%0 Journal Article
%T Research on Feature Extraction of Indicator Card Data for Sucker-Rod Pump Working Condition Diagnosis
%A Yunhua Yu
%A Haitao Shi
%A Lifei Mi
%J Journal of Control Science and Engineering
%D 2013
%I Hindawi Publishing Corporation
%R 10.1155/2013/605749
%X Three feature extraction methods of sucker-rod pump indicator card data have been studied, simulated, and compared in this paper, which are based on Fourier Descriptors (FD), Geometric Moment Vector (GMV), and Gray Level Matrix Statistics (GLMX), respectively. Numerical experiments show that the Fourier Descriptors algorithm requires less running time and less memory space with possible loss of information due to nonoptimal numbers of Fourier Descriptors, the Geometric Moment Vector algorithm is more time-consuming and requires more memory space, while the Gray Level Matrix Statistics algorithm provides low-dimension feature vectors with more time consumption and more memory space. Furthermore, the characteristic of rotational invariance, both in the Fourier Descriptors algorithm and the Geometric Moment Vector algorithm, may result in improper pattern recognition of indicator card data when used for sucker-rod pump working condition diagnosis. 1. Introduction The sucker-rod pump system is the most widely used form of artificial lift for the onshore oil well production [1¨C3]. Approximately, 80% of the oil wells in the world, 90% of those in China, are being produced by the sucker-rod pumps [4, 5]. The maintenance and optimization of a sucker-rod pump system is a costly and time-consuming operation. The indicator card is the relation curve between the load and the displacement of a sucker-rod pump in an intact suck cycle, in which -axis represents displacement and -axis represent load [6]. The indicator card is helpful to analyze the down-hole working condition of the sucker-rod pump wells [7], which can judge the operation condition of the sucker-rod pump well and provide reliable proof of high efficiency, reasonable exploitation for the oil well production. While the system is operating, the card can indicate such shape that might be a normal operation or a fault situation. According to different kinds of real-time indicator card data, the pattern recognition and fault diagnosis techniques are used to identify some different curve shapes, locate which kind of abnormal situation is, and interpret why the fault occurs [8]. Therefore, the correct and quick identification of the sucker-rod pump indicator card is essential to the fault diagnosis of down-hole working condition. The automatic fault diagnosis of sucker-rod pump working condition is a visual interpretation process [9]. Nowadays, the traditional methods of interpretation are not suitable for the automatic fault diagnosis of the down-hole conditions. And several signal processing methods, such as
%U http://www.hindawi.com/journals/jcse/2013/605749/