Moisture Content Of Chips Research Articles

MoistNet: Machine vision-based deep learning models for wood chip moisture content measurement

Quick and reliable measurement of wood chip moisture content is an everlasting problem for numerous forest-reliant industries such as biofuel, pulp and paper, and bio-refineries. Moisture content is a critical attribute of wood chips due to its direct relationship with the final product quality. Conventional techniques for determining moisture content, such as oven-drying, possess some drawbacks in terms of their time-consuming nature, potential sample damage, and lack of real-time feasibility. Furthermore, alternative techniques, including NIR spectroscopy, electrical capacitance, X-rays, and microwaves, have demonstrated potential; nevertheless, they are still constrained by issues related to portability, precision, and the expense of the required equipment. Hence, there is a need for a moisture content determination method that is instant, portable, non-destructive, inexpensive, and precise. This study explores the use of deep learning and machine vision to predict moisture content classes from RGB images of wood chips. A large-scale image dataset comprising 1,600 RGB images of wood chips has been collected and annotated with ground truth labels, utilizing the results of the oven-drying technique. Two high-performing neural networks, MoistNetLite and MoistNetMax, have been developed leveraging Neural Architecture Search (NAS) and hyperparameter optimization. The developed models are evaluated and compared with state-of-the-art deep learning models. Results demonstrate that MoistNetLite achieves 87% accuracy with minimal computational overhead, while MoistNetMax exhibits exceptional precision with a 91% accuracy in wood chip moisture content class prediction. With improved accuracy (9.6% improvement in accuracy by MoistNetMax compared to the best baseline model ResNet152V2) and faster prediction speed (MoistNetLite being twice as fast as MobileNet), our proposed MoistNet models hold great promise for the wood chip processing industry to be efficiently deployed on portable devices, such as smartphones.

Self-Heating, Drying, and Dry Matter Losses of Stockpiled Stemwood Chips: The Effect of Ventilation

The comminution of fuelwood for efficient transportation and handling exposes the material to various biological and chemical decomposition processes. The stockpiling of fuel chips can result in significant dry matter losses (DML) and consequent release of CO2 into the atmosphere. The decomposition processes could be controlled by managing the chip moisture content (MC). MC control by utilizing the self-heating of stockpiled stemwood chips together with wind-driven ventilation was tested in a practical storage experiment, using uncovered and plastic-covered piles as references. The data were analyzed with linear mixed models. The predicted DML was 2.4–3.8% during the monitoring period of 5.9 months, but no significant differences appeared between the storage treatments. The increase in the basic density of the chips decreased DML. On average 1.7–3.5% of the recoverable energy content of the chips was lost during the experiment. The predicted average decline in the MC was ca. 4–8 percentage points (p.p.). The MC of the chip samples stored under plastic tarp was 4–5 p.p. lower than those stored in the uncovered piles. Heat generation within the piles was modest due to the high quality of the chips, and the ventilation solution tested only marginally affected the drying process and the mitigation of DML.

Electrical Capacitance Characteristics of Wood Chips at Low Frequency Ranges: A Cheap Tool for Quality Assessment.

Moisture content is one of the most important parameters related to the quality of wood chips that affects both the calorific and economic value of fuel chips. For industrial applications, moisture content needs to be detected quickly. For this purpose, various indirect moisture content measurement methods (e.g., capacitance, NIR, microwave, ECT, X-ray CT, and nuclear MR) have been investigated with different results in the past. Nevertheless, determining wood chip moisture content in real time is still a challenge. The main aim of this article was therefore to analyze the dielectric properties of wood chips at low frequencies (10 kHz–5 MHz) and to examine the possibility of using these properties to predict wood chip moisture content and porosity. A container-type probe was developed for this purpose. The electrical capacitance and dissipation factor of wood chips with different moisture content was measured by an LCR meter at 10 kHz, 50 kHz, 100 kHz, 500 kHz, 1 MHz, and 5 MHz frequencies. Wood chip porosity was also measured using a gas displacement method. Linear models for moisture content and porosity prediction were determined by backward stepwise linear regression. Mathematical model was developed to better understand the physical relationships between moisture content, porosity, and electrical capacitance. These models were able to predict the moisture content of observed quantities of wood chips with the required accuracy (R2 = 0.9–0.99). This finding opens another path to measuring the moisture content and porosity of wood chips in a relatively cheap and fast way and with adequate precision. In addition, principal component analysis showed that it is also possible to distinguish between individual wood chip fraction sizes from the information obtained.

