JPS637317B2 - - Google Patents

Description

[Detailed Description of the Invention] This invention detects cracks that occur when wood is dried by detecting elastic waves (AE) that occur due to structural changes in the wood that occur prior to the wood cracking. Foretell by
The present invention relates to a wood dry crack prediction and prevention device for preventing dry cracks based on this information.

As is well known, wood is generally sawn and dried, and when drying the sawn wood, the sawn wood is piled up in piles and dried in the sun, a so-called natural drying process. The reasons why natural drying is necessary are: (1) If wood with a high moisture content is used, it will gradually dry out, shrink, and become distorted. (2) Lowering the water content can improve various strength properties, processability, paintability, and adhesion. Examples include.

On the other hand, in recent years, apart from natural drying, artificial drying has been gaining importance for the following reasons. That is, artificial drying requires (1) high dimensional accuracy when making wood products, and to meet this requirement, it is necessary to dry any sawn wood to a predetermined degree of dryness. (2) Adhesive processing is often required, and sufficiently dry materials are required. (3) In order to perform mass production, it is necessary to dry a large amount of wood by significantly shortening the drying period. This is a drying method that emerged from the background of Its special feature is that it can adjust the humidity and dry evenly in a short period of time.

However, in artificial drying, where drying conditions are set strictly, once an initial crack, which is a brittle fracture, occurs in the wood at the early stage of the drying process, the crack tends to easily extend. This tendency is remarkable with expensive furniture materials, and cracked materials often become unusable and suffer great damage.

Therefore, it has traditionally been desired to predict the occurrence of initial cracks in-process without interrupting the drying process, and if prediction is possible, the drying conditions can be changed (mitigated) based on the prediction to prevent the occurrence of initial cracks. This means that drying can be achieved reliably to the target dry state.

Therefore, the present inventor investigated the elasticity that occurs due to microscopic changes in the wood structure, which is a precursor to brittle fracture that occurs prior to the occurrence of cracks that occur during the early drying process when wood is dried, that is, initial cracks. Wave (acoustic emission: hereinafter AE)
It is possible to predict early cracks by focusing on the This invention was conceived based on the idea that dry cracking could be prevented.

In other words, this invention detects AE that occurs due to microscopic changes in the wood structure, which is a precursor to brittle fracture that occurs before initial cracks occur during wood drying, and converts it into an electrical signal. To provide a dry crack prediction and prevention device for wood, which can predict initial cracks in-process without interrupting drying work, and prevent dry cracks in wood.

Therefore, in order to achieve this object, the wood dry crack prediction and prevention device of the present invention is a wood dry crack prediction device that can detect in advance the wood cracks that occur when drying the wood. A detector is mounted in close acoustic contact to detect elastic waves generated by changes in the wood structure that occur prior to wood cracking due to drying, and converts it into an electrical signal. a signal processing device that processes signals from the detector to detect changes in wood structure; and a temperature/humidity control device that controls temperature and humidity around the wood based on at least the signals processed by the signal processing device. It is characterized by comprising the following.

The present invention will be described below based on illustrated embodiments.

FIG. 1 shows a wood drying crack prediction and prevention device according to the present invention, which predicts and prevents drying cracks in materials to be dried in a wood dryer. 1 in the figure is a wood dryer, and inside this wood dryer 1 there is a heater 2,
It has a humidifier 3 and a dehumidifier 4. A plate-shaped material W to be dried is placed inside the wood dryer 1. The material W to be dried is, for example, a tree species such as Quercus oak or walnut, and in the embodiment, raw material with grain that has not been naturally dried is used.

As shown in FIGS. 1 and 2, an AE sensor 7 is attached to the center of the upper surface of the material to be dried W in close acoustic contact with an adhesive coating 6 made of, for example, silicone grease. . This AE sensor 7 is a detector that detects AE (elastic waves) generated due to microscopic changes in the wood structure that occur prior to the initial cracking that occurs in the early stage of the drying process of wood, and converts it into an electrical signal. , piezoelectric vibrators such as lead zirconate titanate piezoelectric ceramics are used.
If its resonant frequency is 536KHz or
It is designed for 143.8KHz etc.

The AE sensor 7 detects AE and further converts it into an AE signal S which is an electrical signal. As shown in FIG. 1, the AE signal S is sent to the wood dryer 1 through a signal processing device 8 that processes only the AE signal S that exceeds a preset threshold value to detect changes in the structure of the wood. It is designed to be input to a temperature/humidity control device 9 for controlling temperature/humidity.

Specifically, the signal processing device 8 processes the AE signal S from the AE sensor 7 through a preamplifier 10, a high-pass filter 11 (for example, a cutoff frequency of 10K),
Hz), it is counted by the counter 12 only when it exceeds the threshold value V _T set through the counter 12.
The configuration is such that the cumulative number of AE counts A _C and the AE occurrence rate A _D can be output from the microcomputer 13 that constitutes the _temperature /humidity control device 9 _. It is now entered into . Here, in the signal processing device 8 of this embodiment, as shown in FIG. 3, the level of noise N in the measurement system is V _N =0.1V or less, so the level of the threshold value V _T of the counter 12 is For example, it is set to 0.5V, and the gate time T of the signal of the counter 12 is set to, for example, 10 seconds. In addition, a high pass filter 11
The oscilloscope 14 connected between the counter 12 and the high-pass filter 11
The waveform of the AE signal S can be observed.

On the other hand, a resistance meter 15a and a thermometer 15b are connected to the material W to be dried, as shown in FIG. 1, and the electrical resistance value R [Ω] of the material W to be dried and the internal temperature T [°C] are , A/D via the A/D converter 16
The data is converted and input to the microcomputer 13. The resistance meter 15a is used to track the change over time in the electrical resistance value R [Ω] during the drying process of the material W to be dried. In other words, the degree of dryness of the material W to be dried is
Since the moisture content (Wa - Wo / Wo × 100%, Wa: weight of the material to be dried at that time, Wo: total dry weight of the material to be dried) corresponds well, the moisture content of the material to be dried depends on the atmosphere inside the wood dryer 1. It is necessary to know how the moisture content of material W changes, but the AE occurrence rate A _C in the drying process
At the same time, the material to be dried W in the wood dryer 1 is being recorded.
Since it is not possible to calculate the moisture content, which changes from moment to moment, by capturing the weight change (weight change due to moisture absorption), it is not possible to calculate the moisture content, which changes from moment to moment. The electrical resistance value R [Ω] is used. For this purpose, two brass screws with a diameter of about 1.5 mm are passed through the material W to be dried with a gap of 20 mm, and the electrical resistance value R between them is
is obtained by a resistance meter 15.

The thermometer 15b is, for example, a thermocouple thermometer that measures the temperature T [° C.] inside the material W to be dried.

Furthermore, the temperature t [°C] and humidity H [%] inside the wood dryer 1 are determined by the thermometer 17 and the hygrometer 1.
8 and the A/D converter 16, the signal is A/D converted and input to the microcomputer 13.

The temperature/humidity control device 9 receives the cumulative AE count A _C and the AE incidence rate A _D from the counter 12, and also inputs the electrical resistance value R of the material to be dried W, the internal temperature T, and the wood dryer. Information on the temperature t and humidity H in the wood dryer 1 is input via the A/ _D converter ₁₆ , and the temperature, humidity, etc. A microcomputer 13 stores a program that determines the range of control (for example, increasing the temperature by 5 degrees Celsius or decreasing the humidity by 3%) and the order of control, and the microcomputer 1.
a D/A converter 19 for D/A converting the output of No. 3;
It is composed of controllers 2a, 3a, and 4a that control the heater 2, humidifier 3, and dehumidifier 4 based on the output of a microcomputer 13.

Next, the operation of the above configuration will be explained.

First, an example of the drying process will be explained based on a diagram of the drying process of the drying work W in the wood dryer 1 (see Fig. 4).As can be seen from Fig. 4, the drying time (TIME) [h] is set to 0 to 8 hours. Temperature t inside the wood dryer 1
(TEMPERATURE) [°C] starts at 10°C, increases to 30°C after 1 hour, and is kept constant at 30°C until the 8th hour. In addition, the humidity H (HUMIDITY) [%] in the wood dryer 1 starts at 70% and changes from 1 hour after 2 hours have passed since it started at 70%.
It is lowered to 40% and held at 40% from the 2nd hour until the 6th hour, and then raised to 70% again at the 7th hour and held until the 8th hour.

