JP6920729B2 - Moisture content estimation method for wood and its equipment - Google Patents

Description

The present invention relates to a moisture content estimation method and an apparatus for estimating the moisture content of wood.

From the aspect of conservation of forest resources, it is desired to promote effective use of domestic timber as a structural member for wooden houses. When using new wood for a new house, if the wood is not completely or dried to a certain extent, it will cause distortion of the building after construction, so it is used under the Building Standards Act. The moisture content of the wood is determined accordingly. Therefore, it is desirable to be able to evaluate the moisture content of wood at various stages of logging, sawing or final products.

There are various methods for measuring the water content of wood, and devices and appliances corresponding to the methods are commercially available.

The electric resistance method utilizes the fact that wood exhibits a resistance value according to the moisture content when a high voltage is applied between needle-shaped probes. The probe is needle-shaped and has four configurations, and the resistance value of the surface layer portion is measured by driving the probe into the sample with a hammer and energizing it. Since the value measured by this method is affected by the tree species, it is premised that the tree species is known in advance (see, for example, Japanese Patent Application Laid-Open No. 11-304741).

The high-frequency method utilizes the fact that the attenuation rate of high-frequency waves differs depending on the water content of wood, but it is affected by the thickness and density of the material, and these measurements must also be performed (for example, special features). See Open 2010-237135).

In the infrared method, since infrared rays are absorbed by water, the sample is irradiated with infrared rays to measure its reflectance. Naturally, the higher the water content, the smaller the reflection intensity.

The drying method is to cut out a sample portion from a raw material, dry it (20 g or more in JAS), and obtain the water content from the weight before and after drying (see, for example, JP-A-11-148892).

Japanese Unexamined Patent Publication No. 11-304741 Japanese Unexamined Patent Publication No. 11-148892 Japanese Unexamined Patent Publication No. 2010-237135

Since the electric resistance method pierces the sample with a needle-shaped probe, it has the drawback of damaging the sample, and it is possible to measure only the ^{periphery (about 3 cm 2) of the part where the probe is in contact, and the entire wood.} It is not possible to measure the water content of. Moreover, since the measurement result depends on the tree species, it cannot be measured with a sample for which the tree species is unknown.

Since the high-frequency method increases the size of the device and depends on the thickness and density, it is necessary to obtain those values separately. There are cases where the measurement is performed by high frequency reflection and cases where the measurement is performed by transmission. In either case, only the peripheral portion of the probe to which the high frequency is applied or the partial measurement in the thickness direction of the sample through which the high frequency is transmitted is performed.

Both of the above two methods use a handy type probe and the measurement work is relatively easy, so they are used in many sites such as wood processing factories to obtain a rough moisture content. However, there is an error depending on the equipment used, and the measured values may differ significantly between the measuring methods, which has a drawback of inferior reliability.

The infrared method is effective for measuring the water content of a thin sample or the surface of a sample as described above, but has a drawback that the water content inside a thick sample cannot be measured.

Further, although the drying method has high accuracy, it is a destructive inspection in which a sample piece is cut out from a material, and it takes time to dry, and of course, it is necessary to measure the weight before and after drying. In addition, there is a drawback that continuous measurement cannot be performed at the site of sawing or use.

The present invention has been proposed in view of the above-mentioned conventional circumstances, and an object of the present invention is to provide a method and an apparatus capable of estimating the water content of the entire sample in a non-destructive manner with a simple apparatus.

The present invention employs the following means in order to achieve the above object.

First, from the database of the water content of wood and the propagation velocity of stress waves (hereinafter sometimes referred to simply as the propagation velocity), the probability of the negative side of the bivariate on the coordinate plane of "moisture content-propagation velocity function" is zero. An equation representing a probability distribution curved surface having the probability density as the vertical axis is obtained together with its parameters. In the above state, obtains the propagation velocity C ₀ wood to be measured, from the propagation speed C _0, the probability distribution and the plane perpendicular to the coordinate plane of the straight line corresponding to the propagation velocity C ₀ on the coordinate plane The estimated value of the water content is obtained from the peak points obtained from the above parameters of the intersection curve of the curved surface.

