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Pump valve fault detection method

A technology for fault detection and pump valves, applied in pump testing, neural learning methods, liquid variable capacity machinery, etc., can solve the problems of incomplete consideration of the model index system, single prediction method, and low prediction accuracy, and achieve practical application Strong performance, high prediction accuracy, and the effect of improving prediction accuracy

Pending Publication Date: 2022-04-29
YANTAI JEREH OILFIELD SERVICES GROUP
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Problems solved by technology

Relatively incomplete consideration of the algorithm model index system in related research, and the single prediction method, resulting in low prediction accuracy and other problems

Method used

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  • Pump valve fault detection method
  • Pump valve fault detection method
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Embodiment Construction

[0041]In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0042] Such as figure 1 As shown, according to a preferred embodiment of the present application, a pump valve fault detection method is provided, the method includes: constructing a pump valve fault index system (S101) reflecting the characteristics of the vibration signal of the pump valve state; using the LSTM depth model and Establishing an LSTM-AE model based on the principle of an autoencoder, and setting a fault discrimination threshold (S102); inputting training data into the LSTM-AE model based on the pump valve fault index system to train the LSTM-AE model (S103);...

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Abstract

The invention provides a pump valve fault detection method. The method comprises the following steps: constructing a pump valve fault index system reflecting the characteristics of vibration signals of a pump valve state; establishing an LSTM-AE model by using an LSTM depth model according to an auto-encoder principle, and setting a fault discrimination threshold value; inputting the training data into the LSTM-AE model based on the pump valve fault index system so as to train the LSTM-AE model; and detecting data of a pump valve to be detected are input into the trained LSTM-AE model based on the pump valve fault index system, an output value obtained by the LSTM-AE model is compared with a set fault judgment threshold value, and therefore whether the detected pump valve breaks down or not is judged, and a first judgment result is output. According to the method provided by the invention, the universality and accuracy of practical application of the model are improved.

Description

technical field [0001] The invention relates to the field of fault detection, in particular to a pump valve fault detection method. Background technique [0002] Reciprocating pumps such as plunger pumps are often complex in structure, have many sources of vibration signals, and are relatively difficult to detect and maintain. The suction valve and discharge valve are usually the most maintenance-requiring parts in the pump equipment. Valve failure is considered the leading cause of unplanned shutdowns in pumping equipment. At present, there have been some related technical researches on pump and valve fault detection, involving the construction of algorithm models through pressure signals, temperature signals, vibration signals, etc. for detection. Due to factors such as the high-pressure environment inside the pump body, it is difficult to install the sensor in the cylinder. Out-of-cylinder sensors usually capture signals through vibration signals and create algorithm m...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06N3/04G06N3/08F04B51/00G06F119/10
CPCG06F30/27G06N3/049G06N3/084F04B51/00G06F2119/10G06N3/044G06N3/045F16K37/0083
Inventor 王新梦王宗文李涛孙明华
Owner YANTAI JEREH OILFIELD SERVICES GROUP
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