JPH01170815A - Combined weighing device - Google Patents

Abstract

PURPOSE:To perform combined weighing of high precision by forming plural partial sets from plural weight data and selecting such combination that the total value of deviation between addition values of weight data and target weight values in respective sets is minimum. CONSTITUTION:Weights W1, W2,...WN of articles weighed by plural weighing machines 1 are inputted to a multiplexer 2, and the multiplexer 2 successively outputs weights W1, W2,...WN to an operation control part 4 through an A/D converter 3 when the control part 4 receives the timing signal from a packing machine 6 to output a switching signal. Plural weight data are divided to plural partial sets and their complementary sets, and weight data are transported between these sets to calculate addition values in sets, and it is checked whether these addition values are within a set allowable range or not. If they are within this range, the total of deviation between addition values in respective partial sets and target weight values set to respective partial sets is obtained, and retrieval is repeated to update and store a combination for which the total value of deviation is smaller, and the last obtained combination is selected as the optimum combination of partial sets.

Description

Detailed Description of the Invention (Field of Industrial Application) The present invention calculates a combination of the weights of objects to be weighed obtained by a plurality of weighing machines, and calculates the optimal combination that is equal to or closest to the target weight value. The present invention relates to a combination weighing device that selects a weighing machine.

(Prior Art) A combination weighing device that finds two different optimal combinations from among a plurality of objects to be weighed that can be combined and participated in one weighing cycle, and discharges them simultaneously or alternately to different discharge routes. It has been known.

In such a device, first, a set of optimal combinations is determined using all the weight data that can be combined, or some of the data, and then the remaining weight data that was not selected as the optimal combination is A method has been adopted in which another set of optimal combinations is determined using the data.

(Problem to be Solved by the Invention) However, in these conventional methods, since the populations from which each optimal combination is sought are different, the deviation between the sum of the optimal combinations found and the target weight value is determined by each population. There is a problem in that even though it is the smallest among the populations, the sum of the deviations between the combined added value and the target weight value is not necessarily the smallest among the populations of both.

To explain specifically, (1) For example, as a result of combining 14 81-volume machines, N0
Weighing machines from 01 to N094 were selected as the optimal combination,
Suppose that the deviation from the target weight value at that time was 0.1 g.・ (2) Next, as a result of combining the remaining 10 weighing machines, No.
, 5 to N008 are selected as the optimal combination of two sets of mouths, and the deviation from the target weight value at that time is 0.7 g.

However, in the first combination, if we select the combination with the second smallest deviation from the target weight value (for example, 0.2 g), for example, the weighing machines from No. 092 to No. 5, then from the remaining Since the combination to be selected is different from the case (2) above, the optimal combination of two sets of ports may have a deviation from the target weight value of 0.4 g, and in that case, the total deviation of the latter value is 0.2 than that of the former
g decreases.

In this way, with the conventional method, it is not possible to minimize the total deviation value of each of the two consecutively determined sets, so it is necessary to minimize the amount of filling when packing the weighed items into bags, including both. The problem was that I couldn't do it.

The present invention aims to solve these problems and provide a combination weighing device that can weigh a combination of both methods with higher precision.

(Means for solving the problem) In order to achieve the above object, the combination weighing device of the present invention has the following features:
It is composed as follows. That is, a plurality of weight data are combined to form a plurality of non-overlapping subsets, and within each formed subset, all weight data belonging to that set are added, and the added value is inscribed in that subset. calculation means for determining the combination of multiple subsets of people within the weight range set by The present invention is characterized by comprising means for selecting a combination of subsets with a minimum total value as an optimal combination.

(Operation) First, divide multiple weight data into multiple subsets and their complementary sets, exchange or move the weight data between these sets, and calculate the sum of the weight data in each subset. Calculate and check whether it is within the set tolerance range. If the added value of any subset is within the set tolerance range, calculate the total value of the deviation between the added value of each subset and the target weight value set for each subset. This value is compared with the previously stored deviation total value to find out which one is smaller. While repeating such searches, the memory of subset combinations with smaller total deviation values is updated, and the last remaining subset combination is selected as the optimal subset combination. This makes it possible to further minimize the total value of multiple subsets.

(Example) An embodiment of the present invention will be described below.

