shipping,railway,mining,etc.Key fundamental issues for further extending the on-line oil monitoring techniques in industries are proposed and they include long-term reliability of sensors in harsh conditions,and agreement with fault or maintenance determination.

Research on the Correlation Between Oil Menitoring and Vibration Monitoring in Information Collecting and Processing Monitoring

Oil monitoring and vibration monitoring are two principal techniques for mechanical fault diagnosis and condition monitoring at present. They monitor the mechanical condition by different approaches, nevertheless, oil and vibration monitoring are related in information collecting and processing. In the same mechanical system, the information obtained from the same information source can be described with the same expression form. The expressions are constituted of a structure matrix, a relative matrix and a system matrix. For oil and vibration monitoring, the information source is correlation and the collection is independent and complementary. And oil monitoring and vibration monitoring have the same process method when they yield their information. This research has provided a reasonable and useful approach to combine oil monitoring and vibration monitoring.

Information Fusion of Online Oil Monitoring System Using Multiple Sensors

Machine lubrication contains abundant information on the equipment operation. Nowadays, most measuring methods are based on offline sampling or on online measuring with a single sensor. An online oil monitoring system with multiple sensors was designed. The measurement data was processed with a fuzzy intelligence system. Information from integrated sensors in an oil online monitoring system was evaluated using fuzzy logic. The analyses show that the multiple sensors evaluation results are more reliable than online monitoring systems with single sensors.

Application of the quantitative oil monitoring to analysing the operating condition of marine machinery

Based on the data of Fourier transform infra-red (FTIR) spectroscopy, spectrometric oilanalysis (SOA) and other routine methods, the experiment of oil monitoring for steering propellersis discussed. The experiment demonstrates the FTIR spectroscopy can rapidly and easily obtainthe results in laboratory analysis, and combine with spectrometer oil analysis, complementary in-formation is most effective to condition monitoring of marine machinery.

On-line monitoring of dissolved gas-in-oil with FTIR spectra

To overcome the disadvantages of conventional DGA (dissolved gas-in-oil)analysis using gas chromatography and other electrochemical sensors, initial researches werecompleted to realize on-line monitoring of dissolved gas-in-oil of power transformers using FTIR(Fourier Transform InfraRed) spectroscopy. Gas cell method is used to determine the characteristicabsorption peaks of each diagnostic gas; simple and novel devices and procedures were designed inorder to get measurable samples and spectra of mixed diagnostic gases with known concentration aretaken using long optical path gas cell. The range of wavelength is estimated to be 3.0-13.9 mum fromexperimental spectra data. Hence the corresponding sampling frequency range should be in 536-4288Hz and usable optical materials are suggested. It is concluded that a resolution of 10 cm^(-1) maywell satisfy the monitoring of all diagnostic gases and water content except hydrogen, and thelowest detection limit may be as low as 2Xl0^(-8) to acetylene with a 2.4-meter-long optical length.

Analysis of condition monitoring methods for electromotor on oil platform

Electromotor on oil platform often has mechanical failures.In order to achieve monitoring and diagnosis of the electromotor,common diagnostic methods of electromotor are summarized first,and then vibration monitoring is regarded as a suitable method for monitoring and diagnosing of mechanical failures by comparing the advantages and disadvantages of each method and characteristics of mechanical faults.At last,the fault frequencies and arrangements of vibration measuring points are analyzed.By using vibration monitoring method,the diagnosis of bearing faults of electromotor is carried out.The results show that the analysis of condition monitoring methods for electromotor is meanning for machine maintenance and repair,and it lays foundation for computerized repair system and resource management system.

