Abstract
Conventional spray particle detection methods have disadvantages such as spray field interference, large subjective standard error, and an inability to specifically analyze the spray particle movement. Manual methods used the uniformity of the liquid deposit in the spray chamber to detect spray particles, which only considered the particle density information. Especially, manual detection results by different observers are significantly different, resulting in the low measurement accuracy of the spray particle size. In order to overcome these challenges, this paper proposes a non-contact spray particle segmentation based on the Residual Atrous Spatial Pyramid Network (RASPN). In the RASPN, the spray angle of the fragranced nozzle and the distribution of spray particles of different sizes are evaluated through the statistical method. The experimental results show that the proposed RASPN outperforms the compared methods in terms of detection accuracy. The injection angle is about 31° under an injection pressure of 0.4 MPa, with the highest proportion of 40–80 pixel spray particles.
Highlights
The atomization performance of the nozzle device is closely related to the fragrance effect
Molecular dynamics (MD) simulations were employed to study the coalescence behaviors of nano-droplets on the stripy substrates decorated with spaced graphene nanoribbons (GNRs) for the first time by Li et al
The characteristic parameters were computed based on image processing techniques, including the spray particle size, equivalent diameter, and centroid position in the image sequence
Summary
As an important production tool, the atomizer has been widely used in agriculture, manufacturing, and chemical industries. The spray quality index is considered the most important index to evaluate the fragrance performance of a nozzle.4 This index is determined based on the following factors: spray size, uniformity, the particle spectrum range of spray particles, the range and flow rate of spray particles from the perfuming nozzle, and the dead time of spray particles before landing.. Yang et al. adopted different spray angles and injection pressures to test atomization characteristics of nozzles with optimized atomization performance It only used software for mathematical analysis and simulation, potentially inducing deviation from the actual situation. Agarwal and Trujillo used the OpenFOAM solver and the algebraic fluid volume method of interFoam to solve the atomization problem of the nozzle, which can be used for atomization classification Since these methods were based on either software or complex mathematical models, they were not intuitive and impractical to detect the spray atomization effect. In order to segment atomized particles and evaluate the atomization effect, this paper proposes a novel network structure, the Residual Atrus Spatial Pyramid Network (RASPN), based on the idea of the residual network and pyramid pooling
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