JP2019002833A - Piping diagnosis method, piping diagnosis device, and piping diagnosis system - Google Patents

Abstract

To predict a time when cleaning of piping is required irrespective of the piping.SOLUTION: A piping diagnosis method of the present invention causes a computer to execute the process of: referring to a storage unit in which the pressure or flow rate of fluid inside the piping relative to time is stored and calculating, for each time, an index value in which the inclination of the pressure or flow rate relative to time after cleaning of the piping is weighted by a weight coefficient based on the pressure or flow rate at each time after cleaning of the piping; modeling a change of the index value relative to time after cleaning of the piping; and notifying information relating to a time when the piping is cleaned on the basis of the model and a relationship between the index value and a time after cleaning of the piping or other piping when abnormality occurred to the piping or other piping in the past.SELECTED DRAWING: Figure 6

Description

  The present invention relates to a piping diagnostic method, a piping diagnostic device, and a piping diagnostic system.

  In order to clean a pipe installed in a building or a factory at an appropriate time, a blockage time of the pipe due to a deposit or the like is predicted (for example, see Patent Document 1).

JP 2008-196889 A

  When the piping path and the position of the seam are different, the deposition tendency of the sediment causing the blockage is also different. Therefore, since the method described in Patent Document 1 derives a model from various parameters for one pipe, the application range may be limited and may not be applied to different pipes.

  In one aspect, an object of the present invention is to provide a pipe diagnosis method, a pipe diagnosis apparatus, and a pipe diagnosis system that can notify the timing of pipe cleaning regardless of the pipe.

  In one aspect, the piping diagnosis method refers to a storage unit that stores the pressure or flow rate of the fluid in the piping with respect to time, and uses the weighting factor based on the pressure or the flow rate at each time after cleaning of the piping. An index value obtained by weighting the slope of the pressure or the flow rate with respect to the time after cleaning of the pipe is calculated for each time, and the change of the index value with respect to the time after cleaning of the pipe is modeled. Alternatively, information on the cleaning timing of the piping is notified based on the relationship between the index value and the time after cleaning of the piping or the other piping when an abnormality occurs in the other piping, and the model. This is a piping diagnosis method in which processing is executed by a computer.

  The cleaning time of piping can be notified regardless of piping.

FIG. 1 is a diagram schematically illustrating a piping diagnosis system according to the first embodiment. FIG. 2 is a diagram illustrating an example of a hardware configuration of the information processing apparatus. FIG. 3 is a functional block diagram of the information processing apparatus. FIG. 4A is a diagram illustrating an example of a piping management table, and FIG. 4B is a diagram illustrating an example of an index data table. FIG. 5 is a diagram illustrating an example of a past data table. FIG. 6 is a flowchart (part 1) of the piping diagnosis process executed by the information processing apparatus. FIG. 7 is a flowchart (part 2) of the piping diagnosis process executed by the information processing apparatus. FIG. 8 is a diagram for explaining the calculation of the pressure index approximate expression. FIG. 9A and FIG. 9B are diagrams for explaining calculation of past data lines. FIG. 10 is a diagram for explaining calculation of the management index line and the alert start line. FIG. 11 is a diagram for explaining the process of step S25 of FIG. FIG. 12 is a diagram illustrating an example of a change in pressure with respect to time in the pipe A. FIG. FIG. 13 is a diagram illustrating a pressure gradient in the pipe A. FIG. FIG. 14 is a diagram illustrating an example of a change in pressure with respect to time in the pipe B. FIG. FIG. 15 is a diagram for explaining a method of predicting the time when the piping B needs to be cleaned. FIG. 16 is a diagram for explaining the effect of the first embodiment. FIG. 17 is a diagram schematically illustrating a piping diagnosis system according to the second embodiment.

  Hereinafter, the piping diagnosis system according to the first embodiment will be described in detail with reference to FIGS. The piping diagnosis system is a system for notifying information related to the timing of piping cleaning.

  FIG. 1 schematically shows the configuration of a piping diagnosis system 100 according to the first embodiment. As shown in FIG. 1, the pipe diagnosis system 100 includes an operator terminal 20 and an information processing apparatus 10 as a pipe diagnosis apparatus. The worker terminal 20 and the information processing apparatus 10 are connected via a wired or wireless network NW such as the Internet, a Local Area Network (LAN), and a Wide Area Network (WAN).

  The worker terminal 20 is a terminal (for example, a dedicated terminal or a tablet terminal) used by a site worker of piping equipment. The field worker reads the detected value (pressure) of the pressure gauge that measures the pressure of the fluid in the pipe and inputs it to the worker terminal 20. The worker terminal 20 transmits the input detection value (pressure) and the measurement date to the information processing apparatus 10 as a set. Further, the site worker inputs the work content performed on the piping to the worker terminal 20. The worker terminal 20 transmits the work content input to the worker terminal 20 and the work execution date to the information processing apparatus 10 as a set.

