67. Sectional normalization and recognization on the PV‑Diagram of reciprocating compressor

Jin-dong Wang1, Yi-qi Gao2, Hai-yang Zhao3, Rui Cong4

School of Mechanical Science and Engineering, Northeast Petroleum University, Daqing, 163318, China

3Corresponding author

E-mail: 1wjd327@126.com, 2gyq327@163.com, 3zhaohaiyang2003@126.com, 4congrui126@126.com

(Received 28 December 2014; received in revised form 24 February 2015; accepted 2 April 2015)

Abstract. The shortcomings of familiar normalization method on the PV‑Diagram of reciprocating compressor are analyzed in the paper. A sectional normalization method of the PV‑Diagram was put forward, and a recognizing technique of fault characteristics based on support vector machines for cylinder and piston system in reciprocating compressor is introduced. Four sections of curve in the PV-Diagram indicate four stages of a gas compression cycle. After the PV‑Diagram is normalized with the new method, the curvilinear curvatures are unchanged in comparison with the original diagram. The contour and shape relations between normal and fault state character curves are retained. The pressure signals collected from cylinder are normalized and treated as characteristic vectors, and the vectors are inputted into a multi‑class classifier composed of many support vector machines in order to classify fault modes. The experimental results show that the method can identify faults of the cylinder and piston system more correctly.

Keywords: reciprocating compressor, PV‑Diagram, normalization, support vector machine, fault diagnosis.

References

[1]        Wang J. D., Zhang J. Z., Yang J. Y. Technique to detect the gas pressure in cylinder of 2D12 reciprocating compressor. Compressor Technology, Vol. 5, 2002, p. 21‑23.

[2]        Zhang Z. S., Li L. J., He Z. J. Multi-fault classifier based on support vector machine and its applications. Mechanical Science and Technology, Vol. 23, Issue 5, 2004, p. 536‑537.

[3]        Cortes C., Vapnik V. Support vector networks. Machine Learning, Vol. 20, 1995, p. 273‑397.

[4]        Jiang A. N., Feng X. T. Case-based SVM method for maximal deformation forecasting of surrounding rocks of tunnels. Journal of Northeastern University (Natural Science), Vol. 25, 2004, p. 793‑795.

Cite this article

Wang Jin‑dong, Gao Yi‑qi, Zhao Hai‑yang, Cong Rui Sectional normalization and recognization on the PV‑Diagram of reciprocating compressor. Journal of Measurements in Engineering, Vol. 3, Issue 2, 2015, p. 35‑41.

 

Journal of Measurements in Engineering. June 2015, Volume 3, Issue 2
JVE International Ltd. ISSN Print 2335-2124, ISSN Online 2424-4635, Kaunas, Lithuania