Parameters of Trucks and Loads in the Transport of Scots Pine Wood Biomass Depending on the Season and Moisture Content of the Load

Transport of wood biomass is one of the key operations in forestry and in the wood industry. An important part is the transport of shredded wood, where the most common forms are chips and sawdust. The aim of the research was to present the variability of the total weight of trucks (gross vehicle weight, GVW), the weight of the empty trucks (tare), and loads of chips and sawdust in different periods of the year. Changes in specific parameters were analyzed: GVW; tare weight; trailer capacity; use of the trailer load capacity; bulk volume and bulk density of wood biomass loads; solid cubic meter (m3) and weight of 1m3 of the load; and load weight depending on the season, with simultaneous measurements of wood chips and sawdust moisture. More than 250 transports from four seasons of the year were analyzed in the research. It was found that the total weight of trucks (GVW) was at a comparable level, on average from 39.42 to 39.64 Mg with slight differences (with SD 0.29 and 0.39). The weight of empty trucks was 16.15 Mg for chip-bearing trucks and 15.93 Mg for sawdust-bearing trucks (with SD 0.604 and 0.526). The type of wood material has an influence on the transported volume. The average quantity of load in the bulk cubic meter was 64.783 m3 for wood chips (SD 3.127) and 70.465 m3 (SD 2.516) for sawdust. Over 30% differences in the volume of transported wood chips and approximately 18% for sawdust were observed. The use of the loading capacity of the trailer was on average 72.58% (SD 5.567) for the transport of wood chips and 77.42% (SD 3.019) for the transport of sawdust. The sawdust bulk density was from 0.3050 to 0.4265 Mg⋅m−3 for wood chips and 0.3200 to 0.3556 Mg⋅m−3 for sawdust. This parameter is significantly dependent on moisture content, and the determined correlation functions can be used for estimating and predicting bulk density. The abovementioned absolute moisture content of chips and sawdust also depends on the season, which also affects the selected parameters of wood biomass loads.

Effect of starch-based edible coating application on potato chips characteristic from tubers and flour of potato variety Granola

Edible coating made from starch contributes to reducing oil uptake during processing. This research aimed to examine the effects of the edible coating application on the characteristics of potato chips prepared from the fresh tuber (PCT) and potato flour (PCF). The raw material for chipping was potato variety Granola. The edible coating was produced from sago starch, arrowroot starch, and tapioca. Edible coating from alginate was also examined. The coating was applied on the potato slices before frying. The parameters observed in this study were fat and moisture content, color parameter, and sensory properties that include crunchiness, a taste of potato, and preference. The results showed that the edible coating made from sago starch, arrowroot starch, and alginate reduced oil absorption of chips 3.90%, 8.29%, and 14.56%, respectively. There was no effect of edible coating found on the moisture content of chips. The L-, a-, and b-value indicate that the coated chips did not have a bright yellow color. All of the treated chips had L-value lower than 55. Most of the sensory properties of coated chips had a low hedonic score (less than 3) that were not preferred by the panelists. Whereas crunchiness and taste of chips made from the flour were still accepted by the panelists, the hedonic score was higher than 3.

Wood Density and Moisture Content Estimation by Drilling Chips Extraction Technique.