  The information processing apparatus 10 accumulates data received from the worker terminal 20, predicts a pipe cleaning time based on the accumulated data, and notifies information related to the cleaning time.

  The information processing apparatus 10 has a hardware configuration as shown in FIG. Specifically, as shown in FIG. 2, the information processing apparatus 10 includes a central processing unit (CPU) 111, a read only memory (ROM) 112, a random access memory (RAM) 113, and a storage device (Hard Disk Drive: HDD). ) 114, a network interface 115, and a portable storage medium drive 117 capable of reading data stored in the portable storage medium 116. Each component of the information processing apparatus 10 is connected to the bus 118. The CPU 111 causes the information processing apparatus 10 to function as each unit of FIG. 3 by executing a program stored in the ROM 112 or the HDD 114 or a program read from the portable storage medium 116 by the portable storage medium drive 117.

  Specifically, as illustrated in FIG. 3, when the CPU 111 executes a program, the information processing apparatus 10 includes an index calculation unit 11, an approximate function calculation unit 12 as a modeling unit, a determination function calculation unit 13, and It functions as the prediction unit 14 as a notification unit.

  The index calculation unit 11 calculates an index (pressure index PI) for modeling a pressure change in the pipe based on data stored in the pipe management table 19 stored in a storage device such as the HDD 114. Store in the index data table 18. Here, the piping management table 19 and the index data table 18 will be described.

  FIG. 4A is a diagram illustrating an example of the piping management table 19. As shown in FIG. 4A, the piping management table 19 has fields of “date and time”, “pressure”, and “work content”. In addition, the piping management table 19 shall be produced for every piping system including a pressure and a flow sensor. For example, FIG. 4A shows a pipe management table 19 for the pipe A.

  In the “date and time” field, the date and time when the pressure was measured or the date and time when the work was performed on the piping is stored. In the “pressure” field, a pressure gauge value (pressure of fluid in the pipe) read by the operator is stored. In the “work content” field, the content of work performed on the piping by the worker is stored. In addition, you may manage the pressure of the fluid in piping, and the operation | work performed with respect to piping by a separate table.

  FIG. 4B is a diagram illustrating an example of the index data table 18. As shown in FIG. 4B, the index data table 18 has fields of “time” and “pressure index”. The index data table 18 is created for each pipe. For example, FIG. 4B is an index data table 18 for the pipe A.

  In the “time” field, an elapsed time since the pipe was cleaned is stored in units of time. The elapsed time after cleaning the pipe is the time after the pipe is cleaned and fluid (water, air, etc.) starts to pass through the pipe (the time after the pipe starts operating after the pipe is cleaned) Say. In the field of “pressure index”, the pressure index P.P. The value of I is stored.

  Returning to FIG. 3, the approximate function calculation unit 12 determines the pressure index P.P. with respect to time based on the data in the index data table 18. The change of I is fitted by polynomial regression, for example, with a cubic equation, and the pressure index P.P. An approximate function of I (hereinafter referred to as a pressure index approximate expression) is calculated. The approximate function calculation unit 12 outputs the calculated pressure index approximation formula to the prediction unit 14.

  The determination function calculation unit 13 calculates a function used for predicting the time when the pipe needs to be cleaned based on the data in the past data table 17 that manages the pressure of the fluid in the past pipe and the work content for the pipe. To the prediction unit 14.

  Here, the past data table 17 will be described. FIG. 5 is a diagram illustrating an example of the past data table 17. The past data table 17 includes fields of “piping name”, “date and time”, “pressure”, and “work content”. “Pipe name” stores a name or identifier for uniquely identifying each pipe. The items “date and time” to “work content” are the same as the items included in the piping management table 19 shown in FIG.

  Returning to FIG. 3, the predicting unit 14 predicts the time when the piping needs to be cleaned based on the pressure index approximate expression calculated by the approximate function calculating unit 12 and the function calculated by the determination function calculating unit 13. Moreover, the prediction unit 14 displays, for example, information on the cleaning timing of the pipe on the display of the operator terminal 20 or the display of the terminal used by the pipe manager based on the prediction result. To inform.

  Next, an example of piping diagnosis processing executed by the information processing apparatus 10 will be described. 6 and 7 are flowcharts illustrating an example of the piping diagnosis process executed by the information processing apparatus 10. The processes in FIGS. 6 and 7 are executed periodically (every other day, every other week), for example. Note that the processing of FIGS. 6 and 7 may be executed at a timing designated by an administrator of the piping facility, for example.

  In the process of FIG. 6, first, the index calculation unit 11 extracts data registered from the date when the previous pipe cleaning was performed in the pipe management table 19 (step S <b> 11). For example, in the pipe management table 19 shown in FIG. 4A, the index calculation unit 11 extracts data after March 25, 2017, in which “pipe cleaning” is registered in the “work content” field.

