JP5969912B2 - Driving efficiency estimation device and program - Google Patents

Description

  The present invention relates to a compressor control technique, and more particularly to an operation efficiency estimation technique for individually estimating compressor operation efficiency for a plurality of compressors operated in parallel.

  In facilities such as factories, a compressed air supply system using a plurality of compressors is provided, and by operating these compressors in parallel, the air (or mixed gas such as refrigerant) is compressed, and the obtained compressed air is used. Once collected in the buffer tank, it is distributed and supplied from the header to each load of the facility.

  The power energy consumed by such a compressed air supply system occupies a relatively large proportion of the power energy consumed by the entire facility. For this reason, when energy saving and CO2 saving of equipment are considered, energy saving and CO2 saving in the compressed air supply system, that is, improvement in operating efficiency in each compressor is required.

  The operating efficiency of the compressor is presented as technical data by the manufacturer. This operating efficiency is the best value obtained during rated operation when the compressor is operated stably for a certain time at the maximum discharge rate, that is, the rated efficiency. Alternatively, the flow rate obtained when the input power drops below the rated power is also the so-called steady state, that is, the characteristics obtained by continuing the operation at the same output for a certain period of time when the relationship between the power and the flow rate is determined stably. Is. Therefore, if the new compressor can be operated at almost the rated value at all times or can be continuously operated at a constant output, the operation efficiency according to such specifications can be obtained.

  However, in the compressed air supply system, the amount of compressed air consumed varies depending on the operating condition on the load side, so the operating state of the compressor is adjusted to maintain the supplied compressed air amount and air pressure at appropriate values. There is a need. For this reason, the rated efficiency cannot be obtained in an actual situation where the operating state of the compressor changes. Therefore, in order to improve the efficiency of the compressed air supply system, it is necessary to grasp what operating efficiency each compressor is actually operating.

  Further, since the operating efficiency of the compressor is lowered not only by the operating state but also by the aging of the compressor, it is necessary to perform maintenance periodically. At this time, by performing maintenance from the compressor having the greatest decrease in operating efficiency, the operating efficiency of the entire compressed air supply system can be improved at an early stage. Therefore, it is important to grasp the operation efficiency of each compressor individually.

  Further, in the compressed air supply system, the number control for efficiently operating the compressors is performed by starting / stopping each compressor according to the magnitude of the load measured by the supply pressure or flow rate of the compressed air. In this case, among the compressors, a method of selecting and starting the compressors in order from those having the highest operating efficiency is a basic concept of unit control based on energy saving and CO2 saving. Therefore, it is important to always keep track of the operation efficiency of each compressor individually.

  Conventionally, in such a compressed air supply system, a technique for managing the operation efficiency of each compressor has been proposed (see, for example, Patent Documents 1-3). According to these, in addition to the supply energy index collected for each compressor, such as the amount of power used in the compressor, the consumption efficiency index such as the flow rate data for the compressor is used to obtain the operating efficiency of each compressor. It has become.

JP 2011-248568 A JP 2012-068878 A JP 2001-191789 A

  In such a conventional technique, the operating efficiency of each compressor is obtained by using a consumption energy index such as flow rate data in each compressor in addition to a supply energy index such as power consumption in each compressor. For this reason, equipment such as a flow meter for measuring the flow rate of the compressed air output from the compressor is required for each compressor. Therefore, according to the prior art, in order to obtain the operation efficiency of the compressor, it is necessary to add equipment to each compressor, and not only the equipment cost but also the management cost is required, or the compressor is installed for measuring instrument installation. There was a problem that it was necessary to stop the operation.

  This invention is for solving such a subject, and it aims at providing the compressor efficiency estimation technique which can estimate the operating efficiency of a compressor easily, without adding an installation apparatus for every compressor. Yes.

  In order to achieve such an object, the operation efficiency estimating apparatus according to the present invention is configured for n (n is an integer of 2 or more) compressors Ci (i = 1 to n) in parallel operation. An operation efficiency estimation device that individually estimates the operation efficiency of a compressor, and uses power consumption Wti indicating individual power used by each compressor Ci at each time t, and compressed air supplied from these compressors Ci A data collection unit that collects an overall flow rate Qt indicating an overall flow rate, and stores the power usage amount Wti and the overall flow rate Qt in a storage unit as a data set of the time t, and the data stored in the storage unit A data set selection unit that selects m (m> n) data sets in which the total flow rate Qt is constant or increasing from the data sets as the target data set Dt; Based on the target data set Dt, each compressor including the partial regression coefficient ai of the multiple regression equation is obtained by obtaining a multiple regression equation representing the objective variable consisting of the total flow rate Qt as an explanatory variable consisting of the power consumption Wti. An operation efficiency calculation unit for calculating the operation efficiency Ui of Ci.

Further, in one configuration example of the operating efficiency estimation device, the data set selection unit may select a data set in which the overall flow rate Qt is reduced among the data sets stored in the storage unit as new target data. Re-select n sets as set Dt,
The operation efficiency calculation unit calculates the flow rate change rate λt related to the total flow rate Qt, the total flow rate Qt, the power usage amount Wti, and the partial regression coefficient ai, which are obtained for each of the reselected target data sets Dt. Using the operation efficiency characteristic coefficient bi for each compressor Ci indicating a slope of a linear function that approximates the relationship between the flow rate change rate and the operation efficiency, the flow rate calculation formula for the total flow rate Qt is calculated for each target data set Dt. The operation efficiency characteristic coefficient bi is calculated by generating n in a flow rate and solving these flow rate calculation formulas as simultaneous equations.