The novelty of this study is the development of an accurate wood moisture content (MC) estimation method based on a relatively brand-new, non-destructive testing technique (drilling chips extraction). The method is especially important in the assessment of existing timber structures, where non-destructive testing (NDT) results are affected by wood MC and should be adjusted to a reference MC, usually 12%. In the assessment of timber structures, it is not possible to determine MC by oven drying method and this should be estimated. Electrical resistance and capacitance are the conventional methods used for MC estimation. This research work aims to present an accurate MC estimation method based on the drilling chips extraction technique. For that, 99 specimens (90 × 65 × 38 mm3) from three softwood and hardwood species covering a wide range of densities (from 355 to 978 kg m−3) were tested after conditioning at five different MCs (5%, 10%, 15%, 20%, 25%). The Wood Extractor device based on the drilling chips extraction technique was used. The mass of the chips collected (drilling residue) from each drill was recorded. The results show that the MC of the chips extracted was statistically significantly different than the MC of the specimen and cannot be directly used as MC determination. However, the chips MC can be used as an estimator of specimen MC with high determination coefficients (R2 from 71% to 86%). As the main result, models to estimate density directly adjusted to a reference 12% MC from the wet and dry mass of chips extracted were developed with an R2 of 98%. In sum, the drilling chips extractor is a dependable and straightforward method to estimate MC and density from only one measurement. Density adjusted to a reference 12% MC can be directly estimated from a single model.

Estimation of moisture in wood chips by Near Infrared Spectroscopy

In order to assess the moisture content of wood chips on an industrial scale, readily applicable techniques are required. Thus, near infrared (NIR) spectroscopy was used to estimate moisture in wood chips by means of partial least squares regressions. NIR spectra were obtained in spectrometer with an integrating sphere and optical fiber probe, on the longitudinal and transverse surface of Eucalyptus wood chips. The specimens had their masses and NIR spectra measured in 10 steps during drying from saturated to anhydrous condition. Principal Component Analysis was performed to explore the effect of moisture of wood chip on NIR signatures. The values of moisture content of chips were associated with the respective NIR spectra by Partial Least Squares Regression (PLS-R) and Partial Least Squares Discriminant Analysis (PLS-DA) to estimate the moisture content of wood chips and its moisture classes, respectively. Model developed from spectra recorded on the longitudinal face by the integrating sphere method presented statistics slightly better (R²cv = 0,96; RMSEcv = 7,15 %) than model based on optical fiber probe (R²cv = 0,90; RMSEcv = 11,86 %). This study suggests that for calibration of robust predictive model for estimating moisture content in chips the spectra should be recorded on the longitudinal surface of wood using the integrating sphere acquisition method.

Effect of Initial Moisture Content of Chips and Steaming Time on the Properties of Medium Density Fiberboard

Effect of Initial Moisture Content of Chips and Steaming Time on the Properties of Medium Density Fiberboard

Measurement of Bulk Electrical Properties Using GPR with a Variable Reflector

Bulk electrical properties of media are important inherently for ground penetrating radar (GPR) applications and for providing a means to determine indirectly other physical properties such as moisture content. We have developed a reflector whose reflectivity can be controlled electronically. This variable reflector controlled by a GPR provides an effective method to measure bulk electrical properties of media. For sample measurements, the GPR is placed on one side of a sample and the variable reflector on the opposite side. GPR trace data are then acquired with the reflector in an on-state and in the off-state. By differencing these measurements, we improve the ability to detect the specific reflection event from the variable reflector. This process removes both the direct wave and clutter from the trace data, improving the quality of the refection event and our ability to accurately pick its arrival time and amplitude. We describe the variable reflector, a prototype instrument based on the reflector and numerical modeling performed to understand its response. We also show the results of testing applications to the measurement of wood chip moisture content and monitoring of the electrical properties of concrete during the curing process.

Moisture content recognition for wood chips in pile using supervised classification

Wood chips moisture content (MC) is a key parameter for controlling the biofuel product qualities and properties. Since no knowledge-based model is available to recognize MC, machine learning methods are promising techniques to design black-box models for MC prediction or recognition. As wood permittivity strongly changes in the presence of water, an electromagnetic module is used to probe the reflectivity of wood chip piles. In the present paper, the recognition of three wood chip piles of different MC categories is performed using support vector machines (SVMs). SVM-recursive feature elimination is implemented to rank and select reflection coefficients to design optimized linear SVM classifiers that attribute MC class of wood chips in a pile. Experiments show that the proposed approach is effective and requires a limited computational power. The global classification performance exceeds 95%.