  Next, the index calculation unit 11 smoothes the extracted data (step S13). In actual operation, the pressure data in the pipe is rarely acquired every day, and is often acquired at intervals of several days to one week or more. Further, since the pressure variation is large, for example, the index calculation unit 11 performs a moving average process on the extracted data for a predetermined period (for example, 14 days).

  Next, the index calculation unit 11 calculates the pressure index P.P. at each time after pipe cleaning based on the smoothed data. I is calculated (step S15). In addition, each time after piping cleaning means each time after fluid (water, air, etc.) starts passing through piping after cleaning piping. The index data table 18 shown in FIG. 4B is obtained by the processing in step S15. Specifically, the index calculation unit 11 calculates the pressure index P.I. I is calculated.

上記の数式１において、Ｐ．Ｉは圧力指標を表す。Ａは配管清掃後の時間に対する圧力の傾きであり、例えば数式２から算出される。Ｂは配管清掃後の各時間における圧力に基づく重み係数であり、配管清掃後の各時間における圧力が小さくなるほど大きな値をとるようになっている。重み係数Ｂは、例えば数式３から算出される。

In Equation 1 above, P.I. I represents a pressure index. A is a pressure gradient with respect to time after pipe cleaning, and is calculated from, for example, Equation 2. B is a weighting factor based on the pressure at each time after pipe cleaning, and takes a larger value as the pressure at each time after pipe cleaning becomes smaller. The weighting coefficient B is calculated from Equation 3, for example.

ここで、Ｃｏｖ（Ｐ，ｔ）は抽出したデータにおける圧力と時間との共分散、δ_ｔは時間の標準偏差を表す。また、Ｐ_０は圧力の管理基準値を表し、Ｐ_ｎは配管清掃後の各時間における圧力を表す。なお、圧力の管理基準値（Ｐ_０）とは、配管内の流体の圧力に基づいて圧力配管の清掃が必要か否かを判断する場合に使用される閾値である。例えば、配管内の流体の圧力が管理基準値を下回った場合に、配管の清掃が必要であると判断される。共分散Ｃｏｖ（Ｐ，ｔ）及び標準偏差δ_ｔはそれぞれ下記の数式４及び数式５により算出される。

Here, Cov (P, t) is the covariance between the pressure and time in the extracted data, [delta] _t represents the standard deviation of the time. P ₀ represents a pressure management reference value, and P _n represents a pressure at each time after pipe cleaning. The pressure management reference value (P ₀ ) is a threshold value used when determining whether or not the pressure pipe needs to be cleaned based on the pressure of the fluid in the pipe. For example, when the pressure of the fluid in the pipe falls below the management reference value, it is determined that the pipe needs to be cleaned. Covariance Cov (P, t) and standard deviation [delta] _t is calculated respectively by Equations 4 and 5 below.

ここで、Ｐ_ａｖｅは圧力の平均値を表し、ｔ_ａｖｅは時間の平均値を表す。

Here, P _ave represents an average value of pressure, and t _ave represents an average value of time.

  Next, the approximate function calculation unit 12 determines the pressure index P.P. with respect to the time after the pipe cleaning based on the index data table 18. A change in I is modeled (step S16). Specifically, the approximate function calculation unit 12 calculates the pressure index P.V. with respect to the time after pipe cleaning. An approximate expression (hereinafter referred to as a pressure index approximate expression) obtained by fitting the change in I with a cubic expression shown in Expression 6 by polynomial regression is calculated. As a result, as indicated by a one-dot chain line in FIG. The change in I is modeled by a cubic equation.

  Next, the determination function calculation unit 13 extracts data when the pressure of the fluid in the pipe is lower than the management reference value in each pipe from the past data table 17, and uses the extracted data for each time according to Equation 1. Pressure index P.I. I (hereinafter referred to as a determination pressure index) is calculated (step S17). Thereby, for example, as shown in FIG. 9A, the time after the pipe cleaning and the pressure index P.P. when the pressure of the fluid in the pipe falls below the control reference value in each pipe. A relationship with I is obtained.

  Next, the determination function calculation unit 13 calculates a past data line (step S19). Specifically, the determination function calculation unit 13 calculates an approximate expression representing the change in the determination pressure index with respect to time obtained in step S17, for example, by the least square method. For example, the determination function calculation unit 13 calculates a linear expression shown in the following Expression 7 as an approximate expression. As a result, as shown in FIG. 9B, an approximate expression (straight line) representing a change in the determination pressure index with respect to time is obtained.

ここで、ｘは時間、ｙは圧力指標Ｐ．Ｉを表す。また、係数Ｃ及び係数Ｄは、それぞれ数式８及び数式９で与えられる。

Here, x is time, y is the pressure index P.I. Represents I. The coefficient C and the coefficient D are given by Expression 8 and Expression 9, respectively.

ここで、y_aveはyの平均、ｘ_aveはｘの平均、δ_ｘはｘの標準偏差である。

Here, y _ave is the average of y, x _ave is the average of x, and δ _x is the standard deviation of x.