The above method can be realized by using the following device including a propagation speed measuring means, a storage means, and an estimated value calculation means.

Probability distribution with the probability density on the negative side of the bivariate as the vertical axis on the coordinate plane of "moisture content-function of propagation velocity" from the database of moisture content and propagation velocity of wood as the storage means. Store the expression representing the curved surface together with its parameters.

The propagation velocity measuring means obtains the stress wave propagation velocity C _{0 of the wood to be measured.} Also, the estimated value calculation means, from the propagation speed C _0, a plane perpendicular to the coordinate plane of the straight line corresponding to the propagation velocity C ₀ on the coordinate plane with the交曲line of the probability distribution curved surface, from the parameter _{The estimated value y 0} of the water content is obtained from the obtained peak point.

The probability distribution curved surface is a curved surface in which the probability on the minus side is zero. A bivariate lognormal distribution, a gamma distribution, a Poisson distribution, or the like can be used as this kind of probability distribution. Each parameter of the equation representing the bivariate lognormal distribution is obtained by the Hamiltonian Monte Carlo method. Further, as a function of the propagation velocity, the square of the reciprocal of the propagation velocity is adopted in the following example.

The moisture content of wood can be easily estimated in a non-destructive manner simply by determining the stress wave propagation velocity of the wood to be measured by the above method, and since the probability distribution is used, the credible interval of the moisture content is also available. Can be calculated. Further, the measurement can be made continuous, and there is an effect that it can be used at the production site and the use site of wood products.

Moisture content measuring device used in the present invention. Probability distribution curve of moisture content MC and propagation velocity C of wood. Probability distribution curve by bivariate normal distribution function. Probability distribution curve by bivariate lognormal distribution function. The figure which shows the error between the estimation by this invention and a true value.

<Principle>
The water content of wood includes a region affected by water bound to the fibrous tissue (bound water) and a region in which water remains as free water even in the cell tissue. The former is a phenomenon in a region where the water content is low, and the Young's modulus increases (strength increases) as the water content decreases, but the increase or decrease in free water does not affect the Young's modulus. The branching point of the form of water contained in wood is called FSP, and the moisture content is approximately 28%. From this simple model of the water content morphology and the water content dependence of Young's modulus, it can be seen that the water content is proportional to the square of the reciprocal of the propagation velocity above FSP. This fact is used below.

Applicants utilize the fact that the relationship of E = v ² ρ (v: propagation velocity of stress waves) holds between Young's modulus E and density ρ, and the Young's modulus E-density ρ plane of a large number of wood samples. A special method is to take the density distribution curved surface of the existence probability (density) above and determine the Young's modulus and density of the sample at the same time from the intersection curve of the curved line and the plane perpendicular to the coordinate plane of the straight line corresponding to the above equation. Proposed in Application 2016-193588.

The fact that the moisture content and Young's modulus have a correlation as described above suggests that the moisture content of wood has some relationship with the stress wave propagation velocity.

Therefore, using the bivariate lognormal distribution, a curved surface of the probability density of a large number of data on the coordinate plane of the "moisture content-propagation velocity function" of the wood sample is created, and the propagation velocity of a specific wood sample is created. The following attempts are made to estimate the water content from _{C 0.}

Here, as a function of the propagation speed, the square of the reciprocal of the propagation speed C is adopted in the following description, and the reason is as described above. The reason for adopting the bivariate lognormal distribution will be described later.

<Probability curved surface>
FIG. 2A shows a scatter diagram of the moisture content and the propagation velocity based on a clear database of the moisture content MC (%) of wood and the propagation velocity C (m / s) of the stress wave.

In the present invention, it is premised that the parameters of the probability distribution are determined by using the Hamiltonian Monte Carlo method. In order to adopt the bivariate normal distribution as a function form of the well-known probability distribution by this method, it is desirable that the dispersal state can be linearly approximated.