Thus, by multiplying the flow rate change rate λx at an arbitrary time x by the operating efficiency characteristic coefficient bi of the compressor Ci and adding the partial regression coefficient ai of the compressor Ci, each compressor Ci at the time x is added. The operation efficiency Uxi can be calculated.
In addition, by preparing 2 × n target data sets Dt and solving simultaneous equations, the partial regression coefficient ai of the compressor Ci and the partial regression coefficient ai of the compressor Ci can be calculated simultaneously. The operation efficiency Uxi for each compressor can be obtained individually.

  Moreover, the program concerning this invention is a program for functioning a computer as each part of the said driving efficiency estimation apparatus.

  According to the present invention, the operating efficiency of each compressor is reduced to the power consumption of each compressor obtained with a power meter installed in advance in a general compressed air supply system and the total flow rate obtained with the flow meter. Calculated based on For this reason, it becomes possible to estimate the operating efficiency of each compressor easily without requiring addition of equipment such as a flow meter for measuring flow rate data in the compressor, for example.

  In addition, since the operation efficiency can be estimated for each compressor, the administrator can easily grasp what operation efficiency each compressor is actually operating. This makes it possible to review the response controllability considering the characteristics of the compressor according to the amount used, set more highly efficient operating conditions, and review the operating sequence in unit control, realizing energy saving and CO2 saving. it can. In addition, it is possible to plan whether or not maintenance is required for each compressor, and from which compressor to perform maintenance in order, and it is possible to provide extremely useful data for determining whether or not to replace a compressor.

It is a block diagram which shows the structure of a driving efficiency estimation apparatus. It is a graph which shows the relationship between electric power consumption and an air flow rate. It is a graph which shows the operation efficiency characteristic depending on the flow rate change rate of an air flow rate. It is a structural example of a data set. It is a structural example of coefficient data. It is a flowchart which shows the driving efficiency calculation process concerning 1st Embodiment. It is an example of a list display screen of operational efficiency. It is a flowchart which shows the coefficient calculation process concerning 2nd Embodiment. It is a flowchart which shows the other coefficient calculation process concerning 2nd Embodiment. It is a flowchart which shows the driving efficiency calculation process concerning 2nd Embodiment. It is an example of an individual display screen of operational efficiency. It is an example of another list display screen of driving efficiency.

[Principle of the Invention]
First, the principle of the present invention will be described.
In a compressed air supply system in which n (n is an integer of 2 or more) compressors C1 to Cn are operated in parallel, the operation efficiency of each compressor C1 to Cn is individually observed and analyzed by a conventional method. In Ci (i = integer from 1 to n), it was confirmed that there was a correlation between the power consumption amount Wi and the air flow rate Qi of the compressed air. On the other hand, since the operating efficiency Ui consisting of the basic unit of the compressor Ci is obtained by the product of the electric power consumption Wi and the air flow rate Qi, the operating efficiency Ui can be estimated by estimating the slope of this correlation function.

FIG. 2 is a graph showing the relationship between the power consumption and the air flow rate. Since this correlation was observed to have a slope ai unique to the compressor Ci, if these slopes ai are used, the overall flow rate Q of the compressors C1 to Cn can be expressed by the following equation (1). it can.

Here, when there are n compressors Ci, there are n slopes ai, and therefore, the air flow rate Qi is measured for each compressor Ci by preparing n equations (1) and solving them as simultaneous equations. Without performing this, the slope ai, that is, the operating efficiency Ui can be obtained from the data set of the total flow rate Q and the power consumption amount Wi.
However, as described above, since the operation state of each of the compressors C1 to Cn is changed in accordance with the load fluctuation, the relationship between the actually measured overall flow rate Q and the power usage amount Wi cannot be ignored in terms of operation management. Thus, it is difficult to accurately obtain the driving efficiency Ui.

  In the present invention, attention is paid to the fact that the relationship between the total flow rate Q and the power consumption amount Wi cannot be ignored, and more than n equations (1) are prepared for each time t. A multiple regression analysis process for obtaining a multiple regression equation that expresses an objective variable consisting of Qt as an explanatory variable consisting of the power consumption Wti is executed, and the operating efficiency Ui of the compressor Ci consisting of the partial regression coefficient ai of the multiple regression equation is calculated. Thus, the operation efficiency Ui in which the influence of variation is reduced is obtained.

  On the other hand, as a result of individually observing and analyzing the operation efficiency of each of the compressors C1 to Cn, it was found that the operation efficiency tends to decrease in a specific time zone. Further, as a result of analyzing the relationship between the air flow rate and the operation efficiency in more detail, it was found that the operation efficiency was reduced during the time zone in which the air flow rate was decreasing.

FIG. 3 is a graph showing operating efficiency characteristics depending on the flow rate change rate of the air flow rate. Here, the horizontal axis indicates the change rate λ [%] of the air flow rate, and the vertical axis indicates the compressor Ci composed of the basic unit.
The operation efficiency Ui [m ³ / kWh] is shown. According to this graph, when the flow rate change rate λ is 0 or more, that is, when the air flow rate is the same or increased as compared with the immediately preceding time, the operation efficiency Ui of the compressor Ci is substantially constant, and the flow rate change rate. When the air flow rate is reduced compared to the negative side region where λ is less than 0, that is, immediately before the time, the operation efficiency Ui is reduced in accordance with the magnitude of the flow rate change rate λ. One reason for this is that when the air flow rate is reduced, the compressor Ci first throttles the flow restrictor in an attempt to reduce the flow rate, but the operation of the motor is reduced with a time delay compared to the operation of the flow restrictor. It can be considered that useless current consumption occurs.

  In the present invention, among the operation efficiency characteristics depending on the flow rate change rate λ of the air flow rate in the compressor Ci, the operation efficiency U is substantially constant when the air flow rate is the same or increased compared to the immediately preceding time. Focusing on the fact, as a data set used when performing multiple regression analysis, the total flow rate Qt when the total flow rate Qt at an arbitrary time t is in a constant state or increasing compared to the immediately preceding time, and the power consumption amount Wti A data set is selected and used.

[First Embodiment]
Next, with reference to FIG. 1, the driving | running efficiency estimation apparatus 10 concerning the 1st Embodiment of this invention is demonstrated. FIG. 1 is a block diagram showing the configuration of the driving efficiency estimation device.

  The operation efficiency estimation device 10 is composed of an information processing device such as a controller, a server device, and a personal computer as a whole, and is collected from the compressed air supply system 1 in which a plurality of compressors C (C1 to Cn) are operated in parallel. Based on the electric power consumption Wti (an integer of i = 1 to n) relating to the compressors C1 to Cn and the overall flow rate Qt, the operation efficiency relating to the individual compressors C1 to Cn is estimated.

  In the compressed air supply system 1 shown in FIG. 1, compressed air obtained by operating the compressors C1 to Cn in parallel with the supplied power PW passes through the pipe 2 and the buffer tank 3 to the pipe 4 and the header. 5 is supplied to each load 6 such as a processing machine that consumes compressed air. These compressors C are provided in the total flow rate Qt of compressed air per unit time measured by the compressor control unit 7 for a predetermined time which is a management target by the flow meter 4A provided in the pipe 4 or in the header 5. By controlling the number of units based on the pressure Pt of the compressed air measured by the pressure gauge 5A, the operation / stop or load / unload is individually controlled to stably supply the compressed air to the load 6.

[Operating efficiency estimation device]
Next, the configuration of the driving efficiency estimation device 10 will be described with reference to FIG.
The driving efficiency estimation apparatus 10 includes a data collection unit 11, an operation input unit 12, a screen display unit 13, a storage unit 14, a data set selection unit 15, and an operation efficiency calculation unit 16 as main functional units. .

  The data collection unit 11 measures the individual electric power used per unit time at each time t measured by the wattmeter 8 (81-8n) provided for each compressor Ci (i = 1 to n). A function of collecting the electric power consumption Wti that is indicated, and an overall flow rate Qt that is measured by the flowmeter 4A provided in the pipeline 4 and that indicates the flow rate of the entire compressed air supplied from the compressor Ci, and these electric power consumptions It has a function of storing Wti and the entire flow rate Qt in the storage unit 14 as a data set 14A for the time t. In addition, when the electric power P (W) is measured with a measuring instrument capable of obtaining the electric energy kWh, it is necessary to set the integrated value.

The operation input unit 12 includes an operation input device such as a keyboard and a mouse, and has a function of detecting and outputting an operator's operation.
The screen display unit 13 includes a screen display device such as an LCD, and has a function of displaying an operation screen for estimating driving efficiency and a data screen obtained by each functional unit.

The storage unit 14 includes a hard disk and a semiconductor memory, and has a function of storing various processing data and programs 14P used for processing in each functional unit.
The program 14P is a program for realizing each functional unit by being executed by a computer, and is read from an external device or a recording medium and stored in the storage unit 14 in advance.

Main processing data stored in the storage unit 14 includes a data set 14A and coefficient data 14B.
The data set 14 </ b> A is data composed of a set of the power usage amount Wti and the total flow rate Qt in each compressor Ci at each time t collected by the data collection unit 11.
FIG. 4 is a configuration example of a data set. Here, the power usage amount Wti and the total flow rate Qt collected by the data collection unit 11 are stored every time t.

The coefficient data 14B is data indicating a partial regression coefficient ai corresponding to the operation efficiency Ui of each compressor Ci.
FIG. 5 is a configuration example of coefficient data. Here, the partial regression coefficient ai is stored for each compressor Ci. In this example, for each compressor Ci, an operation efficiency characteristic coefficient bi is also stored as an index of responsiveness to a change in usage amount described later.

  The data set selection unit 15 sets m data sets in the constant state or increasing in which the overall flow rate Qt continues at the same value from the data sets 14A stored in the storage unit 14 as the target data set Dt. (M> n) has a function to select.

  Based on the m target data sets Dt selected by the data set selection unit 15, the operation efficiency calculation unit 16 represents a multiple regression equation that expresses the objective variable consisting of the total flow rate Qt as an explanatory variable consisting of the power usage amount Wti. A function of calculating the operating efficiency Ui of the compressor Ci composed of the partial regression coefficient ai of the multiple regression equation by executing the obtained multiple regression analysis process, and a function of displaying the operating efficiency Ui on the screen display unit 13 Have.

[Operation of First Embodiment]
Next, operation | movement of the driving efficiency estimation apparatus 10 concerning this Embodiment is demonstrated.
First, with reference to FIG. 6, the driving efficiency calculation process in the driving efficiency estimation apparatus 10 will be described. FIG. 6 is a flowchart showing an operation efficiency calculation process according to the first embodiment.
The data set selection unit 15 executes the operation efficiency calculation process of FIG. 6 according to the operator operation detected by the operation input unit 12, every fixed time, or every time zone set by a program or the like. . In the driving efficiency calculation process, it is assumed that the data set 14A at each time t collected by the data collection unit 11 is stored in the storage unit 14 in advance.

First, the data set selection unit 15 selects a data set at an unselected time t from the data set 14A in the storage unit 14 (step 100), and sets the total flow rate Qt of the data set, for example, from time t to unit time. Compared with the total flow rate Qt-1 measured only before, it is confirmed whether Qt is constant or increasing (step 101).
Here, when Qt <Qt−1 (step 101: NO), the data set selection unit 15 returns to step 100 and newly selects a data set at an unselected time.

On the other hand, when Qt ≧ Qt−1 (step 101: YES), the data set selection unit 15 determines that the compressor Ci is based on the rated output based on the power usage Wti of the compressor Ci during operation. (Step 102).
Here, when there is a compressor Ci that is not operated in the rated operation range (step 102: NO), the data set selection unit 15 returns to step 100 and newly selects a data set at an unselected time.
On the other hand, when all the compressors Ci in operation are operated in the rated operation range (step 102: YES), the data set selection unit 15 extracts the data set as the target data set Dt and stores it in the storage unit 14. (Step 103).

  At this time, the rated output of the compressor may be a value presented as a specification by the manufacturer, but in actuality, the compressor may be operated with a power larger than the presented value. Also, the rated output may be reduced due to aging. Therefore, in such a case, it is only necessary to reset the maximum value of the actually measured power consumption Wti as the rated output for each compressor Ci.

  In this way, the data set selection unit 15 repeatedly executes data sets in which Qt is in a constant state or increasing, until m (m> n) data sets are extracted as Dt (step 104: NO).

  When only Dt are extracted (step 104: YES), the operation efficiency calculation unit 16 assigns a partial regression coefficient ai to each compressor Ci (step 105), and based on these Dt, an objective variable consisting of Qt is assigned. Is calculated by an explanatory variable consisting of Wti to calculate the operating efficiency Ui of the compressor Ci consisting of the partial regression coefficient ai of the multiple regression equation (step 106).

  Thereafter, the operating efficiency calculation unit 16 stores the obtained partial regression coefficient ai as coefficient data 14B in the storage unit 14 (step 107), and the rated efficiency Uri of each compressor Ci stored in the storage unit 14 in advance. By obtaining and subtracting the partial regression coefficient ai, that is, the operation efficiency Ui from these Uri, and dividing by Uri, the operation efficiency deterioration rate Ri is calculated, and these are displayed on the screen display unit 13 (step 108). Then, a series of operation efficiency calculation processing is completed.

FIG. 7 is an example of a list display screen for operating efficiency. Here, the operating efficiency Ui, the rated efficiency Uri, and the operating efficiency deterioration rate Ri are displayed in a list for each of the compressors C1 to Cn.
With this list display screen, it is possible to easily confirm the operation status and the operation efficiency related to each of the compressors C1 to Cn, and to easily compare the compressors C1 to Cn.

[Effect of the first embodiment]
As described above, according to the present embodiment, the data set selection unit 15 selects a data set whose total flow rate Qt is in a constant state or increasing from the data set 14A stored in the storage unit 14 as a target data set. Multiple regression (m> n) is selected as Dt, and the operation efficiency calculation unit 16 represents the objective variable consisting of the total flow rate Qt as an explanatory variable consisting of the electric power consumption Wti based on the target data set Dt. By calculating the equation, the operation efficiency Ui of the compressor Ci consisting of the partial regression coefficient ai of the multiple regression equation is calculated.

  Thereby, the operation efficiency Ui of each compressor Ci was obtained with the electric power consumption Wti of each compressor Ci obtained with the wattmeter 8 previously installed in the general compressed air supply system 1, and with the flow meter 4A. Calculated based on the total flow rate Qt. For this reason, it is possible to easily estimate the operating efficiency Ui of each compressor Ci without requiring the addition of equipment such as a flow meter for measuring flow rate data in the compressor Ci, for each compressor Ci. It becomes. At this time, if the wattmeter 8 is not installed, it is necessary to add the wattmeter 8 for each compressor Ci, but it is not necessary to add a flow meter for each compressor Ci as in the prior art.

  In addition, since the operation efficiency can be estimated for each of the compressors C1 to Cn, the compressors C1 to Cn are actually operated at what operation efficiency by the operation efficiency list display screen as shown in FIG. The administrator can easily grasp whether it is. Thereby, the operation order in the unit control can be reviewed, and energy saving and CO2 saving can be realized. Further, it is possible to plan whether or not maintenance is required for each of the compressors C1 to Cn, and from which compressor C1 to Cn, the maintenance is sequentially performed. It is possible to provide extremely useful data for judgment of time.

  Moreover, in this Embodiment, the case where the driving efficiency calculation process of FIG. 6 was each performed according to operator operation or every fixed time was demonstrated. At this time, since the operation efficiency characteristics of the compressors C1 to Cn do not change so rapidly, the operation efficiency calculation processing is automatically executed, for example, every several months or one year according to the maintenance cycle. Alternatively, it may be automatically performed at an arbitrary frequency such as one day or one week.

Further, in the operation efficiency calculation process of FIG. 6, in order to verify the validity of the obtained operation efficiency Ui, the following process may be executed.
First, in the same manner as in steps 100 to 104, data sets Dt in a time zone in which the overall flow rate Qt is in a constant state or increasing in rated operation are extracted by m times k times the number n of compressors. At this time, k and m may be appropriately set and adjusted as necessary.
Next, in the same manner as steps 105 to 106, multiple regression analysis is performed using about half of m or m1 data sets of a necessary number as appropriate, and a multiple regression equation is obtained.

Thereafter, the obtained operation efficiency Ui and the power consumptions Wt1 to Wtn of the remaining m2 (= m−m1) data sets not used in the multiple regression analysis from the m pieces are expressed in the multiple regression equation. To calculate the total flow rate Qt ′.
Here, Qt ′ obtained by back calculation is compared with the total flow rate Qt (actual measurement value) of m2 data sets, and a range Eq in which the flow rate difference ΔQ = | Qt′−Qt | It is determined whether it is within (practical tolerance), and if ΔQ is within the range of Eq,
It may be determined that the operation efficiency Ui obtained by the multiple regression analysis is valid, and the operation efficiency Ui may be stored or displayed as the current operation efficiency (basic unit).

On the other hand, if ΔQ does not fall within the range of Eq, it is determined that the obtained operation efficiency Ui is not valid, and m1 or m1 ± Δm data sets are re-extracted from m data sets. To do. At this time, the data set to be re-extracted may be an unextracted data set, or a part of the data set may be extracted. Alternatively, m data sets different from the previous time may be newly extracted.
Then, the multiple regression analysis is re-executed using the extracted data set, and the re-extraction of the data set may be repeatedly executed until the validity of the operation efficiency Ui is obtained by comparing ΔQ and Eq. Further, if the re-extraction is repeated a specified number of times and the validity of the operation efficiency Ui cannot be obtained, an alarm may be output or the allowable range Eq may be reviewed.

[Second Embodiment]
Next, the driving efficiency estimation device 10 according to the second exemplary embodiment of the present invention will be described.
In the first embodiment, the case where the operation efficiency Ui of the compressor Ci is calculated is described as an example for the case where the total flow rate Qt is in a constant state or increasing. In the present embodiment, a case where the operation efficiency Ui of the compressor Ci is calculated will be described for the case where the overall flow rate Qt is decreasing.

  As shown in FIG. 3 described above, the operation efficiency characteristic of the compressor depends on the flow rate change rate λ of the air flow rate. In particular, when the flow rate change rate λ is equal to or greater than 0, that is, when the air flow rate is the same or increased compared to the immediately preceding time, the operation efficiency Ui of the compressor Ci is substantially constant, and the flow rate change rate λ is greater than 0 When the air flow rate is reduced compared to a small negative region, that is, the time immediately before, the operation efficiency Ui is reduced according to the magnitude of the flow rate change rate λ.

The present embodiment focuses on the fact that the operating efficiency characteristic in the negative region of the operating efficiency Ui can be approximated by a linear function. When the flow rate change rate of the total flow rate Qt at time t is λt and the intercept and slope of the linear function are ai and bi, respectively, the operating efficiency Uti of the compressor Ci at time t is expressed by the following equation (2). This intercept ai corresponds to the partial regression coefficient ai calculated in the first embodiment.

In addition, it was observed that the intercept ai and the slope bi have unique values for each of the compressors C1 to Cn. From this, using this linear function, the individual flow rate Qti of the compressor Ci at time t is expressed by the following equation (3). When the total flow rate at time t is Qt, the total flow rate at time t-1 that is a unit time backward from time t is Qt-1, and the intercept and slope of the linear function are ai and bi, respectively, λt at t is expressed by the following equation (4).

Therefore, when the electric power consumption in the compressor Ci at time t is Wti, the entire flow rate Qt of the entire compressors C1 to Cn is expressed by the following equation (5).

Here, ai is known, and when there are n compressors Ci, there are n bi, so if n equations (5) are prepared, bi can be obtained by solving these as simultaneous equations. Can do.
Further, the overall flow rate Qt of the entire compressors C1 to Cn and the power consumption Wti of each compressor Ci can be easily measured at every time t in the general compressed air supply system 1 without adding a large facility. .

Therefore, in the present embodiment, n target data sets Dt whose Qt is in a decreasing state are reselected from the data sets of Qt and Wti measured every time t, and n data sets are used using these Dt. Bi is calculated by generating a flow rate calculation formula consisting of the following formula (5) and solving simultaneous equations consisting of these n flow rate calculation formulas.
Thereafter, λx obtained by substituting Qx and Qx-1 at an arbitrary time x into the equation (4) and ai and bi of the compressor Ci obtained previously are substituted into the equation (2). The operation efficiency Uxi of each compressor Ci at time x is obtained.