Next, the determination function calculation unit 13 calculates a management index line (step S21). The management index line is a straight line obtained by moving the intercept of the past data line to the origin side, and is a function used to calculate the time when the piping needs to be cleaned. For example, as shown in FIG. 10, the determination function calculation unit 13 determines the pressure index P.P. When the center (average 0) of the normal distribution (one-dot chain line) of I is positioned in the past data line, a straight line passing through the position of −1σ (σ is the standard deviation) is calculated as the management index line. The management index line at this time is expressed by the following formula 10.

  Next, the determination function calculation unit 13 calculates an alert start line (step S22). The alert start line is a function for determining whether or not to notify the manager or worker of the time when cleaning is required, and is located further on the origin side than the management index line. For example, as shown in FIG. When the center (average 0) of the normal distribution of I is located in the past data line, a straight line passing through the position of −2σ (σ is the standard deviation) is calculated as the alert start line. At this time, the alert start line is expressed by Equation 11 below.

  Note that the execution order of the processes in steps S15 and S16 and the processes in steps S17 to S22 may be switched. If the process of step S16 is executed after the process of step S15 and the process of steps S19 to S21 is executed after the process of step S17, the execution order of steps S16 and S19 to S21 is changed as appropriate. May be.

Returning to FIG. 6, next, the prediction unit 14, as shown in FIG. 11, intersects the pressure index approximate expression f (x) and the management index line (x _NG ), and the pressure index approximate expression f (x) The intersection (x _AL ) with the alert start line is calculated (step S25). When performing the approximation by numerical calculation, the prediction unit 14 obtains x that satisfies the following Expression 12.

ここで、ｇ（ｘ）は、数式１０又は数式１１である。

Here, g (x) is Formula 10 or Formula 11.

Next, the prediction unit 14 determines that the current time t _n (the elapsed time since the start of pipe operation after cleaning the pipe) is the intersection x _NG with the management index line and the intersection x _AL with the alert start line. It is determined whether it is smaller than (step S27). If the determination in step S27 is YES, the time when the piping needs to be cleaned is considerably ahead. Therefore, even if the time when cleaning is required is notified, there is a high possibility that the effect of the notification is thin. Therefore, when the determination in step S27 is YES, the prediction unit 14 notifies that there is no need for cleaning (step S29), and ends the processes of FIGS. For example, the prediction unit 14 displays a message such as “no cleaning is necessary” on the display (not shown) of the terminal used by the operator terminal 20 or the piping manager.

On the other hand, when the determination in step S27 is NO, the prediction unit 14 determines whether or not the current time t _n is smaller than the intersection x _NG with the management index line and larger than the intersection x _AL with the alert start line. Determination is made (FIG. 7: step S31). When the determination in step S31 is YES, the predicting unit 14 determines whether or not x _NG −t _n > threshold (for example, threshold = 336 [time]) (step S33). The threshold value can be determined based on, for example, the time required for assigning an operator who cleans the piping. For example, if it takes about two weeks to assign a worker who cleans the piping, the threshold can be set to 14 days = 336 hours.

If the determination in step S33 is YES, it is highly likely that the effect of the notification is low because the period until the timing for assigning the worker is relatively long even if the time when the piping needs to be cleaned is notified. . Therefore, when x _NG −t _n > threshold (step S33: YES), the prediction unit 14 notifies that cleaning is not necessary (step S35), and ends the processes of FIGS. For example, the prediction unit 14 displays a message such as “No cleaning is necessary” on the display (not shown) of the terminal used by the operator terminal 20 or the piping manager.

On the other hand, when the determination in step S33 is NO, the prediction unit 14 notifies the number of days ((x _NG −t _n ) / 24) until cleaning is required (step S37), and the processing of FIGS. Exit. For example, the prediction unit 14 displays a message such as “It is a minimum of 00 days until cleaning” on the display (not shown) of the terminal used by the operator terminal 20 or the piping manager. As a result, it is possible to urge the operator who performs the cleaning work of the piping, preparation, and the like.

Meanwhile, if the determination in step S31 is NO, i.e., if the current time t _n is greater than the intersection x _AL between the intersection x _NG and alerts start line with the management indicator line, the piping state is already required to clean It is in a state. Therefore, when the determination in step S31 is NO, the prediction unit 14 notifies that cleaning is necessary (step S39), and ends the processes of FIGS. For example, the prediction unit 14 displays a message such as “Needs cleaning” on the display (not shown) of the terminal used by the operator terminal 20 or the piping manager. Thereby, cleaning of piping can be urged.