FIG. 1 is a schematic block diagram of a combination weighing device used in the present invention. In the figure, the plurality of weighing machines 1 are
It has the configuration explained in the figure, and the weight Wl of the article weighed by each weighing machine.

W2. ...WN is input to multiplexer 2.

When the timing signal from the packaging machine 6 that wraps the articles discharged from the optimal combination of weighing machines is inputted to the arithmetic and control section 4, which is composed of a microcomputer, etc., the arithmetic and control section 4 sends the switching signal to the multiplexer. The weights W1 to WN are sequentially output from the multiplexer to the A/D converter 3, and the weight converted into a digital signal by the A/D converter is stored in the arithmetic control unit 4. It is stored in a predetermined area of memory. The target weight set by the target weight setting section 5 is stored in a predetermined area in the memory, and the arithmetic control section selects the optimal combination of weighing machines for the target weight through arithmetic processing described later. Sends a signal to discharge the article from the weighing machine.

Next, the combination processing of the present invention will be explained.

Figures 2 (a) and (b) show N pieces of data A.

This is an example of dividing into three sets: a subset of two sets B and its complementary set C (a group of weighing machines that do not belong to either group A or B), and the sum of the weights of the subsets of group A is is WA, and the sum of the weights of the subsets of group B is WB.
We have shown an operating method for determining each group so that the target weights WtA and WtB of each group are WA≧WtA・WB≧WtB and WA+W,→minimum.

The one in Fig. 2(b) is A, 82 from N pieces of weight data.
This shows a case where a set of groups is formed and the above combination conditions are considered for these groups. In this case, each weight data belongs to either group A, B, or C. It turns out. Therefore, there are three choices (A, B, or C) for each weight data, and the number M of combinations to be considered is eight.

However, in this method, the number of combinations is enormous and the computation time is too long to ignore, so the computation time can be shortened by using the difference matrix method described below.

This difference matrix method divides the total set consisting of N elements into a subset PK and 7 complementary sets, and when the sum of the subsets included in PK does not converge to the target value, ■ 1 of PK By repeating the process, the total value of the elements of PK is reached. It searches for something that converges to a value.

In the search, a difference matrix as shown in Table 1 is used.

→ , jcJ is held po'f >1'4) Here, if Wl is the weight of weighing hopper i, alJ is an element having the following value.

When i≠j, a 1 j = W j - W I (In this case, the selection of alj means to use the weight Wj of weighing hopper j instead of using the weight Wl of weighing hopper i that was used up until then. ) When i=j, al' = Wl (In this case, the selection of alJ means that the weight W1 of the weighing hopper i that has been used until then is not used.) In other words, the off-diagonal element alj is the weighing hopper It can be used to find out how much the total weight IW of the subset changed to the next IW when i was changed to j. Also, to add one new hopper, follow the steps in the previous step.
Just add Wl to W.

By using such a difference matrix, when an appropriate number of weight data has already been selected as a subset, for example, i
When weight data from =1 to M is selected, by examining only the part surrounded by the dashed-dotted line in Table 1, it is possible to find out whether the total weight of a subset changes or not. .

Figure 2(a) shows a plurality of the aforementioned subsets (in the figure, A,
This figure shows the data exchange and communication behavior between each group when two groups (B) are set up, and the operations in this case
phase] has the following contents:

However, ΔJA and ΔJ indicate the amount of change in the total weight (additional weight) in each group of A and B, and i,
j indicates the number of the weighing machine, and W, , Wj indicate the weight data of the weighing machines i and j, respectively.

■If you exchange item i from group A with item j from group B, ■If you exchange item i from group A with item j from group C, ■If you remove item i from group A and transfer it to group C, , ■ When item j from group B is added to group A, ■ When item j from group C is added to group A, ■ When item i from group B is exchanged with item j from group A, ■ When item j from group B is When item i is exchanged with item j from group C, ■When item i from group B is removed and moved to group C, ■When item j from group A is added to group B, [Phase] Item j from group C. When added to group B, we get

Here, the target weight values for groups A and B are JAO + JBO
%If the added value of groups A and B is JA + JB, then to find the optimal combination of the two groups, JA≧JAO+JR
Under the condition of ≧JBO, it is sufficient to find a set that minimizes the objective function J= (JA JAG) + (JB JBO).

