CAJ | 학술논문

原子发射光谱是分析油液中微小磨损颗粒元素浓度的重要方法。作为一种非直接测量方法，油液光谱数据是车辆综合传动装置可靠性评估中的系统性能劣化的重要监测指标，可用于系统失效评估与剩余寿命预测。针对油液光谱数据这类型的一元劣化失效，随机过程尤其是 Wiener 过程模型具有良好的计算分析性质，在基于性能劣化的可靠性分析中应用日趋广泛。通过对车辆综合传动装置运行中的实时采样，共取得50个油液光谱样本。采用其中三种指示元素的线性回归方程来计算综合传动装置运行中每个瞬时的特征值与均值。基于正漂移 Wiener 过程，建立了综合传动装置的劣化失效预测模型，并基于 R 语言环境进行了随机微分方程的仿真与求解。得到了油液光谱中的 Fe，Cu 和 Mo 元素含量增长趋势的预测结果以及三种指示元素各自的首中时间。经比较，劣化失效周期的预测值较之条件维护时间延长了27 Mh（15．9％）。维护时间的延长，能够有效的减少全寿命周期内的维护次数，并最终降低维护成本。研究结果表明，该方法适用于综合传动装置的磨损与失效预测、全寿命周期费用与维护计划的优化。同时，也可推广至其他复杂机械系统的失效预测与评价等相关领域。
원자발사광보시분석유액중미소마손과립원소농도적중요방법。작위일충비직접측량방법，유액광보수거시차량종합전동장치가고성평고중적계통성능열화적중요감측지표，가용우계통실효평고여잉여수명예측。침대유액광보수거저류형적일원열화실효，수궤과정우기시 Wiener 과정모형구유량호적계산분석성질，재기우성능열화적가고성분석중응용일추엄범。통과대차량종합전동장치운행중적실시채양，공취득50개유액광보양본。채용기중삼충지시원소적선성회귀방정래계산종합전동장치운행중매개순시적특정치여균치。기우정표이 Wiener 과정，건립료종합전동장치적열화실효예측모형，병기우 R 어언배경진행료수궤미분방정적방진여구해。득도료유액광보중적 Fe，Cu 화 Mo 원소함량증장추세적예측결과이급삼충지시원소각자적수중시간。경비교，열화실효주기적예측치교지조건유호시간연장료27 Mh（15．9％）。유호시간적연장，능구유효적감소전수명주기내적유호차수，병최종강저유호성본。연구결과표명，해방법괄용우종합전동장치적마손여실효예측、전수명주기비용여유호계화적우화。동시，야가추엄지기타복잡궤계계통적실효예측여평개등상관영역。
The most common methodology used in element concentration measurement and analyzing of wear particles is Atomic emission (AE)spectroscopy.As an indirect measuring method,the oil spectral data is introduced to indicate the performance degradation and the residual life prediction in the reliability evaluation of Power shift steering transmission (PSST).Stochastic methods especially the Wiener process is convenient in solving and analyzing the unitary degradation failure indicated by the oil spectral data.The oil data have been sampled in the real operating condition,and the data set has more than 50 samples taken from PSST.The mean values and time-dependent characteristics of three indicating elements are statistically obtained by the line-ar regression analysis.The model of the degradation and failure prediction has been proposed based on the Wiener process with the positive drift.For modeling and simulation the software R was used.Therefore,the trend curves of diffusion process with their First Hitting Time have been predicted.Through comparison,the time intervals of condition-based maintenance have been extended as 27 Mh (15.9%).This will save the cost of maintenances by eliminate the preventive maintained cycles.The advan-tage and novelty of the outcomes presented in the article are that the stochastic process might be applied for predicting the degra-dation failure occurrence and also for optimizing the maintenance intervals and the cost-benefit.As might be expected,the meth-od can be extended to other cases of wear prediction and evaluation in complex mechanical system.