  As described above in detail, according to the first embodiment, the information processing apparatus 10 refers to the pipe management table 19 that stores the pressure of the fluid in the pipe with respect to time, and at each time after cleaning the pipe. Pressure index P. which weights the slope of the pressure with respect to the time after the pipe cleaning by the weighting factor based on the pressure. An index calculation unit 11 that calculates I for each time, and a pressure index P.P. An approximate function calculation unit 12 that models the change in I, and a time and pressure index P.P. after cleaning of the pipe when an abnormality has occurred in the pipe in the past. I (determination pressure index) and the pressure index P.I. And a prediction unit 14 that notifies information related to the timing of pipe cleaning based on the model I. As a result, even when pipes have different trends in change with respect to time of pressure, the same index (pressure index PI) is used to predict when the pipe needs to be cleaned, and information about the timing of pipe cleaning is reported. it can.

  The effect of the first embodiment will be described in more detail.

  FIG. 12 shows time-series data of pressure in the pipe A, for example. As shown in FIG. 12, in the pipe A, the pressure drops linearly as time elapses after the pipe is cleaned, and the pressure falls below the management reference value in about 4 to 6 months. Here, when the slope of the pressure with respect to the time after pipe cleaning is plotted using the data of FIG. 12, the value varies for a certain period after pipe cleaning as shown in FIG. Converge to (indicated by a dashed line). Therefore, in the piping A, if the pressure value immediately after the piping cleaning is recorded, the piping needs to be cleaned using the slope of the pressure with respect to the time after the piping cleaning obtained from the time series data of the past pressure. The time can be predicted.

  FIG. 14 shows time-series data of pressure in the pipe B different from the pipe A. Unlike piping A, in piping B, the pressure drops in a curved line after cleaning the piping. Here, when the slope of the pressure with respect to the time after pipe cleaning is plotted using the data of FIG. 14, the slope increases as the time after cleaning the pipe increases, as shown in FIG.

  In the pipe B, for example, as shown in FIG. 15, the past data line (straight line) calculated using data when the pressure in the pipe B has previously dropped below the management reference value, and the process after cleaning the pipe. Based on the approximate curve (dotted line) representing the slope of the pressure value with respect to time, the time when the piping needs to be cleaned (intersection of the past data line and the approximate curve) can be predicted.

  As described above, the change tendency of the pressure with respect to time differs between the pipe A and the pipe B. Therefore, in order to predict and notify when the pipe needs to be cleaned based on the pressure gradient, data sufficient for grasping the change tendency of the pressure with respect to time in each of the pipe A and the pipe B. Need to get. For this reason, time for a year unit (for example, 1.5 to 2 years) is required before the operation for predicting the time when piping cleaning is required is started.

  On the other hand, according to the first embodiment, as shown in FIG. 16, the pressure index P.D. weighted with the weighting coefficient based on the pressure at each time for the pressure gradient with respect to time. By using I, it is possible to predict when pipes need to be cleaned by the same index (pressure index PI) even if the pipes have different tendency to change with time. Therefore, the information regarding the cleaning time of the piping can be notified regardless of the piping.

  Further, according to the first embodiment, if an abnormality occurs in a plurality of pipes (if the pressure falls below the management index value), the past data line can be calculated, so that the prediction operation start time can be advanced. . For example, if the pressure of the fluid in the piping falls below the management index value in a plurality of piping during 3 to 4 months, the past data line can be calculated. For this reason, in the present Example 1, the operation | movement of prediction of the time when the cleaning of piping is needed after three to four months can be started. When an abnormality occurs in any of the pipes after the operation is started, the prediction accuracy can be improved by calculating a past data line reflecting the data.

  In addition, according to the first embodiment, since past data lines can be calculated if an abnormality has occurred in a plurality of other pipes, the pipes need to be cleaned even if no abnormality has occurred. The time can be predicted.

  In the first embodiment, the index calculation unit 11 calculates the slope of the pressure with respect to the time after cleaning the pipe by the least square method (see Formula 2), and the weighting factor is the pressure at each time after the pipe cleaning. The smaller the value, the larger (that is, the absolute value of the pressure index PI increases). As a result, the change tendency of the pressure of each pipe is indicated by the pressure index P.D. I can be reflected in I, and as a result, it is possible to predict the time when piping cleaning is required using the same index (pressure index PI).

  In the first embodiment, the index calculation unit 11 smoothes the pressure of the fluid in the pipe with respect to the time stored in the pipe management table 19. As a result, even if the pressure data with respect to time is missing or varies, the pressure index P.I. I can be calculated with high accuracy. Examples of the smoothing method include moving average processing and interpolation processing.

  In the first embodiment, the approximate function calculation unit 12 calculates the pressure index P.P. with respect to the time after the pipe cleaning. The change of I is modeled by an approximate expression by polynomial regression (see Expression 6). Thereby, the time when the piping needs to be cleaned can be predicted more accurately.

  Further, in the first embodiment, the time when the pressure of the fluid in the pipe falls below the management reference value is defined as a time when an abnormality has occurred in the pipe. As a result, the pressure index P.I. when the pressure of the fluid in the pipe falls below the control reference value. Based on I (determination pressure index), the past data line and the management index line can be calculated, and the time when the piping needs to be cleaned can be predicted.