Furthermore, the equilibrium moisture content EMC of the material W to be dried is
(EQUILIBRIUM MOISTURE CONTENT)
[%] takes values in 5 stages from 13.6% to 12.6 corresponding to changes in the temperature t [°C] and humidity H [%].
%, then dropped to 7.5% and then rose again to 12.6%.

Next, based on the above-mentioned diagram of the drying process, as an example, the dried material W of Quercus oak (OaK) is
We will discuss the prediction of drying cracks when dried.
Here, the AE sensor 7 used has a resonance frequency of 53.6 KHz.

The material to be dried W, which is dried according to the drying process diagram shown in FIG. 4, undergoes microscopic changes in the wood structure due to internal moisture movement prior to initial cracking and generates AE. The generated AE is converted into an AE signal S by the AE sensor 7 as shown in FIG.
It is counted by the counter 12 only when V _T is exceeded, and the cumulative AE count A _C and AE for that 10 seconds are counted.
The incidence rate A _D is input to the microcomputer 13 of the temperature/humidity control circuit 9. At this time, the temperature t and humidity H in the wood dryer 1, the electrical resistance value R of the material to be dried W, and the internal temperature T are also input to the microcomputer 13 at the same time.

Figure 5 shows the wood dryer 1 obtained as described above.
Changes in temperature t and humidity H within the drying material W
It shows the time course characteristics of the AE incidence rate A _D of Quercus Quercus (Quercus Quercus) in response to changes in the equilibrium water content EMC of Quercus Quercus (Quercus Quercus).

As shown in Figures 4 and 5, according to the diagram of the drying process described above, the temperature t in the wood dryer 1 is set to 10
After rising from ℃ to 30℃, humidity H is increased from 70% to 40%
In the dehumidification process, which accelerates the drying of the material W to be dried, the AE incidence rate A _D responds sensitively as the equilibrium moisture content EMC of the material W to be dried decreases from 12.6% to 7.5%. To increase.

And humidity H = 40% constant (equilibrium moisture content
AE occurrence rate during constant humidity process (EMC7.5% constant)
A _D is more than 10 times the AE occurrence rate A _D in the dehumidification process mentioned above, and in the humidification process where the humidity H rises again from 40% to 70% to alleviate the degree of dryness, the equilibrium moisture content EMC As the rate rises from 7.5% to 12.6%
AE incidence A _D decreases in response.

As mentioned above, the electrical resistance value R of the material to be dried W constantly increases, that is, the AE signal S reliably and noticeably detects the microscopic changes in the wood structure that occur from the dehumidification process to the humidification process when the material W is constantly being dried. It can be captured by

Therefore, at least the cumulative number of AE counts A _C
The microcomputer 13 calculates the value based on the AE occurrence rate A _D and the electrical resistance value R of the material to be dried, the internal temperature T, the temperature t in the wood dryer 1, and the humidity H. The output is D/A converted via the D/A converter 19 and sent to the controller 2.
Controls a, 3a, and 4a.

Thus, the temperature and humidity inside the wood dryer 1 are optimally controlled by the heater 2, humidifier 3, and dehumidifier 4. That is, based on the information of the cumulative number of AE counts A _C and the AE incidence rate A _D , a sign of initial cracks in the material W to be dried is detected, and the wood dryer 1 is adjusted in order to prevent initial cracks from occurring in-process during the drying process. temperature inside,
Optimally control humidity and change drying schedule.
This will prevent the occurrence of initial cracks.

The above is the first embodiment of the present invention, but in actual wood drying sites where a large number of wood boards are dried at once, multiple wood boards are used as shown in the second embodiment shown in FIG. If a dry crack prediction and prevention device is installed, the prediction and prevention will be improved. However, here, parts having the same functions as those in FIG. 1 are denoted by the same reference numerals.

That is, the drying chamber 100 shown in FIG. 6 is, for example, equipped with a heater (not shown) on the ceiling side and a fan F for circulating hot air on one side. A large number of materials to be dried W piled up in
It is designed to be dried by hot air sent by the In this large number of materials W to be dried, there is a part P 1 facing the fan F where the hot air flows relatively well and the degree of drying progresses quickly, and a part P ₁ where the hot air flows poorly and the degree of drying progresses quickly compared to the part _P1 . There exists a part P ₂ where is slow,
In the portion _P1 where the degree of drying progresses quickly, initial cracking occurs earlier than in the portion _P2 . Therefore, the AE sensors 7 are attached to multiple locations (three locations in the example) in the portion P ₁ via the adhesive coating 6, and the AE signals S from each AE sensor 7 are processed via the signal processing device 8.
The cumulative number of AE counts A _C and the AE incidence rate A _D are input to the microcomputer 13. In addition, as shown in FIG. 6, the temperature t and humidity H in the drying chamber 100 are measured via a thermometer 17, a hygrometer 18, and a D/A converter 9, and further near each AE sensor 7 of the material W to be dried. The electrical resistance value R and the internal temperature T are input to the microcomputer 13 via the resistance meter 15, thermometer 17, and A/D converter 9.

Therefore, when drying a large number of materials W to be dried at once, even if the degree of drying progresses quickly in some parts, it is possible to install AE sensors 7 at multiple locations in advance where the degree of drying is quick. ,
This was done by relying on conventional experience and predicting early cracks in-process during the drying process by capturing the AE that occurs as the wood structure changes, which is a sign of early cracks, and changing the schedule of the drying process accordingly. It is possible to reliably and effectively prevent the occurrence of initial cracks.

In addition, in the first and second embodiments described above,
It is possible to predict drying cracks and change the schedule of the drying process by simply inputting information on the AE incidence rate A _D and the cumulative number of AE counts A _C into the microcomputer 13. Furthermore, the material to be dried is not limited to Quercus oak, but may also be other tree species such as walnut, birch, and beech, and the drying crack prediction device of the present invention can predict early cracks by capturing AE that occurs due to changes in the wood structure. Furthermore, although there are many types of artificial drying chambers other than the above-mentioned types, an AE sensor may be attached to the material to be dried at the position where the degree of drying is fastest in the drying chamber used. Furthermore, the resonant frequency of the AE sensor is
If the resonance frequency is low (KHz order), AE generated from wood can be detected.

Here, the AE incidence rate measured by the wood drying crack prediction device of the present invention with respect to changes in the wet bulb temperature t _w and dry bulb temperature t _d of the wood dryer or wood drying room.
An example of the response of _AD is shown in Figure 7. Figure 7 shows the change in the AE incidence rate A _D when the wet bulb temperature t _w is raised or lowered while keeping the dry bulb temperature t _d at 60℃, for example. From this figure, the response of the AE incidence rate A _D is is sensitive to changes in wet bulb temperature _tw , and as humidity increases,
It can be seen that the AE incidence rate A _D decreases, and as the humidity decreases, the AE incidence rate A _D increases.

This can be done by changing the temperature and humidity inside the wood dryer 1 or the wood drying chamber 100.
This means that dry cracking of wood can be prevented by controlling the AE occurrence rate A _D. In other words, the AE occurrence rate A _D can be measured by the wood dry crack prediction and prevention device of the present invention as described above. By referring to the results, it is now possible to optimally control the drying process in real time by immediately changing the temperature and humidity to minimize dry cracking in the wood, giving the wood drying control system an unprecedented level of originality.

By the way, the most important point of this device is to know the state of AE occurrence (AE occurrence rate A _D and cumulative number of AEs A _C ) just before the moment the wood cracks.
When the occurrence rate reaches a limit value, the purpose is to immediately activate control equipment such as the warmer 3 via the temperature/humidity control device 13 to relax the drying conditions and prevent the occurrence of cracks. Quercus oak at dry bulb temperature 80℃, wet bulb temperature 52℃
Test examples when dried at ℃ are shown in Figures 8 and 9.
As shown in the figure. An electric circuit is set up on the wood to be dried, and if a crack occurs in the wood, the circuit is cut off and the monitor voltage V of the circuit shows 0, so it is possible to confirm when a crack occurs. Figure 8 shows that after the start of drying
It can be seen that the monitor voltage V shows 0 after 120 minutes, and the AE incidence rate A _D at this point is around 380.
A second example is shown in FIG. 9. In FIG. 9, the monitor voltage V shows 0 about 92 minutes after the start of drying, and the AE incidence rate A _D at that point is about 400. Both figures show that the reproducibility of this detection device is good. Under these dry conditions, the limit value of the AE incidence rate A _D is estimated to be about 380 to 400, but in order to warn of the occurrence of cracks, the AE incidence rate A _D of 300 to 350 may be set as a warning range. if
If the control equipment is set to operate when the AE incidence rate A _D reaches 300, there is a margin of about 5 minutes in FIG. 8 and Δt=about 10 minutes in FIG. 9.
As can be seen from Figure 7, if the wet bulb temperature is increased, the AE occurrence rate increases with almost no time lag.
Since A _D decreases, if there is a margin of this degree, dry cracking of the wood can be prevented.

As explained above, according to the present invention, a detector is attached acoustically in close contact with the wood, and this detector detects elastic waves generated due to changes in the wood structure that occur prior to cracking of the wood due to drying. The signal from the detector that exceeds the set threshold is processed by a signal processing device to detect changes in the wood structure, and the temperature of the wood is determined based on the processed signal.・Since the structure is controlled by a humidity control device, it detects AE that occurs due to microscopic changes in the wood structure, which is a precursor to brittle fracture that occurs before initial cracking occurs when wood dries. This information is then converted into an electrical signal and processed, making it possible to predict early cracks in-process without interrupting the drying process.Furthermore, based on this information, temperature, humidity, wood moisture content, etc. are weighted in an appropriate order. By doing so, the drying conditions can be optimally controlled.
Therefore, when drying materials to be dried such as expensive furniture materials, it is possible to optimally control the drying process by changing the drying conditions based on the cumulative number of AEs and the AE occurrence rate obtained by the drying crack prediction device of this invention. This is done in real time, preventing the occurrence of initial cracks, and making it possible to reliably and easily dry the material to the target dry state.

In addition, if the detector (AE sensor) is attached closely to the wood via an adhesive film, the AE
This method has the effect of not only being able to reliably capture the wood acoustically, but also ensuring that the detector and the wood are in close contact with each other during long-term artificial drying even in a drying room equipped with a fan.

[Brief explanation of the drawing]

FIG. 1 is a block diagram showing a device for predicting and preventing dry cracking of wood according to the present invention, which predicts and prevents dry cracking of materials to be dried in a wood dryer, and FIG.
The AE sensor connects wood (drying material) through an adhesive coating.
Figure 3 is a diagram showing the signal voltage threshold of the detector (AE sensor), Figure 4 is a diagram of the drying process, Figure 5 is Changes in temperature and humidity inside the wood dryer, i.e. the equilibrium moisture content of the material to be dried (Quercus oak)
AE incidence rate of Quercus oak in response to changes in EMC A _D
A graph showing the time-lapse characteristics of FIG. 6 is a second embodiment of the present invention, and is an explanatory diagram of an example in which a plurality of drying crack prediction devices are arranged in a wood drying room.
The figure shows an actual measurement example for estimating the AE rate immediately before the occurrence of drying cracks. Figures and Figure 9 show the dry bulb temperature of Quercus
It is a figure which shows the test example when drying at 80 degreeC and wet bulb temperature 52 degreeC. 1... Wood dryer, 6... Adhesive coating film, 7... AE sensor as a detector, 8... Signal processing device,
13... Temperature/humidity control device, 100... Wood drying chamber, W... Material to be dried.

Claims (1)

[Claims] 1. A device that predicts cracks in wood that occur when drying wood and prevents dry cracks based on this information, which acoustically adheres to the wood. a detector that is attached to the wood and detects elastic waves generated due to changes in the wood structure that occur prior to cracking of the wood due to drying and converts it into an electrical signal; A signal processing device that processes signals to detect changes in wood structure; and a temperature/humidity control device that controls temperature and humidity around the wood based on at least the signals processed by the signal processing device. A device for predicting and preventing dry cracking of wood, characterized by: 2. The apparatus for predicting and preventing dry cracks in wood according to claim 1, wherein the detector is attached to the wood in close contact with the wood via an adhesive coating.