JPS6034058B2 - Automatic control equipment for automatic quantitative determination and sorting equipment, etc. - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION This invention provides statistical analysis based on the measurement results during sorting when articles processed by an automatic quantitative bagging device or an automatic sized cutting device are sorted by a predetermined sorting machine. This invention relates to a device that controls a predetermined weight and length adjustment section of a metering device from a practical standpoint.

2. Description of the Related Art Hitherto, automatic devices have been known that automatically cut products that are generally sold in fixed weights or fixed lengths into fixed-quantity bags or cut to fixed sizes.

Although it would be ideal for all articles processed by such automatic machines to have a predetermined weight or size, there is some variation in this type of automatic machine. Therefore, it is common to use an automatic sorting machine. Automatic metering machines usually take the variation into account and make appropriate adjustments, for example, quantitative bagging machines increase the number of bags, resulting in a value that is at least larger than the light weight limit, which is the lightest among the weighing machines. That's what I do. Conventionally, this type of adjustment has been made at the discretion of the operator. However, although this adjustment may be safe if the grain is increased too much, it will result in an economic loss for the producer. Also, if you try to bring the quantitative results closer to the light weight limit by reducing the increment, the lightest weight will be below the light weight limit. Therefore, this operation requires considerable skill. Moreover, even if proper quantification is performed by appropriate intensification, the quantification results may fluctuate due to changes in humidity or temperature, and there is a problem in that more skill is required to deal with this. What can be considered here is a statistical understanding of the variance. Normally, this kind of variation in quantity has a distribution close to normal distribution. Therefore, by knowing the most recent fluctuations in the distribution state and automatically controlling the adjustment section of the metering machine in accordance with the fluctuations, it is possible to always carry out the determination in the most favorable condition. This invention attempts to statistically process data based on measurement results obtained from a measurement section of a sorter, etc., and automatically control the adjustment section of a quantitative processing machine to the most preferable state from a statistical viewpoint.

The structure of the present invention will be explained with reference to FIG. 2 of one embodiment.The metering machine 1 has a quantitative adjustment section 3 and performs quantitative processing on quantities such as weight, volume, length, etc. A measurement unit 5 that measures the amount of each quantitative product processed by the machine.
In the apparatus, the value to be controlled for the amount of the quantitative article is set as a control reference value (p in Figure 1), and the result of the measurement of the quantitative article is placed either above or below the control reference value p. The apparatus is configured to classify the appropriate number of quantitative articles into two according to their belonging, store the number of classified articles for each category, and update the memory every predetermined number of times of measurement, and one of the two categories ( a classification storage section 8 that outputs an output signal representing the ratio of the number of fixed-quantity articles classified as (for example, smaller than p) to the appropriate number; and a ratio setting section 9 that is set to a predetermined ratio and outputs an output signal of that ratio.
Then, the respective output signals of the self-classification storage unit 8 and the ratio setting unit 9 are compared, and the deviation signal is used to calculate the quantitative determination device 1.
The control unit 12 controls the quantitative adjustment unit 3 so that the ratio stored in the classification storage unit 8 becomes equal to the ratio set in the ratio setting unit 9.

According to this configuration, the quantitative machine 1 is an automatic quantitative powder bagging machine, the measuring section 5 is a weight detecting section of an automatic sorting machine, and the absolute limit on the lightweight side, that is, the lower limit weight stipulation in the quantitative machine 1 is Assuming that quantitative processing is carried out with the value a(g), the weight of the quantitatively processed article, that is, the bagged article is detected by the measuring section 5.

The variation in weight is shown in the curve fl shown in Figure 1.
When it is expressed as, a specific control standard value p is determined which is larger than the lower limit weight specification value a, and in an ideal state, what percentage of the total number of items smaller than the value of p corresponds to is obtained in advance, For example, the number of things less than the p value is 2%
Assuming that, 2% is set in the ratio setting section 9.
Further, the classification storage section 8 stores the number of categories for each bagged article depending on whether the weight measured by the measuring section 5 belongs to above or below the control standard value p, and This is the latest data on the appropriate number of stuffing items. The latest data is output as a percentage and compared with a percentage (2%) set in the percentage setting section 9, and the control section 12 controls the quantitative adjustment section 3 of the quantitative meter 1 based on the deviation signal. That is, control is performed so that the quantity below the management reference value p always becomes the proportion (2%) set in the proportion setting section 9. To explain this control state in a little more detail, in Fig. 1, (1) When the curve fl has moved parallel to the weight axis In both cases, when changes 1) and {2} occur at the same time, the above-mentioned control ensures that the quantitative result always falls within the predetermined lower limit weight value a.

In the case of [2} above, control is performed as shown by f2.
That is, the center of the barracks is moved to the right.
In the figure, the vertical axis is the number of articles. The above curve fl,
f2 corresponds to a probability density curve of a normal distribution, and when this is subjected to definite integration from - to x to obtain a probability distribution curve of a normal distribution, curves F1 and F2 are obtained. The vertical axes of the probability distribution curves F1 and F2 indicate proportions. Therefore, it is only necessary to control these curves F1, F2, etc. so that they always intersect at the 2% position with a straight line passing through p and perpendicular to the x-axis. An embodiment of the present invention will be described below with reference to the drawings.

FIG. 2 is a block diagram in which the present invention is applied to a quantitative powder filling device. The automatic quantitative filling machine 1 uses a screw feeder 2, and the amount of rotation of the screw feeder 2 allows a predetermined volume of powder to be sequentially filled into each prepared container.
For example, the screw feeder 2 rotates five times and stops for one container, thereby feeding approximately 200 g of talcum powder, and the quantitative filling machine 1 is designed to finely adjust the amount of rotation. It has an adjustment section 3 at the bottom. The containers filled with powder are sequentially sent to an automatic sorter 4. The automatic sorting machine 4 has a weight detection section 5, a sorting section 6, and a classifier 7. The weight detection section 5 detects the powder weight of the container filled with powder, and the detection signal is sent to the classifier. 7 and the lower limit value (which is the limit on the lightweight side) is sent to the classifier 7 for management.
20 Tsuru), it is classified according to the upper limit value (21st order) that is the boundary value between appropriate amount and excessive amount, that is, the limit on the excessive amount side, and the capacity is classified in the distribution section 6 as either light, appropriate amount, or excessive amount. It is designed to output an output signal that can be distributed. In this case, the specified weight value a is 200 g. This specified weight value of 200g is the lower limit specified value, for example, when a container is displayed as containing 200g in a commercial transaction.
Items that have been quantitatively processed to a quantity smaller than 0.00g are absolutely defective from the perspective of the purchaser. For this reason, it is certain that 2
To ensure that there are 0 females, the lower limit is set at 20 bamboos, which is increased by 10 crabs, for safety reasons, and the width of the tether is determined in consideration of the precision and economic efficiency of the quantitative processing machine. 21
He is the upper limit. The above is the same configuration as that of a conventional sorting device. In this invention,
Classification storage section 8, ratio setting section 9, comparison section 10, intermittent section 11
, a control section 12 are provided. The classification storage unit 8 is mainly composed of a classification storage unit 8a, and counts the output signal of the classifier 7 into one of the number of light items, the number of appropriate amounts, and the number of excessive amounts for each container, and stores each container. It is configured to do this.

The following two methods can be considered as storage methods in the classification storage device 8a. One of them is to detect the weight of a specific number of pieces.
For example, by storing 100 pieces of data based on the weight detection of each ION solid container in the order of detection, and deleting the oldest data each time new data is entered, the 100 pieces of data that are the newest are always stored. It is a method. The other method is to detect the weight of a specific number of containers, for example, each time the weight of a container is detected, old ION data and new low
This is a method of exchanging permanent data and storing new data. No matter which of the two methods is adopted, the lower limit value (20 omitted) is set as the control standard value,
The classification storage unit 8 outputs a signal indicating what percentage of the specific number of items is below the management standard value (20 warm).

In this case, the specific number is 100, so the number remains the same)
It will show the value of %. In other words, if the number of items below the management lower limit is 3, it will be 3%, and if it is 2, it will be 2%.
%. The output signal may be any signal having a weight equal to this percentage. In addition, the display 8b in the figure is for displaying the number of lightweight items, appropriate amount items, and excessive amount items, respectively, and the distribution state of the dispersion can be grasped to a certain extent by this display. When this indicator 8b is not provided, the classification memory 8 classifies and stores the signal from the classifier 7 into the number of lightweight items necessary for the signal output by the classification storage 8, the number of appropriate weight items, and the number of excessive weight items. In this way, the same output signal as above is output. The ratio setting section 9 may be of any type as long as it can freely set the % value r and its output signal can be easily compared with the output signal of the classification storage section 8.

The comparison unit 10 compares the output signal of the classification storage unit 8 and the output signal of the ratio setting unit 9, and provides the result to the controller 12 as a deviation signal.

The interrupter 11' is slightly different depending on the classification storage method of the classification storage section 8 mentioned above, and if the old and new data are replaced every time one weight is detected, On the other hand, if a specific number of old and new data are exchanged every time a specified number of weights are detected, the data exchange is synchronously turned on and off. .

This is a configuration that provides signals to the controller 12 only at necessary times. The control unit 12 controls the automatic filling machine 1 according to the input signal.
This is used to adjust the adjustment section 3 of the controller.

This control section 12 may be one that simply performs a proportional operation. However, considering linearization control in order to prevent the overall loop sensitivity from changing due to the magnitude of fluctuation, a method having characteristics of an inverse function of the F curve of the probability distribution function or characteristics approximating this is considered. It is preferable to install In the one shown in FIG. 2, this linearization controller 12b is installed. To explain this point, when moving the curve F2 to the FI position as shown in Figure 3, the deviation signal △F, (x) is used to correct △x, so the input e is C, △F, output E is C2△×
If so, it is a hot and spicy tsuba: K Hajime.

Therefore, it becomes the gain of the transfer function of the Yochi-type Ihi-class device, and F(
x). The output signal of linearization controller 12b enters controller 12a. This controller 12a is suitably of an integrating type or an integral type with adjustable gain. In some cases, known controllers that perform proportional, integral, or differential operations may be used. The output of the control section 12 is used to adjust the adjustment section 3 of the automatic filling device. Now, the probability density curve and the probability distribution curve of the workpiece when the quantitative filling device having the above-mentioned control device operates with appropriate adjustment are as follows.
It is assumed that the states are shown by fl and FI in FIGS. 4a and 4b, and the output signal of the classification storage section 8 is 2%. The ratio setting section 9 is set to 2%. If the operation is continued and the apparent specific gravity of the powder changes, normally fl and FI will move along the x-axis as shown by dotted curves fl' and FI', for example. That is, in general, the spread of the probability density curve, that is, the width of the variation, appears in a fixed state depending on the equipment, the type of powder, etc., and does not change much. As the equipment itself ages over many years of use, the range of variation gradually increases. Therefore, in most cases, when this change suddenly appears, it should be considered that the device is malfunctioning. Assuming that the control device operates when the state of the curves fl' and FI' is reached, the number of lightweight items (those below 20) stored in the classification storage unit 8 is 0, so it is 0%. A corresponding output signal appears. This signal is compared with a value set in the ratio setting section 9, that is, a signal of 2%. Therefore, this 2% signal directly becomes a negative deviation signal, which is input to the control section 12, and the output signal thereof adjusts the adjustment section 3 of the automatic filling machine 1 in the direction of decreasing the filling amount. Therefore, the number of revolutions of the screw feeder 2 for one filling is reduced, and the amount of powder corresponding to the above Δx is subtracted from the supply amount. As a result, the curves fl', FI'
returns to the original fl and FI positions. Further, when fl moves in the opposite direction to fl', the signal output from the classification storage section 8 exceeds 2%, the deviation signal becomes a positive signal, and the adjustment section 3 increases the filling amount. The amount is adjusted in the direction and in accordance with the signal. As can be understood from the above explanation, the device of this embodiment is constantly filled with new data from a statistical point of view, and the automatic quantitative device is classified into two according to a predetermined lower limit value (control reference value). can be automatically controlled to maintain a constant ratio of one to the other.

