Drying Period Estimation Device

Abstract

To estimate a drying period until water content reaches a target level.SOLUTION: A drying period estimation device 100 comprises: an information acquisition part 210 which acquires initial water content of cutdown tree; and an estimation part 220 which estimates a period until water content of a tree reaches target level on the basis of the acquired initial water content and a predetermined drying speed.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present disclosure relates to a dry period estimation device. [Background technology]

[0002] Wood such as thinned timber cut down in forests is stored in lumberyards for a certain period of time and naturally dried while stored. The naturally dried wood in the lumberyards is transported to lumber utilization facilities. The lumber utilization facilities crush the wood, burn it, or produce chemical raw materials or paper raw materials from the wood.

[0003] As an example of wood utilization equipment, a power plant has been disclosed (for example, Patent Document 1). The technology in Patent Document 1 includes a grinding device, a drying device, a combustion kiln, and a steam turbine generator. The grinding device grinds wood into chips. The drying device dries the chips. The combustion kiln burns the dried chips to generate steam. The steam turbine generator generates electricity by using the steam generated in the combustion kiln. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2014-13552 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, the drying period (storage period) of wood at a lumberyard until it reaches the target moisture content desired by the wood-utilizing facility varies depending on various factors such as the temperature at the lumberyard. For this reason, there is a need to develop a technology that can estimate the drying period until the target moisture content is reached.

[0006] An object of the present disclosure is to provide a drying period estimation device that is capable of estimating the drying period required to reach a target moisture content. [Means for solving the problem]

[0007] In order to solve the above problems, a drying period estimation device according to one aspect of the present disclosure includes an information acquisition unit that acquires an initial moisture content of felled timber, a machine learning unit that corrects the predetermined drying speed by machine learning based on the species of the wood, the thickness of the wood, the length of the wood, the presence or absence of bark on the wood, and one or more of the time when the wood was harvested, the initial moisture content, the final moisture content, and the period from the initial moisture content to the final moisture content, and meteorological information of the storage location of the wood during the period from the initial moisture content to the final moisture content; The obtained initial moisture content, Corrected and an estimation unit that estimates the period for the moisture content of the wood to reach the target moisture content based on the drying rate.

[0008] Also, Prescribed The drying rate may be derived based on one or more of the following: the species of the wood, the thickness of the wood, the length of the wood, whether the wood has bark, and the time of harvest of the wood.

[0010] Also, Prescribed The drying speed may be derived based on one or more of the condition of the location where the wood is placed, the storage manner of the wood at the location, and the air conditioning state at the location. Effect of the Invention

[0011] According to the present disclosure, it is possible to estimate the drying period required to reach the target moisture content. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram illustrating the movement of timber cut down in a forest. [Diagram 2] FIG. 1 is a diagram illustrating a drying period estimation device according to an embodiment. [Diagram 3] FIG. 13 is a diagram illustrating measurement data. [Figure 4] FIG. 13 is a diagram illustrating an example of a tree species table. [Diagram 5] FIG. 13 is a diagram illustrating an example of a diameter table. [Figure 6] FIG. 11 is a diagram illustrating an example of a length table. [Figure 7] FIG. 13 is a diagram illustrating an example of a bark table. [Figure 8]1 is a diagram illustrating the changes in moisture content, temperature, and humidity of wood in a lumber yard when trees are cut down in winter. FIG. [Figure 9] FIG. 1 is a diagram illustrating the changes in moisture content, temperature, and humidity of wood in a lumber yard when trees are cut down in spring. [Figure 10] FIG. 1 is a diagram illustrating the changes in moisture content, temperature, and humidity of wood in a lumber yard when trees are cut down in summer. [Figure 11] 1 is a diagram illustrating the changes in moisture content, temperature, and humidity of wood in a lumber yard when trees are cut down in autumn. [Figure 12] FIG. 13 is a diagram illustrating an example of a felling time table. [Figure 13] FIG. 11 is a diagram illustrating an example of a location state table. [Figure 14] FIG. 13 is a diagram illustrating an example of a storage mode table. [Figure 15] FIG. 13 is a diagram illustrating an example of an air conditioning table. [Figure 16] FIG. 13 is a diagram illustrating an image of a dry period derived by an estimation unit. [Figure 17] 4 is a flowchart showing a process flow of a dry period estimation method according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] An embodiment of the present disclosure will be described in detail below with reference to the accompanying drawings. The dimensions, materials, and other specific numerical values ​​shown in the embodiment are merely examples for ease of understanding, and do not limit the present disclosure unless otherwise specified. In this specification and drawings, elements having substantially the same functions and configurations are given the same reference numerals to avoid repeated explanation. Elements not directly related to the present disclosure are not shown.

