Centrifugal pump performance curve sample acquisition method and its application in machine learning

An acquisition method and centrifugal pump technology, applied in nuclear methods, special data processing applications, instruments, etc., can solve problems such as short calculation time and large calculation amount of performance prediction model, achieve short calculation time, reduce performance test cost, and speed up The effect of the design process

Active Publication Date: 2022-05-24
CHINA JILIANG UNIV
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  • Abstract
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Problems solved by technology

[0005] In view of the lack of samples of the performance prediction model of the existing centrifugal pump and the large amount of calculation of the performance prediction model, the present invention proposes a method for obtaining the performance curve sample of the centrifugal pump, which can be calculated based on a single known performance parameter Obtaining the other two performance parameters can greatly reduce the difficulty of obtaining a complete centrifugal pump performance curve training sample. On this basis, this method is combined with a machine learning model to propose a performance prediction method for centrifugal pumps. Based on the geometric parameters of the centrifugal pump, the corresponding performance parameters can be quickly obtained, the calculation time is short, and the implementation is convenient

Method used

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  • Centrifugal pump performance curve sample acquisition method and its application in machine learning
  • Centrifugal pump performance curve sample acquisition method and its application in machine learning
  • Centrifugal pump performance curve sample acquisition method and its application in machine learning

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Experimental program
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Effect test

Embodiment 1

[0079] Step 1: Data acquisition of head performance curve.

[0080] Collect 10 sets of lift curves of single-stage single-suction clean water centrifugal pumps with different specific speeds, and each lift curve takes the performance of 14 to 20 working conditions.

[0081] Step 2: Power and efficiency curve formula modeling.

[0082] According to the relationship between the power and efficiency performance curves and the flow rate, the formulas of the power and efficiency performance curves are modeled. The specific modeling formulas are:

[0083]

[0084]

[0085] in Q for the flow, Q N is the rated flow, P , n , H represent power, efficiency and head, respectively, k 1 , b is the coefficient of the power formula. k 2 , c is the coefficient of the efficiency formula.

[0086] Step 3: Based on the calculation formula between the three performance parameters and the simplified formula of power and efficiency in Step 2, calculate the calculated value of the...

Embodiment 2

[0107] Step 1: Obtain power performance curve data.

[0108] Collect 10 sets of power curves of single-stage single-suction clean water centrifugal pumps with different specific speeds, and each power curve takes the performance of 14 to 20 working conditions.

[0109] Step 2: Formula modeling of lift and efficiency curves.

[0110] According to the relationship between the head and the efficiency performance curve with the flow rate, the formula of the head and efficiency performance curve is modeled. The specific modeling formula is:

[0111]

[0112]

[0113] in Q for the flow, Q N is the rated flow, H , n represent head and efficiency, respectively, k 3 , d is the coefficient of the lift formula. k 2 , c is the coefficient of the efficiency formula.

[0114] Step 3: Based on the calculation formula between the three performance parameters and the simplified formula of the lift and efficiency in Step 2, calculate the calculated value of the change of powe...

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Abstract

The invention discloses a centrifugal pump performance curve sample acquisition method and its application in machine learning. The method first collects the data of one of the performance parameters of various centrifugal pumps changing with the flow rate; Modeling to obtain the simplified formula of the unknown performance parameters; then based on the relationship between the performance parameters and the simplified formula of the unknown performance parameters, the calculated value of the known performance parameters is calculated; finally, the real value of the known performance parameters and the calculated value The mean square error is used as the objective function of the differential evolution optimization algorithm to optimize the coefficients of two unknown performance parameter calculation formulas; finally, the unknown performance parameter values ​​under different flow rates are calculated. This method can quickly and conveniently obtain a large number of performance parameter samples. The method is further combined with the machine learning model, and the performance prediction results of different centrifugal pumps can be obtained based on the geometric parameters of the centrifugal pump. The calculation time is short and the implementation is convenient, thereby speeding up the research and development progress.

Description

technical field [0001] The invention relates to the field of centrifugal pump performance curve prediction, in particular to a centrifugal pump performance curve sample acquisition method and its application in machine learning. Background technique [0002] Centrifugal pump is a fluid machine that converts the mechanical energy of the prime mover into liquid energy, and is widely used in petrochemical, nuclear power, irrigation, urban water supply and heating systems. However, the internal flow of centrifugal pumps is very complex. The development of a pump product requires tedious processes such as design, trial production, testing, and improvement, which consume a lot of time, manpower and material resources. Therefore, the performance prediction research of centrifugal pump has become the key to product development. The impeller and the volute are the important flow components of the centrifugal pump. If the performance curve of the centrifugal pump can be accurately pr...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/27G06F30/23G06K9/62G06N20/10
CPCG06F30/27G06F30/23G06N20/10G06F18/2411G06F18/214
Inventor 周佩剑罗会灿牟介刚吴登昊谷云庆
Owner CHINA JILIANG UNIV
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