Grey target theory based equipment condition monitoring and wear mode recognition

Chen, Shiwei; Li, Zhuguo; Xu, Qiu

doi:10.1016/j.wear.2005.02.085

Cited by 40 publications

(13 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The top mode relative to the 'bull's-eye' is labeled as the upper edge of the gray target, whereas the bottom mode is called the lower edge of the gray target. The gray relational degree of the bull's-eye and of every pattern in gray relational information difference space is termed the approaching degree [15,16].…”

Section: Gray Target Theorymentioning

confidence: 99%

Application of gray target models in the prediction of coal and gas outburst: the case of jinzhushan coal mine in China

Hu¹,

Peng²,

Xu³

et al. 2015

Int. J. SAFE

View full text Add to dashboard Cite

Coal and gas outbursts in coal mines are a complex dynamic geological phenomenon. A gray target model has been established based on the gray system theory to predict coal and gas outbursts. The model considers four influencing factors for coal and gas outbursts: gas pressure, destructive type of coal, coal rigidity, and initial speed of methane diffusion. Each weight of the factors is given through an improved analytic hierarchy process without consistency checks, and the accuracy of the assessment is high. By using the model, coal and gas outbursts in the Jinzhushan mine were predicted. Results demonstrate the viability of the gray target model in the prediction of coal and gas outbursts.

show abstract

Section: Gray Target Theorymentioning

confidence: 99%

Application of gray target models in the prediction of coal and gas outburst: the case of jinzhushan coal mine in China

Hu¹,

Peng²,

Xu³

et al. 2015

Int. J. SAFE

View full text Add to dashboard Cite

show abstract

“…Ferrography is used to quantify the amount of wear particle within a given oil sample and to conduct microscopic analysis of that debris in order to identify its size, shape and colors of engine parts. [7].…”

Section: Introductionmentioning

confidence: 99%

diagnosis of the condition of components of si engine using wear particles monitoring

2017

IJLTET

View full text Add to dashboard Cite

“…However, the reliability of the monitoring data requires further verification through an industrial experiment. Chen et al 17 developed the grey target theory and derived trend features for oil monitoring data to make predictions. This method relies on accurate, reliable, and continuous monitoring data.…”

Section: Introductionmentioning

confidence: 99%

Correction strategies of debris concentration for engine wear monitoring via online visual ferrograph

Cao

Dong

Chen

et al. 2015

Proceedings of the Institution of Mechanical Engineers, Part J:

View full text Add to dashboard Cite

Changing or replenishing the oil in an engine influences the accuracy of oil monitoring. An online visual ferrograph (OLVF) was used to monitor engine wear in this study. The variation in the debris concentration in an engine lubrication system was studied, and its equilibrium concentration of debris was determined to correct the data acquired using an OLVF after fresh oil was added to the system. This correction made the monitoring data of OLVF continuous, thereby enabling the raw data collected before and after oil replenishment to be compared. Changing the oil caused an interruption in the raw data. By combining different prediction modes, a comprehensive trend prediction framework was constructed to correct the data acquired after the engine's oil was changed. Thus, the data acquired before and after the oil change could be analysed and compared. In addition, the engine's whole wear trends could be observed. This correction strategy could also be used to assess the engine's health and to predict its degradation trend.

show abstract

Grey target theory based equipment condition monitoring and wear mode recognition

Cited by 40 publications

References 16 publications

Application of gray target models in the prediction of coal and gas outburst: the case of jinzhushan coal mine in China

Application of gray target models in the prediction of coal and gas outburst: the case of jinzhushan coal mine in China

diagnosis of the condition of components of si engine using wear particles monitoring

Correction strategies of debris concentration for engine wear monitoring via online visual ferrograph

Contact Info

Product

Resources

About