Effects of Intentional Reduction in Moisture Content of Forest Wood Chips during Transport on Truckload Price

Wood chip transportation is a widespread practice in Poland, with distances between forest sites and power or heating plants reaching 300 km and truck transport times of up to 6 h. Because the basic parameter affecting biomass quality for energy production is moisture content, the objective of the presented economic analysis was to determine its effect on the price of wood chips transported by semi-trailer trucks. This paper considered the possibility of drying biomass in the semi-trailer. No external energy consumption was envisioned; the heat needed for drying was obtained from the truck cooling or exhaust systems via heat exchangers. The moisture content of transported biomass had a dual effect on the final truckload price. While it increased biomass amount by adding to its weight, it decreased its price by lowering its calorific value. Mathematical analysis showed that a decrease in wood chip moisture content increased truckload price, justifying research on technological improvements of this process. Simulations indicated that by reducing moisture content during transportation, biomass suppliers increased their revenues approximately € 3.6 to € 30.0 per truckload, which translates into annual financial profit ranging from tens of thousands of euros (EUR) to more than € 23,810.

Predicting moisture content of chipped pine samples with a multi-electrode capacitance sensor

Woody biomass is currently sold on a weight basis, practical moisture sensors are essential for fair sales, especially in energy markets. To address this need, an 8-electrode electrical capacitance tomography (ECT) sensor was built and tested for predicting moisture content of wood chips and compared with the near infrared spectroscopy (NIR) method. The goal was to find an optimal means of measuring moisture content of woody biomass in the form of chips in two situations: individual chips and bulk samples. Tests were made on chips ranging in moisture content from 4% to 140% (d.b.). Results indicated that NIR had better performance in measuring moisture of single wood chips, while ECT was more accurate and rapid in bulk moisture determination. Knowledge of the mass of wood chips under test was required in the ECT moisture prediction model, unlike in the case of NIR. Both methods had the capability to measure moisture content of biomass while in motion. From a practical standpoint, however, only a portion of the material flowing past a near-infrared sensor could be practically scanned and the sub-sampled biomass would have to be representative of the entire population to be accurate. The ECT sensor, on the other hand, could likely be designed to scan the entirety of a large quantity of moving material and provide an accurate bulk average moisture content. Compared to a single paired-plate capacitance sensor, the ECT system also provided images, through its tomography function, that displayed permittivity distribution variability throughout bulk biomass samples.

Design of methodology for wood chips moisture estimation determined for gasification

The moisture content of the charged wood chips is a significant factor affecting the gasification process. The increased moisture content increases the demand on the energy consumption, which is needed to cover the heat consumption related to the water evaporation and adversely affects the wood gas quality and input fuel amount. Monitoring of the moisture content in wood chips is therefore the diagnostic tools suitable to evaluate the operational parameters of the whole gasification process. Present paper describes the design of the suitable methodology to measure and estimate the wood chips moisture content. The issues related to the moisture content estimation include preliminary the selection of the suitable methodology based on the assumed moisture content in the wood chips. Further factor which needs to be considered is the fact that the moisture content in wood chips is time dependent due to the changing parameters of the ambient air (as temperature, pressure and air humidity). Correctly estimated moisture content will enable to improve the wood chips gasification process.

Effect of processing conditions on the quality characteristics of barley chips.

