Estimation of particle size distribution on an industrial conveyor belt using image analysis and neural networks

Hamzeloo, E.; Massinaei, M.; Mehrshad, Nasser

doi:10.1016/j.powtec.2014.04.038

Cited by 86 publications

(45 citation statements)

References 12 publications

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“…From Figure 4f, it is understood that both at higher (2.6%) and lower (1.4%) level of GMS, the increase in MD% has a marginal positive influence on ΔE*, values being higher for the former level. Bhusari et al (2014) and Telis and Martínez-Navarrete (2009) opined that color difference may occur due to dilution of the pigments present in the original pulp powder by the added colorless drying aids.…”

Section: Overall Color Differencementioning

confidence: 99%

“…Mosquera, Moraga, and Martínez-Navarrete (2012), while working on freeze-dried strawberry powder, stated that MD increases the critical water activity responsible for ensuring glassy state of the product during storage. MD with varied dextrose equivalents (DE) has been used as drying aid for the preparation of powder from rutab (Abdi, Azad, Heidarinasab, & Badii, 2016), guava (Patil, Chauhan, & Singh, 2014), tamarind (Bhusari, Muzaffar, & Kumar, 2014), papaya (Pereira Canuto, Rodrigues Amorim Afonso, & Correia da Costa, 2014), pineapple (Abadio, Domingues, Borges, & Oliveira, 2004), watermelon (Quek, Chok, & Swedlund, 2007), and jamun juice (Santhalakshmy et al, 2015), using different dryers. Practically, in all these studies, stability of the powder was enhanced based on increase of T g (Bhandari & Howes, 1999).…”

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confidence: 99%

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Microwave‐convective hot airdried jamun (Syzygium cuminiL.) pulp powder: Optimization of drying aids

Paul

Das

2019

J Food Process Engineering

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Drying of fruit pulp into powder needs drying aids for achieving desirable powder properties. This article aims to optimize drying aids, such as maltodextrin (MD), tricalcium phosphate (TCP), and glycerol monostearate (GMS) in jamun (Syzygium cumini L.) pulp blend formulation to produce microwave‐convective hot air‐dried jamun pulp powder. Response surface methodology using rotatable central composite design was followed with independent variables MD (1–15), TCP (0–2), and GMS (1–3), % dry basis of pulp, on hygroscopicity (HG), rate of moisture sorption estimated at 60 min (RMS60), flow time (FT), and overall color difference (ΔE*) as responses of the product. The statistically significant factors were: MD for HG; MD, TCP, and GMS for RMS60 and FT; and TCP and GMS for ΔE*. The optimized formulation reduced HG, RMS60, and FT by 29.67, 45.24, and 60%, respectively with respect to the control, with ΔE* being 6.98. Practical Applications The antidiabetic and antioxidant properties of jamun (Syzygium cumini L.) fruit are well established. The therapeutic values of jamun pulp and skin are mainly due to the presence of various phytochemicals. However, it is considered as underutilized fruit due to its highly perishable nature. Properly matured fruit can be stored for maximum 2 days at room temperature and 3 weeks at low temperature. Hence, immediate processing and conversion into value‐added products of jamun fruits are needed for better distribution and utilization during off‐season. Processing of fruit pulp into dry powder is a popular practice to obtain shelf‐stable product having wide scope of utilization. However, preparation of fruit powder has many challenges, the main problem being their stickiness due to the presence of low molecular weight sugars and organic acids. Therefore, production of stable free‐flowing jamun pulp powder with selection of suitable drying aids in proper concentration has enough industrial relevance.

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Section: Overall Color Differencementioning

confidence: 99%

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confidence: 99%

Microwave‐convective hot airdried jamun (Syzygium cuminiL.) pulp powder: Optimization of drying aids

Paul

Das

2019

J Food Process Engineering

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“…The neural network, which was trained by the Levenberg‐Marquardt algorithm, was applied to estimate the cumulative size distribution of the precipitated tar ball aggregates. Prior to this study, a combination of a smart technique and image analysis technique has been employed to forecast the particle size distribution in the industrial operations .…”

Section: Theoretical and Practical Prospectivementioning

confidence: 99%

Evolution of tar ball aggregates in Caspian Sea: Implications of connectionist tools linked with image analysis

Amin

Zendehboudi

Mohamadi

2018

Env Prog and Sustain Energy

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Intensive petroleum activities in the Caspian Sea lead to a considerable oil pollution in the various parts of this region. Tar balls stranded on the south coast of the Caspian Sea evidently cause (and accelerate) this serious environmental threat. In this study, a poloxamine copolymeric surfactant is used to agglomerate tar balls in a system containing the solvent, antisolvent, and Caspian Sea tar balls. This research work is conducted to determine the cumulative size distribution of tar balls in the presence of a poloxamine copolymer. The evolution of tar ball aggregates is experimentally and theoretically investigated and the steady‐state size distribution of the tar balls is estimated by Back Propagation Artificial Neural Network (ANN‐BP) and a new evolutionary algorithm, called Imperialist Competitive Algorithm (ICA). The average size of tar ball aggregates increases with time and reaches a maximum value. It then declines and eventually approaches a steady‐state condition so that an almost constant size for the particles is attained. The statistical analysis shows a good agreement between the predicted values (obtained by the neural network combined with ICA, known as ANN‐ICA) and the real data for the steady‐state size distribution of the aggregates. This research study can considerably help to further understand evolution of tar balls (that hit the beaches) and consequently to find effective and economical ways for tar balls removal from the beaches. © 2018 American Institute of Chemical Engineers Environ Prog, 37: 1901–1907, 2018

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“…applied neural networks and Principal Component Analysis (PCA) algorithm using 10 features to estimate particle size distribution [4]. In another study, Young et al [5] Inspection System (OAOIS).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

An industrial image processing-based approach for estimation of iron ore green pellet size distribution

et al. 2016

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Estimation of particle size distribution on an industrial conveyor belt using image analysis and neural networks

Cited by 86 publications

References 12 publications

Microwave‐convective hot airdried jamun (Syzygium cuminiL.) pulp powder: Optimization of drying aids

Microwave‐convective hot airdried jamun (Syzygium cuminiL.) pulp powder: Optimization of drying aids

Evolution of tar ball aggregates in Caspian Sea: Implications of connectionist tools linked with image analysis

An industrial image processing-based approach for estimation of iron ore green pellet size distribution

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