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Monitoring method of abnormal working condition of pumping unit

A technology for abnormal working conditions and pumping units, which is applied in the field of industrial system working condition monitoring, can solve problems such as low fault detection performance, and achieve the effects of improving fault detection results, improving monitoring capabilities, and overcoming poor monitoring performance.

Active Publication Date: 2022-07-12
CHINA UNIV OF PETROLEUM (EAST CHINA)
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Problems solved by technology

[0004] The present invention provides a method for monitoring abnormal working conditions of pumping units, aiming at the problems of ignoring the probability information in the process information in the traditional KPCA method, resulting in low fault detection performance.

Method used

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  • Monitoring method of abnormal working condition of pumping unit
  • Monitoring method of abnormal working condition of pumping unit
  • Monitoring method of abnormal working condition of pumping unit

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Experimental program
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Embodiment

[0153] Rod pump oil pumping (hereinafter referred to as: SRP) system is the main unit of oil extraction and is widely used in the oil extraction industry. see figure 2 , SRP system consists of motor 1, connecting rod 2, beam 3, oil pump and other components. When the system is running, the power generated by the motor 1 makes the sucker rod 5 reciprocate up and down through the connecting rod 2, the traveling beam 3 and the suspension rope 4, and then transmit the power to the downhole part. On and off, the liquid in the well continuously enters the pump barrel 10, thereby ascending into the oil pipe 6, and finally reaching the surface. During the operation of the pumping unit, the dynamometer diagram is the most common means of collecting status data. In this example, the feature extraction of the dynamometer diagram is carried out according to the gravity center decomposition method and the valve working position, and 7 dynamometer diagram features are collected as monito...

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Abstract

The invention relates to a method for monitoring abnormal working conditions of a pumping unit. The steps are: collecting the dynamometer data of the pumping unit under normal operating conditions as training data, after normalizing the training data, using the KPCA method to extract nonlinear features from the pumping unit training data as a kernel component, Considering the first derivative of the probability density function of the nuclear component and combining with KLD, the training KLD component is obtained, and the statistics are calculated based on the training KLD component and the corresponding control limit is determined; KPCA was used to extract the corresponding kernel components, and the online KLD components of the test data were further calculated. Statistics were calculated based on the online KLD components, and the control limits were used for monitoring. The invention introduces KLD into the traditional KPCA method, and makes full use of the probability information contained in the process data of the pumping unit to improve the monitoring capability of the abnormal working condition of the pumping unit.

Description

technical field [0001] The invention belongs to the technical field of industrial system working condition monitoring, and in particular relates to a method for monitoring abnormal working conditions of a pumping unit. Background technique [0002] The pumping unit is the main device for oil extraction and plays an important role in the oil extraction industry. Since most pumping units operate in harsh environments, there are usually different faults that lead to the deterioration of the safety of the pumping units and the reduction of production profits. Therefore, it is necessary to monitor the pumping unit in real time to ensure the safe and stable operation of the oil extraction process. In the field of pumping unit fault diagnosis, dynamometer diagram is the most commonly used tool. Based on the dynamometer diagram, some methods for fault diagnosis of oil pumping unit have been developed and successfully applied, but these methods are essentially supervised learning me...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): E21B47/008E21B43/12
CPCE21B43/121E21B47/008
Inventor 邓晓刚蔡配配曹玉苹
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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