Grey target theory based equipment condition monitoring and wear mode recognition

Abstract Grey target theory is a newly developed method in grey system theory. Calculating with grey target theory, pattern recognition, mode gradation and optimal mode selection can be performed. Oil samples from one auto press line and one 16V280ZJA diesel engine were analyzed by analytical ferrograph. For every wear particle in every analytical result, the size and quantity were quantified together. And some corresponding series have been established. Grey target theory was applied and a “bull's-eye” was constructed. By calculating the approaching degrees, wear modes have been graded, in conjunction with the running conditions of the press line and the diesel engine for given operation modes. The order of existing wear modes from severe to benign has also been assessed. The results agree with the experts’ analysis. This is the first time that grey target theory has been applied in oil monitoring for wear mode recognition.

[1]  Anil K. Jain,et al.  Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Piotr Wojdyllo,et al.  Neuro-wavelet classifiers for EEG signals based on rough set methods , 2001, Neurocomputing.

[3]  Qinghua Zhang,et al.  Using wavelet network in nonparametric estimation , 1997, IEEE Trans. Neural Networks.

[4]  Professor Dr. Dr. h.c. Hermann Haken,et al.  Synergetic Computers and Cognition , 1991, Springer Series in Synergetics.

[5]  Ding You-ling.  INTERVAL ARITHMETIC BASED ON GRAY MODEL FOR FAULTS DIAGNOSIS , 2002 .

[6]  Edwin N. Cook,et al.  Automated segmentation and classification of multispectral magnetic resonance images of brain using artificial neural networks , 1997, IEEE Transactions on Medical Imaging.

[7]  Richard Alan Peters,et al.  A comparison of neural and statistical techniques in object recognition , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[8]  Sung-Whan Kim,et al.  Automatic detection of epileptiform activity using wavelet and expert rule base , 1998, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286).

[9]  Fei-Yue Wang,et al.  A Robotic Vision System for Object Identification and Manipulation Using Synergetic Pattern Recognition , 1993 .

[10]  M. Hanmandlu,et al.  Fuzzy logic based handwritten character recognition , 1997, Proceedings of International Conference on Image Processing.

[11]  Mo Jian.  Using Probabilistic Neural Network to Diagnose the Fault of Self-propelled Gun Engine , 2000 .

[12]  Dianhui Wang,et al.  Edge-preserving neural network model for image restoration , 2000, IWISPA 2000. Proceedings of the First International Workshop on Image and Signal Processing and Analysis. in conjunction with 22nd International Conference on Information Technology Interfaces. (IEEE.

[13]  N.B. Karayiannis,et al.  Fuzzy vector quantization algorithms and their application in image compression , 1995, IEEE Trans. Image Process..

[14]  Zhu Jun.  A Fuzzy Enhancement Based Approach to Image Segment , 1999 .

[15]  Ken-ichi Funahashi,et al.  Multilayer neural networks and Bayes decision theory , 1998, Neural Networks.

[16]  Michael Negnevitsky,et al.  Automatic disturbance recognition in power systems , 1998 .

[17]  Joon H. Han,et al.  A fuzzy K-NN algorithm using weights from the variance of membership values , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[18]  Qinghua Zhang,et al.  Wavelet networks , 1992, IEEE Trans. Neural Networks.

[19]  Thomas Brett Kirk,et al.  Wear particle classification in a fuzzy grey system , 1999 .

[20]  Li Chen,et al.  A fuzzy K-nearest-neighbor algorithm to blind image deconvolution , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[21]  Wang Hong.  The Grey Target Decision-making to Choose Weaving Machine , 2002 .

[22]  Zhao Yan.  Grey pattern recognition under the condition of uncertain information , 2003 .