  Further, in the first embodiment, the prediction unit 14 determines the time after the pipe cleaning and the pressure index P.P. An approximate expression (for example, Expression 7) that approximates the relationship with I (determination pressure index) by linear regression is calculated. Thereby, it is possible to predict the time when the piping needs to be cleaned using the approximate expression.

  Further, in the first embodiment, the predicting unit 14 includes an approximate expression that approximates the relationship between the time after the pipe cleaning when the abnormality has occurred in the pipe in the past and the determination pressure index by linear regression, and after the pipe cleaning. The pressure index P. An intersection point with a pressure index approximate expression obtained by approximating a change in I by polynomial regression is calculated. Thereby, the time when the piping needs to be cleaned can be predicted more accurately.

  Moreover, in the present Example 1, the estimation part 14 alert | reports the information regarding the timing of piping cleaning in steps (step S29, S35-S39). Thereby, the worker or the manager can perform work or processing necessary for cleaning the pipe at an appropriate time, or clean the pipe at an appropriate time.

  In the first embodiment, the pressure index P.sub. The change of I was approximated by a cubic equation. What is necessary is just to select suitably the order of the formula which approximates I. For example, it may be approximated by a quartic expression, a quintic expression, a sixth expression, a seventh order expression, or the like.

  In the first embodiment, the pressure index P.P. based on the pressure of the fluid in the pipe is used. I is calculated and the pressure index P.I. Although the time change of I is modeled, a flow index based on the flow rate of the fluid in the pipe may be calculated, and the time change of the flow index may be modeled.

  Moreover, in the said Example 1, although abnormality occurred in piping in the past, it was set as the time when the pressure of the fluid in piping fell below a control reference value, it is not restricted to this. A time when a predetermined operation is performed on the pipe (for example, a close inspection or cleaning caused by blockage of the pipe) may be a time when an abnormality occurs in the pipe.

  Moreover, in the said Example 1, although the estimation part 14 calculated the approximate expression showing the determination pressure parameter | index with respect to the time after piping cleaning by linear regression, you may calculate by polynomial regression.

  Moreover, in the said Example 1, although the value which remove | divided the management reference value by the pressure in each time was used for the weighting coefficient, it is not restricted to this. As long as the pressure at each time decreases, the weight coefficient increases.

  Moreover, in the said Example 1, although the estimation part 14 calculated | required the intersection of a pressure parameter | index approximation formula, a management parameter | index line, and an alert start line, it is not restricted to this. The prediction unit 14 may obtain an intersection between the pressure index approximate expression and the past data line, and may predict and notify when an abnormality (blocking) occurs in the pipe.

  FIG. 17 is a diagram schematically illustrating a pipe diagnosis system 100 ′ according to the second embodiment. In the first embodiment, the field worker inputs the pressure of the fluid in the pipe to the worker terminal 20, but as shown in FIG. 17, the pipe diagnosis system 100 ′ measures the pressure of the fluid in the pipe. The pressure gauge 30 may be provided, and the pressure gauge 30 may transmit the pressure value to the information processing apparatus 10 every certain time (for example, one day). Since other configurations are the same as those of the first embodiment, the description thereof is omitted.

  In the first and second embodiments, the information processing apparatus 10 may be a cloud.

  The above processing functions can be realized by a computer. In that case, a program describing the processing contents of the functions that the processing apparatus should have is provided. By executing the program on a computer, the above processing functions are realized on the computer. The program describing the processing contents can be recorded on a computer-readable recording medium (except for a carrier wave).

  When the program is distributed, for example, it is sold in the form of a portable recording medium such as a DVD (Digital Versatile Disc) or a CD-ROM (Compact Disc Read Only Memory) on which the program is recorded. It is also possible to store the program in a storage device of a server computer and transfer the program from the server computer to another computer via a network.

  The computer that executes the program stores, for example, the program recorded on the portable recording medium or the program transferred from the server computer in its own storage device. Then, the computer reads the program from its own storage device and executes processing according to the program. The computer can also read the program directly from the portable recording medium and execute processing according to the program. Further, each time the program is transferred from the server computer, the computer can sequentially execute processing according to the received program.

  The above-described embodiment is an example of a preferred embodiment of the present invention. However, the present invention is not limited to this, and various modifications can be made without departing from the scope of the present invention.