From the scatter plot of FIG. 2 (a), when a conversion that can obtain a scatter state that can be linearly approximated is attempted, as described above, the square of the reciprocal of the water content-propagation velocity (C- ² ) (unit is s ² / m ^2). ), As shown in FIG. 2 (b), a substantially linear scatter plot can be obtained. However, if the square of the reciprocal of the propagation speed (C- ² ) is expressed as it is, it will be a very small value, so it is multiplied by ^{10 -8.}

Further, FIG. 3 is a probability distribution diagram based on a bivariate normal distribution with the axis perpendicular to the coordinate plane of the "moisture content-propagation velocity function" as the probability axis from the scatter diagram shown in FIG. 2 (b). .. In the state of FIG. 3, since the water content MC also exists in the negative region (see the arrow in FIG. 3), it is inconvenient to use the bivariate normal distribution function as the distribution function. Therefore, the bivariate lognormal distribution function shown in Eq. (1) below is adopted as the distribution function. As a result, the probability distribution map shown in FIG. 4 can be obtained. The parameters that determine the specific form of the above two probability distribution functions can be obtained by applying the Hamiltonian Monte Carlo method of Bayesian statistics.

Here, μ is the mean, σ is the standard deviation, and R is the correlation coefficient. The subscripts x and y indicate their attributes (that is, x is the propagation speed and y is the water content).

_{The five parameters μ x} , μ _y , σ _x , σ _y , and R of the above equation (1) can be obtained by the Hamiltonian Monte Carlo method (HMC method) of Bayesian statistics, and the specific probability distribution function equation (1) , (2) is applied and the results obtained are shown in Table 1.

When the probability distribution curved surface of the square of the reciprocal of the water content-propagation velocity C is drawn based on the equation (1) in which the parameters are determined as described above, it becomes as shown in FIG. 5 (a) as in FIG. Here, the propagation velocity C ₀ for a specific sample is measured, and the square of the inverse C ₀ ^-2 = a plane raised perpendicularly to the square coordinate plane of the reciprocal of the water content-propagation velocity from a constant straight line ( The position of the peak (d) of the intersection curve (c) between b) and the stochastic curved surface is the estimated water content y _{0 obtained} for the specific sample.

Here, the position of the peak is given by the following equation (3).

y: Obtained water content, x: Square of the reciprocal of propagation velocity x 10 ^-8
Table 2 shows the estimated value of the water content calculated by the above method based on the propagation speed measured for a plurality of samples. For comparison, the moisture content obtained by the drying method is also shown.

Further, since the probability distribution is used, the credible interval for the water content obtained as described above can be calculated, and Table 2 shows the 70% credible interval. Here, taking sample No. 153 as an example, it means that it is possible to say that "the water content is 34.9% or less with a probability of 85%."
That is, the water content can be expressed in another way using the upper limit of the credible interval.

FIG. 1 shows an example of a water content estimation device according to the present invention. Basically, it is composed of a propagation speed measuring means 10, a storage means 20, and an estimated value calculating means 30.

The propagation velocity measuring means 10 includes a pair of needle-shaped probes 11 and 11, and the two probes 11 and 11 are driven into a specific sample at a predetermined distance, and one probe 11 is not shown as a hammer or the like. When hit with, the time from the detection of the impact sound by the one probe 11 to the detection of the impact sound by the other probe 11 is measured. As a result, the stress wave propagation velocity C ₀ propagating the wood by the propagation velocity measuring means 10 can be obtained.

The propagation velocity C ₀ of the specific sample thus obtained is input to the estimated value calculation means 30. On the other hand, in the storage means 20, the stochastic curved surface is stored in advance as the equation (1) and five parameters, and the equation (3) for obtaining the peak position (moisture content) is also stored.

In this state, when the stress wave propagation velocity C ₀ is obtained from the propagation velocity measuring means 10, the estimated value calculation means 30 reads out the equation (3) and the five parameters from the storage means 20 and sets them at the peak position. The corresponding moisture content y ₀ will be obtained. The water content y ₀ thus obtained is displayed on the display unit 40.

In addition to the above, there is a tapping method as a means for measuring the propagation speed.

That is, when one end of the wood as a sample is hit with a hammer, the sample vibrates vertically at the natural frequency f of the sample. The relationship between the natural frequency f and the stress wave propagation velocity C is C = 2Lf, where L is the length of the sample. Therefore, the stress wave propagation velocity can be obtained by obtaining the natural frequency.

In the above, the square of the reciprocal of the stress wave propagation velocity is used as one axis of the probability distribution curve, but if it is a function that can obtain a linear approximation with the water content of the other axis, stick to this. It's not a thing. In addition, although a bivariate lognormal distribution is adopted as the probability distribution, it is not limited to this, and the probability on the minus side is zero regardless of any element of the two variables, for example, a gamma distribution. , Poisson distribution, etc. can be used.

As described above, the present invention can obtain a practical level of water content of wood only by obtaining the propagation speed, and since the probability distribution curve is used, the credible interval for the obtained water content is also available. It will be possible to calculate. Therefore, it is considered that the utility value at production sites and distribution sites that use wood resources is great.

11 ... Probe 10 ... Propagation speed measuring means 20 ... Storage means 30 ... Estimated value calculation means 40 ... Display unit

Claims (10)

From the database of water content and stress wave propagation velocity of wood, the probability density at which the probability of the minus side of the bivariate on the coordinate plane of "moisture content-propagation velocity function" becomes zero is defined as the axis perpendicular to the plane. Steps to find the formula representing the probability distribution plane together with its parameters,
Steps to find _{the propagation velocity C 0} of the wood to be measured,
From the propagation velocity C ₀ , the water content is higher than the peak point obtained from the parameter of the intersection curve of the plane perpendicular to the coordinate plane of the straight line corresponding to the propagation velocity C _{0 on the coordinate plane and the probability distribution curved surface.} Steps to get an estimate and
A method for estimating the moisture content of wood, which is characterized by being equipped with. The method for estimating the moisture content of wood according to claim 1, wherein in addition to the estimated value of the moisture content, the credit interval of the value is obtained. The method for estimating the water content of wood according to claim 1, wherein the square of the reciprocal of the stress wave propagation velocity is used as a function of the stress wave propagation velocity. The method for estimating the water content of wood according to claim 1, which uses an equation representing a bivariate lognormal distribution as a probability distribution in which the probability of the negative side of the bivariate becomes zero. The method for estimating the water content of wood according to claim 4, wherein each parameter of the bivariate lognormal distribution is obtained by the Hamiltonian Monte Carlo method. From the wood moisture content and propagation velocity database, the probability distribution on the coordinate plane of "moisture content-propagation velocity function" with the probability density at which the probability of the negative side of the bivariate is zero is the axis perpendicular to the plane. A storage means that stores the expression representing the curved surface together with its parameters,
Propagation velocity measuring means for obtaining the stress wave propagation velocity C _{0 of the wood to be measured,}
An estimated value calculation means for obtaining an estimated value of the water content from the propagation velocity C _{0 and the peak point on the probability distribution curved surface obtained from the parameter.}
A wood moisture content estimation device characterized by being equipped with. The wood moisture content estimation device according to claim 6, wherein in addition to the moisture content estimation value, a credit interval of the value is obtained. The wood water content estimation device according to claim 6, wherein the square of the reciprocal of the stress wave propagation velocity is used as a function of the stress wave propagation velocity. The wood water content estimation device according to claim 6, wherein the equation representing the bivariate lognormal distribution is used as the probability distribution in which the probability on the negative side of the bivariate becomes zero. The wood water content estimation device according to claim 9, wherein each parameter of the bivariate lognormal distribution is obtained by the Hamiltonian Monte Carlo method.

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