Method of Phase Diagrams for the Analysis of Seism-Acoustical Spatial-Time Monitoring Data in Oil Wells

Experimental and theoretical studies of the mechanisms of vibration stimulation of oil recovery in watered fields lead to the conclusion that resonance oscillations develop in fractured-block formations. These oscillations, caused by weak but long-lasting and frequency-stable influences, create the conditions for ultrasonic wave’s generation in the layers, which are capable of destroying thickened oil membranes in reservoir cracks. For fractured-porous reservoirs in the process of exploitation by the method of water high-pressure oil displacement, the possibility of intensifying ultrasonic vibrations can have an important technological significance. Even a very weak ultrasound can destroy, over a long period of time, the viscous oil membranes formed in the cracks between the blocks, which can be the reason for lowering the permeability of the layers and increasing the oil recovery. To describe these effects, it is necessary to consider the wave process in a hierarchically blocky environment and theoretically simulate the mechanism of the appearance of self-oscillations under the action of relaxation shear stresses. For the analysis of seism acoustic response in time on fixed intervals along the borehole an algorithm of phase diagrams of the state of many-phase medium is suggested.

A Dual-Parameter Fusion Distributed Optical Fiber Sensor System for Oil and Gas Pipeline Monitoring

For oil and gas pipeline monitoring applications, this paper proposed a dual-parameter fusion distributed fiber optic sensor system that enables distributed temperature and distributed vibration measurements in a single fiber. Through the fiber-scattering spectrum time domain detection combined with coded pulse sequence and Raman scattering spectrum is obtained, which realizes high-resolution temperature measurement and wide-band vibrational wave measurement. The experimental results show that, on 10 km optical fiber measurement, temperature resolution up to 0.1?C and vibration response frequency range 20 Hz - 5 kHz. This sensing system achieves temperature and vibration dual-parameter measurements with fiber optics, greatly simplifying the system and facilitating installation and it can be widely used in oil and gas pipeline monitoring.

基于油液分析的航空发动机健康评估方法研究

被称为飞机“心脏”的航空发动机对飞机的正常运行起着至关重要的作用,为更加科学准确地评估航空发动机的运行状态,本文提出了一种改进综合赋权法的评价模型。以光谱分析法、铁谱分析法、理化分析法等3种方法获取的油液指标为前提,建立了基于油液分析的航空发动机的状态评估体系;通过三标度层次分析法和CRITIC法对指标进行主客观赋权,采用改进的基于博弈论的组合赋权法来求取各个指标的权重,从而获得相对健康度,对飞机运行状态做出评价。结果表明,改进后的博弈论组合赋权法比传统的博弈论组合赋权法更适用于油液指标的权重分配,并且该方法评价的结果符合实际情况,可以为视情维修提供依据。

动车组齿轮箱油中硫含量的红外光谱分析

针对高铁动车组牵引系统中齿轮箱润滑油中硫元素损失较快的问题,需要对在用齿轮油硫含量进行监测,以确定最佳的换油时机。分析了红外光谱图中齿轮油含硫添加剂特征吸收峰的衰减机制;选择与硫含量相关性最高的1164 cm-1特征峰的峰高作为输入变量构建了一元线性回归模型(LR),采用5折交叉验证下的测试集R^(2)确定最佳主成分个数构建了偏最小二乘回归模型(PLSR),最后根据偏最小二乘回归系数优选了6个特征吸收峰用于构建特征峰优化后的PLSR模型(RF-PLSR)。采用所建的模型分别对预测集39个油样进行预测,结果表明一元线性回归模型和偏最小二乘回归模型均具有很好的预测能力。一元线性回归模型的预测R^(2)为0.961,RMSE为973.1,RPD为5.084。PLSR模型和特征峰优化后的RF-PLSR模型的预测R^(2)分别为0.997和0.994,RMSE分别为250.1和376.3,RPD分别为19.780和13.149。说明经过特征峰优化后建立的RF-PLSR模型在降低模型复杂度的同时,仍可以保持较高的精度和预测能力,由于消除了不相关变量的信息,使模型的可解释性更好。红外光谱技术为齿轮油中硫含量的检测提供了一种可靠而精确的方法,为齿轮油的状态监测提供一种可行的解决方案。

