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A machine learning-based prediction method for key indicators of water pumps

A technology of key indicators and machine learning, applied in the direction of machine/engine, instrument, pump control, etc., can solve the problems of high manpower, money and time costs, lack of accurate prediction of key indicators, and inability to finely control working conditions, etc., to achieve good results Effects on Model Performance

Active Publication Date: 2022-04-26
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

There are some problems in this kind of operation, such as the inability to respond to quantitative effects in a timely manner, the inability to finely control the working conditions, and the lack of accurate prediction of key indicators
Through the real-time monitoring of coal mill indicators and the regulation of equipment parameters manually, there will be high manpower, money and time costs

Method used

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  • A machine learning-based prediction method for key indicators of water pumps
  • A machine learning-based prediction method for key indicators of water pumps
  • A machine learning-based prediction method for key indicators of water pumps

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Embodiment Construction

[0025] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0026] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0027] Such as figure 1 As shown, the present invention provides a kind of water pump key index prediction method based on machine learning, comprises the following steps:

[0028] S1. Extract the daily work data...

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Abstract

The invention provides a method for predicting key indicators of water pumps based on machine learning. The relationship between indicators and other data builds a prediction model, and inputs the training set into the prediction model for model training and parameter adjustment, and evaluates the model; builds a test set, and predicts the key indicators of the water pump based on the test set and the prediction model , to guide the optimization of the working conditions of the key indicators of the pump. The present invention can accurately predict the state value of the key indicators of the water pump equipment according to the data generated during the working process of the water pump, and output the important characteristics affecting the key factors of the water pump, so as to guide the equipment staff to find the optimal working state.

Description

technical field [0001] The invention relates to the technical field of hydroelectric power generation, in particular to a method for predicting key indicators of water pumps based on machine learning. Background technique [0002] Water pumps are important equipment in thermal power plants, irrigation and drainage, and other industrial and agricultural production. Monitoring its key indicators, analyzing and predicting the development trend of operation can improve the working efficiency of the pump and ensure the normal operation of the equipment. [0003] At present, the field of water pump control mostly relies on traditional industrial control software to do some simulation prediction and monitoring of the entire control state. There are some problems in this kind of operation, such as the inability to respond to quantitative effects in a timely manner, the inability to finely control the working conditions, and the lack of accurate prediction of key indicators. Throug...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): F04B49/06G05B13/04
CPCF04B49/065G05B13/042
Inventor 曾丹姚文迪张亦驰
Owner SHANGHAI UNIV