In the present embodiment, the data set selection unit 15 reselects n data sets in which the overall flow rate Qt is reduced among the data sets 14A stored in the storage unit 14 as new target data sets Dt. It has a function.
The operation efficiency calculation unit 16 calculates the flow rate change rate λt per unit time related to the total flow rate Qt, the total flow rate Qt, the power usage amount Wti, and the partial regression coefficient ai obtained for each of the reselected target data sets Dt. And an operation efficiency characteristic coefficient bi indicating a slope of a linear function approximating the relationship between the flow rate change rate and the operation efficiency for each compressor Ci, and a flow rate calculation formula for the total flow rate Qt shown in Equation (5). , A function of generating n for each target data set Dt, a function of calculating the operating efficiency characteristic coefficient bi by solving these flow rate calculation formulas as simultaneous equations, and a flow rate change rate λx at an arbitrary time x, The operation of the compressor Ci at the time x is performed by multiplying the operation efficiency characteristic coefficient bi of Ci and adding the partial regression coefficient ai of the compressor Ci. And a function of calculating the efficiency Uxi.

[Operation of Second Embodiment]
Next, operation | movement of the driving efficiency estimation apparatus 10 concerning this Embodiment is demonstrated.
First, with reference to FIG. 8, the coefficient calculation process in the driving efficiency estimation apparatus 10 will be described. FIG. 8 is a flowchart illustrating a coefficient calculation process according to the second embodiment. Here, a processing procedure for calculating the operation efficiency characteristic coefficient bi stepwise after the first embodiment is shown.

  The driving efficiency calculation unit 16 executes the coefficient calculation process of FIG. 8 according to the operator operation detected by the operation input unit 12 or at regular time intervals. In the coefficient calculation process, the storage unit 14 includes a data set 14A at each time t collected by the data collection unit 11, and coefficient data 14B indicating the partial regression coefficient ai obtained in the first embodiment. Are stored in advance.

First, the data set selection unit 15 reselects a data set at an unselected time t from the data set 14A of the storage unit 14 (step 200), and the total flow rate Qt of the data set is changed from, for example, time t to unit time. Compared with the total flow rate Qt-1 measured a minute before, it is confirmed whether Qt is decreasing (step 201). In this case, the flow rate change rate λt may be calculated first to confirm the sign of λt.
When Qt ≧ Qt−1 (λt ≧ 0) (step 201: NO), the data set selection unit 15 returns to step 200 and newly selects an unselected data set.

On the other hand, in the case of Qt <Qt−1 (λt <0) (step 201: YES), the data set selection unit 15 determines the compressor Ci based on the power usage Wti of the compressor Ci during operation in the data set. Is operated in a predetermined rated operation range with reference to the rated output (step 202).
Here, when there is a compressor Ci that is not operated in the rated operation range (step 102: NO), the data set selection unit 15 returns to step 100 and newly selects a data set at an unselected time.
On the other hand, when all the compressors Ci in operation are operated in the rated operation range (step 202: YES), the data set selection unit 15 extracts the data set as a new target data set Dt, and stores the storage unit 14 (Step 203).

  At this time, the rated output of the compressor may be a value presented as a specification by the manufacturer, but in actuality, the compressor may be operated with a power larger than the presented value. Also, the rated output may be reduced due to aging. Therefore, in such a case, it is only necessary to reset the maximum value of the actually measured power consumption Wti as the rated output for each compressor Ci.

  In this manner, the data set selection unit 15 repeatedly executes data sets in which Qt is in a decreasing state until D new data sets are extracted as Dt (step 204: NO).

  When n Dt are extracted (step 204: YES), the operation efficiency calculation unit 16 assigns an operation efficiency characteristic coefficient bi for each compressor Ci (step 205), and per unit time for the Qt for each Dt. Is calculated based on the above-described equation (4) (step 206).

Subsequently, the operation efficiency calculation unit 16 generates n flow rate calculation formulas related to Qt of the above-described formula (5) for each Dt, using Qt and Wti for each Dt and ai and bi for each compressor Ci. (Step 207).
Thereafter, the operation efficiency calculation unit 16 generates simultaneous equations such as the above-described equation (6) from these n flow rate calculation equations (step 208), and solves this to obtain the bi of each compressor Ci. The calculated bi is stored as coefficient data 14B in the storage unit 14 (step 210), and a series of coefficient calculation processing is completed.

In addition, you may perform the coefficient calculation process concerning the driving efficiency estimation apparatus 10 in the process sequence shown in FIG. FIG. 9 is a flowchart illustrating another coefficient calculation process according to the second embodiment. Here, a processing procedure is shown in which 2 × n sets of target data Dt are acquired, simultaneous equations are solved, and ai and bi are obtained simultaneously.
That is, 2 × n sets of data are extracted in steps 200, 203, and 204 without the steps 201 and 202 shown in FIG. Subsequently, steps 205 to 207 are executed in the same manner as in FIG. 8, and simultaneous equations are generated from 2 × n flow rate calculation formulas in step 208. Thereafter, in step 208, ai and bi can be obtained by solving the simultaneous equations.

Next, the driving efficiency calculation process in the driving efficiency estimation apparatus 10 will be described with reference to FIG. FIG. 10 is a flowchart illustrating an operation efficiency calculation process according to the second embodiment.
The driving efficiency calculation unit 16 executes the driving efficiency calculation process of FIG. 10 in accordance with the operator operation detected by the operation input unit 12 or at regular time intervals or at predetermined intervals. In the operation efficiency calculation process, it is assumed that the partial regression coefficient ai and the operation efficiency characteristic coefficient bi are stored in the storage unit 14 as coefficient data 14B for each compressor Ci.

  First, the operation efficiency calculation unit 16 refers to the data set 14A in the storage unit 14 and obtains the total flow rate Qx from the data set at an arbitrary time x designated as the operation efficiency target (step 220). Thus, the flow rate change rate λx is calculated (step 221).

  Thereafter, the operation efficiency calculation unit 16 acquires ai and bi of each compressor Ci from the coefficient data 14B of the storage unit 14, and substitutes these ai and bi and the flow rate change rate λx into the above-described equation (2). Thus, the operation efficiency Uxi at time x is calculated for each compressor Ci (step 222).

  Further, the operating efficiency calculation unit 16 obtains the rated efficiency Uri of each compressor Ci stored in advance in the storage unit 14, and divides the value obtained by subtracting Uxi from Uri by Uri, thereby obtaining the operating efficiency deterioration rate Rxi. These are calculated (step 223), these are displayed on the screen display unit 13 (step 224), and the series of operation efficiency calculation processing is terminated. At this time, when Uxi, Uri, and Rxi are displayed on the screen, ai and bi may also be displayed on the screen at a time, and the necessity of screen display may be selectable by option setting.

  FIG. 11 is an example of an individual display screen for operating efficiency. Here, the operation efficiency Ux1 and the operation efficiency characteristic at a specific time x “11:00” regarding the compressor C1 among the compressors C1 to Cn are displayed in a graph, and the horizontal axis indicates the flow rate change rate λx. The vertical axis represents the operating efficiency Ux1. The graph also shows the rated efficiency Ur1 of the compressor C1, the operating efficiency deterioration rate Rx1 indicating the deterioration rate of the operating efficiency Ux1 with the rated efficiency Ur1 as a reference, the maximum efficiency Uxmax1 composed of the partial regression coefficient a1, and the operating efficiency characteristic coefficient b1. The reduction rate Rdx1 of the operation efficiency Ux1 per unit flow rate change rate is displayed together.

  With this individual display screen, the administrator can easily confirm under what circumstances the selected compressor Ci is operating at time x based on the operation efficiency Uxi and the operation efficiency deterioration rate Rxi. In addition, the maximum efficiency Uxmaxi can grasp the best efficiency obtained by the compressor Ci, and the reduction rate Rdxi details how much the operating efficiency Uxi decreases as the flow rate change rate λx decreases. Can be confirmed.

FIG. 12 shows another list display screen example of the driving efficiency. Here, the operation efficiency Uxi (= partial regression coefficient ai: static characteristic), rated efficiency Uri, operation efficiency deterioration rate Rxi, maximum efficiency Uxmaxi, and reduction rate Rdxi (= operation efficiency characteristic coefficient bi: dynamic characteristics) at the time x described above. ) Is displayed in a list for each of the compressors C1 to Cn.
With this list display screen, it is possible to easily confirm the operation status and the operation efficiency characteristics regarding the compressors C1 to Cn at the time x, and to easily compare the compressors C1 to Cn.

[Effect of the second embodiment]
Thus, in the present embodiment, the data set selection unit 15 sets the data set 14A stored in the storage unit 14 as a new target data set Dt as a new target data set Dt. The operation efficiency calculation unit 16 re-selects each of the target data sets Dt, and the flow rate change rate λt per unit time regarding the total flow rate Qt, the total flow rate Qt, the power usage amount Wti, And a partial regression coefficient ai, and an operation efficiency characteristic coefficient bi indicating a slope of a linear function approximating the relationship between the flow rate change rate and the operation efficiency for each compressor Ci, and a flow rate calculation formula regarding the total flow rate Qt, By generating n for each target data set Dt and solving these flow rate calculation formulas as simultaneous equations, the operation efficiency characteristic coefficient bi is calculated, and the flow rate change rate λx at an arbitrary time x is The operation efficiency Uxi of the compressor Ci at the time x is calculated by multiplying the operation efficiency characteristic coefficient bi of the compressor Ci and adding the partial regression coefficient ai of the compressor Ci.

  Thereby, not only the operating efficiency Ui of the compressor Ci when the overall flow rate Qt is constant or increasing, but also the operating efficiency Ui of the compressor Ci when the overall flow rate Qt is decreasing can be accurately estimated. . Therefore, even when the overall flow rate Qt is increased or decreased in actual operation, it is possible to accurately estimate the operation efficiency Ui at an arbitrary time.

Further, in the present embodiment, the simultaneous equations in which the operation efficiency characteristic coefficient bi for each compressor Ci is an unknown are expressed as the operation efficiency characteristic coefficient when the coefficient data is expressed as an n × n matrix A and the constant data is expressed as an n-dimensional vector d. Is converted into a form Ab = d.
When solving these simultaneous equations, the solution may become unstable depending on the combination of coefficient data and constant data. As a result, there are cases where the operation efficiency index of each compressor cannot be calculated with the required accuracy.

As a countermeasure against such a case, κ (A) = || A ||||||| as a condition number that is an index representing the stability of a fixed solution using coefficient data of simultaneous equations. (Where B = A ⁻¹ ) is calculated.
If the condition number is equal to or greater than a preset threshold value, a part or all of the n data sets Dt (where t = 1, 2,..., N) are exchanged until the condition number becomes less than the threshold value. Thus, the new equation data A ′ and the constant data d ′ are replaced with the simultaneous equations to calculate the compressor operation efficiency index that satisfies the required accuracy. On the other hand, when there is no combination of data that satisfies the condition of less than the threshold, the calculation results up to that point are stored, and the calculation result when the minimum condition number is within the range of history information is stored. The operating efficiency index may be used.