[0014] FIG. 1 is a diagram for explaining the movement of timber felled in a forest 10. Timber felled in the forest 10 is first stored in a mountain yard 20. The mountain yard 20 is a collection site set up in the vicinity of the forest 10. The mountain yard 20 may be located, for example, several hundred meters away. 2 More than a few thousand meters 2 The area is as follows. Timber (e.g., thinned timber) felled in the forest 10 is de-branched and cut into logs of appropriate length in the mountain yard 20, where it is stored. Hereinafter, timber that has been de-branched and cut into logs of appropriate length is referred to as "short stem timber." Timber is processed into short stem timber, transported within the forest, or transported from the mountain yard 20 to the street yard 30 after a large amount has been produced. For this reason, the short stem timber is stored in the mountain yard 20 for a predetermined period of time (e.g., about 2 to 5 months) after it is felled. In the mountain yard 20, the short stem timber is accumulated in units of the number of pieces that can be loaded onto one trailer truck (e.g., 100 pieces). The short stem timber stored in the mountain yard 20 is transported by trailer truck in units of accumulation (one group (one pile)) to the street yard (intermediate yard) 30.

[0015] The lumberyard 30 is a collection site provided between the mountain lumberyard 20 and the wood utilization facility 40. Short logs are transported in collection units from multiple mountain lumberyards 20 to one lumberyard 30. The lumberyard 30 is, for example, 20,000 m 2 The lumber yard 30 is adjacent to a public road and is located in a place where a trailer vehicle (towing vehicle) can reach it. Public roads are, for example, city roads, metropolitan roads, prefectural roads, prefectural roads, and other roads that are paved with asphalt or crushed stone. In the lumber yard 30, the short timber is stored in the above-mentioned accumulation units. While stored in the lumber yard 30, the short timber is naturally dried. The short timber is stored (stacked) in the lumber yard 30 by pile or flat stack. The short timber stored in the lumber yard 30 is transported by trailer vehicle for each accumulation unit to the wood utilization facility 40.

[0016] The wood utilization facility 40 is a facility for crushing short stems, burning short stems, and producing chemical raw materials or paper raw materials from short stems. Examples of the wood utilization facility 40 include a pellet manufacturing plant, a thermal power plant, a biofuel manufacturing plant, a paper mill, and a plant for synthesizing raw materials.

[0017] The drying period (storage period) of the short timber in the lumber yard 30 until the wood utilization facility 40 reaches the desired target moisture content (for example, 25%) varies depending on various factors such as the temperature of the lumber yard 30. For this reason, when short timber with the target moisture content is shipped from the lumber yard 30, the moisture content of the short timber has to be measured at the lumber yard 30 every time it is shipped.

[0018] In this embodiment, a drying period estimation device 100 that estimates the drying period from when short timber is received at the lumber yard 30 until the lumber reaches a target moisture content will be described.

[0019] [Drying period estimation device 100] 2 is a diagram illustrating the drying period estimation device 100 according to this embodiment. The drying period estimation device 100 includes a communication unit 110, a central control unit 120, and a memory .

