About Simple photovoltaic glue board parameters
The grey relational grade results of particle gluing production parameters of fcore, fsurface, vcore, vsurface, pcore, psurface, Icore and Isurface on IB.
As shown in Fig. 8, although the GRA–SVR model had high accuracy, there was still 8.83% of the relative deviation of the predicted.
The prediction model of particle gluing process parameters and IB using GRA–SVR was trained. The input variables were fcore, fsurface, vcore, vsurface, pcore, psurface.
Manufacturers would change PB production according to different order requirements. The particle discharge speed in the belt scale in the particle gluing process would.
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6 FAQs about [Simple photovoltaic glue board parameters]
Can particle gluing production parameters predict internal bond strength?
The production parameters of particle gluing have an important influence on the internal bond (IB) strength of PB. In this study, using grey relation analysis (GRA) and support vector regression (SVR) algorithm, a prediction model was developed to accurately predict IB of PB through particle gluing processing parameters in a PB production line.
How can the operating parameters of particle gluing be adjusted?
The operating parameters of particle gluing can be adjusted based on the NSGA2-SVR multi-objective prediction model according to the actual gluing requirements, to improve the MOE, MOR, and IB of the produced PB. It was assumed that fcore ran at 300 kg/min in a certain period.
Do particle gluing production parameters affect IB of Pb?
Finally, the influence of particle gluing production parameters on IB of PB was evaluated according to the model prediction results. Since the real PB production is an extremely complex process, it is a big challenge to optimize the PB production parameters.
What is the multi-objective prediction model of particle gluing operating parameters?
The multi-objective prediction model of particle gluing operating parameters was developed based on NSGA2-SVR, which can realize the simultaneous predictions of multiple mechanical properties of PB by coupling and nonlinear particle gluing operating parameters.
Can particle gluing parameters be tuned?
However, due to the lack of theoretical guidance related to the produc-tion parameters of particle gluing, tuning its parameters can only be completed based on the actual experiences of workers, which is dificult to meet the accuracy of parameter regulation in the gluing process .
What is the relational grade between particle gluing processing parameters and IB?
GRA was used to analyze the grey relational grade between the particle gluing processing parameters and IB of PB, and the variables were screened. The SVR algorithm was used to train 724 groups of particle gluing sample data between six particle gluing processing parameters and IB. The SVR model was tested with 181 sets of experimental data.