终聚减速机在线监测技术的应用及优化

在聚酯装置中,终聚减速机齿轮箱输出轴转速小于3 r/min,采用振动检查方法,很难检测出轴承故障信号,无法通过噪音和温度变化发现齿轮箱低速轴轴承故障。结合一起终聚减速机齿轮箱故障实例,通过优化状态检测方法,及时发现齿轮箱存在的严重隐患,实现设备的预知性检修。

海上平台生产水水质多参数在线监测系统

从海上平台对水质监测的实际需求出发,结合海上平台作业环境,自主研发了一套耐腐蚀、集成度高、具备自动清洗功能的海上平台生产水水质多参数在线监测系统DC-01。30 d的连续监测试验结果表明,该系统运行稳定,可准确测定水质6项参数。DC-01与标准方法(《油田水分析方法》(SY/T 5523—2016))对水中油、悬浮物、溶解氧、总铁、硫化物和pH测定结果的相关系数分别为0.996、0.997、0.965、0.999、0.999和0.963,相对误差在±10%以内。该监测系统大幅缩短了水质分析时间,具有测量精度高、检测效率高、可实时上传监测数据等优点,同时自动清洗功能保证了系统的长期稳定运行,可满足监测海域使用要求。

基于KNN的水电站水轮机监控系统研究

针对大型水轮机轴承故障诊断和预警准确率低,导致抽水蓄能电站存在状态监测与运维管理效果不佳的问题,提出一种大型水轮机轴承润滑油液在线监测系统。利用电涡流传感器对轴承油液数据采集,采用改进的K最近邻算法对轴承故障进行准确分类与诊断。结果表明,通过改进KNN算法,得到新故障与集合A中故障识别球的相似度最大值为0.4787,低于相似度匹配阀值0.6,说明改进KNN算法可实现新故障类型的准确识别,具备一定的自适应性和可扩展性;实际应用也进一步证明该算法可满足对水轮机轴承的状态监测、故障诊断和预警需求,实现水电站的准确监测和智能化运维管理。

光声光谱法油中溶解气体自动化监测装置高烃干扰消除技术研究

油浸式变压器内部过热或放电产生烯烃、烷烃类气体溶于绝缘油,监测这些气体对诊断变压器故障至关重要,但丙烷、丙烯等C_(3)类高烃气体会干扰油中溶解气体监测装置对C_(1)、C_(2)低烃类气体的准确检测。基于光声光谱技术原理,设计了一种C_(3)类高烃气体过滤装置能可靠分离混合气体中的C_(3)类高烃气体,并具备过滤柱自修复、自清理功能。实验证明,装置能有效消除干扰,甲烷、乙烷、乙烯测量误差、重复性及最小检测浓度均满足标准要求。

电磁耦合智能分层采油技术

针对现有分层采油工艺技术存在的不适应检泵作业、有效工作寿命短、通讯可靠性差等问题,提出了电磁耦合智能分层采油技术,研制了核心工具及配套工具,并开展了现场试验。采用生产和配产管柱分离的丢手管柱结构,当两管柱在井下对接后,利用电磁耦合原理实现管柱间电能与信号的近距离无线传输,为井下多个智能配产器供电,并实现双向通讯。研制了适应井下复杂工况的电磁耦合传能与通讯装置、智能配产器、地面控制器等核心工具,以及大通径丢手锚定器、油井过电缆封隔器等配套工具,实现了技术定型。在大庆油田完成10口井现场试验,两管柱井下对接快捷、可靠,电磁耦合传能与通讯装置工作稳定,实现了井下分层流量、压力、温度的实时监测和分层产液量调控,提高了储层认识程度,取得了增油、降含水的生产实效。

临近煤矿工作面油气井泄漏监测方法研究

为了研究煤矿工作面附近油气井泄漏情况,采用对比分析法,在煤矿工作面附近的油气井、井下工作面附近巷道和采空区中采集了一定量的气体样品,进行了气体组分研究和碳同位素分析研究。研究表明,在试验区域,通过气体组分难以判断油气井是否向煤矿工作面发生泄漏;甲烷碳同位素值测定方法为临近煤矿工作面的油气井泄漏监测的有效技术。