[0020] The communication unit 110 communicates with the weather server 60 , the tree-cutting server 70 , the shipping server 80 , and the utilization facility server 90 via the communication network 50 .

[0021] The weather server 60 is provided at a weather information provider. Examples of the weather information provider include the Japan Meteorological Agency and POTEKA (registered trademark). The weather server 60 holds weather information for the area of ​​the landslide yard 30. The weather information includes temperature, humidity, weather, wind direction, wind speed, sunshine hours, etc.

[0022] The felling server 70 is installed in a felling company. The felling server 70 creates a felling plan based on a production plan for the local forest 10 obtained from the producer of the forest 10 (e.g., a forestry association). The felling plan includes the location of the forest 10 to be felled, the felling time, the area to be felled, the degree of felling (degree of thinning, clear-cutting, etc.), the species of trees to be felled, the average size of the species, tree height, breast height diameter, and classification by use. The number of timber trees to be felled is determined based on the forest 10 to be felled, the area to be felled, and the degree of felling.

[0023] A felling company fells timber in forest 10 based on a felling plan, and processes the timber into short stems in mountain yard 20 for storage. The felling company attaches an IC tag to the timber (short stems) while it is waiting to be transported to mountain yard 20, or while it is in mountain yard 20. For example, the felling company attaches an IC tag to one short stem for each short stem that constitutes an accumulation unit stored in mountain yard 20. In this embodiment, the felling company forms an accumulation unit with short stems that are substantially the same in terms of felling date, tree species, diameter D (cm), length L (m), and whether or not they have bark.

[0024] Furthermore, in the daily report for the day of felling, the felling date, felling location, information on the heavy machinery used for felling, and information on the felled timber are entered by the felling contractor. Information on the heavy machinery includes the type of equipment (including attachments), number of units, energy consumption [kWh], fuel consumption, etc. Information on the timber includes information on the standing trees in forest 10 (tree species, breast height diameter, tree height, forest age, felling history), weight Wi (kg) of the felled timber, average diameter D, length L, identification number stored in the IC tag, etc.

[0025] Immediately after felling, the harvester processes the wood into stub timber, and immediately after processing, measures the weight Wi, diameter D, and length L of the stub timber with an IC tag attached.

[0026] The felling contractor then inputs information into the daily report and the IC tag via a personal computer (for example, a notebook PC or tablet PC). The information entered into the daily report via the personal computer is transferred to the felling server 70 and stored therein.

[0027] The felling server 70 also derives the initial moisture content Xi (%) of the short-stem timber based on the weight Wi, diameter D, length L, and tree species of the short-stem timber to which the IC tag is attached. In this embodiment, the felling server 70 derives the initial moisture content Xi of the short-stem timber based on the following formulas (1) to (3). Volume Ms (m 3 ) = (average value of diameter D ÷ 2 ÷ 100) 2 × length L × π … formula (1) Weight when completely dry Wzs (kg) = Specific gravity when completely dry Z (kg / m 3 ) × volume Ms … Equation (2) Initial moisture content Xi = [weight Wi - weight when completely dry Wzs] ÷ weight when completely dry Wzs × 100 … Equation (3) The absolute dry density Z is a characteristic value of each tree species. For example, the absolute dry density Z of Japanese cedar is 0.38 (kg / m 3 ).

[0028] The felling server 70 then stores the derived initial moisture content Xi as the initial moisture content Xi of the entire short stem material that constitutes the collection unit.

[0029] The shipping server 80 is provided at a shipper who ships short stems from the city yard 30 to the wood utilization facility 40. The shipping server 80 holds the state of the placement location of the short stems at the city yard 30, the storage state of the short stems at the city yard 30, the presence or absence of air conditioning at the city yard 30, the date on which the short stems were received from the mountain yard 20 (receiving date), and the date on which the short stems are shipped to the wood utilization facility 40 (shipping date). The state of the placement location is, for example, asphalt, concrete, crushed stone (with drainage mechanism), or soil.