The aim of the present study was to study the effect of lime concentration, frying temperature and frying time on quality characteristics of barley chips. Effect of salt concentration and packaging material on the quality and stability of the product was also studied during 180days of storage under ambient conditions. An increase in fat content of chips was observed with the increase in lime concentration, frying temperature and time, whereas a decreasing trend was observed in moisture content of chips. An increase in amylose content of chips was observed during frying. However, it was found that the amylopectin in chips decreased during frying as frying temperature and time was increased. An increase in colour difference (ΔE) and crispness was noted in chips during frying as frying temperature and time increased. With the increase in lime concentration (0.5 and 1.0%) both ΔE and break force of chips was found decreased. The results further revealed that there was gradual decrease in fat (%) and amylopectin (%) during storage, whereas moisture (%) and amylose (%) increased during storage period. Organoleptic evaluation of the product revealed that scores of colour, texture, flavour and over all acceptability decrease during storage. However the treatment (salt 2% and aluminium based laminate) recorded better score with respect to colour, flavour, texture and overall acceptability.

Multiresponse optimization based on statistical response surface methodology and desirability function for the production of particleboard

It is very difficult to determine the actual level of process parameters responsible for the quality production of particleboard due to the high degree of process variable interactions and lack of robust methodology for optimization. In this study, an attempt was made to optimize the process parameters of particleboard production by using multi-response optimization process. Plackett–Burman factorial design was first employed to eliminate some factors from selected seven important parameters: flake thickness, flake length, dried chips moisture content (MC%), amount of adhesive, pressing time, pressure, and press temperature. By using this screening procedure, three important factors: flake thickness, dried chips moisture content and press temperature were found to have significant effect on particleboard properties. Afterwards, Box–Behnken design was performed as response surface methodology (RSM) with desirability functions to attain the optimal flake thickness, MC% and press temperature that affect modulus of rapture (MOR) and modulus of elasticity (MOE) of particleboard production. The optimized parameters for maximum MOR and MOE determined were found to be: flake thickness, 0.15mm; press temperature, 182°C; and dried chip MC% 3.5. Finally, a confirmation study was executed by using optimized levels of parameters which showed well response to the predicted model.

Economic, energetic and environmental impact in short rotation coppice harvesting operations

Abstract In Italy, agro-energy’s contribution to the national primary energy demand is still moderate. Among the energy crops Short Rotation Coppice (SRC) has taken up about 6500 ha, using poplar clones. For this crop, the harvesting operations, usually, are carried out by modified forage harvester equipped with dedicated headers and by tractor coupled with trailers. This, besides the high economic costs, involves also energy inputs and green house gas (GHG) emissions that must be carefully taken in account when the sustainability of the whole agro-energy chain is assessed. This study shows the results of filed tests carried out on 69.2 ha of biennial SRC with two different poplar plantation systems. Yield ranges from 16.7 to 33.71 t dm /ha (dry matter), chip moisture content between 50.4 and 64.8% and bulk density between 118.8 and 169.2 kg dm /m 3 . Effective field capacity and theoretical field capacity are highly variable, respectively, from 0.77 to 1.67 ha/h and from 1.18 to 2.15 ha/h. Economic cost, energetic input and GHG emissions depend on yield, annual use of the machines and scheduling of operations. The analysis shows that the best performances are achieved when harvest and transport are carried out on a area upper than 400 ha, with an efficient plantation design, a proper-sized transport system and without mechanical failures. In these case the productivity of the harvest-transport system can arrive at 65 t wb /h (wet basis) while the economic cost, the energetic input and the GHG emissions reach, respectively, 15 €/t dm , 212 MJ/t dm and 16 kgCO 2 eq/t dm .

Effects of Mountain Pine Beetle Grey-Stage Infestation and Chip Moisture Content on TMP Pulping of Lodgepole Pine

We performed pilot-plant thermomechanical pulping on green and dry, mountain pine beetle-infested, grey-stage lodgepole pine sapwood chips with different moisture contents. The energy requirements and the tensile strength of the thermomechanical pulps (TMPs) from the dry, early-grey-stage chips were similar to those from the green chips, but there were indications of slightly higher energy requirements and lower tensile strength for the pulps from the late-grey-stage chips. The late- or early-grey-stage TMP had lower sheet density (because of the lower chip moisture content), lower ISO brightness, and higher handsheet surface roughness than the green TMP. Chip blends with 50% and 25% of late-grey-stage chips could be used to produce TMP pulps with energy require-ment, tensile strength, handsheet surface roughness, and density similar to those of green TMP, but with lower ISO brightness. The fiber saturation points of the green and the late-grey-stage chips were estimated to be 23.1% and 22.4% (wet basis), respectively.