Further, as a countermeasure for the above case, the following method can be used. First, L sets of coefficient data A and constant data d are prepared in advance, and simultaneous equations with unknown vector b (j) (where j = 1, 2,..., L) for each set j. Find the solution of
Then, the variance for j of solution bi (j) is calculated for each i, and if the condition that this variance is less than the threshold for each i set in advance is satisfied for all i, then bi (j) A statistical quantity such as an average value or a median value for j may be used as an operation efficiency index.

  Here, if the condition is not satisfied for a certain i, the calculation process is performed by sequentially adding a set of coefficient data A and constant data d until a result satisfying the condition is obtained. Since the addition of the data set is limited to the additional upper limit number M set in advance, if the condition is not finally satisfied, all the calculation results bi (j) (where j = 1, 2, .., L, L + 1,..., L + M) may be used as a driving efficiency index for i.

  As a method for determining the stability of a solution using simultaneous equations, a determination method different from the determination method using a threshold can be used. For example, the operation efficiency index obtained by the calculation is substituted into the above-described equation (5), and the flow rate change rate λt related to the total flow rate Qt that was not used when calculating the operation efficiency index, the total flow rate Qt, and the power usage amount Wti. It is possible to determine the stability of the solution by confirming that the equation is approximately established within a certain error range using a set of verification data.

[Extended embodiment]
The present invention has been described above with reference to the embodiments, but the present invention is not limited to the above embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention. In addition, each embodiment can be implemented in any combination within a consistent range.

  In each embodiment, the compressed air supply system that generates compressed air by the compressor and supplies it to the load has been described as an example of the target for estimating the operation efficiency. However, the present invention is not limited to this. Other than the above, for example, each embodiment can be applied to other systems such as a compressed gas supply system that compresses a mixed gas such as water or a refrigerant and supplies the compressed gas to the load in the same manner as described above, and obtains the same effects. Can do.

  DESCRIPTION OF SYMBOLS 1 ... Compressed air supply system, C1-Cn, Ci ... Compressor, 2, 4 ... Pipe line, 3 ... Buffer tank, 4A ... Flow meter, 5 ... Header, 5A ... Pressure gauge, 6 ... Load, 7 ... Compressor control part , 8 (81 to 8n) ... watt meter, 10 ... operating efficiency estimation device, 11 ... data collection unit, 12 ... operation input unit, 13 ... screen display unit, 14 ... storage unit, 14A ... data set, 14B ... coefficient data , 14P ... program, 15 ... data set selection unit, 16 ... operation efficiency calculation unit, Qt, Qx ... total flow rate, Wt1 to Wtn, Wti ... power consumption, Dt ... target data set, λt, λx ... flow rate change rate, ai ... partial regression coefficient (intercept), bi ... operating efficiency characteristic coefficient (slope), Uti, Uxi ... operating efficiency, Uri ... rated efficiency, Rxi ... operating efficiency deterioration rate, Uxmaxi ... maximum efficiency, Rdxi ... reduction rate.

Claims (3)

An operating efficiency estimation device that individually estimates the operating efficiency of n (n is an integer of 2 or more) compressors Ci (i = an integer of 1 to n) that are operated in parallel,
At each time t, a power usage amount Wti indicating individual power used by each compressor Ci and an overall flow rate Qt indicating the total flow rate of compressed air supplied from the compressor Ci are collected, and these power usage amounts are collected. A data collection unit for storing Wti and the total flow rate Qt in the storage unit as a data set of the time t;
A data set selection unit that selects m (m> n) data sets in which the total flow rate Qt is constant or increasing from the data sets stored in the storage unit as the target data set Dt;
Based on these target data sets Dt, each of the multiple regression equations ai of the multiple regression equation is obtained by obtaining a multiple regression equation representing the objective variable consisting of the total flow rate Qt as an explanatory variable consisting of the power consumption Wti. An operation efficiency estimation device comprising: an operation efficiency calculation unit that calculates an operation efficiency Ui of the compressor Ci. In the driving efficiency estimating device according to claim 1,
The data set selection unit reselects n data sets in which the overall flow rate Qt is reduced among the data sets stored in the storage unit as new target data sets Dt,
The operation efficiency calculation unit calculates the flow rate change rate λt related to the total flow rate Qt, the total flow rate Qt, the power usage amount Wti, and the partial regression coefficient ai, which are obtained for each of the reselected target data sets Dt. Using the operation efficiency characteristic coefficient bi for each compressor Ci indicating the slope of a linear function that approximates the relationship between the flow rate change rate and the operation efficiency,

Are generated for each target data set Dt, and the flow rate calculation formulas are solved as simultaneous equations to calculate the operating efficiency characteristic coefficient bi, and at any time x The operation efficiency Uxi of the compressor Ci at the time x is calculated by multiplying the flow rate change rate λx by the operation efficiency characteristic coefficient bi of the compressor Ci and adding the partial regression coefficient ai of the compressor Ci. Driving efficiency estimation device.   The program for functioning a computer as each part of the driving | running efficiency estimation apparatus of Claim 1 or Claim 2.

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