[0030] In addition to the receipt date and the shipping date, the shipper may use a contact moisture meter to measure the moisture content of the surface of the short stem timber to which an IC tag is attached (hereinafter referred to as "surface moisture content") at predetermined intervals (for example, once a month) during the drying period between the receipt date and the shipping date. The surface moisture content measured by the contact moisture meter is stored in the shipping server 80.

[0031] The utilization facility server 90 is provided in the wood utilization facility 40. In the wood utilization facility 40, the weight Wf(t) of one trailer truck of short stems transported from the lumber yard 30 and the total number of short stems loaded on one trailer truck are measured (truck weight check). The utilization facility server 90 then derives the final moisture content Xf(%) on the day the short stems are transported to the wood utilization facility 40 (transportation date) based on the measured weight Wf of one trailer truck of short stems and the total number of short stems loaded on one trailer truck, as well as the diameter D, length L, and tree species associated with the IC tag. In this embodiment, the utilization facility server 90 derives the final moisture content Xf based on the above formula (1) and the following formulas (4) and (5). Absolutely dry weight Wzt(t) = Absolutely dry specific gravity Z(kg / m 3 ) × volume Ms × total number … Equation (4) Final moisture content Xf = [weight Wf - weight when dry Wzt] ÷ weight when dry Wzt × 100 … Equation (5)

[0032] The central control unit 120 is composed of a semiconductor integrated circuit including a CPU (Central Processing Unit). The central control unit 120 reads out programs and parameters for operating the CPU itself from the ROM. The central control unit 120 manages and controls the entire drying period estimation device 100 in cooperation with a RAM as a work area and other electronic circuits.

[0033] The memory 130 is composed of a ROM, a RAM, a flash memory, a HDD, etc. The memory 130 stores programs used by the central control unit 120 and various data.

[0034] In this embodiment, the central control unit 120 also functions as an information acquisition unit 210, an estimation unit 220, and a machine learning unit 230.

[0035] The information acquisition unit 210 acquires meteorological information (temperature, humidity, weather, wind direction, wind speed, and sunshine hours) from the weather server 60. The information acquisition unit 210 also acquires information indicating the felling date, tree species, diameter D, length L, the presence or absence of bark, and the initial moisture content Xi from the felling server 70 for each collection unit. The information acquisition unit 210 also acquires information indicating the state of the placement location of the short-stem lumber in the lumber yard 30, the storage state of the short-stem lumber in the lumber yard 30, the presence or absence of air conditioning in the lumber yard 30, the acceptance date, the shipping date, and the surface moisture content from the shipping server 80. The information acquisition unit 210 also acquires information indicating the final moisture content Xf from the utilization facility server 90.

[0036] Then, the information acquisition unit 210 creates measurement data for each accumulation unit. Fig. 3 is a diagram for explaining the measurement data. As shown in Fig. 3, the measurement data includes the felling date, tree species, diameter D, length L, presence or absence of bark, initial moisture content Xi, and weight Wi obtained from the felling server 70, the state of the placement location, storage state, presence or absence of air conditioning, surface moisture content on the day of receipt, surface moisture content on a specified measurement date, surface moisture content on the day of shipment obtained from the utilization facility server 90, and the final moisture content Xf on the day of transportation obtained from the utilization facility server 90.

[0037] The information acquisition unit 210 associates the measurement data with meteorological information for the period from the felling date indicated in the measurement data to the transportation date of the wood utilization facility 40, and stores the measurement data in the memory 130. In this manner, the measurement data created for each accumulation unit is stored in the memory 130 in association with the meteorological information.

