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Fault diagnosis method and system of monitoring system and electronic equipment

A monitoring system and fault diagnosis technology, which is applied in neural learning methods, character and pattern recognition, construction, etc., can solve problems such as component failures, abnormal waveforms of moving liquid surfaces, etc., achieve accurate classification results, ensure comprehensive efficiency and yield effect

Inactive Publication Date: 2022-08-09
上海珪舸科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] In order to obtain real-time data, the oil well dynamic liquid level monitoring system runs for a long time, which will lead to component failures and abnormalities in the collected dynamic liquid level waveforms

Method used

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  • Fault diagnosis method and system of monitoring system and electronic equipment
  • Fault diagnosis method and system of monitoring system and electronic equipment
  • Fault diagnosis method and system of monitoring system and electronic equipment

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Embodiment Construction

[0050] Hereinafter, exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application, and it should be understood that the present application is not limited by the example embodiments described herein.

[0051] Scenario overview

[0052] As mentioned above, in order to obtain real-time data, the oil well dynamic liquid level monitoring system will run for a long time, which will lead to component failure, and the collected dynamic liquid level waveform will be abnormal. Therefore, the fault diagnosis of oil well dynamic liquid level monitoring system is an essential work. Therefore, a fault diagnosis method of the monitoring system is expected to accurately judge the fault type of the dynamic liquid level of the oil well, so as to ensure the comprehen...

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Abstract

The invention relates to the field of fault diagnosis of working fluid levels, and particularly discloses a fault diagnosis method and system of a monitoring system and electronic equipment. Furthermore, global associated feature extraction is carried out on the multiple pieces of frequency data and phase data of each time point based on a context encoder model, and deep abstract feature mining is carried out on the input matrix through a convolutional neural network after two-dimensional arrangement. Therefore, the feature maps of the two can be fused, so that the classification result is more accurate. In this way, the fault type of the working fluid level of the oil well can be accurately judged, and therefore the comprehensive efficiency and yield of oil well exploitation are guaranteed.

Description

technical field [0001] The present invention relates to the field of fault diagnosis of dynamic liquid level, and more particularly, to a fault diagnosis method, system and electronic device of a monitoring system. Background technique [0002] In the process of oil well production, the maximization of production and overall efficiency is the ultimate goal, and the fluid supply capacity of the formation is the fundamental factor restricting the realization of this goal. The dynamic liquid level of an oil well is an important indicator reflecting the liquid supply capacity of the formation, and it is an important basis for the oilfield to determine a reasonable subsidence degree and formulate a reasonable working system. Through the analysis of the dynamic liquid level, the pump depth is determined and the bottom hole flow pressure is calculated; according to the change of the dynamic liquid level, the matching of the working system of the oil well and the formation energy is...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08E21B47/047
CPCG06N3/08E21B47/047G06N3/047G06N3/048G06N3/045G06F2218/08G06F2218/12G06F18/2415G06F18/241G06F18/253
Inventor 王冰
Owner 上海珪舸科技有限公司