Therefore, in the case of a metering device in which there is little variation in the width of the variation and the width of the variation is smaller than or approximately the same as the width between the upper and lower control limits, the apparent Even if the probability density curve shifts to the left or right due to changes in specific gravity, it will be automatically corrected to maintain the ideal increasing condition, allowing good quantitative processing to be maintained and maximizing the efficiency of the quantitative device. It can be operated with. Furthermore, if there is a fluctuation in the range of variation and the range becomes large, the percentage of items that are below the predetermined lower limit value will be maintained constant; As a result, a malfunction in the quantitative filling machine 1 can be discovered. Although the above embodiment controls weight, it can also be applied to statistical control of not only weight but also other measured quantities, such as length, volume, and other analog quantities.

Furthermore, it can of course be applied to control in which the ratio of one of the two categories is maintained constant using the upper limit value, which is the opposite of the lower limit value, as a control standard. In general, when there are probabilistically correlated events that occur repeatedly, by manipulating one event (e.g., the number of revolutions), the other event (e.g., the weight number) can be manipulated. ) can be applied to control. The control lower limit value or control upper limit value used as the control reference value is based on the probability density of a population of many measured values of the workpiece when the quantitative processing machine is operated with appropriate adjustment. Determined based on standard deviation, usually. (standard deviation)
20 (2.3%) or 30 (0.15%), which is twice or three times wider than
%) is often used, but there is no particular restriction, and in some cases, the center line (50%) may be used as a set value to control the average value. As described above, this invention is very economically advantageous because it can be controlled so that the ideal increase is always constant in, for example, an automatic quantitative filling machine. The effect is that the machine can be operated at maximum efficiency with the least number of machining defects.

[Brief explanation of the drawing]

FIG. 1 is a diagram showing a probability density curve and a probability distribution curve for explaining the control contents according to the present invention, FIG. 2 is a block diagram showing one embodiment of the present invention, and FIG. 3 is a diagram showing the contents of linearization control. FIG. 4 is a diagram showing a probability distribution curve for explanation, and shows the controlled state of the quantitative filling machine of the embodiment, where a is a probability density curve and b is a probability distribution curve. 1...Automatic quantitative filling machine, 2...Screw feeder, 3...Adjustment section, 4...Automatic sorting machine, 5...Weight detection Section, 7... Classifier, 8... Classification storage section, 9... Ratio setting section, 10... Comparison section, 1 1... Intermittent ,
12...control unit (12a...controller,
12b... linearization controller). Figure 2, Figure 3, Figure 4.

Claims (1)

[Claims] 1 Equipped with a metering machine that has a quantitative adjustment section and performs quantitative processing on quantities such as weight, volume, length, etc., and a measuring section that subsequently measures the amount of each quantitative article processed by the meter. In the apparatus, the value to be controlled for the quantity of the quantitative article is set as a control reference value, and the results of the measurement of the quantitative article are classified into two groups, so as to belong to either the upper or lower side of the control standard value, and the above-mentioned quantitative determination is performed. The number of quantified articles classified into one of the two classifications is configured to store the classified number of the appropriate number of articles by category, and update the memory every predetermined number of measurements. a classification storage unit that emits an output signal of a proportion to an appropriate number; a proportion setting unit that emits an output signal of a proportion set to a predetermined proportion;
The respective output signals of the classification storage section and the ratio setting section are compared, and based on the deviation signal, the quantitative adjustment section of the meter is set to the ratio stored in the classification storage section in the ratio setting section. an automatic control device comprising: a control unit that controls the ratio so that the ratio is equal to the ratio of the current ratio;