Investigation of efficiency of pellet burning methods in a full scale rotary dryer

Güler, Birkut

doi:10.1007/s13399-022-03381-5

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…China is rich in agricultural straw, but most kinds of straw are burned in the field, and the use of straws as fuels for domestic cooking or heating in rural areas is limited [6]. Recently, the application of biomass in bioenergy production has been extensively studied, and the most widely used technology for converting biomass to energy is still direct combustion, partly because the other biomass chemical technologies have difficulties in overcoming the high investment costs and high losses [4,7].…”

Section: Introductionmentioning

confidence: 99%

“…In China, over 900 million tons of agricultural crops and forestry biomass wastes are produced annually [8]. A significant portion of these biofuels can be effectively utilized for heat energy through direct combustion in biomass boilers, making it a practical and favorable option for biomass recycling and direct heat supply [7]. Before combustion, a variety of agricultural and forestry biomass wastes can be pulverized, stirred, and compacted into biomass briquettes to increase the mass and energy densities of biomass fuels [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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Self-Attention-Mechanism-Improved YoloX-S for Briquette Biofuels Object Detection

Wang,

Liu,

Wang

et al. 2023

Sustainability

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Fuel types are essential for the control systems of briquette biofuel boilers, as the optimal combustion condition varies with fuel type. Moreover, the use of coal in biomass boilers is illegal in China, and the detection of coals will, in time, provide effective information for environmental supervision. This study established a briquette biofuel identification method based on the object detection of fuel images, including straw pellets, straw blocks, wood pellets, wood blocks, and coal. The YoloX-S model was used as the baseline network, and the proposed model in this study improved the detection performance by adding the self-attention mechanism module. The improved YoloX-S model showed better accuracy than the Yolo-L, YoloX-S, Yolov5, Yolov7, and Yolov8 models. The experimental results regarding fuel identification show that the improved model can effectively distinguish biomass fuel from coal and overcome false and missed detections found in the recognition of straw pellets and wood pellets by the original YoloX model. However, the interference of the complex background can greatly reduce the confidence of the object detection method using the improved YoloX-S model.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Self-Attention-Mechanism-Improved YoloX-S for Briquette Biofuels Object Detection

Wang,

Liu,

Wang

et al. 2023

Sustainability

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Moulding Test and Process Parameter Optimization of Biomass Seedling Pots for Cow Dung and Corn Stover

Chen,

Ma,

Wang

et al. 2024

Agronomy

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In order to determine the optimal moulding process parameters of biomass seedling pots prepared from fermented cow dung mixed with corn stover, the moulding pressure, baking time, and baking temperature of biomass seedling pots were taken as the influencing factors, and the expansion rate, durability rate, wet swelling rate (48 h), and resistance to damage were taken as the evaluation indexes, and the Box–Behnken design of the response surface method was used to analyze the significance of interactions among the different influencing factors in the moulding process of biomass seedling pots and to optimize the moulding process. The experiment was conducted in the Biomass Laboratory of Heilongjiang Bayi Agricultural University. The response surface method Box–Behnken design was used to analyze the significance of the interaction between different influencing factors in the biomass seedling pots moulding process and optimize the moulding process. The results showed that the optimum moulding process conditions obtained using the Box–Behnken design were the following: a moulding pressure of 520.393 kN, baking temperature of 202.870 °C, and baking time of 8.573 min. The model was validated by testing and a response value of 10.522% was obtained for expansion, 99.598% for durability rate, 11.145% for wet swelling (48 h), and 4503.545 N for resistance to damage. The experimental verification showed that the deviation of the actual value obtained under this condition from the predicted value is less than 5%, indicating that the model reproduces well and meets the experimental requirements. Based on the optimal moulding process conditions determined in this experiment, the total porosity, EC, and pH of the Biomass seedling pots were determined to be 67.32%, 1.63 mS/cm, and 6.7, respectively, which met the seedling requirements.

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Investigation of efficiency of pellet burning methods in a full scale rotary dryer

Cited by 2 publications

References 14 publications

Self-Attention-Mechanism-Improved YoloX-S for Briquette Biofuels Object Detection

Self-Attention-Mechanism-Improved YoloX-S for Briquette Biofuels Object Detection

Moulding Test and Process Parameter Optimization of Biomass Seedling Pots for Cow Dung and Corn Stover

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