In this case, in order to decrease the objective function J among the operations from ■ to 0 above, it is only necessary to perform operations that cause the added value of each group to decrease after the operation. Therefore, operations ■ and ■ Only ■ and ■ correspond to this (operation ■ has the same exchange method as operation ■, only i and j have been exchanged, and there is no change in the sum J of the two groups A and B) . Therefore, only a limited number of operations are required during calculation, and thereby the calculation time for finding the optimal combination can be significantly reduced.

Furthermore, as an objective function, J' = (JA JAO) 2+ (Ja −Ja
o) If 2 is determined, the distance from the target weight value of each group can be made smaller by minimizing this J'.

The above arithmetic processing procedure can be summarized as follows.

(a) The above J or J' is used as the evaluation function.

(b) The initial value is determined by selecting a weighing machine in an appropriate manner.
Each additional value of group B is the target weight value JAO + J 8
A combination that exceeds 0.

(C) Next, select a combination that minimizes JA≧JAO, JB≧JBO and J (or J'). This process approaches the target weight value from above to below (in the decreasing direction).

Conversely, it is also possible to search from below the target weight value and converge to the target weight value.

In this case, it is sufficient to perform the operations of (1), (2), (2), and [phase] described above to find the one that minimizes the absolute value of the objective function J.

Figure 3 is an explanatory diagram of the calculation process using the difference matrix when two groups of subsets are provided, and the processing of ■~[phase]' corresponds to the process of ■~[phase] in Figure 2(a). I'm letting you do it. The diagonal lines ``■'' and ``■'' in this matrix indicate cases where they are not used for combination processing, as explained in Table 1.

The evaluation function J=JA+JB in this case is obtained as a superposition of the two matrices JA and JR shown in FIG.

Incidentally, in the above embodiments, the case where the optimal combination of two different sets is determined is explained, but the present invention can be similarly applied to the case where the optimal combination of three or more sets is determined. Further, the target weight values of each group may be equal or different, and the present invention is applicable in either case.

Although the gist of the present invention has been described above with reference to specific embodiments thereof, it is clear that various modifications or modifications of the present invention based on what has already been described are possible.

(Effects of the Invention) As described above, according to the present invention, the total weight of each set can be minimized, so a highly accurate combination weighing device with fewer insertions can be provided.

[Brief explanation of the drawing]

FIG. 1 is a block diagram showing a schematic configuration of a combination weighing device to which the present invention is applied, and FIG. 2(a). (b), FIG. 3 is an explanatory diagram, and FIG. 4 is an explanatory diagram of the combination weighing device. 1... Weighing machine, 2... Multiplexer, 3... A
/D converter, 4... Arithmetic control section, 5... Target weight setting section, 6... Packaging machine. Patent applicant Calbee Co., Ltd. and two other agents
Patent attorney Minoru Tsuji Figure 1 Figure 2 (α) (, b,) Figure 3 Procedural amendment (voluntary) 1988 Patent application No. 330898 2, name combination measuring device 3 of the invention, case of person making an amendment Relationship with Patent Applicant Address 1-20-1 Akabaneminami, Kita-ku, Tokyo Name Calbee Co., Ltd. Satoshi Matsuo Representative Satoshi Matsuo (2 others) 4, Agent 6, " Insert "Disclosed in 1989 Patent Application Publication No. 189419" in column 7 of "Detailed Description of the Invention", in front of "difference matrix method" on page 8, line 14 of the specification of contents of the amendment. .

Claims (3)

[Claims] (1) Combine multiple pieces of weight data to form multiple non-overlapping subsets, add all weight data belonging to that set within each formed subset, and the added value is calculated for that subset. calculation means for determining the combination of multiple subsets that fall within the weight range set by the calculation means; and the sum of the deviations between the sum of the weight data in each of the determined subsets and the target weight value set for each subset. 1. A combinational weighing device comprising means for selecting a combination of subsets with a minimum value as an optimal combination. (2) The calculation means divides the plurality of weight data into a plurality of subsets and their complementary sets, and exchanges or moves the weight data between these sets to combine the plurality of non-overlapping subsets. A combination weighing device according to claim (1), characterized in that the combination weighing device is one that requires the following. (3) The selection means selects the combination of subsets that minimizes the absolute value of the deviation between the added value of the weight data in each subset and the target weight value set for each subset as the optimal combination. A combination measuring device according to claim (1), characterized in that: