JPH0376607A - Method for correcting surface water rate preset value in ready-mixed concrete manufacturing plant - Google Patents

Abstract

PURPOSE:To automatically correct a sand surface water rate preset value by driving a fuzzy inference on the basis of both the deviation amount of a load electric power value at the time of completion of the mixing with respect to the reference load electric power value preset at every mix for a mixer driving motor and the variation amount of a sand surface water rate preset value which constitutes a computation factor for measuring water. CONSTITUTION:The load electric power value of a mixer driving motor 3 at the time of completion of the mixing is detected to compute a deviation amount DELTAP with respect to a reference load electric power value preset at every mix, and the variation amount St of a sand surface water rate preset value is also computed from the value found this time and the preceding value stored in a memory section 12. The deviation amount of the load electric power value and the variation amount of the sand surface water rate preset value are set as the antecedent of a fuzzy inference rule, and a fuzzy inference is drawn based on the membership function of a preset fuzzy set and said inference reference to estimate the correction amount W of the sand surface water rate preset value which is set as the consequent. Thereupon, the sand surface water rate preset value is corrected by the correction amount W thus estimated. By this method, an operational control which is carried out by a skillful operator based on his experiences can be automated.

Description

[Detailed Description of the Invention] [Industrial Application Field] The present invention relates to surface water content in a ready-mixed concrete production plant that produces ready-mixed concrete by measuring and kneading various concrete materials such as gravel, sand, cement, water, and admixtures. This relates to a correction method.

[Prior Art] When producing ready-mixed concrete, it is important to maintain the slump value, which is related to the quality of the ready-mixed concrete, in accordance with the mix design. To do this, it is necessary to measure and knead various concrete materials according to the mix design, but sand, which is one of the concrete materials, has surface water attached to it, so when measuring materials, subtract the surface water amount of the measured sand. You must make sure to measure the water. Since the slump value also fluctuates greatly due to fluctuations in the sand surface water percentage, test room personnel regularly measure the sand surface water percentage and correct the sand surface water percentage setting value on the operation panel. We are also installing moisture meters to monitor the ever-changing surface water content of the sand.

[Problems to be Solved by the Invention] However, it is a heavy burden for laboratory staff to regularly measure the surface water content of sand, and the measured surface water content of sand and the sand that is actually weighed are very burdensome. It is fully conceivable that there may be variations in the surface water content of the concrete, and in that case, the slump value of the ready-mixed concrete to be manufactured will also vary, making it impossible to obtain the desired quality. Therefore, plant operators are required to constantly check whether a product with the desired slump has been achieved by visually checking the ready-mixed concrete being mixed in the mixer or by using a slump meter, which places a heavy burden on them.

Also, it would be good if the surface moisture content of sand could be measured with a moisture meter and this value could be fed back to automatically correct the sand surface moisture content setting value, but it would be better to measure the sand surface moisture content continuously with high accuracy. There is no moisture meter, and most of the moisture meters that are actually installed are just for the operator's reference, and the operator uses this as a reference to manually adjust the sand surface water rate setting value on the operation panel. However, there was a drawback that only a skilled operator could operate the system.

In view of the above points, it is an object of the present invention to apply fuzzy reasoning that makes use of the experience of a skilled operator to automatically correct the sand surface water rate set value.

[Means for Solving the Problems] In order to achieve the above object, the present invention detects the load power value of the mixer drive motor, and calculates the load power value at the time of kneading with respect to the reference load power value of the mixer drive motor set for each mixture. Based on the deviation amount of the load power value and the amount of change in the sand surface water rate setting value, which is a calculation factor for the measured water, fuzzy inference is performed to estimate the correction amount of the sand surface water rate setting value and calculate the appropriate sand surface water. This is to correct the rate setting value.

In addition, at the start of ready-mixed concrete production, fuzzy inference is performed based on the previous and current shipping time interval and the sand surface water rate set value, which is a calculation factor for the measured water, to estimate the correction amount for the sand surface water rate set value. After correcting the sand surface water percentage using the correction amount and resetting the correction amount for the sand surface water percentage setting value, kneading is started, and after that, the load power value of the mixer drive motor installed in the mixer is detected. , Fuzzy inference is performed based on the deviation amount of the load power value at the time of kneading with respect to the reference load power value of the mixer drive motor set for each formulation and the sand surface water rate setting value that is a calculation factor for the measured water. The sand surface water rate setting value is appropriately corrected by estimating the correction amount of the surface water rate setting value.

[Function] In the surface water rate setting value correction method in a ready-mixed concrete manufacturing plant according to the present invention, the load power value of the mixer drive motor during mixing is detected, and the load power value is compared with the reference load power value set for each mixture. The amount of deviation is calculated, and the amount of change thereof is calculated from the previous and current sand surface water rate setting values stored in the storage unit.

Then, the deviation amount of the load power value and the change amount of the sand surface water rate setting value are used as the antecedent part of the fuzzy inference rule, and fuzzy inference is performed based on the preset membership function of the fuzzy set and the inference rule. Then, the correction amount of the sand surface water rate set value which becomes the consequent part is estimated, and the sand surface water rate set value is corrected by the correction amount.

Additionally, if a long time has elapsed since the last shipment when ready-mixed concrete production starts, the water content on the surface of the sand near the discharge part of the sand storage bin has increased. The shipping time interval and sand surface water rate set value are used as the antecedents of the fuzzy inference rule, and the sand that becomes the calculation factor for the measured water is calculated based on the preset membership function of the fuzzy set and the inference rule. The correction amount for the surface water rate set value is estimated, and the sand surface water rate set value is corrected by the estimated correction amount.

By applying such fuzzy reasoning, it becomes possible to automate driving operations that are performed empirically by skilled operators.

[Example] Embodiments of the present invention will be described below based on the drawings.

l is a mixer for kneading various concrete materials,
Kneading blades 3 disposed inside are rotated at a constant speed by a mixer drive motor 2. Disposed above the mixer 1 are various measuring tanks (not shown) for gravel, sand, cement, etc., and a water measuring tank 5 supported by a weight detector 4. A water storage tank 6 is arranged above the water measuring tank 5.
A predetermined amount of water discharged by the opening/closing control of the water metering valve 7 is measured in the water metering tank 5, and the water is poured into the mixer 1 as metered water.

A load power detector 8 that detects the load power (or load current) of the motor is connected to the mixer drive motor 2, and the signal detected by the load power detector 8 is sent to a surface water rate set value correction device 9. Let me input it. The surface water rate setting value correction device 9 includes a fuzzy control unit 10 that performs fuzzy inference using fuzzy set membership functions and fuzzy inference rules, which will be described later, and a calculation unit 11 that calculates various input signals.
and a storage unit 12 that stores various data serving as the antecedent of the input fuzzy inference rule and data input for inference.
It consists of etc. Further, the surface water rate set value correction device 9 is connected to the operation panel 13, and when the sand surface water rate set value corrected from the surface water rate set value correction device 9 is input to the operation panel 13, the concrete mixture is changed. Calculates the amount of water to be measured and controls the amount of water.

Next, a method of fuzzy inferring the correction amount of the sand surface water rate setting value based on the load power value of the mixer drive motor 2 detected by the load power detector 8 and the amount of change in the sand surface water rate setting value will be described.

When production of ready-mixed concrete is started by operating the operation panel 13, the surface water rate set value correction device 9 receives the material measurement start signal as well as the mixture number, kneading capacity, and sand surface water rate set value from the operation panel 13, and stores it in the storage section. 12. Next, control panel 1
When the kneading start signal is received from 3, the load power detector 4 detects the load power value of the mixer drive motor 2 at regular intervals and stores it in the storage section 12. Furthermore, when a kneading end signal is received from the operation panel 13, detection of the load power value of the mixer drive motor 2 is stopped, and among the load power values stored in the storage unit 12,
A plurality of load power values at the time of elaboration are taken out to the calculation unit 11 and an average value is obtained. Then, the reference load power value corresponding to the blending number received from the operation panel 13 is retrieved from among the reference load power values at the time of kneading for each blend that have been set and stored in the storage unit 12 in advance, and the reference load power value corresponding to the blending number received from the operation panel 13 is taken out to the calculation unit 12, and according to the kneading capacity. The reference load power value calculated is calculated and compared with the average value of the load power values at the time of kneading to calculate the deviation amount ΔP (KW) of the load power value. Further, the sand surface water percentage set value set during the previous kneading is compared with the sand surface water percentage set value set during the current kneading to calculate the change st (%) in the sand surface water percentage set value. The deviation amount ΔP of the load power value calculated by the calculation unit 12 and the amount of change in the sand surface water rate setting value are input to the fuzzy control unit 11.

The fuzzy control unit 11 performs fuzzy inference based on the membership function of the fuzzy set and the inference twin law in order to estimate the appropriate correction amount W (%) of the sand surface water rate setting value from the input signal. Figure 2 shows the deviation amount Δ of the load power value.
This is a membership function for qualitatively evaluating the size of P. ΔP(i) (i=1 to 7) in the figure is a constant that defines the form of the membership function and is determined as appropriate.

PB, PM, PS, ZR%NS, NM, and NB are names given to membership functions for qualitatively evaluating the magnitude of the deviation amount ΔP of the load power value, and each has the following meaning.

PB: Po5itive BigPM:
Po5itive MediumPS:
Po5itive SmallZR: Zer.

NS: Negative Small NM
: Negative MediumNB :
Negative Big Also, the vertical axis of the figure is the membership value. Using this membership value, the deviation amount ΔP of the load power value is qualitatively evaluated.

FIG. 3 shows membership functions for qualitatively evaluating the magnitude of the change St in the sand surface water rate setting value. S in the diagram
t (i) (i=1 to 7) is a constant that defines the form of the membership function and is determined as appropriate. PB, PM, PS
, Z.R., N.S., N.M.

NB is the name given to the membership function in order to qualitatively evaluate the magnitude of the change St in the sand surface water rate setting value.

Figure 4 shows an inference rule for qualitatively determining the correction amount W of the sand surface water rate setting value from the qualitative relationship between the deviation amount ΔP of the load power value and the change amount St of the sand surface water rate setting value. be. For example, the inference rule on the top left is IF(△P is PB
and 5tisPB) THEN W is
It means NB.

This means ``If the load power value of the mixer at the time of kneading is very large compared to the standard load power value, and the amount of change in the sand surface water rate setting value is extremely large on the positive side (the surface water rate set at this time ``If the surface water rate is much larger than the surface water rate set during the previous mixing,'' (antecedent part) and ``the correction amount of the sand surface level set value should be greatly increased to the negative side.'' (consequent part) It shows the rules.

FIG. 5 shows membership functions for converting the qualitatively determined correction amount of the sand surface water rate setting value into a quantitative value. W(i) (i=1 to 7) in the figure is a constant that defines the shape of the membership function, and is a correction amount for the sand surface water rate setting value, which is determined as appropriate. PB%PM, PS%ZR
, NS, NM, and NB are the names given to the membership functions for qualitatively expressing the magnitude of the correction amount of the sand surface water rate setting value, and correspond to the names used in FIG. Also, the vertical axis of the figure is the membership value.

Then, the correction amount for the sand surface water rate setting value is determined qualitatively from the applied inference rules. In addition, when the correction amount of the sand surface water rate setting value is defined by a plurality of membership functions based on a plurality of inference rules, the actual correction amount is a weighted average value according to each membership value. The correction amount of the sand surface water rate set value obtained by fuzzy reasoning in this way is added to or subtracted from the current sand surface water rate set value, and the result is transmitted to the operation panel 13 as the next sand surface water rate set value. The operation panel controls water metering based on this sand surface water rate setting value.

Furthermore, a method of fuzzy inferring the correction amount of the sand surface water percentage setting value based on the shipping time interval and the sand surface water percentage at the time of starting production of ready-mixed concrete will be described.

If a considerable amount of time has passed between the previous shipping time and the current shipping time, the sand surface water rate setting value is corrected based on the shipping time interval and the sand surface water rate setting value, and the operation When production of ready-mixed concrete is started by operating the panel 13, the sand surface water rate setting value correction device 9 receives a measurement start signal for each material from the operating panel 13. Then, the time at that point is stored in the storage unit 12, and the subsequently received sand surface water rate setting value S (%) is stored in the storage unit 12. Then, the calculation unit 11 compares the time of the current measurement with the time of the previous measurement, and calculates the shipping time interval Δt (minutes).

When this shipping time interval △t and the sand surface water rate set value S are sent to the fuzzy control unit 10, the fuzzy control unit IO determines whether the shipping time interval △t exceeds a predetermined time (for example, 20 minutes). If it exceeds the set value, fuzzy inference is performed based on the membership function of the fuzzy set and the inference rule to determine the correction amount S'' (%) of the sand surface water rate setting value.

FIG. 6 shows membership functions for qualitatively evaluating the size of the shipping time interval Δt. △t (i
) (i=1 to 7) are constants that define the form of the membership function and are determined as appropriate.

B7, B6, B5, B4, B3, B2, and Bl are symbols given to the membership functions to qualitatively evaluate the magnitude of the shipping time interval Δt, and unlike the above-mentioned names, they have no particular meaning. Also, the vertical axis of the figure is the membership value. This membership function is used to qualitatively evaluate the size of the shipping time interval Δt.

Figure 7 shows membership functions for qualitatively evaluating the size of the sand surface water rate setting value S, and shows B7, B6, B
5, B4, B3, B2, and Bl are symbols given to the membership function in order to qualitatively evaluate the magnitude of the sand surface water rate setting value S. FIG. 8 shows an inference rule for qualitatively determining the correction amount S' of the sand surface water rate setting value from the qualitative relationship between the shipping time interval Δt and the size of the sand surface water rate setting value S. The rules are the same as described for Figure 4. For example, if one of the inference rules is written, IF(Δt
is B7 and S 1sB7 TH
EN S' is PB). This means that ``if the shipping time interval is very long and the sand surface water rate setting value is a very high value'' (antecedent part), ``the correction amount of the sand surface water rate setting value is extremely positive. Make it more.”
(Consequent part) shows the rule.

This is because if the sand stored in the sand storage bin (not shown) is left undischarged for a long time, the surface water of the sand will settle and the surface water content of the sand near the bottom of the storage bin will increase. This tendency becomes stronger as the surface water percentage of sand increases, so the sand surface water percentage setting value is compensated for by the shipping time interval and the sand surface water percentage setting value.
It is something that does justice.

FIG. 9 shows a membership function for converting the qualitatively determined correction amount of the sand surface water rate setting value into a quantitative value. In the figure, S'(i) (i=1 to 7) is a constant that defines the shape of the membership function, and is a correction amount from the previously set sand surface water rate setting value, which is determined as appropriate. P.B., P.M.
, PS, ZR, NS, NM, and NB are the names given to the membership functions to qualitatively represent the magnitude of the correction amount of the sand surface water rate setting value, and the names used in Fig. 8 are as follows. Compatible. And its meaning is as described above.

Also, the vertical axis of the figure is the membership value. The applied inference rule qualitatively determines which membership function the sand surface water rate setting value belongs to. If the correction amount for the sand surface water rate set value is specified by multiple membership functions based on multiple inference rules, the weighted average value according to each membership value is used as the correction amount for the actual sand surface water rate set value. .

The correction amount of the sand surface water rate setting value for which this fuzzy inference has been performed is added or subtracted from the previous sand surface water rate setting value, and the result is transmitted to the operation panel 13 as the current sand surface water rate setting value. The operation panel 13 controls the water metering by taking this sand surface water rate setting value into consideration.

This fuzzy inference based on the shipping time interval and sand surface water rate setting value is applied only when the shipping time interval exceeds a preset time (for example, 20 minutes or more), and usually the load power during mixing of the mixer described above is applied. The sand surface level set value is corrected based on the deviation amount of the value and the change rate of the sand surface water rate set value.

Although the membership functions used in this example were all triangular, they are not necessarily limited to this shape, and various curves may be adopted based on the characteristics of the dispersion of the sand surface level and the operator's past experience. This does not change the essence of the present invention. Further, the essence of the present invention does not change even if not only the form of the membership function but also the number thereof is arbitrarily set.

Further, in the embodiment, an example is shown in which the operation panel and the surface water rate setting value correction device are separated, but the surface water rate setting value correction device may be integrated into the operation panel.

[Effects of the Invention] As explained above, according to the method for correcting the surface water percentage setting value for a ready-mixed concrete producing blunt according to the present invention, the amount of deviation in the mixer load power value and the amount of change in the sand surface water percentage setting value at the time of mixing are reduced. Since the amount of correction for the sand surface water rate set value is determined by performing fuzzy inference from the size of be able to.

In addition, at the start of production of ready-mixed concrete, the sand surface water rate set value is corrected by fuzzy inference based on the shipping time interval and the sand surface water rate set value, and then the sand surface water rate set value is corrected by the fuzzy inference. As a result, even if the surface water content of the sand at the bottom of the sand storage bin changes after a considerable shipping time interval, the surface water content can be automatically corrected using the experience of a skilled operator. can be done,
Ready-mixed concrete of consistently stable quality can be produced.

[Brief explanation of drawings]

Figure 1 is a diagram illustrating an embodiment of the method of the present invention, Figure 2 is a diagram showing a membership function for evaluating the amount of deviation in the load power value of the mixer, and Figure 3 is the amount of change in the sand surface water rate setting value. Figure 4 is a diagram showing an example of a rule for predicting the correction amount of the sand surface water rate setting value, and Figure 5 is the membership for the correction amount of the sand surface water rate setting value. Figure 6 shows the Menpage-knob function for evaluating the shipping time interval, Figure 7 shows the Menpage-Tub function for evaluating the sand surface water rate setting value, and Figure 8 shows the correction amount for the sand surface water rate setting value. FIG. 9, which is a diagram showing an example of the prediction rule, is a membership function for the correction amount of the sand surface water setting value.

Claims (2)

[Claims] (1) The load power value of the mixer drive motor installed in the mixer that mixes various concrete materials is detected, and the amount of deviation of the load power value at the time of mixing with respect to the reference load power value of the mixer drive motor set for each mixture. and the amount of change in the sand surface water rate set value, which is a calculation factor for the measured water, are taken as the antecedent part of the fuzzy inference rule, and the correction amount of the sand surface water rate set value is taken as the consequent part of the fuzzy inference rule. Fuzzy inference is performed based on the load power value of the mixer drive motor detected at the time of mixing, and the amount of change in the sand surface water rate setting value calculated from the sand surface water rate set at the current and previous mixing. A method for correcting a surface water rate setting value in a ready-mixed concrete manufacturing plant, comprising estimating a correction amount for the rate setting value, and correcting and resetting the sand surface water rate using the correction amount. (2) At the start of ready-mixed concrete production, the shipping time interval and the sand surface water rate are used as the antecedents of the fuzzy inference rule, and the correction amount of the sand surface water rate set value, which is the calculation factor for the measuring water, is calculated after the fuzzy inference rule. Based on the time elapsed from the previous shipment to the current shipment and the sand surface water rate set value, fuzzy inference is performed to estimate the correction amount for the sand surface water rate set value, and the sand surface After correcting and resetting the water ratio, kneading is started. From then on, the load power value of the mixer drive motor installed in the mixer is detected, and the kneading is performed based on the mixer drive motor standard load power value set for each mixture. The amount of deviation in the load power value at the time of rise and the amount of change in the sand surface water rate set value, which is a calculation factor for the measured water, are used as the antecedents of the fuzzy inference rule, and the correction amount of the sand surface water rate set value is calculated using fuzzy inference. This is the consequent part of the rule, and is based on the load power value of the mixer drive motor detected at the time of mixing and the amount of change in the sand surface water rate setting value calculated from the sand surface water rate set at the current and previous mixing. Surface water rate setting in a ready-mixed concrete production plant, characterized in that the sand surface water rate is corrected and reset by performing fuzzy inference and estimating the correction amount of the sand surface water rate setting value using the correction amount. Value correction method