JPH10151336A - Granulation control method for granular particle in fluidized bed treating device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To determine operation conditions of a fluidized bed treating device corresponding to properties of raw material by metrically formularizing properties such as average particle size, uniformity and apparent density of granular particles and determining constants contained in this numerical formula from the minimum granulation experiment. SOLUTION: In a method of granulating granular particles G using a fluidized bed granulator, based on the following formula, control parameters are controlled to obtain a granulated product of desired average particle size. Average particle size = a1 × spray droplet diameter × effective control moisture value + b1 (wherein, a1 , b1 are constants determined by raw material). Therefore, by predicting average particle size of granular particles as a function of operating factors of the fluidizing bed treating device and a physical property recipe of powdery raw material, operation of the fluidized bed treating device is performed corresponding to desired physical properties of the granulated product.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for controlling granulation of a granular material using a fluidized bed treatment apparatus, and more particularly to a method of formulating characteristics such as average particle diameter, uniformity, and apparent density. The present invention relates to a granulation control method capable of setting optimal granulation conditions and obtaining a powder having desired characteristics.

[0002]

BACKGROUND OF THE INVENTION Fluid bed granulation is widely used as a method for granulating powder into fine granular particles (hereinafter referred to as "granules"). Fluidized bed processing equipment for performing this fluidized bed granulation method has many operating factors, and the optimal conditions for obtaining the desired average particle size, uniformity, and apparent density of the obtained granulated product are determined by trial and error. Needs to be sought, and for this reason it depends heavily on the experience and skills of the operator. Specifically, the control value of the operation factor is set in advance, and the apparatus is operated, and the adjustment of the operation factor during granulation is performed by changing the control value by visual observation.

[0003] In addition, since natural materials and the like are used as raw materials, operation under the same operating conditions due to fluctuations in physical properties of raw materials may cause a lack of stability in product quality. Also from this point, the setting change of the operation factor is left solely to the experience of the operator, and as a result, an operation error may be caused.

[0004] In order to automate the driving operation based on the experience and technology of the operator, the development of an online measurement technology and the development of an automatic control system have been carried out, but the growth mechanism of the granular material has not been elucidated. Therefore, the actual situation is that an optimal control system has not yet been constructed.

[0005]

SUMMARY OF THE INVENTION The present invention has been made based on the recognition of the background described above, and the characteristics such as the average particle diameter, uniformity, and apparent density of a granular material are expressed by a mathematical formula to minimize the characteristics. By determining the constants included in this equation from the granulation experiment of
An attempt was made to develop a method for controlling granulation of a granular material in a novel fluidized bed processing apparatus, which can determine operating conditions of the fluidized bed processing apparatus according to the characteristics of raw materials.

[0006]

According to a first aspect of the present invention, there is provided a method for controlling granulation of a granular material in a fluidized bed processing apparatus, wherein the method for granulating a granular material using a fluidized bed granulating apparatus comprises: And controlling the control parameters based on the above to obtain a granulated product having a desired average particle diameter.

[0007]

[Equation 4] Average particle diameter = a ₁ × appropriate diameter of spray liquid × effective control moisture value + b ₁ (where a ₁ and b ₁ are constants determined by raw materials)

According to the present invention, a fluidized bed suitable for the desired physical properties of a granulated product is obtained by predicting the average particle size of the granular material as a function of the operating factor of the fluidized bed treatment apparatus and the physical property formulation of the raw material powder. The operation of the processing device can be performed.

According to a second aspect of the present invention, there is provided a method of controlling granulation of a granular material in a fluidized bed processing apparatus, wherein the control parameter is set based on the following equation in the method of granulating the granular material using a fluidized bed granulating apparatus. It is characterized in that a granulated product having a desired uniformity is obtained by controlling.

[0010]

## EQU5 ## Uniformity = (average particle diameter + 0.68 × standard deviation)
/ (Average particle diameter−0.68 × standard deviation) (however, standard deviation = a ₂ × spray droplet diameter × effective control moisture value + b ₂ a ₂ , b ₂ are constants determined by the raw material system, and 0.68 is one side Measure for probability 25.175%)

According to the present invention, the uniformity of the granular material is predicted as a function of the operation factor of the fluidized bed processing apparatus and the physical property formulation of the raw material powder, so that the fluidized bed processing according to the desired physical properties of the granulated product is performed. The operation of the device can be performed.

According to a third aspect of the present invention, there is provided a method for controlling granulation of a granular material in a fluidized bed processing apparatus, wherein the control parameter is set based on the following equation in the method of granulating the granular material using a fluidized bed granulating apparatus. It is characterized in that a granulated product having a desired apparent density is obtained by controlling.

[0013]

[Equation 6] Apparent density = a ₃ × (average particle diameter / uniformity) ⁻¹ + b ₃ (where a ₃ and b ₃ are constants determined by raw materials)

According to the present invention, the apparent density of the granular material is predicted as a function of the operating factor of the fluidized bed processing apparatus and the physical property formulation of the raw material powder, so that the fluidized bed corresponding to the desired physical properties of the granulated product is obtained. The operation of the processing device can be performed.

According to a fourth aspect of the present invention, there is provided a method for controlling granulation of a granular material in a fluidized bed processing apparatus, wherein the control parameter is a spray droplet diameter in addition to the above requirements. ADVANTAGE OF THE INVENTION According to this invention, the physical property of the granulated product according to the spray droplet diameter which is one of the operation factors of a fluidized-bed processing apparatus can be predicted.

According to a fifth aspect of the present invention, there is provided a method for controlling granulation of a granular material in a fluidized bed processing apparatus, wherein the control parameter is an effective control moisture value in addition to the requirement according to the first, second or third aspect. It is characterized by. ADVANTAGE OF THE INVENTION According to this invention, the physical property of the granulated product according to the effective control moisture value which is one of the operation factors of a fluidized-bed processing apparatus can be predicted.

According to a sixth aspect of the present invention, in the method for controlling granulation of a granular material in a fluidized bed treatment apparatus, in addition to the requirement of the fifth aspect, the effective control moisture value is set by a control moisture value. And According to the present invention, it is possible to change the effective control moisture value by the control moisture value which is an operation factor of the fluidized bed treatment apparatus, and to predict the physical properties of the granulated product according to the effective control moisture value.

According to a seventh aspect of the present invention, there is provided a method for controlling granulation of a granular material in a fluidized bed processing apparatus, wherein the effective control moisture value is set by a water content in addition to the requirement of the fifth aspect. I do. According to the present invention, the effective control moisture value can be changed by the amount of water that is an operating factor of the fluidized bed treatment apparatus, and the physical properties of the granulated product according to the effective control moisture value can be predicted.

According to a further aspect of the present invention, there is provided a method for controlling granulation of a granular material in a fluidized bed treatment apparatus, wherein the effective controlled moisture value is set by a controlled moisture increase rate. Features. According to the present invention, the physical property of the granulated product according to the effective control moisture value can be predicted by changing the effective control moisture value by the control moisture increase rate which is an operation factor of the fluidized bed treatment apparatus.

According to a ninth aspect of the present invention, there is provided a method for controlling granulation of a granular material in a fluidized bed processing apparatus, wherein the moisture value of the granular material during fluidization is set to a near value. It is characterized by measuring using an infrared moisture meter, and using operating data at the time of preparing a calibration curve to obtain constants in a prediction equation that varies depending on the physical properties of raw materials. According to the present invention, it is possible to formulate a prediction equation according to the fluidized bed processing apparatus and the raw material powder. The object of the present invention is achieved by means of the configuration of the invention described in each of the claims.

[0021]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The configuration of a fluidized bed processing apparatus 1 to which the present invention is applied will be described below, and then the granulation control method of the present invention will be described together with its operating state. Reference numeral 1 denotes a fluidized bed treatment apparatus for drying, granulating,
This is an apparatus having a known configuration for performing coating or the like, and is configured by connecting a flowing air blowing chamber 2, a flowing chamber 3, a spray chamber 4, and a filter chamber 5 as shown in FIG.

The fluidized-air blowing chamber 2 is located at the lowermost part of the fluidized-bed processing device 1 and is formed of a cylindrical hollow member having an open upper surface, and a hot-air supply device or the like is appropriately connected to a side peripheral portion thereof.
The flow chamber 3 is, for example, an inverted truncated cone-shaped hollow chamber located at the upper part of the flowing air blowing chamber 2, and a bottom plate, that is, a boundary between the flowing chamber 3 and the flowing air blowing chamber 2, is provided with a perforated plate or a wire mesh. Is provided. A near-infrared moisture meter 3a is provided with its sensing part facing the inside of the flow chamber 3.

The spray chamber 4 is composed of a cylindrical member located above the flow chamber 3, and has a spray nozzle 6 for spraying water or a binder liquid B serving as a binder. The spray nozzle 6 is provided with a pump 6a, a valve 6b and the like as appropriate on the outside so that the speed of the spray liquid such as the binder liquid B ejected from the spray nozzle 6 or the spray air pressure can be adjusted. A tank 6c for the binder liquid B is provided with a liquid level sensor or the like, or a pipe or the like connecting the tank 6c and the pump 6a is provided with a flow meter. Measurement of the amount of the binder liquid B is performed.

The filter chamber 5 is located above the spray chamber 4 and incorporates a bag filter 7 for separating the powder G from the gas, so that the powder G does not flow out of the apparatus. It is like that.

Reference numeral 10 denotes a particle size measuring device, which is provided at an appropriate position outside the fluidized chamber 3 of the fluidized bed processing apparatus 1, and includes a sampling device 11 and a conduit 15
And a laser beam type particle size sensor 20 and an air piping 16.

As an example, the sampling device 11 is provided outside the fluidizing chamber 3 by using a sampling hole which may be provided as a standard specification in the fluidizing chamber 3 of the fluidized bed processing apparatus 1. In that case, the existing device can be installed without modification. This sampling device 11 substantially constitutes a screw conveyor, and is installed with the particle inlet 14 at one end facing the inside of the flow chamber 3. The powder particles G in a fluidized state in the fluidized chamber 3 are taken in from the particle inlet 14 and transferred to the inside of the sampling device 11.

Next, the conduit 15 will be described. This is mounted between the sampling device 11 and an air transportation pipe 16 described later. An anti-reflective coating glass 17 is provided on both sides of the conduit 15. This is an optical glass whose surface is coated, and transmits an incident laser beam without being reflected and scattered at a boundary surface thereof. An air purge mechanism may be appropriately provided inside the anti-reflection coating glass 17.

Next, the laser beam type particle size sensor 20 will be described. This is an existing sensor, and as shown in FIG. 2, the laser light emitted from the He-Ne laser 21 and passing through the collimator 22 is scattered by the powder G, and the laser light is received by the sensor 23. The particle size of the powder G, which is a scattering substance, is measured from the strength or the like. In particular, the type using the Raman effect has a high SN ratio because the wavelength of the scattered light is different from that of the emitted light, so that highly accurate measurement is possible. The sampling period is variable in the range of 0.6 to 500 ms. Although a laser light scattering type particle size sensor is used in this embodiment, a particle size sensor such as a laser light diffraction method may be used. Further, a type in which the sensing part of the laser beam type particle size sensor 20 directly faces the flow chamber 3 and does not require the sampling device 11 can be used.

The particle size measuring apparatus 1 configured as described above
On the other hand, the powder G falls in the conduit 15 by gravity, passes through almost the center between the anti-reflection coating glasses 17 during the fall, and the particle diameter is measured by the laser beam irradiated at that time. Will be

The required measurement time by the laser beam type particle size sensor 20 performed as described above is about 2 seconds. During this time, 200 measurements can be performed, and the average can be calculated and output. . Further, the laser beam type particle size sensor 20 can measure a very wide range of particle size from 1 to 2000 μm with one sensor, and covers the entire range of particle size in a normal granulation operation.

Next, the computer 25 for analyzing the measured values by the particle size measuring apparatus 10 will be described. This is, for example, an existing personal computer, which calculates the average particle diameter, uniformity, particle size distribution, and the like necessary for particle processing, and outputs the result. It is preferable that the output value conforms to a JIS sieve. Although a personal computer is used as the computer 25 in the present embodiment, a single-board computer, EWS, or the like may be used.

The fluidized bed processing apparatus 1 to which the present invention is applied
Is as described above, and a granulation control method of the present invention using the same will be described below. The outline of the granulation control method of the present invention is based on the operation data (raw material moisture value, spray droplet diameter, average particle diameter, maximum control moisture value, effective control moisture value) at the time of preparing the calibration curve, and the data is used for granulation. The physical properties of the raw materials involved are estimated, the operating conditions of the fluidized bed treatment apparatus 1 are predicted based on the estimated values, and the granulation experiment is repeated under the operating conditions, whereby the average particle diameter and average Once, the apparent density and the like are gradually approached to the target. The calibration curve experiment is a preliminary experiment for associating the absorbance value of the infrared moisture meter with the water content in the bed.
This is an experiment in which the granules G are granulated using the above method.

Average Particle Diameter Prediction As shown in FIG. 3, as a result of a fluidized bed granulation experiment using various raw materials, the average particle diameter of the granular material G obtained by using the fluidized bed treatment apparatus 1 is as follows. Is approximated by

[0034]

Average particle diameter = a ₁ × spray droplet diameter × effective control moisture value + b ₁ ─── (1) a ₁ , b ₁ ; constant determined by raw material system effective control moisture value; f (control moisture value, Water content, controlled water rise rate)

Here, the term “spray droplet diameter” refers to the droplet diameter of the binder liquid B sprayed from the spray nozzle 6. The control moisture value is a moisture value in the fluidized chamber 3 and is a value set as a target value. Furthermore, the amount of water is the amount of the binder liquid B sprayed into the fluid chamber 3. Furthermore, the control water increase rate is a value determined at the time of creating a calibration curve as described later. The effective control moisture value is a function of the control moisture value, the amount of water added, and the control moisture increase rate, and is defined by the following equation as an example.

[0036]

[Equation 8] Effective control moisture value = ((Cw−Rm) / Aw) × (Aw− (Cw−Rm) / 2L) ─── (2) Cw; Control moisture value Aw; Water content L; Control moisture rise Rate Rm; raw material moisture value

When the above equation (1) was applied to data obtained from various raw material powders, the correlation coefficient was found to be 0.1 depending on the raw material system.
The range was from 75 to 0.97. Therefore, if the constants a ₁ and b ₁ are determined, the average particle size in each raw material system can be estimated.

As shown in FIG. 4, the constant a ₁ can be obtained by the following equation with some exceptions such as raw materials that are easily soluble in water.

[0039]

A ₁ = (3.98 / (maximum controlled moisture−raw material moisture value)) − 0.03─── (3)

Here, the maximum control moisture value means the maximum value of the moisture in the fluidized chamber in which the granulation operation is possible. When the above equation (3) was applied to data obtained from various raw material powders, the correlation coefficient was around 0.8 depending on the raw material system. Since the determination of the maximum control moisture value requires skill and the raw material moisture value also fluctuates, the data in the calibration curve experiment are provisional values, and the value of a ₁ obtained from the equation (3) is used as the value. (1) are substituted into equation to calculate the provisional value of b _1.

The above-mentioned controlled water increase rate depends on the speed of the spray liquid, the temperature and the amount of hot air, the physical properties of the raw material, and the like, and can be obtained by the following equation.

[0042]

## EQU10 ## Controlled water increase rate = d (controlled water value,%) / d (water content,%) / (4)

Since the control moisture value and the water content in the above equation (4) can be easily measured, they can be determined when a calibration curve is prepared.

In determining the operating factors of the fluidized bed treatment apparatus 1 using these equations, the provisional values of the coefficients a ₁ and b ₁ are substituted into the above equation (1), and the target average particle diameter is substituted. Thus, “spray droplet diameter × effective control moisture value” is calculated, and the first experiment is performed under the conditions. The results of the first experiment and the data of the calibration curve experiment are substituted into equation (1) again, and the coefficients a ₁ ,
to compute an estimate of b _1, and calculates the condition of the next experiment. The average particle size is predicted by repeating the above steps.

Uniformity Prediction Another parameter related to the particle size distribution of the granular material G is the particle size uniformity, which is defined by the following equation. The uniformity is a parameter that greatly affects the appearance, yield, and apparent density of the granulated product.

[0046]

## EQU11 ## Uniformity = 75% particle diameter / 25% particle diameter

The uniformity thus defined can be approximated by the following equation by assuming that the particle size distribution is a normal distribution and estimating the standard deviation.

[0048]

(12) Uniformity {(mean particle size + 0.68 × standard deviation) / (mean particle size−0.68 × standard deviation)} (5) 0.68; Measure for one-sided probability 25.175%

The reason for estimating the standard deviation of the particle size distribution is that the value of the standard deviation of the particle size distribution has a high positive correlation with the value of the average particle size, and the standard deviation of the particle size distribution is This is because it can be estimated by the following equation in the same steps as the prediction of.

[0050]

## EQU13 ## Standard deviation = a ₂ × spray droplet diameter × effective control moisture value + b ₂ ） (6) a ₂ , b ₂ ; constant determined by raw material system effective control moisture value; f (control moisture value, addition Water volume, controlled moisture rise rate)

When this type of equation was applied to data obtained from various raw material powders, the correlation coefficient was in the range of 0.70 to 0.98 depending on the raw material system. Also, a _{2 has the} following relationship.

[0052]

A ₂ = 0.707 × a ₁ −0.101─── (7)

Therefore, the standard deviation of the particle size distribution is calculated by the equation (6) and the uniformity is estimated by the equation (5) in the same procedure as that for predicting the average particle diameter. Equation (5) shows that the uniformity is a function of the average particle diameter. Therefore, the uniformity can be controlled by controlling the average particle diameter.

Apparent Density Prediction Apparent density is an important factor in determining the content of a product and the size of a packaging container. The apparent density of an individual raw material system depends on the apparent density of the raw material and the average particle size and uniformity, that is, the particle size distribution (contribution ratio is around 75%). Therefore, the prediction of the apparent density is equivalent to the prediction of the average particle diameter and the standard deviation of the distribution. Conversely, the average particle diameter and the apparent density cannot be set independently at the time of product design.
The relationship between the apparent density and the particle size distribution is as follows.

[0055]

[Expression 15] Apparent density = a ₃ × (average particle diameter / uniformity) ⁻¹ + b ₃ ８ (8)

When the above equation (8) was applied to data obtained from various raw material powders, the correlation was found to be 0,1 depending on the raw material system.
The range was from 78 to 0.99. B ₃ is approximated by the following equation.

[0057]

B ₃ = apparent density of raw material−432.8 × log (average particle diameter of raw material / apparent density of raw material) ─── (9)

Therefore, the apparent density is also predicted by the equation (8) in the same procedure as the prediction of the average particle diameter. Equation (8) shows that the apparent density is a function of the average particle diameter. Therefore, the apparent density can be controlled by controlling the average particle diameter.

Verification Test Results of the Prediction System The verification test of the prediction system according to the present invention described above was carried out using three kinds of raw material systems which were exactly the same as the commercially available products. The demonstration experiment shows how many experiments were required (the number of experiments reached) in order to set conditions for granulating the set target quality granules. The results are shown in Table 1 below and FIGS.

[0060]

[Table 1]

Each raw material system is a mixture of nearly 10 types of raw materials including the auxiliary raw materials, and the physical properties of the raw materials used in the production were about four times (including the calibration curve experiment) despite the fact that the raw materials were used for production. A value of 90% of the target value was achieved. In addition, it is assumed that an error of about 10% cannot be escaped due to an error in sampling, measurement, etc., an error in the operation state of the apparatus, and the like. In fact, even if the granulation operation is repeated under the same conditions, such an error is recognized. This was regarded as an allowable range.

Scale-up By the way, there is a scale-up from an experimental machine to a production machine as an esoteric operation related to the quality operation by the fluidized bed processing apparatus 1. Until now, the appropriate scale-up factor could not be determined, so that the granulation conditions obtained on the experimental machine had to be changed greatly on the production machine, and the setting of these conditions had to rely on expert intuition and experience. Especially the number 10
In a production machine using as much as 0 kg of raw material, it is not easy to determine conditions by trial and error.

Under the assumption that only the “control moisture rise rate” affects the scale-up factor, the production machine FLO
-300 type (300k capacity, manufactured by Okawara Corporation)
g) was measured, and this was measured using the experimental machine F.
The prediction was performed by a production machine by substituting into a prediction formula obtained by LO-5M (manufactured by Okawara Seisakusho Co., Ltd., capacity: 5 kg). As shown in Table 2 below, the results show that the “controlled moisture increase rate” is a good scale-up factor.

[0064]

[Table 2]

Therefore, the maximum control moisture value and the control moisture increase rate differ between the experimental machine and the production machine due to the difference in the installation conditions and the flow state. However, if this is measured together with the calibration curve experiment in the production machine, The scale-up is performed smoothly using the data. Further, by detecting the "control moisture increase rate" online and finely adjusting the control moisture value, it is possible to absorb the existing fluctuations and the variation in the quality of the granulation raw material, thereby enabling a stable quality granulation operation.

Automatic control system As described above, the evaluation parameters of the quality of the powder G are as follows.
The target values of the particle size distribution (average particle size), apparent density, and uniformity were set, and the relationship with the operation factor was investigated. As a result, the following relationships were found. When calculating the case where the target average particle diameter in cocoa granulation is set to 300 μm based on the equation (1), there is a relationship shown in FIG. 7 between the operation factors. However, here, the hot air temperature is 60 ° C and the hot air flow rate is 1m / s.
The calculation was performed as ec. Among the operating factors of the fluidized bed processing apparatus 1, the spray droplet diameter was adopted as the main control target because the spray droplet diameter was the easiest to handle as the operating condition. The amount of water added, water content, hot air temperature, and flowing air velocity were fixed, and were used supplementarily only when the diameter of the sprayed droplet exceeded the control range. The fuzzy control rules for controlling the average particle size at this time are shown in Tables 3 and 4 below.

[0067]

[Table 3]

[0068]

[Table 4]

SP in Tables 3 and 4 is a set value (set point) of the average particle diameter.

[0070]

The present invention has the above-described configuration and has the following effects. First, claim 1
According to the described invention, the fluidized bed in accordance with the desired physical properties of the granulated product is predicted by predicting the average particle size of the granular material G as a function of the operating factor of the fluidized bed treatment apparatus 1 and the physical property formulation of the raw material powder. The operation of the processing apparatus 1 can be performed.

According to the second aspect of the present invention, the desired granulated product is obtained by predicting the uniformity of the granular material G as a function of the operating factor of the fluidized bed treatment apparatus 1 and the physical property formulation of the raw material powder. The operation of the fluidized bed processing apparatus 1 according to the physical properties can be performed.

Furthermore, according to the third aspect of the present invention, the apparent density of the granular material G is predicted as a function of the operating factor of the fluidized bed processing apparatus 1 and the physical property prescription of the raw material powder, so that the desired production is achieved. The operation of the fluidized bed processing apparatus 1 according to the physical properties of the granular product can be performed.

According to the fourth aspect of the present invention, it is possible to predict the physical properties of the granulated product according to the spray droplet diameter, which is one of the operating factors of the fluidized bed processing apparatus 1.

Further, according to the fifth aspect of the present invention, it is possible to predict the physical properties of the granulated product according to the effective control moisture value which is one of the operating factors of the fluidized bed processing apparatus 1.

Further, according to the present invention, the effective control moisture value is changed by the control moisture value which is an operation factor of the fluidized bed treatment apparatus 1, and the physical properties of the granulated product according to the effective control moisture value are changed. Can be predicted.

According to the seventh aspect of the present invention, the effective control moisture value is changed by the amount of water which is an operating factor of the fluidized bed treatment apparatus 1 to predict the physical properties of the granulated product according to the effective control moisture value. can do.

According to the eighth aspect of the present invention, the effective control moisture value is changed by the control moisture increase rate which is an operation factor of the fluidized bed treatment apparatus 1, and the physical properties of the granulated product according to the effective control moisture value are changed. Can be predicted.

Further, according to the ninth aspect of the present invention, it is possible to formulate a prediction equation according to the fluidized bed processing apparatus 1 and the raw material powder. With these, it is possible to obtain a prediction formula for the optimum granulation conditions even for the material handled for the first time with the minimum number of granulation experiments, and by performing granulation control using the obtained prediction formula, the fluidized bed granulation method Automatic operation of the fluidized bed processing apparatus 1 becomes possible.

[Brief description of the drawings]

FIG. 1 is a skeleton diagram showing a fluidized bed processing apparatus to which a granulation control method of the present invention is applied.

FIG. 2 is a block diagram schematically illustrating a measurement principle of a laser beam type particle size sensor.

FIG. 3 is a graph showing the relationship between the droplet diameter of various raw materials × effective control moisture value−average particle diameter characteristics.

[Figure 4] - is a graph illustrating the (maximum control moisture material water content value) -a ₁ properties.

FIG. 5 is a graph showing (droplet size × effective control moisture) -average particle size characteristics.

FIG. 6 is a graph showing (average particle diameter / uniformity) -apparent density characteristics.

FIG. 7 is a graph showing the relationship between the spray droplet concentration, the amount of water added, and the controlled moisture, which are operating factors for the average particle diameter.

[Explanation of symbols]

 REFERENCE SIGNS LIST 1 fluidized bed treatment device 2 fluidized air blowing chamber 3 fluidized chamber 3A perforated plate 3a near infrared moisture meter 4 spraying chamber 5 filter chamber 6 spraying nozzle 6a pump 6b valve 6c tank 6d fluid meter 7 bag filter 10 particle size measuring device 11 sampling Apparatus 14 Particle inlet 15 Conduit 16 Airborne pipe 17 Anti-reflection coating glass 20 Laser beam type particle size sensor 21 He-Ne laser 22 Collimator 23 Sensor 25 Computer B Binder liquid G Powder

 ──────────────────────────────────────────────────続 き Continued on the front page (72) Inventor Makoto Ono 4-5-1, Shirayama, Aso-ku, Kawasaki City, Kanagawa Prefecture (72) Inventor Takuya Inoue 5434-4, Hirado-cho, Totsuka-ku, Yokohama-shi, Kanagawa Prefecture (72) Inventor Kazuki Wakiya 9-10 Asahigaoka, Fujieda City, Shizuoka Prefecture (72) Inventor Kazumasa Yamazaki 283-13, Kamiyabuta, Fujieda City, Shizuoka Prefecture (72) Koji Tabata 628-2 Ogawa, Yaizu City, Shizuoka Prefecture Eishin II-102

Claims (9)

[Claims] 1. A method of granulating a granular material using a fluidized-bed granulator, wherein a control parameter is controlled based on the following equation to obtain a granulated product having a desired average particle diameter. , A method for controlling granulation of powder and granules. ## EQU1 ## Average particle diameter = a ₁ × appropriate diameter of spray liquid × effective control moisture value + b ₁ (where a ₁ and b ₁ are constants determined by raw materials) 2. A method for granulating a granular material using a fluidized-bed granulator, wherein a granulated product having a desired uniformity is obtained by controlling a control parameter based on the following equation. Granulation control method for granules. ## EQU2 ## Uniformity = (average particle diameter + 0.68 × standard deviation)
/ (Average particle diameter−0.68 × standard deviation) (however, standard deviation = a ₂ × spray droplet diameter × effective control moisture value + b ₂ a ₂ , b ₂ are constants determined by the raw material system, and 0.68 is one side Measure for probability 25.175%) 3. A method of granulating a granular material using a fluidized bed granulator, wherein a granulated product having a desired apparent density is obtained by controlling a control parameter based on the following equation. ,
Granulation control method for granules. [Equation 3] Apparent density = a ₃ × (average particle diameter / uniformity) ⁻¹ + b ₃ (where a ₃ and b ₃ are constants determined by raw materials) 4. The method according to claim 1, wherein the control parameter is a spray droplet diameter. 5. The granulation method according to claim 1, wherein the control parameter is an effective control moisture value. 6. The method according to claim 5, wherein the effective control moisture value is set by a control moisture value. 7. The method according to claim 5, wherein the effective control moisture value is set based on the amount of water added. 8. The method according to claim 5, wherein the effective control moisture value is set based on a control moisture increase rate. 9. The method according to claim 1, wherein the moisture value of the flowing granular material is measured using a near-infrared ray moisture meter, and constants in a prediction equation differing depending on physical properties of the raw material are obtained using operation data at the time of preparing a calibration curve. The method for controlling granulation of a granular material according to claim 1, 2 or 3.