In addition, regarding the description of the embodiment, the following additional notes are disclosed.
(Supplementary note 1) Referring to the storage unit storing the pressure or flow rate of the fluid in the pipe with respect to time, the time after cleaning the pipe by the weighting factor based on the pressure or the flow rate at each time after cleaning the pipe Calculating an index value weighted with respect to the pressure or the slope of the flow rate with respect to each time,
Model the change of the index value with respect to the time after cleaning the pipe,
Based on the relationship between the time after the cleaning of the piping or other piping and the index value when an abnormality has occurred in the piping or other piping in the past, and the timing of cleaning the piping based on the model Broadcast information,
A piping diagnosis method in which processing is performed by a computer.
(Appendix 2) The slope of the pressure or the flow rate with respect to the time after cleaning of the piping is calculated by the least square method,
The weighting factor increases as the pressure or the flow rate at each time decreases.
The piping diagnostic method according to supplementary note 1, wherein:
(Appendix 3) Smoothing the pressure or flow rate of the fluid in the pipe with respect to the time after cleaning of the pipe stored in the storage unit,
The piping diagnosis method according to appendix 1 or 2, wherein the processing is executed by a computer.
(Additional remark 4) The process which models the change of the said index value includes the process which models the change of the said index value with respect to the time after the cleaning of the said piping with the approximate expression by polynomial regression, The additional remark 1 characterized by the above-mentioned. The piping diagnosis method according to any one of?
(Supplementary Note 5) When an abnormality has occurred in the piping or other piping in the past, when the pressure or the flow rate falls below a predetermined threshold, and a predetermined operation is performed on the piping. The pipe diagnostic method according to any one of appendices 1 to 4, wherein the pipe diagnostic method is at least one of the above.
(Additional remark 6) The process which alert | reports the information regarding the time of the cleaning of the said pipe | tube is the time after the said pipe | tube or the said other pipe | cleaning when abnormality has generate | occur | produced in the said pipe | tube or another pipe | tube, and the said index value The piping diagnosis method according to any one of appendices 1 to 5, further including a process of calculating an approximate expression obtained by approximating the relationship with the linear regression or the polynomial regression.
(Additional remark 7) The process which alert | reports the information regarding the time of cleaning of the said pipe | tube is the time after the said pipe | tube or the said other pipe | cleaning when abnormality has generate | occur | produced in the said pipe | tube or another pipe | tube, and the said index value A process of calculating an intersection of an approximate expression approximated by linear regression or polynomial regression and an approximate expression approximated by polynomial regression of a change in the index value with respect to time after cleaning of the pipe. The piping diagnosis method according to any one of appendices 1 to 6.
(Additional remark 8) The process which alert | reports the information regarding the timing of the said piping cleaning includes the process which alert | reports the information regarding the cleaning timing of the said pipe in steps, The additional notes 1-7 characterized by the above-mentioned. Piping diagnosis method.
(Supplementary Note 9) With reference to the storage unit storing the pressure or flow rate of the fluid in the pipe with respect to time, the time after cleaning the pipe by the weighting factor based on the pressure or the flow rate at each time after cleaning the pipe An index calculation unit that calculates an index value weighted with a slope of the pressure or the flow rate with respect to each time, a modeling unit that models a change in the index value with respect to a time after cleaning of the pipe, and a past Information on the time of cleaning of the piping based on the relationship between the time after the cleaning of the piping or the other piping when the abnormality occurs in the piping or other piping and the index value, and the model A piping diagnostic device comprising: a notification unit that notifies
(Additional remark 10) The said index calculation part calculates the inclination of the said pressure or the said flow volume with respect to the time after the cleaning of the said piping by the least square method, and the said weight coefficient is so that the said pressure or the said flow volume in each said time becomes small. The piping diagnostic device according to appendix 9, wherein the piping diagnostic device becomes larger.
(Additional remark 11) The said index calculation part smoothes the pressure or flow volume of the fluid in the said piping with respect to the time after the cleaning of the said piping memorize | stored in the said memory | storage part, The additional remark 9 or 10 characterized by the above-mentioned. The piping diagnostic device described.
(Additional remark 12) The said modeling part models the change of the said index value with respect to the time after the cleaning of the said piping by the approximate expression by polynomial regression, The piping in any one of Additional remarks 9-11 characterized by the above-mentioned. Diagnostic device.
(Supplementary note 13) When an abnormality has occurred in the piping or other piping in the past, when the pressure or the flow rate falls below a predetermined threshold, and a predetermined operation is performed on the piping. The piping diagnostic device according to any one of appendices 9 to 12, wherein the piping diagnostic device is at least one of the above.
(Supplementary note 14) Approximation formula approximating the relationship between the index value and the time after cleaning of the pipe or other pipe when an abnormality has occurred in the pipe or other pipe in the past by linear regression or polynomial regression The piping diagnosis device according to any one of appendices 9 to 13, further comprising a determination function calculation unit that calculates
(Additional remark 15) The said alerting | reporting part is a linear regression or a polynomial regression about the relationship between the time after the cleaning of the said piping or said other piping, and the said index value when abnormality has generate | occur | produced in the said piping or other piping in the said past. The pipe diagnostic device according to any one of appendices 9 to 14, wherein an intersection point between the approximate expression approximated by the above and the approximate expression approximated by polynomial regression of the change in the index value with respect to the time after the pipe cleaning is calculated.
(Additional remark 16) The said alerting | reporting part is a piping diagnostic apparatus in any one of Additional remarks 9-15 which leaves the information regarding the cleaning time of the said pipe in steps.
(Supplementary note 17) a detection device for detecting the pressure or flow rate of the fluid in the pipe;
A storage unit for storing a value detected by the detection device with respect to time;
Referring to the storage unit, the index values obtained by weighting the slope of the pressure or the flow rate with respect to the time after the pipe cleaning by the weighting factor based on the pressure or the flow rate at each time after the pipe cleaning is described above. An index calculation unit for calculating with respect to time;
A modeling unit for modeling a change in the index value with respect to the time after cleaning of the pipe;
Based on the relationship between the time after the cleaning of the piping or other piping and the index value when an abnormality has occurred in the piping or other piping in the past, and the timing of cleaning the piping based on the model An informing unit for informing information;
A piping diagnostic device including:
Piping diagnosis system with