[0038] Based on the initial moisture content Xi acquired by the information acquisition unit 210 and a predetermined drying rate, the estimation unit 220 estimates the period (drying period) for the moisture content of the short-stem timber to reach a predetermined target moisture content Xo in the lumber yard 30. The drying rate is derived based on the tree species, diameter D, length L, presence or absence of bark, felling time, condition of the storage location, storage manner of the short-stem timber at the storage location, and air conditioning status at the storage location of the short-stem timber.

[0039] In this embodiment, the estimation unit 220 derives the dry period K based on the following formulas (6) and (7). Drying period K = [Initial moisture content Xi (%) - Target moisture content Xo] / Drying rate (% / day)...Equation (6) Drying rate (% / day) = Initial coefficient α × P1 × P2 × P3 × P4 × P5 × P6 × P7 × P8 … Equation (7) Here, the initial coefficient α is a theoretical value for wood drying, and is, for example, 0.6. Parameters P1 to P8 are variables that contribute to the drying speed. The higher the contribution rate of parameters P1 to P8, that is, the greater the degree to which they contribute to increasing the drying speed, the larger the values ​​become.

[0040] Parameter P1 is a variable related to the tree species. FIG. 4 is a diagram for explaining an example of a tree species table. Parameter P1 is determined by the tree species and the tree species table. As shown in FIG. 4, in the tree species table, the largest value is determined when the tree species is cedar. Also, in the tree species table, a smaller value is determined when the tree species is cypress than when the tree species is cedar. In the tree species table, a smaller value is determined when the tree species is larch than when the tree species is cedar and a larger value is determined when the tree species is cypress.

[0041] Parameter P2 is a variable related to the diameter D of the wood. FIG. 5 is a diagram for explaining an example of a diameter table. Parameter P2 is determined by the diameter D and the diameter table. As shown in FIG. 5, in the diameter table, the smaller the diameter D is, the larger the value determined. In other words, in the diameter table, the larger the diameter D is, the smaller the value determined.

[0042] Parameter P3 is a variable related to the length L of the wood. Fig. 6 is a diagram illustrating an example of a length table. Parameter P3 is determined by the length L and the length table. As shown in Fig. 6, in the length table, the shorter the length L, the larger the value determined. In other words, in the length table, the longer the length L, the smaller the value determined.

[0043] Parameter P4 is a variable related to the presence or absence of bark. Fig. 7 is a diagram for explaining an example of a bark table. Parameter P4 is determined by the presence or absence of bark and the bark table. As shown in Fig. 7, in the bark table, a smaller value is determined when bark is present than when bark is absent.

[0044] Parameter P5 is a variable related to the time of felling of the timber. The moisture content (%) of the timber in the lumberyard 30 was measured and the trends were summarized as follows. Note that the lumberyard 30 was placed on a concrete floor when the measurements were taken. Furthermore, the timber was stored in the lumberyard 30 in a flat pile.

[0045] FIG. 8 is a diagram for explaining the transitions of moisture content, temperature, and humidity of wood in the lumber yard 30 when felling occurs in winter. FIG. 9 is a diagram for explaining the transitions of moisture content, temperature, and humidity of wood in the lumber yard 30 when felling occurs in spring. FIG. 10 is a diagram for explaining the transitions of moisture content, temperature, and humidity of wood in the lumber yard 30 when felling occurs in summer. FIG. 11 is a diagram for explaining the transitions of moisture content, temperature, and humidity of wood in the lumber yard 30 when felling occurs in autumn. In FIG. 8 to FIG. 11, the left vertical axis indicates the moisture content (%) and humidity (%) of wood, and the right vertical axis indicates the temperature (°C). In FIG. 8 to FIG. 11, the horizontal axis indicates the date. In FIG. 8 to FIG. 11, a circle indicates moisture content, a triangle indicates the average temperature over 10 days, and a square indicates the average humidity over 10 days. As described above, after being felled, the short stems are stored in the mountain yard 20 for a predetermined period (for example, about 140 days) and then transported from the mountain yard 20 to the street yard 30. For this reason, the moisture content of the short stems on the day they are received at the street yard 30 is lower than their initial moisture content.

[0046] As shown in Figure 8, it was found that when the felling season is winter (for example, from December to February), the moisture content of the timber on the day it is received at the street lumber yard 30 is low, at around 140%. Also, as described above, timber is stored in the mountain lumber yard 20 for around four months, so when the felling season is winter, the temperature at the street lumber yard 30 is high during the storage period there (from early June to early September). For this reason, when the felling season is winter, the period from when the timber is received at the street lumber yard 30 until it reaches the target moisture content Xo (here, 25%) is short (around 80 days in Figure 8).

[0047] Furthermore, as shown in Figure 9, when felling occurs in the spring (for example, from March to May), the moisture content of the timber on the day it is received at the lumber yard 30 is high at around 200%, but in the early part (mid-August) of the storage period at the lumber yard 30 (from mid-August to mid-November), the temperature at the lumber yard 30 is higher than when felling occurs in the winter. For this reason, when felling occurs in the spring, the period from receipt at the lumber yard 30 until the target moisture content Xo is reached is the shortest (around 70 days in Figure 9).

[0048] Furthermore, as shown in Figure 10, when felling occurs in summer (e.g., from June to August), the moisture content of the timber on the day it is received at the lumber yard 30 is low at around 160%, but the temperature at the lumber yard 30 during its storage period (from mid-November to mid-February) is lower than when felling occurs in winter. For this reason, when felling occurs in summer, the period from receipt at the lumber yard 30 until the lumber reaches the target moisture content Xo is longer than when felling occurs in winter (around 86 days in Figure 10).

[0049] Furthermore, as shown in Figure 11, when felling occurs in the fall (for example, from September to November), the moisture content of the timber on the day it is received at the lumber yard 30 is high at around 210%, and the temperature at the lumber yard 30 during its storage period (from early January to early April) is lower than when felling occurs in the winter. For this reason, when felling occurs in the fall, the period from receipt at the lumber yard 30 until the target moisture content Xo is reached is the longest (around 90 days in Figure 11).

[0050] Therefore, the parameter P5 is set based on the result of the felling time. Fig. 12 is a diagram for explaining an example of the felling time table. The parameter P5 is determined by the felling time and the felling time table. As shown in Fig. 12, in the felling time table, the felling times determined to have larger values ​​in the order of autumn, summer, winter, and spring.

[0051] Parameter P6 is a variable related to the state of the placement location of the short stems in the landslide yard 30. Fig. 13 is a diagram illustrating an example of a location state table. Parameter P6 is determined based on the state of the placement location of the short stems and the location state table. As shown in Fig. 13, in the location state table, the largest values ​​are determined in the order of soil, crushed stone paving, concrete paving, and asphalt paving.

[0052] Parameter P7 is a variable related to the storage manner of short stems in the landslide yard 30. Parameter P7 is determined by the storage manner of short stems and a storage manner table. Figure 14 is a diagram illustrating an example of a storage manner table. As shown in Figure 14, in the storage manner table, a larger value is determined when the storage manner of short stems is flat stacked than when the stems are piled. Also, in the storage manner table, when the storage manner of short stems is piled, a smaller value is determined as the number of short stems in the pile increases.

[0053] Parameter P8 is a variable related to the presence or absence of air conditioning in the street land lot 30. Parameter P8 is determined based on the presence or absence of air conditioning and an air conditioning table. Fig. 15 is a diagram for explaining an example of the air conditioning table. As shown in Fig. 15, in the air conditioning table, a larger value is determined when air conditioning is present than when air conditioning is not present.

[0054] The machine learning unit 230 corrects the parameters P1 to P8 by machine learning, based on the measurement data accumulated in the memory 130 by the information acquisition unit 210 and past weather information at the time the measurement data was acquired.

