A Performance Prediction Method for Axial Piston Pumps of the Swashplate Type

1982 ◽  
Author(s):  
W. J. Beswarick ◽  
F. S. Bhinder
Keyword(s):  
Performance Prediction ◽  
Prediction Method ◽  
Axial Piston Pumps ◽  
Axial Piston ◽  
A Performance

A performance prediction method for solar energy systems

Solar Energy ◽  
1992 ◽  
Vol 48 (3) ◽  
pp. 169-175 ◽  
Author(s):  
H. Suehrcke ◽  
P.G. McCormick
Keyword(s):  
Solar Energy ◽  
Performance Prediction ◽  
Prediction Method ◽  
Energy Systems ◽  
A Performance

Development of a performance prediction method for centrifugal compressor channel diffusers

2002 ◽  
Vol 16 (8) ◽  
pp. 1144-1153
Author(s):  
Jeong-Seek Kang ◽  
Sung-Kook Cho ◽  
Shin-Hyoung Kang
Keyword(s):  
Centrifugal Compressor ◽  
Performance Prediction ◽  
Prediction Method ◽  
A Performance

scholarly journals A Performance Prediction Method for a High-Precision Servo Valve Supported by Digital Twin Assembly-Commissioning

Machines ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Xuemin Sun ◽  
Shimin Liu ◽  
Jinsong Bao ◽  
Jie Li ◽  
Zengkun Liu
Keyword(s):  
High Precision ◽  
Performance Prediction ◽  
Model Simulation ◽  
Measurement Data ◽  
Prediction Method ◽  
Correction Method ◽  
Small Sample ◽  
Servo Valve ◽  
Digital Twin ◽  
A Performance

The manufacturing of a high-precision servo valve belongs to multi-variety, small-batch, and customized production modes. In the process of assembly and commissioning, various characteristic parameters are critical indicators to measure product performance. To meet the performance requirements of a high-precision servo valve, the traditional method usually relies on the test bench and manual experience for continuous trial and error commissioning, which significantly prolongs the whole assembly-commissioning cycle. Therefore, this paper proposed a performance prediction method for a high-precision servo valve supported by digital twin assembly-commissioning. Firstly, the cloud-edge computing network is deployed in the digital twin assembly-commissioning system to improve the efficiency and flexibility of data processing. Secondly, the method workflow of performance prediction is described. In order to improve the accuracy of measurement data, a data correction method based on model simulation and gross error processing is proposed. Aiming at the problem of high input dimension of the prediction model, a key assembly feature parameters (KAFPs) selection method, based on information entropy (IE), is proposed and given interpretability. Additionally, to avoid the poor prediction accuracy caused by small sample data, a performance prediction method based on TrAdaboost was utilized. Finally, the hysteresis characteristic commissioning of a high-precision servo valve is taken as an example to verify the application. The results indicate that the proposed method would enable accurate performance prediction and fast iteration of commissioning decisions.

A Performance Prediction Methodology for Integral Collection-Storage Solar Domestic Hot Water Systems

1985 ◽  
Vol 107 (4) ◽  
pp. 265-272 ◽  
Author(s):  
A. Zollner ◽  
S. A. Klein ◽  
W. A. Beckman
Keyword(s):  
Performance Prediction ◽  
Prediction Method ◽  
Water Systems ◽  
Test Methods ◽  
Hot Water ◽  
Climatic Data ◽  
Domestic Hot Water ◽  
Long Term Performance ◽  
Term Performance ◽  
A Performance

A performance prediction methodology is developed which is applicable to most commercially available integral collection-storage passive solar domestic hot water systems. A computer model of a general ICS component was created to be compatible with the transient simulation program TRNSYS[3], and was used to develop and verify the simpler monthly performance prediction method. The method uses the system parameters from available test methods, monthly average climatic data, and load size to predict long term performance of ICS systems.

Sign in / Sign up

Export Citation Format

Share Document