DESCRIPTION OF SYMBOLS 10 Information processing apparatus 30 Pressure gauge 11 Index calculation part 12 Approximation function calculation part 13 Judgment function calculation part 14 Prediction part 17 Past data table 19 Piping management table 100,100 'Piping diagnosis system

Claims (10)

With reference to the storage unit storing the pressure or flow rate of the fluid in the pipe with respect to time, the pressure or the pressure with respect to the time after cleaning of the pipe is determined by the weighting factor based on the pressure or the flow rate at each time after cleaning of the pipe. An index value weighted with the slope of the flow rate is calculated for each time,
Model the change of the index value with respect to the time after cleaning the pipe,
Based on the relationship between the time after the cleaning of the piping or other piping and the index value when an abnormality has occurred in the piping or other piping in the past, and the timing of cleaning the piping based on the model Broadcast information,
A piping diagnosis method in which processing is performed by a computer. The slope of the pressure or the flow rate with respect to the time after cleaning the pipe is calculated by the least square method,
The weighting factor increases as the pressure or the flow rate at each time decreases.
The piping diagnosis method according to claim 1, wherein: Smoothing the pressure or flow rate of the fluid in the pipe with respect to the elapsed time after cleaning of the pipe stored in the storage unit;
The piping diagnosis method according to claim 1 or 2, wherein the computer executes the processing. The process of modeling the change of the index value includes a process of modeling the change of the index value with respect to the time after cleaning of the pipe by an approximate expression by polynomial regression.
The piping diagnosis method according to any one of claims 1 to 3, wherein When an abnormality has occurred in the piping or other piping in the past, at least when the pressure or the flow rate falls below a predetermined threshold, and when a predetermined operation is performed on the piping On the other hand,
The piping diagnosis method according to any one of claims 1 to 4, wherein: The process of notifying information related to the cleaning timing of the pipe is a relationship between the index value and the time after cleaning the pipe or the other pipe when an abnormality has occurred in the pipe or the other pipe in the past. Including a process of calculating an approximate expression approximated by linear regression or polynomial regression,
The piping diagnosis method according to any one of claims 1 to 5, wherein: The process of notifying information related to the cleaning timing of the pipe is a relationship between the index value and the time after cleaning the pipe or the other pipe when an abnormality has occurred in the pipe or the other pipe in the past. A process of calculating an intersection of an approximate expression approximated by linear regression or polynomial regression and an approximate expression approximated by polynomial regression of a change in the index value with respect to the time after cleaning of the pipe,
The piping diagnosis method according to any one of claims 1 to 6, wherein The process of informing information on the timing of cleaning the pipe includes a process of informing information on the timing of cleaning of the pipe in stages.
The piping diagnosis method according to any one of claims 1 to 7, wherein With reference to the storage unit storing the pressure or flow rate of the fluid in the pipe with respect to time, the pressure or the pressure with respect to the time after cleaning of the pipe is determined by the weighting factor based on the pressure or the flow rate at each time after cleaning of the pipe. An index calculation unit that calculates an index value weighted with the gradient of the flow rate for each time;
A modeling unit for modeling a change in the index value with respect to the time after cleaning of the pipe;
Based on the relationship between the time after the cleaning of the piping or other piping and the index value when an abnormality has occurred in the piping or other piping in the past, and the timing of cleaning the piping based on the model An informing unit for informing information;
A piping diagnostic device comprising: A detection device for detecting the pressure or flow rate of the fluid in the pipe;
A storage unit for storing a value detected by the detection device with respect to time;
Referring to the storage unit, the index values obtained by weighting the slope of the pressure or the flow rate with respect to the time after the pipe cleaning by the weighting factor based on the pressure or the flow rate at each time after the pipe cleaning is described above. An index calculation unit for calculating with respect to time;
A modeling unit for modeling a change in the index value with respect to the time after cleaning of the pipe;
Based on the relationship between the time after the cleaning of the piping or other piping and the index value when an abnormality has occurred in the piping or other piping in the past, and the timing of cleaning the piping based on the model An informing unit for informing information;
A piping diagnostic device including:
Piping diagnosis system with

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