[0055] Fig. 16 is a diagram for explaining an image of the drying period K derived by the estimation unit 220. When the parameters P1 to P8 are corrected by the machine learning unit 230, the drying speed derived by the above formula (7) is corrected. As a result, the slope of the moisture content shown in Fig. 16 is corrected. By including the machine learning unit 230, the estimation unit 220 can estimate the drying period K with high accuracy.

[0056] [Drying period estimation method] Next, a drying period estimation method using the drying period estimation device 100 will be described. FIG. 17 is a flowchart showing the process flow of the drying period estimation method according to this embodiment. As shown in FIG. 17, the drying period estimation method includes a wood information acquisition step S110, a storage information acquisition step S120, a drying rate derivation step S130, and an estimation step S140. Each step will be described below. The drying period estimation method is started, for example, on the day when the shipper receives short stem lumber from the mountain lumber yard 20 to the city lumber yard 30.

[0057] [Wood information acquisition process S110] The information acquisition unit 210 acquires the identification information of the IC tag attached to one of the short-stem timbers of the accumulation unit transported to the lumber yard 30. The information acquisition unit 210 then acquires from the felling server 70 information indicating the felling date, the tree species of the short-stem timber, the diameter D, the length L, the presence or absence of bark, and the initial moisture content Xi, which are associated with the identification information of the IC tag.

[0058] [Storage information acquisition process S120] The information acquisition unit 210 acquires from the shipping server 80 the state of the placement location of the short stem lumber at the lumber yard 30, the storage conditions of the short stem lumber at the lumber yard 30, and whether or not the lumber yard 30 is air-conditioned.

[0059] [Drying rate derivation step S130] The estimation unit 220 determines the parameter P1 based on the tree species acquired in the wood information acquisition step S110 and the tree species table (see FIG. 4).

[0060] The estimation unit 220 also determines a parameter P2 based on the diameter D acquired in the wood information acquisition step S110 and the above-mentioned diameter table (see FIG. 5).

[0061] The estimation unit 220 determines the parameter P3 based on the length L acquired in the wood information acquisition step S110 and the above-mentioned length table (see FIG. 6).

[0062] Furthermore, the estimation unit 220 determines a parameter P4 based on the presence or absence of bark acquired in the wood information acquisition step S110 and the bark table (see FIG. 7).

[0063] The estimation unit 220 determines the parameter P5 based on the felling date (felling time) acquired in the wood information acquisition step S110 and the felling time table (see FIG. 12).

[0064] Furthermore, the estimation unit 220 determines a parameter P6 based on the state of the storage location of the short stems acquired in the storage information acquisition step S120 and the location state table (see FIG. 13).

[0065] The estimation unit 220 determines the parameter P7 based on the storage state of the short stems in the landslide yard 30 acquired in the storage information acquisition step S120 and the storage state table (see FIG. 14).

[0066] Furthermore, the estimation unit 220 determines the parameter P8 based on the presence or absence of air conditioning in the landslide yard 30 acquired in the storage information acquisition step S120 and the air conditioning table (see FIG. 14).

[0067] Then, the estimation unit 220 derives the drying speed using the determined parameters P1 to P8 and the above formula (7).

[0068] [Estimation process S140] The estimation unit 220 acquires the target moisture content Xo from the utilization-facility server 90. Then, the estimation unit 220 derives the drying period K using the above formula (6) based on the initial moisture content Xi acquired in the wood information acquisition step S110, the drying rate derived in S130, and the target moisture content Xo.

[0069] The estimation unit 220 stores the information indicating the dry period K in the memory 130 in association with the identification number of the IC tag.

[0070] The estimation unit 220 then notifies the user when the drying period K has elapsed since the day the short stem timber was received from the mountain yard 20 to the city yard 30, that is, since the day the wood information acquisition step S110 was executed.

[0071] As described above, the drying period estimation device 100 according to this embodiment can estimate the drying period K until the target moisture content Xo is reached based on the initial moisture content Xi. Therefore, the drying period estimation device 100 makes it possible to ship short-stem timber with the target moisture content Xo to the wood utilization facility 40 at the lumber yard 30 simply by knowing the period of time that has passed since the felling date, without having to measure the moisture content of the short-stem timber at the time of shipment.

[0072] As described above, the drying speed used to derive the drying period K is derived based on parameter P1 (tree species), parameter P2 (diameter D), parameter P3 (length L), parameter P4 (presence or absence of bark), parameter P5 (cutting time), parameter P6 (condition of the placement location), parameter P7 (storage mode), and parameter P8 (presence or absence of air conditioning). This allows the drying period estimation device 100 to derive the drying speed with high accuracy.

[0073] Although one embodiment has been described above with reference to the accompanying drawings, it goes without saying that the present disclosure is not limited to the above embodiment. It is clear that a person skilled in the art can think of various modified or altered examples within the scope of the claims, and it is understood that these also naturally belong to the technical scope of the present disclosure.

[0074] For example, in the above embodiment, the felling server 70 derives the initial moisture content Xi based on the above formulas (1) to (3). However, the felling server 70 may hold a table in which the initial moisture content Xi is associated with the weight Wi, diameter D, length L, and tree species of the short stem, and may refer to the table to extract the initial moisture content Xi based on the weight Wi, diameter D, length L, and tree species of the short stem.

[0075] Similarly, the utilization facility server 90 may store a table in which the final moisture content Xf is associated with the weight Wf, diameter D, length L, and tree species of the short stem, and by referring to the table, extract the final moisture content Xf based on the weight Wf, diameter D, length L, and tree species of the short stem.

[0076] In the above embodiment, the estimation unit 220 uses the diameter D as the thickness of the short stem. However, the estimation unit 220 may use the radius or cross-sectional area of ​​the short stem as the thickness of the short stem.

[0077] In the above embodiment, the estimation unit 220 derives the drying speed based on the presence or absence of air conditioning. However, the estimation unit 220 may derive the drying speed based on the state of air conditioning, such as the wind speed and temperature.

[0078] In the above embodiment, the estimation unit 220 derives the drying rate based on the short-stem tree's species, diameter D, length L, presence or absence of bark, felling time, state of the storage location, storage manner, and presence or absence of air conditioning at the storage location. However, it is sufficient for the estimation unit 220 to derive the drying rate based on at least one or more of the short-stem tree's species, diameter D, length L, presence or absence of bark, and felling time.

[0079] In the above embodiment, the drying period estimation device 100 and the shipping server 80 are separate entities. However, the drying period estimation device 100 and the shipping server 80 may be integrated. [Industrial Applicability]

[0080] The present disclosure can be used in a dry period estimation device. [Explanation of symbols]

[0081] 100 Drying period estimation device 210 Information Acquisition Department 220 Estimation Department 230 Machine Learning Department

Claims

1. An information acquisition unit that acquires the initial moisture content of felled timber; a machine learning unit that corrects a predetermined drying speed by machine learning based on the species of the wood, the thickness of the wood, the length of the wood, the presence or absence of bark on the wood, the harvest time of the wood, one or more of the initial moisture content, the final moisture content, and the period from the initial moisture content to the final moisture content, and meteorological information of a storage location of the wood during the period from the initial moisture content to the final moisture content; an estimation unit that estimates a period for the moisture content of the wood to reach a target moisture content based on the acquired initial moisture content and the corrected drying speed; A drying period estimation device comprising:

2. The drying period estimation device according to claim 1, wherein the predetermined drying speed is derived based on one or more of the species of the wood, the thickness of the wood, the length of the wood, the presence or absence of bark on the wood, and the time of harvesting of the wood.

3. The drying period estimation device according to claim 2, wherein the predetermined drying speed is derived based on one or more of the condition of the location where the wood is placed, the storage manner of the wood in the storage location, and the air conditioning state in the storage location.

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