Elman Network in Kappa Number Prediction

AbstractVariations in the pulp quality are mainly due to variations in the quality of wood chips used for pulping. Moisture content of chips, chip size and chip composition vary, and the measurements to reflect these variations do not always exist. Kappa number is the usual way of describing the pulp quality and it measures the residual lignin content in the pulp. In batch digesting, the main difficulty in maintaining consistent Kappa number is the lack of on-line Kappa number measurement. The most common way is to use the calculated H-factor to define the cooking end-point. Kappa number cannot be measured on-line in batch digesters, but there are many approaches to model, or predict, it from the existing measurement, and use the predicted Kappa to complement the H-factor control. Both mechanistic and data-based model are in use, but due to the complexity of fundamental models, current industrial practices rely almost exclusively on simple empirical or semi-empirical models. Several intelligent methods (neural networks and fuzzy logic) together with advanced controls have found applications also on this arena. This paper concerns with using recurrent Elman network together with alkali measurement and H-factor in Kappa number modelling.

Moisture sorption isotherm and xerophilic moulds associated with dried cocoyam chips in storage in Nigeria

SummaryExtended storage of cocoyams (Colocasia antiquorum and Colocasia esculenta) is achieved in parts of Nigeria by processing them into smoked and dried chips. In this study, cocoyam chips were collected from parts of Nigeria at the end of drying, at various periods of storage and from markets, and analysed for moisture content, moisture sorption characteristics and xerophilic moulds. Moisture content of chips ranged from 7.07 ± 1.1% for freshly dried samples to 16 ± 2.2% for samples stored up to 8 months. Six mould species from four groups of the genus Aspergillus (including five xerophiles) identified as Aspergillus fumigatus, Eurotium repens, Eurotium amstelodami, Eurotium chevalieri and Aspergillus flavus and Aspergillus niger and Mucor sp. were isolated. The variety of moulds increased with storage and moisture content of samples. Moisture sorption in dried chips showed type II sigmoidal behaviour. Wood smoke significantly protected chips from mould colonization, but in cooperation with reduced water activity. Simple and inexpensive storage of freshly dried samples in airtight bags led to prolonged storage of up to 14 months without deterioration.

Harvesting technology and the cost of fuel chips from early thinnings

This study compared and analyzed the procurement cost of whole tree chips when using supply chains based on comminution at the roadside landing or at the terminal. It also identified the bottlenecks of the most common logging systems used in Finland. The study was done by using existing and published productivity parameters and models. The procurement cost calculations were made for a stand where the forwarding distance was 200 metres, removal of whole trees was 60 m per hectare and the area of the stand was 2.0 hectares. The average size of the removed whole trees was 30 litres. The direct transport distance from the stand to the terminal or to the end use facility was 40 km while the secondary distance from the terminal to the end use facility was 10 km. A stumpage price for the harvested raw material was not included in this study. According to the study the cost of whole trees chips were 31.9–41.6 euros/m at the plant, or 14.9–19.4 euros/MWh when the moisture content of chips was estimated to be 40%. The two-machine system was found to be the most cost competitive logging system in pre-commercial thinnings thanks to both efficient cutting and, especially, forwarding work. In the manual worker based logging, the costs of felling bunching were the same as the mechanised system, whereas in forwarding the costs were almost double. Using the harwarder system the logging costs were found to be the highest, but in the larger tree volumes and removals the costs were almost equal to the manual worker based logging. The supply chain based on chipping at the roadside landing was more cost efficient compared to the chipping at the terminal system. The lower comminution cost at the terminal was not enough to cover the higher transportation cost of unprocessed material to the terminal, handling cost of chips at the terminal or the delivery cost to the end use facility.